In higher eukaryotes, the genes’ architecture has become an essential determinant of the variation in the number of transcripts (expression level) and the specificity of gene expression in plant tissue under stress conditions. The modern rise in genome-wide analysis accounts for summarizing the essential factors through the translocation of gene networks in a regulatory manner. Stress tolerance genes are in two groups: structural genes, which code for proteins and enzymes that directly protect cells from stress (such as genes for transporters, osmo-protectants, detoxifying enzymes, etc.), and the genes expressed in regulation and signal transduction (such as transcriptional factors (TFs) and protein kinases). The genetic regulation and protein activity arising from plants’ interaction with minerals and abiotic and biotic stresses utilize high-efficiency molecular profiling. Collecting gene expression data concerning gene regulation in plants towards focus predicts an acceptable model for efficient genomic tools. Thus, this review brings insights into modifying the expression study, providing a valuable source for assisting the involvement of genes in plant growth and metabolism-generating gene databases. The manuscript significantly contributes to understanding gene expression and regulation in plants, particularly under stress conditions. Its insights into stress tolerance mechanisms have substantial implications for crop improvement, making it highly relevant and valuable to the field.

Silymarin, a bioactive compound derived primarily from the seeds and fruit of the milk thistle (Silybum marianum) plant, has garnered increasing attention in recent years due to its potential applications in agriculture. This comprehensive review explores the multifaceted role of silymarin in agricultural practices, shedding light on its chemistry, biological activities, and diverse applications. The chemical structure and properties of silymarin are elucidated, emphasizing its unique solubility, stability, and bioavailability, which render it suitable for agricultural use. A significant portion of the review is dedicated to examining the biological activities of silymarin, which encompasses its antioxidant properties. The underlying mechanisms responsible for these activities are explored, highlighting their potential as a natural solution for mitigating environmental stressors that adversely affect crop health and productivity. Illustrative examples from research studies and practical applications underscore its effectiveness in safeguarding agricultural yields and ensuring food security. Furthermore, the review delves into the potential of silymarin to enhance crop growth, yield, and quality. Mechanisms through which silymarin influences plant physiology and metabolism are examined, providing valuable insights into its role as a growth-promoting agent in agriculture. The review concludes with a forward-looking examination of the prospects of silymarin in agriculture, highlighting emerging trends and areas of innovation that hold promise for sustainable and resilient farming systems. In summary, this review consolidates the current body of knowledge surrounding silymarin’s potential in agriculture. It underscores the versatility of silymarin as a natural tool for crop protection, growth enhancement, and environmental sustainability, offering valuable insights for researchers, practitioners, and policymakers seeking innovative approaches to address the challenges of modern agriculture.

Horticultural crops are rich in constituents such as proteins, carbohydrates, vitamins, and minerals important for human health. Under biotic and abiotic stress conditions, rhizospheric bacteria are powerful sources of phytohormones such as indole acetic acid (IAA), gibberellic acid (GA), abscisic acid (ABA) and Plant growth regulators including cytokines, ammonia, nitrogen, siderophores, phosphate, and extra cellular enzymes. These phytohormones help horticultural crops grow both directly and indirectly. In recent agricultural practices, the massive use of chemical fertilizers causes a major loss of agricultural land that can be resolved by using the potent plant growth-promoting rhizospheric bacteria that protect the agricultural and horticultural crops from the adverse effect of phytopathogens and increase crop quality and yield. This review highlights the role of multifunctional rhizospheric bacteria in the growth promotion of horticultural crops in greenhouse conditions and agricultural fields. The relevance of plant growth hormones in horticultural crops highlighted in the current study is crucial for sustainable agriculture.

This study aims to identify the impact of inheritance literacy, inheritance socialization, inheritance stress, and peer influence on the inheritance behaviors among FELDA communities in Malaysia. Inheritance literacy pertains to individuals’ comprehension of wealth transfer and estate planning, while peer influencer evaluates friends’ impact on inheritance attitudes; inheritance socialization explores family interactions’ role in shaping inheritance attitudes, and inheritance stress measures emotional strain in inheritance matters, with inheritance behaviors encompassing asset management and wealth transfer decisions for future generations by individuals and families. Understanding inheritance behaviors is crucial, as it helps individuals depict their inheritance knowledge and attitudes toward FELDA inheritance better, fostering a more favorable inheritance attitude. Through self-administered survey questionnaires, data related to FELDA communities are obtained using convenience sampling from 413 respondents. This study applies Partial Least Squares Structural Equation Modeling (PLS-SEM) technique to test the research hypotheses. The present study’s outcome confirms that two determinants, which are inheritance literacy and inheritance socialization significantly influence the inheritance behavior of FELDA communities. However, inheritance stress and peer influence determinants have statistically insignificant influence inheritance behavior. This study’s theoretical framework enriches the discussions on wealth management and financial behavior by refining and expanding upon existing financial behavior theories to incorporate inheritance-specific behaviors. The present study is exclusive in its effort to ascertain the relative importance of both inheritance behavior and the FELDA communities. This paper will assist the government, inheritance service providers, and policymakers in offering innovative economic schemes and designing policies that may enhance the inheritance behavior wellbeing of FELDA communities. This article also provides a roadmap to guide future research in this area.

In this paper, the characteristic behavior of the disc consisting of thermoplastic composite CF/PA6 material was considered. Analysis was made by taking into account the usage areas of the materials and referring to certain temperatures between 30 ℃ and 150 ℃. Composite materials are lightweight; they show high strength. For these reasons, they are preferred in technology, especially in the aircraft and aerospace industry. With this study, the radial and tangential stresses determined within a certain temperature The temperatures were determined and compared with previous studies in the literature. According to the results obtained, it is believed that the thermoplastic composite CF/PA6 disc design can be used in engineering.

This study thoroughly examined the use of different machine learning models to predict financial distress in Indonesian companies by utilizing the Financial Ratio dataset collected from the Indonesia Stock Exchange (IDX), which includes financial indicators from various companies across multiple industries spanning a decade. By partitioning the data into training and test sets and utilizing SMOTE and RUS approaches, the issue of class imbalances was effectively managed, guaranteeing the dependability and impartiality of the model’s training and assessment. Creating first models was crucial in establishing a benchmark for performance measurements. Various models, including Decision Trees, XGBoost, Random Forest, LSTM, and Support Vector Machine (SVM) were assessed. The ensemble models, including XGBoost and Random Forest, showed better performance when combined with SMOTE. The findings of this research validate the efficacy of ensemble methods in forecasting financial distress. Specifically, the XGBClassifier and Random Forest Classifier demonstrate dependable and resilient performance. The feature importance analysis revealed the significance of financial indicators. Interest_coverage and operating_margin, for instance, were crucial for the predictive capabilities of the models. Both companies and regulators can utilize the findings of this investigation. To forecast financial distress, the XGB classifier and the Random Forest classifier could be employed. In addition, it is important for them to take into account the interest coverage ratio and operating margin ratio, as these finansial ratios play a critical role in assessing their performance. The findings of this research confirm the effectiveness of ensemble methods in financial distress prediction. The XGBClassifier and RandomForestClassifier demonstrate reliable and robust performance. Feature importance analysis highlights the significance of financial indicators, such as interest coverage ratio and operating margin ratio, which are crucial to the predictive ability of the models. These findings can be utilized by companies and regulators to predict financial distress.