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The outbreak of COVID-19 not only had serious negative impacts on the world economy but also on the global mental health because of the psychological disorders associated with the spread of the pandemic, the increased degree of uncertainty and the unprecedented measures taken by different countries to face the pandemic’s spread. This paper analyses the mental health well-being of individuals in selected MENA countries (Jordan, Morocco, Tunisia and Egypt) during the pandemic.

The study employs a pooled OLS model using the Economic Research Forum (ERF) COVID-19 MENA Monitor Survey panel dataset collected during 2020 and 2021.

The findings show that there is no association between the mental health of individuals in the selected countries and their age, gender, family size, marital status, receipt of social support and participation in care work. Mental health improved at higher levels of education, being employed, being a rural area resident and living in Morocco or Tunisia compared to living in Jordan while it worsened as income declined, food insecurity and anxiety about being infected with Covid-19 increased, being a resident in camps, and during waves 4 and 5. Based on these results, it is recommended that suitable financial, physical and human resources should be directed towards the provision of mental health care services in the region. Also, mental health care services should be accessible to different population groups, with a special focus towards the most vulnerable since they are more prone to mental illnesses, especially during health crises and economic shocks. This should be accompanied by increasing awareness about the provided services and reducing stigma against mental illnesses. Furthermore, introduction of policies targeted towards reducing food insecurity and income instability can play a key role in enhancing mental well-being.

Although few papers have previously investigated the impact of COVID-19 on mental health in MENA countries, most of them have focused on a country-level analysis and adopted a gender perspective. Hence, this paper aims at exploring the association between mental health well-being and socio-economic factors in selected MENA countries during the pandemic.

To reduce the heat load of a gas turbine blade, its surface is covered with an outer layer of ceramics with high thermal resistance. The purpose of this paper is the selection of ceramics with such a low heat conduction coefficient and thickness, so that the permissible metal temperature is not exceeded on the metal-ceramics interface due to the loss ofmechanical properties.

Therefore, for given temperature changes over time on the metal-ceramics interface, temperature changes over time on the inner side of the blade and the assumed initial temperature, the temperature change over time on the outer surface of the ceramics should be determined. The problem presented in this way is a Cauchy type problem. When analyzing the problem, it is taken into account that thermophysical properties of metal and ceramics may depend on temperature. Due to the thin layer of ceramics in relation to the wall thickness, the problem is considered in the area in the flat layer. Thus, a one-dimensional non-stationary heat flow is considered.

The range of stability of the Cauchy problem as a function of time step, thickness of ceramics and thermophysical properties of metal and ceramics are examined. The numerical computations also involved the influence of disturbances in the temperature on metal-ceramics interface on the solution to the inverse problem.

The computational model can be used to analyze the heat flow in gas turbine blades with thermal barrier.

A number of inverse problems of the type considered in the paper are presented in the literature. Inverse problems, especially those Cauchy-type, are ill-conditioned numerically, which means that a small change in the inputs may result in significant errors of the solution. In such a case, regularization of the inverse problem is needed. However, the Cauchy problem presented in the paper does not require regularization.

This study aims to analyze the imbalances in the public finance structure of Pakistan’s economy and highlight the need for comprehensive reforms. Specifically, it aims to contribute to the empirical literature by analyzing the relationship between fiscal vulnerability, financial stress and macroeconomic policies in Pakistan’s economy between 1971 and 2020.

The study develops an index of fiscal vulnerability, an index of financial stress and an index of macroeconomic policies. The fiscal vulnerability index is based on the patterns of fiscal indicators resulting from past trends of the selected variables in Pakistan’s economy. The financial stress in Pakistan is caused from the financial disorders that are acknowledged in the composite index, which is based on variables with the potential to indicate periods of stress stemming from the foreign exchange market, the securities market and the monetary policy components. The macroeconomic policies index is developed to analyze the mechanism through which fiscal vulnerability and financial stress have influenced macroeconomic policies in Pakistan. The causal association between fiscal vulnerability, financial stress and macroeconomic policies is analyzed using the auto-regressive distributive lags approach.

There exists a long-run relationship between the three indices, and a bi-directional causality between fiscal vulnerability and macroeconomic policies.

This study contributes to the development of a fiscal monitoring mechanism, which has the basic purpose of analyzing the refinancing risk of public liabilities. Moreover, it focuses on fiscal vulnerability from a macroeconomic perspective. The study tries to develop a framework to assess fiscal vulnerability in light of “The Risk Octagon” theory, which focuses on three risk components: fiscal variables, macroeconomic-disruption-associated shocks and non-fiscal country-specific variables. The initial contribution of this work to the literature is to develop a framework (a fiscal vulnerability index, financial stress index and macroeconomic policies index) for effective and result-oriented macro-fiscal surveillance. Moreover, empirical literature emphasized and advised developing countries to develop their own capacity mechanisms to assess their fiscal vulnerability in light of the IMF guidelines regarding vulnerability assessments. This study thus attempts to fulfill the said gap identified in literature.

This paper explores how a firm's public stand on a social-political issue can be a salient signal of the firm's values, identity and reputation. In particular, it investigates how boycott participation–conceptualized as a cue of a corporation's stand on important social-political issues–may affect the stock market valuation of that corporation, as well as how corporations legitimise their stand on the issues.

The authors employ a mixed-methods design that uses both qualitative techniques (content analysis) and quantitative methods (event study methodology) to examine a sample of US firms who participated in a boycott campaign that sought to call attention to issues of hate speech, misinformation and discriminatory content on social media platform Facebook.

Findings from the qualitative content analysis of company statements show that firms legitimise their stand on, and participation in, the boycott by expressing altruistic values and suggesting to stakeholders that their stand aligns not only with organizational values/convictions but also with the greater social good. Importantly, the event study results show that firms who publicly announced their intention to participate in the boycott, on average, earn a statistically significant positive abnormal stock return of 2.68% in the four days immediately after their announcements.

Findings relate to a specific case of a boycott campaign. Also, the sample size is limited and restricted to US stocks. The signalling value of corporate social advocacy actions may vary across countries due to institutional and cultural differences. Market reaction may also be different for issues that are more charged than the ones examined in this study. Therefore, future research might investigate other markets, use larger sample sizes and consider a broader range of social-political issues.

The presence of significant stock price changes for firms that publicly announced their decision to side with activists on the issue of hate propaganda and misinformation offers potentially valuable insights on the timing of trades for investors and arbitrageurs. Insights from the study also provide a practical resource that can be used to inform organizations' decision-making about such issues.

Taking the lead to push on social-political issues, such as hate propaganda, discrimination, among others, and communicating their stands in a way that speaks to their values and identity, could be rewarding for companies.

This study provides novel evidence on the impact that corporate stances on important social-political issues can have on stock market valuation of firms and therefore extends the existing related research which until now has focused on the impact on consumer purchasing intent and brand loyalty.

This paper examines the correlation of economic policy uncertainty (EPU) with nonperforming loans and loan loss provisions for 22 major developed countries over the 2008–2017 period.

The study used the Pearson correlation methodology to assess the correlation between EPU, bank nonperforming loans and loan loss provisions.

The findings reveal that EPU is negatively correlated with nonperforming loans and loan loss provisions in the banking sector of EU countries but not for non-EU countries. Also, EPU is negatively correlated with nonperforming loans in the banking sector of the most advanced economies – the G7 countries, while loan loss provisions are more responsive to changes in EPU than NPLs in EU countries.

The implication of the findings is that the correlation of EPU with loan loss provisions and nonperforming loans is influenced by regional characteristics.

This study is the first to analyze the association of EPU with bank nonperforming loans and loan loss provisions under regional classifications such as the EU, non-EU and the G7 countries. This study provides insights on how regional differences might explain the co-movement of EPU with bank nonperforming loans and loan loss provisions.

With the use of the grey incidence analysis (GIA), indicators such as the absolute degree of grey incidence (ε_ij), relative degree of grey incidence (r_ij) or synthetic degree of grey incidence (ρ_ij) are calculated. However, it seems that some assumptions made to calculate them are arguable, which may also have a material impact on the reliability of test results. In this paper, the authors analyse one of the indicators of the GIA, namely the relative degree of grey incidence. The aim of the article was to verify the hypothesis: in determining the relative degree of grey incidence, the method of standardisation of elements in a series significantly affects the test results.

To achieve the purpose of the article, the authors used the numerical simulation method and the logical analysis method (in order to draw conclusions from our tests).

It turned out that the applied method of standardising elements in series when calculating the relative degree of grey incidence significantly affects the test results. Moreover, the manner of standardisation used in the original method (which involves dividing all elements by the first element) is not the best. Much more reliable results are obtained by a standardisation that involves dividing all elements by their arithmetic mean.

Limitations of the conducted evaluation involve in particular the limited scope of inference. This is since the obtained results referred to only one of the indicators classified into the GIA.

In this article, the authors have evaluated the model of GIA in which the relative degree of grey incidence is determined. As a result of the research, the authors have proposed a recommendation regarding a change in the method of standardising variables, which will contribute to obtaining more reliable results in relational tests using the grey system theory.

The purpose of this paper is to execute the efficiency analysis of the selected metaheuristic algorithms (MAs) based on the investigation of analytical functions and investigation optimization processes for permanent magnet motor.

A comparative performance analysis was conducted for selected MAs. Optimization calculations were performed for as follows: genetic algorithm (GA), particle swarm optimization algorithm (PSO), bat algorithm, cuckoo search algorithm (CS) and only best individual algorithm (OBI). All of the optimization algorithms were developed as computer scripts. Next, all optimization procedures were applied to search the optimal of the line-start permanent magnet synchronous by the use of the multi-objective objective function.

The research results show, that the best statistical efficiency (mean objective function and standard deviation [SD]) is obtained for PSO and CS algorithms. While the best results for several runs are obtained for PSO and GA. The type of the optimization algorithm should be selected taking into account the duration of the single optimization process. In the case of time-consuming processes, algorithms with low SD should be used.

The new proposed simple nondeterministic algorithm can be also applied for simple optimization calculations. On the basis of the presented simulation results, it is possible to determine the quality of the compared MAs.

Leadership development has been viewed as a foundational component of agriculture education and the FFA since the early 20^th century (Hoover, Scholl, Dunnigan, & Mamontova, 2007). To contribute to previous research in the field of leadership, this study lays the framework for future studies on the leadership styles of those individuals who lead today’s youth in FFA programs across the State of Texas. This study describes FFA advisors of successful FFA programs in terms of their leadership styles, leadership training/educational background, and suggests how FFA advisors could use their leadership styles to improve their programs. Participants reported engaging in behaviors related to transformational leadership, M = 3.15, more often than those related to transactional, M = 2.45, or laissez-faire leadership styles, M = 0.86

This paper aims to perform thermal and mechanical characterization for silver-based sintered thermal joints. Layer quality affects thermal and mechanical performance, and it is important to achieve information about how materials and process parameters influence them.

Thermal investigation of the thermal joints analysis method was focused on determination of thermal resistance, where temperature measurements were performed using infrared camera. They were performed in two modes: steady-state analysis and dynamic analysis. Mechanical analysis based on measurements of mechanical shear force. Additional characterizations based on X-ray image analysis (image thresholding), optical microscope of polished cross-section and scanning electron microscope image analysis were proposed.

Sample surface modification affects thermal resistance. Silver metallization exhibits the lowest thermal resistance and the highest mechanical strength compared to the pure Si surface. The type of dynamic analysis affects the results of the thermal resistance.

Investigation of the layer quality influence on mechanical and thermal performance provided information about different joint types.