The rapid expansion of smart cities has led to the widespread deployment of Internet of Things (IoT) devices for real-time data collection and urban optimization. However, these interconnected systems face critical cybersecurity risks, including data tampering, unauthorized access, and privacy breaches. This paper proposes a blockchain-based framework designed to enhance the security, integrity, and resilience of IoT data in smart city environments. Leveraging a private blockchain, the system ensures decentralized, tamper-proof data storage, and transaction verification through digital signatures and a lightweight Proof of Work consensus mechanism. Smart contracts are employed to automate access control and respond to anomalies in real time. A Python-based simulation demonstrates the framework’s effectiveness in securing IoT communications. The system supports rapid transaction validation with minimal latency and enables timely detection of anomalous patterns through integrated machine learning. Evaluations show that the framework maintains consistent performance across diverse smart city components such as transportation, healthcare, and building security. These results highlight the potential of the proposed solution to enable secure, scalable, and real-time IoT ecosystems for modern urban infrastructures.

Improving the practical skills of Science, Technology, Engineering and Mathematics (STEM) students at a historically black college and university (HBCU) was done by implementing a transformative teaching model. The model was implemented on undergraduate students of different educational levels in the Electrical Engineering (EE) Department at HBCU. The model was also extended to carefully chosen high and middle schools. These middle and high school students serve as a pipeline to the university, with a particular emphasis on fostering growth within the EE Department. The model aligns well with the core mission of the EE Department, aiming to enhance the theoretical knowledge and practical skills of students, ensuring that they are qualified to work in industry or to pursue graduate studies. The implemented model prepares students for outstanding STEM careers. It also increases enrolment, student retention, and the number of underrepresented minority graduates in a technology-based workforce.

In higher eukaryotes, the genes’ architecture has become an essential determinant of the variation in the number of transcripts (expression level) and the specificity of gene expression in plant tissue under stress conditions. The modern rise in genome-wide analysis accounts for summarizing the essential factors through the translocation of gene networks in a regulatory manner. Stress tolerance genes are in two groups: structural genes, which code for proteins and enzymes that directly protect cells from stress (such as genes for transporters, osmo-protectants, detoxifying enzymes, etc.), and the genes expressed in regulation and signal transduction (such as transcriptional factors (TFs) and protein kinases). The genetic regulation and protein activity arising from plants’ interaction with minerals and abiotic and biotic stresses utilize high-efficiency molecular profiling. Collecting gene expression data concerning gene regulation in plants towards focus predicts an acceptable model for efficient genomic tools. Thus, this review brings insights into modifying the expression study, providing a valuable source for assisting the involvement of genes in plant growth and metabolism-generating gene databases. The manuscript significantly contributes to understanding gene expression and regulation in plants, particularly under stress conditions. Its insights into stress tolerance mechanisms have substantial implications for crop improvement, making it highly relevant and valuable to the field.

This study employs a transfer matrix, dynamic degree, stability index, and the PLUS model to analyze the spatiotemporal changes in forest land and their driving factors in Yibin City from 2000 to 2022. The results reveal the following: (1) The land use in Yibin City is predominantly characterized by cultivated land and forest land (accounting for over 95% of the total area). The area of cultivated land initially increased and then decreased, while forest land continued to decline and construction land expanded significantly. The rate of forest land loss has slowed (with the dynamic degree decreasing from −0.62% to −0.04%), and ecosystem stability has improved (the F-value increased from 2.27 to 2.9). The conversion of cultivated land to forest land is the primary driver of forest recovery, whereas the conversion of forest land to cultivated land is the main cause of reduction; (2) cultivated land is concentrated in the central and northeastern regions, while forest land is distributed in the western and southern mountainous areas. Construction land is predominantly located in urban areas and along transportation routes. Areas of forest land reduction are mainly found in the central and southern regions with rapid economic development, while areas of forest land increase are concentrated in high-altitude zones or key ecological protection areas. Stable forest land is distributed in the western and southern ecological conservation zones; (3) changes in forest land are primarily influenced by annual precipitation, elevation, and distance to rivers. Road accessibility and GDP have significant impacts, while slope, annual average temperature, and population density exert moderate influences. Distance to railways, aspect, and soil type have relatively minor effects. The findings of this study provide a scientific basis for the sustainable management of forest resources and ecological conservation in Yibin City.

Hospital waste containing antibiotics is toxic to the ecosystem. Ciprofloxacin is one of the essential, widely used antibiotics and is often detected in water bodies and soil. It is vital to treat these medical wastes, which urge new research towards waste management practices in hospital environments themselves. Ultimately minimizes its impact in the ecosystem and prevents the spread of antibiotic resistance. The present study highlights the decomposition of ciprofloxacin using nano-catalytic ZnO materials by reactive oxygen species (ROS) process. The most effective process to treat the residual antibiotics by the photocatalytic degradation mechanism is explored in this paper. The traditional co-precipitation method was used to prepare zinc oxide nanomaterials. The characterization methods, X-Ray diffraction analysis (XRD), Fourier Transform infrared spectroscopy (FTIR), Ulraviolet-Visible spectroscopy (UV-Vis), Scanning Electron microscopy (SEM) and X-Ray photoelectron spectroscopy (XPS) have done to improve the photocatalytic activity of ZnO materials. The mitigation of ciprofloxacin catalyzed by ZnO nano-photocatalyst was described by pseudo-first-order kinetics and chemical oxygen demand (COD) analysis. In addition, ZnO materials help to prevent bacterial species, S. aureus and E. coli, growth in the environment. This work provides some new insights towards ciprofloxacin degradation in efficient ways.