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.

Context: With the rapid development of the Fourth Industrial Revolution, legal violations in cyberspace are increasing, posing threats to information security and social order. Students majoring in National Defense and Security Education (NDSE) at Ho Chi Minh City University of Education (HCMUE) are required not only to have a clear understanding of cyber laws to protect themselves but also to possess sufficient knowledge to educate and raise awareness within the broader community. Findings: By employing practical survey methods, interviews, and observation, this study analyzes and evaluates the current awareness levels of NDSE students at HCMUE regarding cyber law violations. The survey results show that although students are aware of the illegality of such behaviors, they still engage in them due to gaps in their understanding of legal regulations and consequences. Discussion: Based on the findings, the study proposes several measures to enhance students' awareness of common cyber law violations, including promoting legal education on cyber violations; strengthening monitoring and enforcement of cyber regulations within the university; intensifying media coverage of cyber violations through social platforms; and fostering critical thinking and responsible information verification skills. Enhancing awareness not only encourages students to comply with the law but also contributes to building a safe and healthy online environment in line with national security demands in the digital era.

The research examines the application of Artificial Intelligence (AI) in waste management systems, using Bee'ah AI City Vision in Sharjah, UAE, as a case study. Research checks the application of advanced AI models, including long short-term memory (LSTM) network and transformer-based models, in adaptation to waste collection efficiency and sustainable urban rule. Conclusions display a 30% lower environmental footprint due to a 25% decrease in operating costs, waste volume prediction, and LSTM network in passage optimization. The transformer model also enabled a 20% increase in public satisfaction by increasing the accountability of services through emotion analysis. Research reflects AI's ability to increase operational efficiency, environmental stability, and governance in the public sector, as well as the main challenges, including AI decision-making data secrecy, algorithm bias, and transparency.

Smart Maintenance and Reliability Engineering (SMRE) in manufacturing leverages advanced technologies such as Industrial Internet of Things (IIoT), Artificial Intelligence (AI), and Machine Learning (ML) to enhance asset performance, reduce downtime, and optimize maintenance strategies. By integrating predictive maintenance, condition monitoring, and real-time data analytics, SMRE improves operational efficiency and extends equipment lifespan. This paper explores the role of digital twins, cloud computing, and cyber-physical systems in revolutionizing maintenance practices. The study also discusses challenges, implementation strategies, and future trends in smart maintenance for sustainable and resilient manufacturing systems.

Earthquakes are among the hidden forces that threaten human life and the future of civilization. Earthquakes can result in landslides, ground shaking, fires, fissures, structural damage to buildings, tsunamis and damage to highways and bridges. The extent of destruction and suffering caused by an earthquake depends on: duration, magnitude, and intensity. And with the technological progress and studies in space sciences, the Earth did not receive the attention of studies and researches, especially that related to pre-earthquakes prediction. This paper presents a brief study of some modern methods for pre-earthquakes prediction through study of physical changes in the Earth's atmosphere, especially in the ionosphere.

The reshoring of American industries has become a strategic priority to enhance domestic manufacturing resilience, reduce supply chain dependencies, and drive economic growth. Advanced lean manufacturing principles, coupled with automation, present a transformative approach to achieving cost-effective and sustainable production. This research explores the integration of smart automation, robotics, and digital lean methodologies to improve efficiency, reduce waste, and optimize operations in reshoring initiatives. By leveraging Industry 4.0 technologies such as cyber-physical systems, artificial intelligence, and real-time data analytics, manufacturers can achieve higher productivity while maintaining flexibility and quality. The study aims to identify the key enablers, challenges, and impact of advanced lean automation on reshoring efforts. Additionally, it investigates how digital lean tools and automated systems contribute to competitiveness, workforce development, and supply chain resilience in the U.S. manufacturing sector.

Metal implants are commonly used in orthopedics for treating degenerative conditions and fractures. These materials are generally considered non-toxic. However, rare instances of malignancy linked to certain implants have been documented in the literature. The formation of high-grade sarcoma on orthopedic implants is an exceptionally rare complication. In this report, we present the case of an unclassified high-grade sarcoma in a 51-year-old patient to highlight the rarity of this condition and the challenges associated with its diagnosis.