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This chapter analyses the structure, content and development trends of the system of postgraduate teacher training in Russia. It is shown that the system of postgraduate training in Russia has a long history and consists of postgraduate and doctoral levels. The trends that influenced the dynamics and essence of the modernisation processes of Russian postgraduate education are revealed. The content, logic and shortcomings of the not quite successful attempt to standardise the process of training higher-qualified personnel in postgraduate studies are substantiated. Changes in the nomenclature of scientific specialties, which are used to award academic degrees in pedagogy, are revealed.

The main part of the material is devoted to the general characteristics of the current pedagogical postgraduate programmes in Russia. It describes the peculiarities of the admission procedure and the organisation of training for graduate students, the nuances of the choice of supervisor, the definition of the thesis topic, and the current, intermediate, and final certification of graduate students. The essence of co-doctoral studies as a form of dissertation preparation is revealed. The requirements for the preparation, design and defence of candidate dissertations in pedagogy are outlined. The form of advanced training of scientific and pedagogical staff for the preparation of doctoral dissertations is briefly described.

As data centres grow in size and complexity, traditional air-cooling methods are becoming less effective and more expensive. Immersion cooling, where servers are submerged in a dielectric fluid, has emerged as a promising alternative. Ensuring reliable operations in data centre applications requires the development of an effective control framework for immersion cooling systems, which necessitates the prediction of server temperature. While deep learning-based temperature prediction models have shown effectiveness, further enhancement is needed to improve their prediction accuracy. This study aims to develop a temperature prediction model using Long Short-Term Memory (LSTM) Networks based on recursive encoder-decoder architecture.

This paper explores the use of deep learning algorithms to predict the temperature of a heater in a two-phase immersion-cooled system using NOVEC 7100. The performance of recursive-long short-term memory-encoder-decoder (R-LSTM-ED), recursive-convolutional neural network-LSTM (R-CNN-LSTM) and R-LSTM approaches are compared using mean absolute error, root mean square error, mean absolute percentage error and coefficient of determination (R²) as performance metrics. The impact of window size, sampling period and noise within training data on the performance of the model is investigated.

The R-LSTM-ED consistently outperforms the R-LSTM model by 6%, 15.8% and 12.5%, and R-CNN-LSTM model by 4%, 11% and 12.3% in all forecast ranges of 10, 30 and 60 s, respectively, averaged across all the workloads considered in the study. The optimum sampling period based on the study is found to be 2 s and the window size to be 60 s. The performance of the model deteriorates significantly as the noise level reaches 10%.

The proposed models are currently trained on data collected from an experimental setup simulating data centre loads. Future research should seek to extend the applicability of the models by incorporating time series data from immersion-cooled servers.

The proposed multivariate-recursive-prediction models are trained and tested by using real Data Centre workload traces applied to the immersion-cooled system developed in the laboratory.

This study explores how public sector risk management (RM) is implemented in 6 Brazilian state governments, given the existence of contextual factors in the settings.

The cases were selected following a methodological protocol, resulting in the collection of 12 interviews with government policymakers (GPMs), supplemented with legislation and website content. All collected data were analysed through the qualitative content analysis method under the multi-case study methodology.

Empirical evidence shows that the settings strive to operationalise public sector RM by using implementation strategies. These strategies are developed by the GPMs and represent the consequence of the influence of three perceived contextual factors: weak sup-port from some public top managers, a pre-existent innovation-oriented culture, and risk types. Moreover, developing the maturity of RM implementation was observed as being difficult given the weak support from public top managers.

This study suggests that RM is not always easily implemented in the public context. Therefore, this article provides some tips that help mitigating this problem by involving actions that stimulate a deeper engagement of public top managers and that bring RM to a more strategic place in the governments.

This article explores RM in the public sector at the government level, demonstrating that strategies can be developed by GPMs to address contextual factors that can make the implementation of RM difficult, as indicated in the study.

This study explores the moderating effect of board gender diversity (BGD) between a firm's Environmental, Social, and Governance (ESG) performance and Economic value added (EVA) using NSE-listed 331 companies' data from 2015 to 2020, forming 1986 firm-year observations.

Our study is based on panel data; hence, we use a system GMM panel regression model to confirm whether the BGD moderates ESG and EVA. We also address the endogeneity issues.

Overall, our study reported a positive moderating effect of BGD between ESG and EVA. Similar results were observed across the chemical and financial services industries. However, in the case of the healthcare and consumer goods industries, we did not find support for the moderating effect.

The implications of our results are considerable and relevant for regulators, governing bodies, and corporate managers. It helps them understand how BGD plays a vital role in influencing the effect of ESG on a firm's EVA.

No existing research has explored the moderating effect of BGD between ESG and EVA, to the authors' best knowledge. Therefore, our study extends the existing literature and further supports resource dependency, agency, and stakeholder theories of corporate governance.

COVID-19 has had various effects on women’s labour supply worldwide. This study investigates how women’s labour market outcomes in the MENA region have been affected by the stringency of governments’ COVID-19 responses and school closures. We examine whether women, particularly those with children at young age, reduced their labour supply to take care of their families during the pandemic.

To investigate whether having a family results in an extra penalty to women’s labour market outcomes, we compare single women to married women and mothers. Using the ERF COVID-19 MENA Monitor Household Surveys, we analyse the key conditions underlying women’s labour market outcomes: (1) wage earnings and labour market status including remaining formally employed, informally, unpaid or self-employed, unemployed or out of the labour force and (2) becoming permanently terminated, being suspended, seeing a reduction in the hours worked or wages, or seeing a delay in one’s wage payments because of COVID-19. Ordered probit and multinomial logit are employed in the case of categorical outcomes, and linear models for wage earnings.

Women, regardless of whether they have children or not, appear to join the labour market out of necessity to help their families in the times of crisis. Child-caring women who are economically inactive are also more likely to enter the labour market. There is little difference between the negative experiences of women with children and child-free women in regard to their monthly pay reduction or delay, or contract termination, but women with children were more likely to experience reduction in hours worked throughout the pandemic.

These findings may not have causal interpretation facilitating accurate inference. This is because of potential omitted variables such as endogenous motivation of women in different circumstances, latent changes in the division of domestic work between care-giving and other household members, or selective sample attrition.

Our analysis explores the multiple channels in which the pandemic has affected the labour outcomes of MENA-region women. Our findings highlight the challenges that hamper the labour market participation of women, and suggest that public policy should strive to balance the share of unpaid care work between men and women and increase men’s involvement, through measures that support child-bearing age women’s engagement in the private sector during crises, invest in childcare services and support decent job creation for all.

This paper primarily aims to identify the multilevel learning processes emerging from abrupt telework implementation in a public knowledge-intensive organization (KIO) amid the COVID-19 crisis.

This single-case process research was guided by interpretivist epistemology. Empirical data from documentary research and 41 interviewed managers were processed by inductive qualitative analysis using the multilevel learning theoretical model.

Eight types and three modes of learning processes during the COVID-19 pandemic were identified in a public KIO, iteratively emerging in multilevel learning dynamics during the compulsory adoption of telework and replacing the face-to-face work mode conducted since its foundation.

As insider researchers, while daily and privileged access to the field was obtained, it also demanded their continuous effort to maintain transparency and scientific distancing; conceptual results are restricted to process theorisation studies, specifically the 4Is theoretical model in the scope of crisis learning process studies concerning KIOs.

This study provides evidence for managers to adopt interactive dynamics among eight multilevel types and three learning modes of emergent learning, developed during the COVID-19 pandemic, and support learning practices’ implementation and routinisation across three organizational levels in crisis situations. In addition, evidencing emergent types of learning enables organizational learning (OL) researchers to examine how organizational structures and work practices either promote or inhibit different learning types and impact multilevel learning when adopting teleworking during a crisis.

This research has theoretical value in two ways: (i) Providing empirically supported knowledge: This involves understanding multilevel learning processes resulting from emergent learning in a public KIO that abruptly adopted teleworking during a crisis context; (ii) deepening process theorization studies on OL: To achieve this, we enhance the 4I model by incorporating eight types and two modes of learning processes. These processes iteratively emerge from the individual and group levels towards the institutional level in a public KIO.

The purpose of this study is to investigate the position of religion for the three constitutions of Egypt.

In this study, by tracing religious identity-related studies and seeing whether their existence is attributed to the ruling elites’ attitudes, it examines how factors such as new elites and new in ideology affect change of articles of religion.

The results demonstrate that the most significant factor was the existence of a new elite having a different ideology, which was obvious in the three constitutions: 1971, 2012 and 2014.

The manner in which studies of religion are written is the basis for legislation and the source of public policies that affect the discourse of political systems or results in economic and social rights that affect public policies. Therefore, if people are engaged in the process of drafting identity articles, they would participate in the reformation of their traditions and systems and there would be more integration in the society.

Few studies have attempted to work on the sociology of constitutions and religion in the Egyptian context.

This paper examines the relationships between bank switching and both customer vulnerability and consumer-oriented policies (financial education and disclosure practices).

The analysis employs microdata from the Special Eurobarometer on Financial Products and Services, for 24 European nations. It carries out a probit estimation on the factors explaining propensity of bank switching, focusing on three characteristics associated with customer vulnerability: an advanced age, low educational attainment and residence in a rural or a relatively poor region.

The authors report that the probability of bank switching is significantly lower for three groups of vulnerable customers: the elderly, the less educated and those living in deprived regions. Further the authors identify that national financial education policies and disclosure practices have no significant effects on bank switching.

Based on these results, the authors propose more targeted policies recognising customers' heterogeneity are required to increase bank switching behaviour.

This paper exploits a unique source of information on bank switching behaviour and customer characteristics across European nations. These data are complemented with information about consumer financial education policies and disclosure practices from the World Bank and geographical, market and regulatory factors at the regional and national levels. The paper contributes to two academic areas. First, it presents further evidence on heterogeneity of bank customer switching behaviour, addressed at improving the understanding of customer vulnerability in banking services. Second, it examines the efficacy of consumer-oriented policies (financial literacy and disclosure practices) in encouraging bank switching.

Human development is critical for fostering economic growth and development. Given the importance of human development, this study examines the asymmetric impact of Foreign Direct Investment (FDI) on human development by decomposing total FDI into positive and negative shocks in five South Asian countries from 1990 to 2021.

The study uses the panel Non-linear Autoregressive Distributive Lag model (NARDL) to examine asymmetric long and short-run effects of FDI. Further, the direction of causality between HDI and FDI is examined using the recently developed (Joudis et al., 2021) panel granger non-causality test.

The positive and negative FDI shocks positively impact HDI, but positive shocks have a higher effect than negative shocks in the long run. The Wald Test rejects the long-run symmetric effect, confirming the asymmetric relationship between FDI and human development. More importantly, causality results reveal the FDI-led HDI and HDI-led FDI development in South Asia.

FDI should be encouraged by formulating a well-tailored policy intervention. The development policies should be interlinked with FDI policies. Absorptive capacities such as infrastructure facilities, a threshold level of human capital, and institutions should be strengthened to attract higher FDI into high-tech sectors.

Unlike the previous empirical studies, this study provides asymmetric evidence between FDI and human development in South Asia.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0380.