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.

This study investigates the impact of corporate carbon performance on financing costs, focusing on S&P 500 companies from 2015 to 2022. Utilizing a fixed-effects regression model, the research reveals a complex U-shaped nonlinear relationship between carbon intensity (CI) and cost of debt (COD). The sample comprises 2896 firm-year observations, with CI measured by the ratio of Scope 1 and 2 greenhouse gas (GHG) emissions to annual sales. The findings indicate that companies with higher CI initially face increased COD due to heightened regulatory and operational risks. However, as CI falls below a certain threshold, further reductions in emissions can paradoxically lead to increased COD, likely due to the substantial investments required for advanced technologies. Additionally, a positive relationship between CI and cost of equity (COE) is observed, suggesting that shareholders demand higher returns from companies with greater environmental risks. These results underscore the importance of balancing short-term and long-term environmental strategies. The study highlights the need for corporate managers to communicate the long-term benefits of environmental efforts effectively to creditors and investors. Policymakers should consider these dynamics when designing regulations that incentivize lower carbon emissions.

Desert environments face the challenge of promoting sustainable tourism while balancing economic growth with cultural and environmental preservation. In the context of rapid global tourism expansion, effective destination management becomes crucial for positive economic impact and long-term preservation. This study aims to identify key factors influencing the sustainability of tourism. It explores the interactions between local stakeholders, the supply of tourism products and services, and tourism governance. Utilizing structural equation modeling through the PLS-SEM method, data was collected from 150 stakeholders in desert environments. The findings reveal that the involvement of local tourism stakeholders and the supply of tourism products and services significantly impact sustainable tourism in the desert environment. However, we observe a lack of influence between tourism governance and sustainable desert tourism. The novelty of the study lies in the identification of promotional factors for sustainable desert tourism. The originality of this study lies in its in-depth exploration of the mechanisms for promoting sustainable tourism.

Primary reason for interpretation the paper was the creation of a starting position for setting up e-learning in the structures of the executive forces of the Slovak Republic, which absent in the current dynamic environment. Problems with education arose mainly in connection with the global problem of Europe, such as the influence of illegal migrants, and it was necessary to retrain a large number of police officers in a short time. We reflect on the combined model of LMS Moodle and proctored training through MS TEAMS and their active use in practice. We focused on the efficiency in the number of participants in individual trainings and costs per participant according to the field of training. We compared the processed data with the costs of the pilot introduction of analytical organizational unit providing e-learning and interpreted the positive results in the application of e-learning compared to conventional (face-to-face) educational activities. As a basic (reference) comparative indicator, the costs of educational activities of selected organizational unit of state institution represented by own educational organizations and the number of trained employees for the periods in question were chosen. To measure effectiveness, we set financial—cost KPIs. Our findings clearly demonstrated that it is possible to significantly optimize costs when changing the current form of ICT education to e-learning. The implementation of another educational activities form of education, e-learning, within public institutions, according to the results of the analysis, can simplify and at the same time make education processes more efficient in the context of individual subjects of the Ministry of the Interior of the Slovak Republic.

This study investigates how corruption impacts sustainability in African countries. Using public databases, the research draws on the African Development Bank’s corruption indicators and the World Bank’s financial inclusion metrics. The findings reveal that as financial inclusion increases, particularly through the use of digital financial services, perceptions of corruption decrease. However, economic growth paradoxically correlates with an increased perception of corruption due to rising consumption demands. The study concludes that promoting financial literacy, along with robust governance, is essential for combating corruption and fostering sustainable development.

The idea of emotions that is concealed in human language gives rise to metaphor. It is challenging to compute and develop a framework for emotions in people because of its detachment and diversity. Nonetheless, machine translation heavily relies on the modeling and computation of emotions. When emotion metaphors are calculated into machine translation, the language is significantly more colorful and satisfies translating criteria such as truthfulness, creativity and beauty. Emotional metaphor computation often uses artificial intelligence (AI) and the detection of patterns and it needs massive, superior samples in the emotion metaphor collection. To facilitate data-driven emotion metaphor processing through machine translation, the study constructs a bi-lingual database in both Chinese and English that contains extensive emotion metaphors. The fundamental steps involved in generating the emotion metaphor collection are demonstrated, comprising the basis of theory, design concepts, acquiring data, annotating information and index management. This study examines how well the emotion metaphor corpus functions in machine translation by proposing and testing a novel earthworm swarm-tunsed recurrent network (ES-RN) architecture in a Python tool. Additionally, the comparison study is carried out using machine translation datasets that already exist. The findings of this study demonstrated that emotion metaphors might be expressed in machine translation using the emotion metaphor database developed in this research.