Social Services are vital for addressing adversity and safeguarding vulnerable individuals, presenting professionals with complex challenges that demand resilience, recovery, and continual learning. This study investigates Organizational Resilience within Community Social Services, focusing on strategic planning, adaptive capacity, and user perspectives. A cross-sectional study involved 534 professionals and service users from Community Social Services Centers in Spain. Centers were selected based on the characteristics of their population and the representativeness of their geographic location. The study utilized the Benchmark Resilience Tool (BRT) to evaluate Organizational Resilience and the SERVPERF questionnaire to gauge user-perceived service quality. The results demonstrate satisfactory levels of Organizational Resilience and user satisfaction, while also highlighting key areas for enhancing resilient strategies: reinforcement of personnel for thinking outside the box or in the resources available to the organization to face unexpected changes. These findings suggest the need to develop and optimize measures that improve the organization’s ability to adapt to and recover from adverse situations, ensuring a positive user experience. Emphasizing the importance of resilience in Social Services as a quality predictor, future research should explore innovative strategies to bolster Organizational Resilience. The findings emphasize the need to strengthen resilience in Social Services, enhancing practice, policy, and adaptability to support vulnerable populations.

Nigeria’s palm oil processing industry poses significant environmental pollution risks, jeopardizing the country’s ability to meet the UN’s 17 Sustainable Development Goals (SDGs) by 2030. Traditional processing methods generate palm oil mill effluent (POME), contaminating soil and shallow wells. This study investigated water samples from five locations (Edo, Akwa-Ibom, Cross River, Delta, and Imo states) with high effluent release. While some parameters met international and national standards (WHO guidelines, ASCE, NIS, and NSDWQ) others exceeded acceptable limits, detrimental to improved water quality. Results showed, pH values within acceptable ranges (6.5–8.5), high total conductivity and salinity (800–1150 µS/cm), acceptable hardness values (200–300 mg/L), nitrite concentrations (10–45 mg/L), excessive magnesium absorption (> 50 mg/L), biochemical oxygen demand (BOD) indicating significant pollution (75–290 mg/L), total dissolved solids (TDS) exceeding safe limits in four locations, total solids (TS) exceeding allowable limits for drinking water (310–845 mg/L), water quality index (WQI) values ranged from “poor” to “very poor”. POME contamination by metals like magnesium, nitrite, chloride, and sodium compromised shallow well water quality. Correlation analysis confirmed robust results, indicating strong positive correlations between conductivity and TDS (r = 0.85, p < 0.01) and pH and total hardness (r = 0.65, p < 0.05). The study emphasizes the need for environmentally friendly palm oil processing methods to mitigate pollution, ensure safe drinking water, and achieve Nigeria’s SDGs. Implementation of sustainable practices is crucial to protect public health and the environment.

Mediating role of artificial intelligence in the relationship between higher education quality and scientific research ethics among faculty members: A Study in carrying out the study, specific research objectives were derived, and based on the derived objectives, null hypotheses were formulated and tested for the study. This study, thus, employed survey research design. This study’s population comprised postgraduate students from Middle Eastern University, Jordan, with 1200 students. Using the population, a sample size of 291 respondents was selected based on Krecie and Morgan The students in the sample completed Google Forms questionnaires. The data were statistically processed, and the analysis’s most significant level was 0.25. The research questions were analyzed using descriptive statistics, and the null hypothesis was tested using Pearson Product Moment Correlational Analysis (PPMC). Also, the study showed a significant relationship between artificial intelligence and the quality of higher education and the relationship of significance between artificial intelligence and ethics in scientific research. The researcher suggested a need for ongoing education, cross-discipline cooperation, and the development of solid ethical frameworks for the integration ethics of AI academia.

Physical sampling of water on site is necessary for various applications like drinking water quality checking in lakes and checking for contaminants in freshwater systems. The use of water surface vehicles is a promising technology for monitoring and sampling water bodies, and they offer several advantages over traditional monitoring methods. This project involved designing and integrating a drone controller, water collection sampling contraption unit, and a surveillance camera system into a water surface vehicle (WSV). The drone controller unit is used to operate the boat from the starting location until the location of interest and then back to the starting location. The drone controller has an autopilot system where the operator can set a course and be able to travel following the path set, whereas the WSV will fight the external forces to keep itself in the right position. The water collection sampling unit is mounted onto WSV so when it travels to the location, it can start collecting and holding water samples until it returns to the start location. The field of view (FOV) surveillance camera helps the operator to observe the surrounding location during the operation. Experiments were conducted to determine the operational capabilities of the robot boat at the Ayer Keroh Lake. The water collection sampling contraption unit collected samples from 44 targeted areas of the lake. The comprehensive examination of 14 different water quality parameters were tested from the collected water samples provides insights into the factors influencing the pollution and observation of water bodies. The successful design and development of a water surface surveillance and pollution tracking vehicle marks the key achievements of this study. The developed collection and surveillance unit holds the potential for further refinement and integration onto various other platforms. They are offering valuable assistance in water body management, coastal surveillance, and pollution tracking. This system opens up new possibilities for comprehensive water body assessments, contributing to the advancement of sustainable and efficient water testing. Through careful sampling efforts, a thorough overview of the substances presents in the water collected from Ayer Keroh Lake has been compiled. This in-depth analysis provides important insights into the lake’s current condition, offering valuable information about its ecological health.

This study examines the determinants of audit quality and their impact on detecting financial statement fraud at public accounting firms member of OAI Solusi Manajemen Nusantara in Indonesia. Using a quantitative approach, data was collected through a structured questionnaire distributed to auditors and staff. Key findings highlight the significant influence of auditor independence, professional proficiency, and supervision actions on conducting effective audits, thereby enhancing fraud detection capabilities. The research identifies challenges such as the focus on Indonesian firms and potentially limiting broader applicability. Recommendations include enhancing auditor training, adopting stringent audit procedures and technology, and ensuring adherence to auditing standards to improve audit quality and uphold financial reporting integrity. This study underscores the critical role of audit quality in preventing and detecting financial statement fraud, suggesting avenues for future research to explore additional influencing factors.

Given the multifaceted nature of crime trends shaped by a range of social, economic, and demographic variables, grasping the fundamental drivers behind crime patterns is pivotal for crafting effective crime deterrence methodologies. This investigation adopted a systematic literature review technique to distill thirty key factors from a corpus of one hundred scholarly articles. Utilizing the Principal Component Analysis (PCA) for diminishing dimensionality facilitated a nuanced understanding of the determinants deemed essential in influencing crime trends. The findings highlight the necessity of tackling issues such as inequality, educational deficits, poverty, unemployment, insufficient parental guidance, and peer influence in the realm of crime prevention efforts. Such knowledge empowers policymakers and law enforcement bodies to optimize resource allocation and roll out interventions grounded in empirical evidence, thereby fostering a safer and more secure societal environment.