This study examined the effect of green accounting adoption on the firm value of quoted service  firms in Nigeria between 2015 and 2023. The study employed secondary data sourced from annual reports of 35 industrial firms listed on the Nigerian Stock Exchange. A quantitative research design using panel regression analysis was adopted. Findings revealed that green accounting adoption has a positive and significant effect on firm value (β = 0.438, t = 4.57, p < 0.01). Firm size also positively influenced firm value (β = 0.312, t = 3.21, p < 0.05), while leverage had a negative significant effect (β = -0.274, t = -2.89, p < 0.05). Firm age demonstrated a positive effect but was marginally significant (β = 0.142, t = 1.96, p = 0.051). Combined regression results indicated that green accounting adoption together with firm-specific factors explained 63% of the variation in firm value (Adjusted R² = 0.63, F = 15.74, p < 0.01). The study concludes that industrial firms adopting comprehensive environmental accounting and disclosure practices are likely to experience higher market valuation. The study recommends that Industrial firms should fully adopt and integrate green accounting practices into corporate reporting to enhance market valuation.

This position paper provided major highlights of the impact of highway banditry on the people residing along the Zamfara-Katsina highway, precisely Gusau-Funtua road in the North-Western part of Nigeria, taking into account the socio-economic influence of the area under discussion. The paper examined how banditry affected a series of economic activities, especially farming, which is known in the areas, and also conducted inquiries as to why armed banditry continues to transform beyond the time frame anticipated by Nigerians as a result of a series of operations and measures claimed to have been adopted by the Nigerian government. The paper adopted a mixed research methodology of literature review and oral interview with a view to comparing data collected from the field and its relationships with the findings contained in the existing literature.

This study aimed to determine the effectiveness of structured and unstructured laboratory approaches on the scientific comprehension and performance skills of Third Year High School students in one of the private secondary schools in Central Philippines towards Chemistry Subject. Quasi-experimental design with matched pairs and post-test only control and experimental groups was employed to 100 respondents who were assessed through comprehensive tests on the physical and chemical properties of matter and performance skill evaluations using teacher-made rubrics. T-test and Pearson Product Moment Correlation were applied at the 0.05 level of significance as the applied statistical tools. Findings revealed that students exposed to the unstructured laboratory approach achieved higher mean scores in scientific comprehension compared to those under the structured approach, both interpreted as satisfactory. Performance skills were also superior in the unstructured group, interpreted as Highly Skilled while the structures group was Highly Skilled. There were significant differences found in both comprehension and performance skills between the two approaches, endorsing the unstructured method.

Additionally, comprehension and performance skills under both approaches showed strong positive correlation which indicated that the cognitive and psychomotor domains complement each other in laboratory learning. The results suggest that unstructured laboratory activities promote stronger independence, critical thinking, and skill acquisition, underscoring their academic significance in Chemistry instruction. Recommendations involve organizational support for unstructured laboratory manuals, assimilation of lecture and laboratory schedules, and focus on safety and proactive student participation.

This study proposes a self-aware retrofitting framework for ground-supported steel petroleum storage tanks that integrates embedded structural sensing with Bayesian causal damage localization to predict and mitigate seismic buckling risk. Unlike conventional monitoring that reports damage after occurrence, the proposed system extracts causal indicators—energy localization, uplift activity, and shell softening gradients—from strain, acceleration, and uplift measurements and uses Bayesian inference to identify future-critical zones before global instability. A controlled low-variance synthetic benchmark is adopted to ensure numerical stability and isolate mechanism-driven effects across intensity-scaled ground motions. Results show that the self-aware intervention reduces mean buckling probability from 0.63 (baseline) to 0.17 and collapses normalized global response variance by approximately 22%, while enabling targeted strengthening with substantially lower material demand compared to uniform retrofitting. The findings demonstrate that adaptive structural intelligence can transform storage tanks from passive components into predictive, damage-aware infrastructure assets, providing a replicable pathway for resilient energy-system continuity under seismic uncertainty.