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Religion and philosophy satisfy the basic human needs of understanding, belonging, and finding meaning. They provide tranquility of mind and satisfy the desire to be loved and lovable. However, they present their own failings and can counter each other in positive and negative ways, that threaten the communities of beliefs they form and their interactions. An appropriate institutional framework can control the fanaticism and sectarianism that can come with established religion and philosophy.

The agricultural sector is a critical component of global economic development, and its significance has grown significantly in recent years. The risks associated with agriculture and the behaviors of farmers in handling these risks are becoming increasingly important, given the sector’s increasing dependence worldwide. Various activities related to agriculture are vulnerable to multiple risks, which can have severe consequences for farmers’ livelihoods. The purpose of this systematic review is to present a comprehensive analysis of the sources of risk faced by farmers and their choices in adopting risk management strategies worldwide.

The Preferred Reporting Items for Systematic reviews and Meta-Analyses protocol was utilized to select relevant literature, and a total of 102 studies were analyzed. Through the use of Venn diagrams and graphical methods, the authors provide a transparent overview of the risks faced by farmers and the adoption of risk management strategies in developed and developing countries.

From the analysis, the authors found that, in terms of risk management strategies, diversification, reserve credit and accumulated assets are frequently used in developing countries, while developed countries tend to rely on future/forward contracts, crop insurance and hedging. Diversification is the most widely used risk management strategy across both developed and developing countries. Our study also highlights the different perceptions of weather-related risks among growers in developed and developing countries.

This systematic review provides valuable insights into the risks associated with agriculture and farmers' strategies in managing these risks, which could inform policy decisions and promote sustainable agricultural practices. For instance, understanding the individualistic nature of farmers' risk perception and the varying risk sources and management strategies depending on the locality and provide assistance to the farmers accordingly.

The paper explains how farmers behave during uncertainty in terms of risk perception and their decision to adopt risk management strategies in developed and developing countries.

European rural development programmes are driving multi-actor interactive innovation initiatives and alliances to create an environment in which innovation acts as a tool for accelerating rural development processes. In Europe, where rural areas are facing many challenges, identifying which challenges, difficulties, obstacles or risk factors that interactive innovation projects have had to face in rural areas while being planned and set up would be interesting. The objective of this research work was to, therefore, identify and analyse the risk factors of 200 rural projects and initiatives that were selected as case studies from the whole of Europe.

The employed methodology consisted in conducting interviews to subsequently perform statistical independence analyses of the qualitative variables characterising the found projects and risk factors.

The findings indicated that most of the risks that rural projects and initiatives faced were related to the social domain which was, in turn, the fundamental pillar of interactive innovation. Dependence was found between social risk factors appearing and the innovation type carried out; the risk factors corresponding to the political–legal risks category and the project or initiative coordinating country; and the economic–technical risks category and the initiatives' geographic magnitude.

This paper exposes the main risks identified within various rural innovation initiatives and projects around Europe. For this purpose, a statistical analysis of independence was performed, allowing us to generate reliable and accurate results of the main risks associated with certain descriptive characteristics (coordinating region, domain, innovation type, gender balance and geographic magnitude) of the initiatives studied.

This chapter begins by covering four parenting styles and their effects on college students’ wellbeing. Next, the effects of parents’ divorce and parental death on college students are explored. In addition to relationships with their parents, the chapter also examines college students’ relationships with their friends. Friendships based on utility or pleasure are contrasted with those based on virtue. Next, the chapter explores the effects of college students’ friendships on various aspects of their academic performance (e.g., dropping out of school) and social lives (e.g., drinking behaviors). The role of social media in college students’ relationships is considered as well. The chapter concludes with a focus on college students’ romantic relationships.

The purpose of this study is twofold. First, to estimate an optimal inflation rate for Ghana and second, to investigate factors that account for the differences between observed and target inflation.

The paper explored the questions within two econometric frameworks, the Autoregressive Distributed Lag (ARDL) and Threshold Regression Models using data spanning the period 1965–2019.

The study estimated a range of 5–7% optimal inflation for Ghana. While this confirms the single-digit inflation targeting by the Bank of Ghana, the range is lower than the central bank's band of 6–10%. The combined behaviours of the central bank, banks and external outlook influence inflation target misses.

The study urges the central bank to continue pursuing its single-digit inflation targeting. However, it implies that there is still room for the Bank to further lower the current inflation band to achieve an optimal outcome on growth and welfare. Again, the Bank should commit to increased transparency and accountability to enhance its credibility in attaining the targeted inflation.

The study is one of the first attempts in Africa in Ghana to estimate an optimal inflation target and investigate the underlying factors for deviation from the targets.

This study aims to measure the perception of the residents regarding peer assisted learning in emergency medicine residency program as well as assessing the psychometric properties of the questionnaire used as the research tool.

A descriptive cross-sectional study was conducted at King Abdullah Medical City, Saudi Arabia, Makkah on a Convenience sample of Emergency Medicine residents who completed peer assisted learning sessions. Data were collected through a questionnaire evaluating the residents’ perception of Peer Assisted Learning. Descriptive statistics were used and statistical significance was set at p < 0.05. The Peer Assisted Learning (PAL) satisfaction questionnaire was tested for construct validity and reliability. Exploratory Factor Analysis (EFA) was conducted. The reliability of the used questionnaire was assessed using Cronbach’s coefficient alpha.

The study showed that the PAL questionnaire yielded four factors. The four factors are labeled as the following: Factor 1: Cognitive congruence, Factor 2: Social congruence; Factor 3: Teaching skills in Peer Assisted Learning (PAL) session; and Factor 4: Professional development. These results indicated that questionnaire has a good structure validity. In addition, the study showed high internal consistency of the questionnaire. Cronbach’s alpha coefficient value for the total scale was 0.88. The perception of residents was assessed and results revealed residents’ satisfaction regarding Peer Assisted Learning.

Up to the authors’ knowledge, this is the first study which assessed the psychometric properties of a questionnaire measuring the residents’ perceptions regarding Peer Assisted Learning. The study contributed to improving information regarding the psychometric properties and usefulness of PAL questionnaire.

The purpose of this paper is to highlight the key technical challenges that derive from the recently proposed European Artificial Intelligence Act and specifically, to investigate the applicability of the requirements that the AI Act mandates to high-risk AI systems from the perspective of AI security.

This paper presents the main points of the proposed AI Act, with emphasis on the compliance requirements of high-risk systems. It matches known AI security threats with the relevant technical requirements, it demonstrates the impact that these security threats can have to the AI Act technical requirements and evaluates the applicability of these requirements based on the effectiveness of the existing security protection measures. Finally, the paper highlights the necessity for an integrated framework for AI system evaluation.

The findings of the EU AI Act technical assessment highlight the gap between the proposed requirements and the available AI security countermeasures as well as the necessity for an AI security evaluation framework.

AI Act, high-risk AI systems, security threats, security countermeasures.

Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

Design-based research (DBR) involves multiple iterations, and innovations are needed in analytical methods for understanding how learners experience a learning experience in ways that both embrace the complexity of learning and allow for data-driven changes to the design of the learning experience between iterations. The purpose of this paper is to propose a method of crafting design moves in DBR using network analysis.

This paper introduces learning experience network analysis (LENA) to allow researchers to investigate the multiple interdependencies between aspects of learner experiences, and to craft design moves that leverage the relationships between struggles, what worked and experiences aligned with principles from theory.

The use of network analysis is a promising method of crafting data-driven design changes between iterations in DBR. The LENA process developed by the authors may serve as inspiration for other researchers to develop even more powerful methodological innovations.

LENA may provide design-based researchers with a new approach to analyzing learner experiences and crafting data-driven design moves in a way that honors the complexity of learning.

LENA may provide novice design-based researchers with a structured and easy-to-use method of crafting design moves informed by patterns emergent in the data.

To the best of the authors’ knowledge, this paper is the first to propose a method for using network analysis of qualitative learning experience data for DBR.