Manyanda tradition, a tradition of taking over social roles after death, in addition to successfully maintaining social continuity in the family structure, is also a potential capital in strengthening social cohesion. However, this context has not been discussed comprehensively in previous studies so it is very important to explain. In addition to responding to the shortcomings of previous studies, this study also aims to explain the mechanisms, factors and implications of the practice of this tradition as a reflection of social cohesion based on customary and religious values. By using a qualitative descriptive case study approach, this study shows three important findings. First, the spontaneity of the community and traditional leaders when hearing the news of death and social activities forty days afterwards. Second, the dominance of spiritual and cultural factors in addition to social and structural factors that encourage the community to preserve this tradition. Third, the Manyanda tradition has implications for strengthening the community’s commitment and belief in the meaning of death, the importance of a replacement figure who takes over social roles and strengthens the tribal identity of the Nagari (local village) community. This study recommends the importance of this tradition to be preserved as the root of social cohesion.

Cases of human trafficking are becoming more prevalent and represent grave abuses of human rights. Both locally and internationally, victims of human trafficking run the danger of being exploited, violent, or infected with contagious illnesses. The Indonesian government has not fully complied with the minimal criteria for safeguarding victims of human trafficking, notwithstanding Law Number 21 of 2007 for the Eradication of the Crime of Human Trafficking. Human rights restoration and respect for victims of human trafficking must be given priority in the implementation of legal protection for these individuals. To strengthen and increase the security of victims’ rights in the future, this study intends to conduct a thorough analysis of the humanism approach model and policies for safeguarding victims of human trafficking. This research uses an empirical technique to support its normative legal analysis. Primary and secondary legal sources are used in this research. The study’s findings show that the protection provided by humanist criminal law for victims of human trafficking is founded on humanitarian principles that derive from the divine principles found in the Pancasila ideology. There are additional requirements for punishment, such as its purpose, its ability to serve as therapy, and its determination to reflect the victim’s and society’s sense of justice. This criminal law is founded on the principles of legality and balance.

In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

The rapid advancement of biotechnologies involves human subjects that brings forth intricate ethical, legal, social, and religious challenges. Recent breakthroughs in cloning and stem cell research have generated new hopes as well as presents considerable promise for treating severe diseases and regenerative medicine. In this regard, for advancements in biotechnology to be clinically applicable in medicine, it’s essential to comprehend both scientific principles and ethical implications, taken into consideration the scientific roadblocks impeding advancement in therapeutic cloning such as tumorigenicity, epigenetic reprogramming and interspecies pathogen transfer. As research in this area progresses, it will clarify that stem cells can be obtained from various sources, including therapeutic cloning, which involves cloning embryos from the nuclei of somatic cells or cloning individual organs in the laboratory. This article studies  the legitimacy extent of therapeutic cloning in Islamic Fiqh and comparative law, using the comparative analytical approach. Thus, we have reached a number of results, the most important of which is that the Islamic Fiqh perspective on the illegality of extracting stem cells by creating therapeutic embryos using Somatic Cell Nuclear Transfer (SCNT). It is deemed unacceptable to create an embryo for the purpose of its development and then destroying it for the purpose of stem cells, as this is unacceptable that turns the human being into a source for spare parts. Conversely, cloning specific organs and tissues in the laboratory for medical purposes is considered permissible, provided that it does not harm anyone or violate their sanctity that is consistent with many comparative laws.

This article evaluates the Didactic Strategies for Teaching Mathematics (DSTM) program, designed to enhance the teaching of mathematical content in primary and secondary education in a hybrid modality. In alignment with SENACYT’s Gender-STEM-2040 Policy, which emphasizes gender equality as a foundational principle of education, this study aims to assess whether initial teacher training aligns with this policy through the use of mathematical strategies promoting gender equality. A descriptive-correlational approach was applied to a sample of 64 educators, selected based on their responses during the training, with the goal of improving teaching and data collection methodologies. Findings indicate that, although most teachers actively engage in training, an androcentric approach persists, with sexist language and a curriculum that renders girls invisible, hindering the fulfillment of the National Gender Equality Policy in Science, Technology, and Innovation of Panama (Gender-STEM Policy 2040). Additionally, through a serendipitous finding, a significant gap in student activity levels, especially in secondary school, was discovered. While in primary school, activity levels were similar between genders, a decline in active participation among girls in secondary school was observed. This discovery, not initially contemplated in the study’s objectives, provides valuable insights into gender differences in active participation, particularly in higher educational stages. The serendipity suggests the need for further exploration of social, environmental, and family factors that may influence this decrease in girls’ active participation. The article concludes with a preliminary diagnosis and a call to deepen gender equality training and the effective implementation of coeducation in Panama’s educational system.

Currently, there is a unique situation in the global economy, industrial eras coexist together, there is interaction and transformation of financial systems simultaneously within the framework of Industry 4.0 and Industry 5.0. New, digital resources are entering the economy, intellectual capital is becoming virtual, artificial intelligence is increasingly finding its application in the structure of financial support. Financial intermediation in developing countries is also subject to global trends, the active development of new instruments for developing economies is especially important. The aim of the study is to identify effective ways to develop financial intermediation in Industry 5.0 for the economies of developing countries. Based on the results of the study on the development of financial institutions mediation revealed a problem related to the lack of reasonable tools that could be used to improving the efficiency of the financial intermediaries market, proposed the main directions of such a process: mobilization of savings, distribution financial assets, payment system, risk management and control over market agents involved in financial operations.

Since 1999, China’s higher education has experienced significant growth, with the government dramatically increasing college enrollment rates, thereby enhancing the overall quality of education. However, most existing studies have primarily focused on the quantity of education, with little attention having been given to the impact of higher education quality (HEQ) on economic growth. This study aims to explore how higher education quality (HEQ) contributes to regional economic growth through scientific and technological innovation (STI) and human capital accumulation. Using panel data from 31 Chinese provinces from the period 1999 to 2022, panel regression models and instrumental variable methods were employed to analyze both the direct and indirect impacts of higher education quality (HEQ) on economic growth. The results confirm that improving higher education quality (HEQ) is crucial for sustaining China’s economic growth. More specifically, higher education promotes regional economic expansion both directly, by enhancing labor productivity, and indirectly, by facilitating scientific and technological innovation. Furthermore, the study suggests that the balanced distribution of educational resources across regions should be prioritized to support coordinated regional development. This research provides insights for policymakers on how balanced regional economic development can be achieved through educational and technological policies. This work also lays a foundation for future studies.

This study examines the financial integration between Jordan and the BRIC economies (Brazil, Russia, India, and China) to determine whether long-term equilibrium relationships exist and to assess implications for portfolio diversification and policy. Drawing on daily stock index data from 01 January 2014, to 31 August 2024, the study employs econometric techniques, including Granger Causality tests, Johansen Cointegration, and Vector Autoregression (VAR). The stationarity of stock indices at the first difference level is confirmed through unit root testing. Results indicate minimal long-term cointegration between Jordan and BRIC markets, pointing to low integration and potential diversification benefits for institutional investors. However, short-term causal links—particularly between Jordan and the Russian and Indian markets—highlight these countries’ influence on Jordan’s stock fluctuations. The findings suggest that, in the absence of long-term cointegration, investors may mitigate risk by investing in less correlated markets, such as Jordan, while leveraging short-term partnerships with Russia and India. Additionally, the study provides valuable insights for business leaders considering strategic alliances with BRIC counterparts in sectors like technology, agriculture, and energy, and calls for future research into factors like regulatory frameworks and geopolitical stability that may limit long-term financial integration. These results have significant implications for institutional investors, business executives, and policymakers, suggesting targeted strategies for financial stability, risk mitigation, and economic collaboration.