Gender inequality is a structural social problem, associated with history, culture, education, religion and politics, this difficulty occurs in all social institutions due to the heterogeneity of the structure in the sexual division of labor, socioeconomic inequality, inclusion and inequity in participation in the public space between men and women. Public policies and attitudes towards gender equality in Peruvian university students were analyzed according to socio-academic variables. A descriptive-comparative study, with a quantitative approach, and not experimental cross-sectional, involved 776 university students from a public and a private university in Peru, intentionally selected. Adaptive attitudes (57.9%) were found to tend to be sexist; Likewise, in the study dimensions, the same trend was found in the sociocultural and relational levels, while in the personal dimension students develop sexist attitudes (62.4%). It is concluded, attitudes towards gender equality are sexist reproduction that is influenced by the sociocultural environment of the family, this situation occurs to a greater extent in men, while female students present attitudes of equality in greater intensity to seek equity in the distribution of roles.

In Costa Rica, there is no explicit recommendation from the competent authorities for the use of a specific phantom, so experts must explore what suppliers offer, among which the Normi Mam Digital phantom from PTW stands out. This article presents the results of the dosimetry and image quality control applied to the Normi Mam Digital phantom to validate it as equipment that complies with the recommendations of the Human Health Series No. 17. The results obtained were satisfactory, proving that the equipment complies with the tolerances recommended by international health bodies.

Objective: This research analyzed the psychometric properties of the Ambivalent Classism Inventory (ICA) in Peru. Methodology: A critical review of literature related to poverty, inequality, and structural gaps was conducted, involving 882 participants aged 14 to 89 years (M = 24.61, SD = 9.07). Results: Exploratory-confirmatory factor analyses were satisfactory, finding a similar factorial structure to the original scale and the adaptation (hostile classism, protective paternalism, and complementary class differentiation). Regarding items, there was a reduction, leaving only 12; however, comparing alternative models, the three-factor structure with 12 reagents showed adequate fit (χ² = 214.588, df = 51, p < 0.001; CFI = 0.996; RMSEA = 0.060; SRMR = 0.033), allowing for invariance testing. Practical Implications: The scale allows for investigating attitude profiles of individuals with privileged social class. Contribution: The instrument is a valuable contribution, considering that the nation has a high poverty rate, leading to economic, political, and social inequality among the population.

The purpose of this study is to investigate different factors associated with remote online home-based learning (thereafter named OHL), including technical system quality, perceived quality of contents, perceived ease of use, and perceived usefulness in relation to the satisfaction of undergraduate students following the post-COVID-19 pandemic in Malaysia. Additionally, the mediating roles of attitude are also investigated. Two hundred questionnaires were distributed using judgmental sampling method and 156 completed responses were collected. The data were subsequently analyzed using PLS-SEM. The findings imply that the OHL system is an effective method although it is challenging to operate. In terms of perceived technical system quality, OHL is currently more gratifying for students; however, some have reported that the quality of the content delivered via the remote system is still unsatisfactory. Moreover, the study found that attitude is a significant determinant of undergraduates’ satisfaction with OHL. This study contributes to the advancement of current knowledge by inspecting the factors of the Undergraduate Level OHL System using the mediating roles of attitude. In terms of underpinning theories, Technology Acceptance Model and Information System Model were employed as the guiding principles of the current study.

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 study examines the relationship between macroeconomic determinants and education levels in eight selected African oil-exporting countries (AOECs) over the period 2000–2022. Drawing on human capital theory, the paper scrutinizes the impact of factors such as income inequality, health outcome, economic growth, human development, unemployment, education expenditure, institutional quality, and energy consumption on education levels. Employing robust estimation techniques such as fixed effects (FE), random effects (RE), pooled mean group (PMG) and cross-section autoregressive distributed lag model (CS-ARDL), the study unveils vital static and dynamic interactions among these determinants and education levels. Findings reveal notable positive and significant connections between education levels and some of the variables—human capital development, institutional quality, government expenditure on education, and energy consumption, while income inequality demonstrates a consistent negative relationship. Unexpectedly, health outcomes exhibit a negative impact on education levels, warranting further investigation. Furthermore, the analysis deepens understanding of long-run and short-run relationships, highlighting, for example, the contradictory impact of gross domestic product (GDP) and unemployment on education levels in AOECs. Finally, the study recommends targeted human development programs, enhanced public investment in education, institutional reforms for good governance, and sustainable energy infrastructure development.