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The pandemic and subsequent 'lockdowns' dramatically changed the educational landscape of higher education institutions. Before-COVID-19, traditional universities had choices in pedagogical practice, which included a variety of teaching delivery modes. Overnight, a single mode of delivery became the only option for traditional higher education institutions. All services migrated to digital platforms, leading to a period of "emergency eLearning". The full impact of this sudden shift to digital platforms on all cohorts of students is still unclear. A measure of disruption to the normal student learning experience, especially for those attending traditional universities, was inevitable. Moreover, this disruption was varied depending on the University's country and the country's lockdown logistics. This international, comparative, quantitative research project investigated and explored higher education students' perceptions of emergency eLearning during the COVID-19 pandemic. Experiences of students at universities in three countries were evaluated in terms of four dimensions: (1) home learning environment; (2) engagement; (3) participation preference; and (4) impact on learning skills. The research revealed significant differences between the participating universities students' experiences. The most important differences were in the 'home learning environment', followed by 'engagement' and the perception of 'impact on learning skills'. The differences in the 'home learning environment' can be attributed to the differing economic and digital development of the surveyed countries: South Africa, Wales, and Hungary. Finally, different cultural backgrounds suggest a noticeable difference in student engagement, participation, and learning skills.

Concerns about climate change are a hot topic in the current debate about a sustainable future, and despite more than 30 years of international conferences, including the Intergovernmental Panel on Climate Change (IPCC) and the United Nations Climate Change Conference (COP), the annual usage amount of fossil fuel-based energy sources has remained largely unchanged, and the green transition to a carbon-free energy system is progressing at a much slower pace than anticipated. This paper presents an original approach that consists in addressing the green transition's dilemmas by analyzing the complex interplay of strongly interwoven forces hindering the rapid adoption of so-called green energy sources scrutinized from a three-fold perspective: socio-psychological; political–strategic and territorial; and technological. Moreover, these forces are ranked according to the magnitude of their impact on the anticipated transition to green, and it is estimated by logistic fit extrapolation that the total share of the contribution of low-carbon sources might reach a maximum of about 25% among all energy sources in 2050. A final original picture is presented, summarizing how all the involved forces are acting upon the expected transition as well as their consequences. [ABSTRACT FROM AUTHOR]

The global energy transition is an uneven process, fundamentally related to the level of economic development of countries and their access to energy resources (renewable and non-renewable) to a large extent. The global climate is interconnected, and all nations impact it through their products and services. The six countries discussed—China, Brazil, Germany, Japan, Russia, and India—account for 44.8% of global primary energy consumption and 49% of global CO2 emissions. Each of them has its own strategy for achieving carbon neutrality, based on different decarbonization scenarios, which, according to the authors, depend on geopolitical factors, national economy characteristics, and the established pragmatic goals and objectives. However, the "green agenda" itself may not always be among the top priorities when formulating energy strategies. The study objective is to analyze the feasibility of the stated goals in these countries using a combined logistic curve-based forecasting tool for predicting solar and wind production as well as investment volumes. It aims to justify the relation between solar and wind energy production and investment policies using a calculated technological coefficient. Results show similar, but time-shifted fluctuating investment dynamics in solar and wind energy trends in Japan, Germany and China, with Germany and Japan outperforming investment forecasts when considering the technology efficiency coefficient. Furthermore, the findings highlight the overwhelming appreciation of the unevenness of the green transition process, which will consequently make it impossible to meet the goals of the Paris Agreement until 2050. Taking these factors into consideration, exploratory decarbonization scenarios for these six major world economies alongside two dimensions, namely, the pace of green transition versus green technology and versus resources, are presented. [ABSTRACT FROM AUTHOR]

Vaccination is critical to preventing the spread of diseases. It stimulates the immune system to produce antibodies that fight specific diseases, eradicating and reducing their incidence. However, despite the proven benefits, there is hesitation and skepticism in some areas due to side effects and lack of knowledge. Developing a data collection and processing system to analyze vaccination is critical in today's world. Vaccines are necessary to minimize morbidity and mortality, but success depends on analyzing data on vaccine use and efficacy. This system can identify potential side effects and adverse reactions, ensuring vaccine safety and building public confidence. This research focuses on IT support for analyzing vaccination side effects. The aim of this work is to develop an architecture model of the system to collect and process data on the health status of vaccinated patients. The research methodology consists of analyzing sources on the consequences and side effects of vaccination. On the basis of this knowledge, the key attributes (stakeholders, sources of information, input data, data analysis processes) of the data collection and analysis system were analyzed using an enterprise architecture approach. As a result, a general model of the architecture of the data collection and analysis system was proposed. [ABSTRACT FROM AUTHOR]

In an unstable economic climate, all market participants want to know is when is the timing to overcome a recession, and what measures and means to use for economic recovery. In this regard, the process through which the Eurozone economy has gained momentum since the summer of 2022 has been a volatile one. This was reflected in a sharp rise in the price level, followed by a sharp rise in the ECB interest rates. The purpose of this paper is to provide short-term forecasts of the main parameters of monetary and fiscal policy by the euro area monetary authorities, based on a model developed by the authors. The distinctive feature of the presented and proposed model lies in the particularly careful selection of the parameter values based on actual statistical data. The statistics used for the proposed model cover the period from 2015 to December 2022. The simulation results show that the European Central Bank (ECB) needs to maintain a policy of high interest rates for a period of 12 to 14 months, which will help to bring inflation down to 2–3 percent in the future and move to a stage and phase of sustainable economic growth. [ABSTRACT FROM AUTHOR]