FACULTY OF PHYSICAL SCIENCE

This study examines impact of social media trends on the behavioural pattern of the Three local government areas of Benin Students. The study adopted the survey design using simple random sampling to source data from a sample of 400 respondents. The data collected was analysed using percentage and chi-square statistical technique. The Result shows that social media contribution impacts on the behavioural pattern of three local government areas Students in Edo State , social media platform impacts on students reading habit, social media trends affects daily relations of students in the Three local government areas. Social media trend impact on students’ academic performance in the Three local government areas. The study recommended that students should be monitored by teachers and parents on how they use these sites. Teachers should ensure they use the Social media as a tool to improve the academic performance of students in schools and students lifestyles. Students should better manage their study time in and prevent distractions that can be provided by the Social media. There should be a decrease in the number of time spent by students when surfing the net. Social Networking Sites should be expanded and new pages should be created to enhance academic activities and avoid setbacks in the students’ academic performance and students lifestyles. The students should create a balance between chit-chatting and academic activities. More attention should be directed to research. The use of Social media network by students should focus on the academic relevance of those sites instead of using them for negative purposes.

Designers and developers find themselves always using the same system for nearly all distinct projects they come across. Such act imply their limited knowledge in the
usability of alternative systems. Designers usually employ star rating system in all e- commerce platforms they work on. Meanwhile many e-commerce platforms are not the
same. Some are focused on different products and also have different brand personalities, and can significantly impact their branding with a tailored user interface. Star rating is effective, but limited in its ability to communicate certain information that can greatly influence consumer purchase decision and behaviour towards a product. Facial expression emoji rating have the potential to communicate such information and increase user satisfaction. This study compared the user experience of emoji and star rating systems using an e-commerce platform prototype. The findings inform designers, developers, and brand strategists in e-commerce field.

Background to the Study
National income measures the total value of all goods and services produced in a country in a year. It is the main way to know if an economy is growing or not (World Bank, 2020). For a country like Nigeria, understanding what makes national income rise or fall is very important for planning and improving the lives of its people.

The face-centered cubic (FCC) crystal structure is one of the most significant arrangements in materials science, particularly in metals such as aluminum, copper, and gold. This research explores the crystallographic arrangement of FCC atoms into distinct planes, emphasizing their geometric configuration, atomic packing, and the significance of close-packed structures. The study provides an in-depth analysis of Miller indices to describe the most prominent planes in FCC lattices, including the {111}, {110}, and {100} planes.

Elections are the cornerstone of democratic governance, enabling citizens to select leaders and influence policy direction. However, Nigeria’s electoral processes have been plagued by challenges such as vote tampering, lack of transparency, logistical inefficiencies, and voter disenfranchisement. These issues diminish public trust and undermine the credibility of election outcomes. To address these concerns, this project introduces a block chain-based voting system, leveraging the Ethereum blockchain and Solidity smart contracts to ensure decentralization, transparency, and immutability of election data. The proposed Voting App integrates a Solidity-based smart contract deployed on the Ethereum Sepolia testnet, handling essential voting processes such as voter registration, candidate management, secure vote casting, and real-time result verification. The smart contract ensures that votes are securely recorded on the blockchain, preventing tampering and enabling public verifiability. Voter authentication is strengthened through facial recognition technology and wallet-based verification using wallets such as MetaMask, ensuring that only verified voters can participate. The frontend, built with Next.js, interacts seamlessly with a Node.js backend and MongoDB database, providing a responsive and user-friendly experience. The system’s architecture supports robust election management, with administrative functions restricted to authorised personnel through role-based access controls. Performance evaluations demonstrated low-latency transaction processing, gas-efficient operations, and high scalability, while comprehensive security testing confirmed resilience against vulnerabilities such as reentrancy attacks and unauthorised access. Despite the current reliance on a local host environment for testing, future deployment on public blockchain networks and integration with national identification databases could revolutionise Nigeria’s electoral landscape. The Voting App presents a secure, transparent, and efficient alternative to traditional voting systems, showcasing the transformative potential of blockchain technology and Solidity smart contracts in delivering credible and inclusive democratic elections.

Effective management of financial flows is essential for sustaining liquidity stability and operational efficiency within multi-tier supply chain networks. Traditional optimisation models
tend to prioritise either cost reduction or risk mitigation, often neglecting the balance between
working capital efficiency and financial stability. This study proposes a Hybrid Mathematical Framework that integrates dynamic discounting mechanisms and risk mitigation strategies to optimise financial flows across supply chains. The framework addresses four primary objectives: developing a financial flow optimisation model, incorporating dynamic discounting into the
model, embedding stochastic variables representing demand volatility and credit risk, and
evaluating model performance through numerical simulations. A quantitative modelling approach is employed, formulating an objective function that minimises total financial costs while controlling for risk using Conditional Value at Risk (CVaR). The model integrates early payment incentives, late payment penalties, and financial risk thresholds to support strategic decision-making. Numerical simulations using synthetic financial data were conducted to assess the model’s performance. Results indicate that the Hybrid Model offers a superior trade-off between cost efficiency and financial stability. Dynamic discounting reduces total financial costs, while CVaR integration ensures liquidity remains risk-sensitive. The study recommends adopting dynamic discounting with risk-sensitive optimisation models and exploring technologies like real-time analytics and AI. Future research could refine the framework via industry-specific adaptations and block chain enabled contracts.

This study aims to design and implement a secure file-sharing platform that addresses the privacy, integrity, and access control challenges inherent in modern digital collaboration. The study highlights how mainstream cloud-based file-sharing solutions often compromise user privacy by lacking true End-to-End Encryption (E2EE) and failing to prevent the distribution of malicious files. This project introduces a web-based system that uses client-side encryption to ensure that only the sender and intended recipient can access file contents, even excluding the server from decryption capabilities. In addition, it integrates real-time malware detection using ClamAV and enforces a granular, per-file Access Control List (ACL) model to restrict file operations. Developed using a Python-based backend and the React JavaScript frontend, the system adopts a Zero-Trust architecture and defense-in-depth design to provide a strong and easy-to-use alternative to conventional file-sharing platforms. The solution not only enhances data privacy and threat prevention but also serves as a reference implementation for secure and accountable file sharing in both personal and organizational contexts. The project concludes with a set of practical recommendations and a comprehensive security assessment, demonstrating the system’s effectiveness against common web application threats and affirming the feasibility of privacy-first development without compromising usability.

The rapid expansion of local area networks (LANs) has brought about a significant increase in security vulnerabilities, making traditional firewalls insufficient against sophisticated internal and external threats. This project focuses on the Design and Implementation of an Intrusion Detection System (IDS) specifically engineered for LAN environments using packet sniffing techniques. The primary objective of this study is to develop a robust system capable of monitoring network traffic in real-time, identifying malicious patterns, and alerting administrators to potential security breaches. The methodology involves the use of raw socket programming or specialized libraries to capture data packets as they traverse the network interface. By analyzing these packets at the protocol level (TCP/IP), the system performs Signature-Based Detection to match traffic against known attack patterns and Anomaly-Based Detection to identify deviations from normal network behavior. The system was tested across various attack scenarios, including Denial of Service (DoS), unauthorized port scanning, and packet injection. Results from the implementation demonstrate that the IDS effectively captures and decodes packets with minimal latency, providing a high detection rate for common network-layer attacks. The study concludes that integrating packet sniffing into a localized IDS offers an essential layer of "defense-in-depth," providing network administrators with the visibility needed to maintain data integrity and availability. Recommendations include the integration of machine learning algorithms to improve the system's ability to detect zero-day vulnerabilities and the implementation of automated response protocols to mitigate threats instantly.

The surface free energy of nanoparticles is important as it gives us vital information about the reactivity and stability of nanoparticles. Starting from a previously reported equation, a theoretical model that involves a specific term for calculating the cohesive energy of nanoparticles, is established in a view to describe the surface free energy of metallic nanoparticles ( using different shapes of particle; sphere, cube and disk). The results show that the behaviour of surface free energy for spherical nanoparticles is the most realistic shape compared to disk and cubic shaped nanoparticles. As the surface free energy differs from shape to shape we also see that its value falls as the number of atoms (nanoparticle size) decreases. The results are in close agreement with the results of Fathi and Ayyad (2014).

Acalypha indica Linn. stem, a widely utilised medicinal plant in traditional health systems, was investigated for its phytochemical composition, anti-inflammatory, anti-diabetic, and anti-benign prostatic hyperplasia (BPH) activities. The stem bark was successfully extracted with ethyl acetate using cold maceration techniques. The phytochemical examination, antioxidant capacity, anti-inflammatory activity, glucose adsorption assay, and in vivo anti- BPH evaluation were carried out using established analytical methods.Phytochemical profiling using GC–FID revealed appreciable levels of phenolics, flavonoids and alkaloids, including ephedrine (19.21 mg/g), cortisol (10.06 mg/g), rutin (0.64 mg/g) and quercetin (0.50 mg/g), alongside phenolic compounds such as resveratrol (1.43 mg/g). The antioxidant potential were examined using Total Antioxidant Capacity (TAC) Assay. The extract
displayed concentration-dependent total antioxidant capacity, increasing from approximately 15%-19.7% across near 0–80 mg/mL concentration. In anti-inflammatory assessment, the extract significantly inhibited heat-induced haemolysis, with values increasing from approximately 45% to 55% inhibition at the highest concentration, indicating potent membrane-stabilising ability. In anti-diabetic evaluation, the glucose adsorption capacity of the extract ranged from 1.38–0.17 mM/g at (0–80 mg/mL glucose) concentration, having higher adsorption at 20mg/ml lower than acarbose (4.84–10.78 mM/g), but showing inconsistent adsorption behaviour across concentrations. In testosterone-induced BPH rats, the extract produced significant modulation of prostate biomarkers. Serum prostate specific antigen (PSA) decreased from 2.40 ± 0.64 ng/mL in testosterone induced BPH control to 1.37 ± 0.03, 1.07 ± 0.09 and 1.17 ± 0.15 ng/mL at 25, 50 and 100 mg/kg, respectively, approaching values similar to normal control at higher doses. dihydrotestosterone (DHT) levels reduced from 66.23 ± 11.03 ng/mL in testosterone induced BPH control to 47.70 ± 3.91, 38.40 ± 4.33 and 42.30 ± 5.08 ng/mL, while prostate volume and weight were markedly lowered, with 100 mg/kg producing the greatest reduction (0.06 ± 0.01 mL and 0.190 ± 0.01 g), comparable to finasteride -a standard control drug. All extract-treated groups showed consistent increases in body weight over 14 days, particularly at 50 and 100 mg/kg, indicating
good tolerance. The combined antioxidant, and anti-inflammatory activities demonstrated the protective ability of the extract against BPH-associated changes. These findings conclude that Acalypha indica stem extract possesses promising therapeutic
potential as a natural agent for the management of benign prostatic hyperplasia, warranting further toxicological and clinical investigations.