To fight inflation, European Central Bank (ECB) announced 10 successive interest rate hikes, starting on 27 July 2022, igniting an unprecedented widening of interest rate spreads in the euro area (ΕΑ). Greek banks, however, recorded among the highest interest rate spreads, far exceeding ΕΑ median and weighted average. Indeed, we document a strong asymmetric response of Greek banks to ECB interest rate hikes, with loan interest rates rising immediately, whilst deposit interest rates remained initially unchanged and then rose sluggishly. As a result, the interest rate spread hit one historical record after another. Greek systemic banks, probably taking advantage of the high concentration and low competition in the domestic sector benefited from key ECB interest rate hikes, recording gigantic increases in net interest income (NII), and consequently, substantial profits (almost €7.4 billion in the 2022–2023 biennium). Such excessive accumulation of profits (that deteriorates the living conditions of consumers) by the banking system could be called the inflation of “banking greed”, or bankflation. This new source of inflation created by the oligopolistic structure of the Greek banking sector counterworks the very reason for ECB interest rate increases and requires certain policy analysis recommendations in coping with it.

The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R² from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R² is compared to the experiments. No changes in Test R²’s were observed on GBM and XGBoost, which retained same Test R² across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R² of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R²; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.

Central Sulawesi has been grappling with significant challenges in human development, as indicated by its Human Development Index (HDI). Despite recent improvements, the region still lags behind the national average. Key issues such as high poverty rates and malnutrition among children, particularly underweight prevalence, pose substantial barriers to enhancing the HDI. This study aims to analyze the impact of poverty, malnutrition, and household per capita income on the HDI in Central Sulawesi. By employing panel data regression analysis over the period from 2018 to 2022, the research seeks to identify significant determinants that influence HDI and provide evidence-based recommendations for policy interventions. Utilizing panel data regression analysis with a Fixed Effect Model (FEM), the study reveals that while poverty negatively influences with HDI, underweight prevalence is not statistically significant. In contrast, household per capita income significantly impacts HDI, with lower income levels leading to declines in HDI. The findings emphasize the need for comprehensive policy interventions in nutrition, healthcare, and economic support to enhance human development in the region. These interventions are crucial for addressing the root causes of underweight prevalence and poverty, ultimately leading to improved HDI and overall well-being. The originality of this research lies in its focus on a specific region of Indonesia, providing localized insights and recommendations that are critical for targeted policy making.

National unity is a matter of great concern for many countries around the world today. The study of policy evaluation is an important aspect of the study of national unity. The evaluation of policy implementation effects can help policymakers analyze whether there are problems in the formulation and implementation of the policy, thereby promoting further policy adjustments to better achieve national unity. This article adopts thematic searches and a systematic literature review as research methods. Through the systematic review, it summarizes and analyzes the research on national unity policies across different regions and countries. The article has two objectives: First, to explore the current perspectives in the research on national unity policies, and second, to analyze the state of research regarding the effectiveness of national unity policies. Among the 35 papers analyzed, 7 were on integration policy, 6 were on education policy and 4 were on language policy. To a certain extent, this reflects the perspectives of some countries in Europe, Asia and Africa, including France, Greece, Russia, Turkey, China, Sri Lanka, Nepal, Kenya, South Africa, Nigeria and other countries on the governance of national unity. Research on policy effectiveness is mainly conducted from the perspectives of policy content and policy implementation. However, there is little analysis of successful cases that achieved the desired goals. The main contributions of this article are as follows: first, it summarizes and identifies the characteristics of national solidarity-related policies in different continents and countries. Secondly, the experience of the success and failure of the national unity policy is studied and summarized. In addition, this article also found that there are still gaps in the research on successful experiences and causes.

This research introduces a novel framework integrating stochastic finite element analysis (FEA) with advanced circular statistical methods to optimize heat pump efficiency under material uncertainties. The proposed methodologies and optimization focus on balancing the mean efficiency and variability by adjusting the concentration parameter of the Von Mises distribution, which models directional variability in thermal conductivity. The study highlights the superiority of the Von Mises distribution in achieving more consistent and efficient thermal performance compared to the uniform distribution. We also conducted a sensitivity analysis of the parameters for further insights. The results show that optimal tuning of the concentration parameter can significantly reduce efficiency variability while maintaining a mean efficiency above the desired threshold. This demonstrates the importance of considering both stochastic effects and directional consistency in thermal systems, providing robust and reliable design strategies.

In order to replace conventional materials in the existing composite world, there has been a focus on adopting coir fibres, which are lightweight, adaptable, efficient, and have great mechanical qualities. This study describes the creation of environmentally responsible bio-composites with good mechanical characteristics that employ coir powder as a reinforcement, which has good interfacial integrity with an epoxy matrix. And these epoxy-coir composites supplemented with coir particles are predicted to function as a reliable substitute for traditional materials used in industrial applications. Here, untreated and alkali-treated coir fibres powder were employed as reinforcement, with epoxy resin serving as a matrix. An experimental investigation has been carried out to study the effect of coir powder reinforcement at different weight percentages (5 wt%, 10 wt%, 15 wt%, 20 wt%, 25 wt%, and 30 wt%). The morphological study, followed by a scanning electron microscope (SEM) and an optical microscope (OM), demonstrated that the powder and matrix had the strongest adhesion at 20 wt% coir powder-reinforced composite, with no voids, bubbles, or cracks. Based on the entire investigation, the polymer composite with 20 wt% reinforcement exhibited better mechanical qualities than the other combinations.