The initiation of tapering, sparked by heightened inflation in the United States, reverberates across global markets, with notable implications for Indonesia. This study delved into the nuanced impact of tapering on Sharia-compliant stocks in both Indonesia and Malaysia. The rationale behind selecting Sharia stocks for analysis lies in their composition, featuring companies boasting low debt-to-asset and equity ratios, thereby positing robust resilience in the face of the Federal Reserve’s implementation of tapering. Employing a time series dataset with a weekly sampling period spanning from January to September 2022, the analysis adopted the Error Correction Model (ECM) within a multiple regression framework to circumvent potential spurious regression pitfalls. The results of this study indicate that the impact of tapering off policy in Indonesia has a positive impact in the short term and long term, while in Malaysia it tends to be insignificant in the short term and has a positive impact from the US 10-year bond yield variable and a negative impact from US 1-Year Treasury Bills. This result is interesting because it differs from the general theory. The causal factors include the agility of the Indonesian central bank in maintaining the benchmark interest rate spread with the Fed, the economic stability of both countries, and the increasing trend of coal, with Indonesia being one of the largest producers of the commodity. Investors, in navigating these intricate dynamics, may find strategic insights derived from this research invaluable for shaping their investment decisions. while government policymakers may use them as a reference for shaping policies related to Sharia stock investments, including the incorporation of artificial intelligence.

This research aims to analyze the relationship between financial literacy variables and financial inclusion, the relationship between financial literacy variables and financial technology, and the relationship between financial technology variables and financial inclusion. The analysis of this research is to learn more about how financial literacy and the use of financial technology influence financial inclusion. This type of research is associative quantitative. Next, the relationship between these variables is explained using statistical formulas. Consequently, the term for this research is “quantitative research”. The study population is the number of people who use financial services. For this sampling, the purposive random sampling method was used. The following criteria are determined in sampling: 1) Minimum age 17 years, this is intended to take the minimum age standard in sampling and is considered capable of understanding the contents of the questionnaire statements. 2) Have ever used financial services. In this study, 11 question items were used to measure 3 variables, so this study used the largest range, namely 231 respondents. The intervention variable will be used as a reference for the Partial Least Square (PLS) method to analyze this research data. This study uses a causal model (causal modelling, relationships, and influence) or path analysis. The hypothesis that will be discussed in this research is tested using the Structural Equation Model (SEM), which is operated with Smart PLS. The results of this research show that financial literacy has a positive and significant impact on financial inclusion in society. Financial literacy has a positive and significant impact on financial technology. financial technology has a positive and significant impact on financial inclusion, financial technology can offset the impact of financial literacy on financial inclusion. The results of this research are used as input for the community so that they pay more attention to their internal human resources related to financial products that can be used for investment. With knowledge of the right financial products, it is hoped that they can create good financial behaviour so that an awareness of the importance of carrying out good financial planning. For financial institutions, it is hoped that this can increase easy access to financial products and services, in particular credit for businesses as additional capital for the community.

This research delves into the urgent requirement for innovative agricultural methodologies amid growing concerns over sustainable development and food security. By employing machine learning strategies, particularly focusing on non-parametric learning algorithms, we explore the assessment of soil suitability for agricultural use under conditions of drought stress. Through the detailed examination of varied datasets, which include parameters like soil toxicity, terrain characteristics, and quality scores, our study offers new insights into the complexities of predicting soil suitability for crops. Our findings underline the effectiveness of various machine learning models, with the decision tree approach standing out for its accuracy, despite the need for comprehensive data gathering. Moreover, the research emphasizes the promise of merging machine learning techniques with conventional practices in soil science, paving the way for novel contributions to agricultural studies and practical implementations.

This review summarizes some of the recent advances related to shallow penetration conformance sealants (SPCS) based on cross-linked polymer nanocomposite gels. The cross-linked polymer nanocomposite gels formed a three-dimensional (3D) gel structure upon contact with either water or oil when placed at the downhole. Therefore, the cross-linked polymer nanocomposite gels offer a total or partial water shutoff. Numerous polymeric gels and their nanocomposites prepared using various techniques have been explored to address the conformance problems. Nevertheless, their instability at high temperature, high pressure, and high salinity down-hole conditions (HT-HP-HS) often makes the treatments unsuccessful. Incorporating inert particles into the cross-linked polymer nanocomposite gel matrices improves stability under harsh down-hole conditions. This review discusses potential polymeric nanocomposite gels and their successful application in conformance control.

Regional differentiation in the Russian Federation is considered to be high in terms of gross regional product (GRP) per capita level, growth rate, and other indicators. Inefficient use of region-specific spaces entails redistribution processes in order to maximize positive agglomeration effects throughout the country. These encompass economic restructuring based on production value-added chain extension and expanding inter-regional collaborative linkages. Besides, it is vital to assess the opportunities of individual Russian territories for participation therein. The research goal is to develop a scientifically based methodology to determine promising sectoral composition of the regional economies and that of spatial interactions. Such methodology would consider the feasibility of combining “smart” industrial specializations, regional resource potential, prevailing contradictions in the economic, innovative, and technological development of the country’s internal space. The proposed methodological approach opens the way to exploit the existing regional economic potential to the full, firstly, via establishing sectoral priorities of the region regarding the regulatory factors for the territorial capital to have a major effect on the increased potential GRP level; secondly, through benchmarking performance of the available development reserves within leading regions from homogeneous groups having similar characteristics and factor potentials; thirdly, via developing inter-regional integration prospects in terms of regional potential redistribution to ensure growth in potential gross domestic product. An extensive analytical and applied investigation of the proposed methodological approach was carried out from 2014 to 2020. Diversified estimates were obtained for a wide range of indicators due to evidences from 85 Russian regions and 13 types of economic activity. Such an integrated approach allows revealing actual imbalances and barriers that impede regional development, ensures the efficient use of production factors, and enables to trace ways to implement transformation policies and design effective regulatory mechanisms. The results provide arguments in favor of strengthening inter-regional connectivity and supporting inter-regional cooperation. This insight not only contributes to the academic discourse on complex development of a territory but also holds practical implications for policymakers and regional planners aimed at ensuring comprehensiveness and robustness of the evaluation supporting the decision-making process.

The Moroccan economy has undergone significant structural changes since the 1980s. Attracting Foreign Direct Investment (FDI) has been a key strategy for the country’s economic growth and development, particularly in some specific high value-added sectors, such as the automotive supply industry. This paper uses the results of a survey to examine the reasons why multinational enterprises (MNEs) in the automotive supply sector set up in Morocco. Our findings show that proximity to Europe and labor costs and skills are the most important considerations for investing in this sector in Morocco. However, some institutional issues are still of concern to these MNEs.