Background: This study investigates hairline patterns among the Etche people in Rivers State, Nigeria, with a focus on the distribution and variation in hairline shapes, lengths, and widths. Materials and Methods: Using a descriptive research design, data were collected from 227 participants through anthropometric measurements using a digital vernier caliper and measuring tape, assessing patterns by gender, age, and marital status. Results and Discussion: The results revealed that the most common hairline type was straight-lined (34.4%), followed by bell-shaped (30.8%) and widow’s peak (30%). The least common hairline patterns were low and high hairlines, each observed in only 0.4% of participants. The average hairline length and width were 61.98 mm and 293.89 mm, respectively, with males displaying longer and wider hairlines compared to females. Singles also showed greater hairline dimensions compared to married individuals. Conclusion: No significant variation was found in hairline characteristics by religious affiliation. These findings contribute valuable anthropometric data on the Etche population and highlight the role of genetic and environmental factors in shaping craniofacial features. The study fills a gap in anthropometric literature and provides a foundation for further genetic, medical, and cultural studies on Nigerian ethnic groups.

Diabetes mellitus (DM) is one of the most common diseases worldwide. Its effects on oral and dental health are well distinguished. As this disease is increasing worldwide, it is essential for dental care providers to be fully aware of the disease diagnosis and management and to deal with it confidently. This review discusses the oral manifestations and dental considerations that should be followed when treating patients with DM.

Open defaecation (OD) has been strongly linked to high prevalence of cholera and other sanitation-related diseases. This study was conducted to assess the effect of community-led total sanitation (CLTS) on sanitation facilities and the bacteriological quality of natural water sources in Cross River State. The study design was a community-based randomized controlled trial. A multi-stage sampling technique was used in selecting respondents. Data were collected from 744 respondents at pre- and post-intervention. A purposive sampling method was used in sampling natural water sources. Observational checklist and sterilized sample bottles were used in data collection. Data were analyzed using Statistical Product and Service Solution (SPSS version 24). Results were presented as frequencies, percentages and tables. The findings showed that respondents indicated that the major challenges of owning toilets (pre-intervention) were cost of constructing one 244 (32.8%), and distance of the toilet location 259 (34.8%) as major causes of OD practice. The same challenges were reported at post-intervention; as cost of construction 270 (36.3%) and distance of the toilet location 283 (38.0%). At pre-intervention, practice of OD was 253 (34.0%) among respondents who had no access to toilets but later reduced to 102 (13.7%) at post-intervention due to improved access to toilets. This infers that there was a statistically significant association between access to toilet and the reduction of OD practices due to the CLTS intervention. The test of hypothesis at both pre- (ϰ2 = 287.749; df = 1; P-value = 0.001) and post-intervention (ϰ2 = 8.334; df = 1; P-value = 0.001) was significant (P < 0.05). At pre-intervention, respondents with access to improved water sources were 119 (16.0%) which was improved to 569 (76.5%) at post-intervention, indicating that there was a statistically significant association between access to improved water sources and the reduction of sanitation-related diseases among respondents due to the CLTS intervention. Bacterial analysis showed that the total coliform and faecal coliform counts for all water samples exceeded the World Health Organisation (WHO) and the Nigerian Standard for Drinking Water Quality (NSDWQ) limits. Based on the findings, the CLTS intervention was effective in increasing knowledge of OD practice, changing wrong perceptions about OD and improving toilet ownership and maintenance. To scale-up the gains of this study, continued commitments to the eradication of OD practices from community members, community leaders, governments at all levels and NGOs is crucial.

This paper compares corporate governance frameworks in Saudi Arabia, Germany, the United Kingdom, and the United States, highlighting key similarities and differences. Saudi Arabia’s governance framework is shaped by Shariah principles and emphasizes shareholder protection, while Germany employs a dual-board system that prioritizes stakeholder engagement. The UK follows a principles-based approach, promoting flexibility, whereas the US adopts a rules-based system with strict regulatory oversight and shareholder accountability. The study examines key governance aspects, including board structures, shareholder rights, transparency, and regulatory compliance. Findings indicate that Saudi Arabia has made significant progress in aligning with international governance standards but still faces challenges in areas such as board independence, transparency, and investor protection. Compared to Germany’s stakeholder-oriented approach and the shareholder-centric models of the UK and US, Saudi governance remains more conservative, with room for improvement in corporate disclosure and regulatory enforcement. The paper concludes by identifying areas for reform in Saudi Arabia’s corporate governance, such as enhancing board independence, improving reporting standards, and increasing regulatory oversight. Aligning governance practices with global standards could strengthen investor confidence and corporate sustainability in the region.

Renal cell carcinoma (RCC), the most common form of kidney cancer, is often diagnosed incidentally through routine imaging or unexplained laboratory abnormalities. We report the case of a 62-year-old male with a medical history of type 2 diabetes mellitus, hypertension, dyslipidemia, and previously treated hepatitis C, who presented with an asymptomatic, mildly elevated alanine aminotransferase (ALT) level discovered during routine follow-up. Despite normal values for other liver enzymes, an abdominal ultrasound performed to investigate the abnormal ALT revealed a well-defined lesion in the left kidney. Further imaging with contrast-enhanced CT confirmed the presence of a renal mass, and histopathological evaluation following partial nephrectomy diagnosed clear cell RCC. This case illustrates the potential of minor ALT elevations as early indicators of extrahepatic malignancies such as RCC. It emphasizes the importance of thorough evaluation for persistent, unexplained ALT abnormalities, particularly in patients with metabolic risk factors or past hepatic conditions. Increasing evidence suggests a possible pathophysiological link between RCC and liver enzyme alterations, including cytokine release and hepatic congestion. Future studies are warranted to investigate the predictive value of ALT as a biomarker for RCC and the role of inflammatory mediators such as IL-6 in RCC-associated liver function changes.

The integration of Supervisory Control and Data Acquisition (SCADA) systems with Industrial Internet of Things (IIoT) technologies, cloud computing, and advanced cybersecurity measures is reshaping industrial automation. This paper presents a conceptual framework for smart SCADA systems, emphasizing the role of cloud connectivity for real-time monitoring, IIoT for enhanced data acquisition, and cybersecurity to safeguard critical infrastructure. The integration of these technologies enables improved operational efficiency, predictive maintenance, and remote accessibility, fostering more scalable and flexible industrial operations. However, challenges such as data security risks, interoperability, and system complexity remain prominent. The paper discusses theoretical models to address these challenges, proposing strategies for seamless integration and robust security mechanisms. Future trends such as edge computing, AI-driven analytics, and blockchain-based security are also explored as potential avenues for advancing SCADA systems. This paper contributes to the understanding of how these technologies converge to drive the future of industrial automation while addressing the complexities of data integrity and system resilience.

Ransomware attacks have become a significant cybersecurity threat, causing severe financial and operational damage to enterprises worldwide. Traditional security measures often fail to detect and mitigate these threats before they inflict harm. This paper explores the application of machine learning (ML) techniques for the early detection of ransomware attacks in enterprise networks. By analyzing network traffic patterns, system behaviors, and anomaly detection methods, ML models can identify suspicious activities indicative of ransomware execution. The study evaluates various supervised and unsupervised learning algorithms, including decision trees, support vector machines (SVM), deep learning, and clustering techniques. Experimental results demonstrate that ML-based approaches can enhance the accuracy and efficiency of ransomware detection, minimizing response times and reducing potential losses. The findings suggest that integrating machine learning into cybersecurity frameworks can significantly improve an organization’s resilience against ransomware threats.