The integration of Big Earth Data and Artificial Intelligence (AI) has revolutionized geological and mineral mapping by delivering enhanced accuracy, efficiency, and scalability in analyzing large-scale remote sensing datasets. This study appraisals the application of advanced AI techniques, including machine learning and deep learning models such as Convolutional Neural Networks (CNNs), to multispectral and hyperspectral data for the identification and classification of geological formations and mineral deposits. The manuscript provides a critical analysis of AI's capabilities, emphasizing its current significance and potential as demonstrated by organizations like NASA in managing complex geospatial datasets. A detailed examination of selected AI methodologies, criteria for case selection, and ethical and social impacts enriches the discussion, addressing gaps in the responsible application of AI in geosciences. The findings highlight notable improvements in detecting complex spatial patterns and subtle spectral signatures, advancing the generation of precise geological maps. Quantitative analyses compare AI-driven approaches with traditional techniques, underscoring their superiority in performance metrics such as accuracy and computational efficiency. The study also proposes solutions to challenges such as data quality, model transparency, and computational demands. By integrating enhanced visual aids and practical case studies, the research underscores its innovations in algorithmic breakthroughs and geospatial data integration. These contributions advance the growing body of knowledge in Big Earth Data and geosciences, setting a foundation for responsible, equitable, and impactful future applications of AI in geological and mineral mapping.

In this research, we explore the psychological factors that SMB owners who are micro-entrepreneurs and use SNS for entrepreneurial purposes rely on to make their self-employment decisions. Research-based on a merger of the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB) deals with how perceived ease of use (PEU), perceived usefulness (PU), attitude, subjective norms (SN), perceived behavioral control (PBC), openness to experience (OTE), and dominance contribute to people’s behavioural intention (BI) to use SNS for Data was collected from 342 SMB micro-entrepreneurs in the Delhi/NCR region of India by the means of a standardized questionnaire. Employing PLS-SEM, a partial least squares structural equation modeling was used to analyze the data. The results point out an impact of PU, attitude, and behavioral intention, and unappealing presentations, unacceptance of an explanation, unclear mechanisms, and domination do not make any difference. The research emphasizes how technophobe’s attitude, and the perception of effectiveness would impact micro-entrepreneurs desire to avail SNS for entrepreneurship efforts. Moreover, research shows the psychological understanding based on the SNS adoption by the small business owners, micro-entrepreneurs as well as for the practitioners and policymakers who are working to enhance the capability of the SMB. More investigations should be conducted on the other personality traits and cover more nations as demographic dividends in comparison to acquire more inclusive data.

Due to rising global environmental challenges, air/water pollution treatment technologies, especially membrane techniques, have been focused on. In this context, air or purification membranes have been considered effective for environmental remediation. In the field of polymeric membranes, high-performance polymer/graphene nanocomposite membranes have gained increasing research attention. The polymer/graphene nanomaterials exposed several potential benefits when processed as membranes. This review explains the utilization of polymer and graphene-derived nanocomposites towards membrane formation and water or gas separation or decontamination properties. Here, different membrane designs have been developed depending upon the polymer types (poly(vinyl alcohol), poly(vinyl chloride), poly(dimethyl siloxane), polysulfone, poly(methyl methacrylate), etc.) and graphene functionalities. Including graphene in polymers influences membrane microstructure, physical features, molecular permeability or selectivity, and separations. Polysulfone/graphene oxide nanocomposite membranes have been found to be most efficient with an enhanced rejection rate of 90%–95%, a high water flux >180 L/m²/h, and a desirable water contact angle for water purification purposes. For gas separation membranes, efficient membranes have been reported as polysulfone/graphene oxide and poly(dimethyl siloxane)/graphene oxide nanocomposites. In these membranes, N₂, CO₂, and other gases permeability has been found to be higher than even >99.9%. Similarly, higher selectivity values for gases like CO₂/CH₄ have been observed. Thus, high-performance graphene-based nanocomposite membranes possess high potential to overcome the challenges related to water or gas molecular separations.

The study’s purpose is to evaluate the influence of some factors of the model of planned behavior (TPB) and the perceived academic support of the university on the attitude toward entrepreneurship and entrepreneurial intention of students. The results of Structural Equation Modeling (SEM) linear structural model analysis with primary data collected from 1162 students indicated that entrepreneurial intention is influenced by attitude toward entrepreneurship, subjective norm, perceived educational support, and perceived concept development support. In addition, this study also found the positive influence of perceived educational support, concept development support, and business development support on attitude towards entrepreneurship. Interestingly, the influence of perceived business development support on entrepreneurial intention was rejected, and personal innovativeness is demonstrated to promote an attitude toward entrepreneurship. Notably, this study also highlights the moderating role of personal innovativeness on the relationship between attitude toward entrepreneurship and entrepreneurial intention. Based on these findings, several implications were suggested to researchers, universities, and policymakers.

This study examines how circular economy (CE) practices contribute to energy resilience by mitigating the impacts of energy shocks and supporting sustainable development. Through a systematic literature review (SLR) of recent studies, we analyze the ways in which CE strategies—such as resource recovery, renewable energy integration, and closed-loop supply chains—enhance energy security and reduce vulnerability to energy disruptions. Our research draws on academic databases, focusing on publications from 2018 to 2024, to identify key themes and practices that illustrate the transformative potential of the circular economy. Findings reveal that CE practices at macro, mezzo, and micro levels support resilience by fostering efficient resource use, reducing dependency on non-renewable energy sources, and promoting sustainable economic growth. Additionally, we highlight the roles of foreign direct investment (FDI), research and development (R&D), and supportive policies in accelerating the adoption of circular systems. The study concludes with recommendations for future research to address identified gaps, suggesting a roadmap for advancing circular economy practices as a means to enhance energy resilience and sustainability aims to reveal how wide array of factors affect transition towards more sustainable or circular economy.

This study investigates the interaction between audit firms and key audit matters (KAMs) to measure their impact on financial reporting quality in Palestine, thereby enriching the discourse on financial reporting. A descriptive statistical method was used to analyze the audit reports of listed Palestinian firms from 2018 to 2022. A methodology that scrutinizes the clarity and informativeness of KAMs across different audit firms and KAM types, the research investigates how audit procedures and risk assessments contribute to the comprehensibility of KAM disclosures. The findings highlight a significant disparity in the readability of KAMs attributable to audit firm selection, with the non-Big Four firms exhibiting distinct approaches. This understanding, gathered through multivariate analysis, offers valuable contributions to the ongoing discourse on financial reporting quality, emphasizing the essential role of audit firms in shaping the effectiveness of audit reports and KAM disclosures.