Journal of Engineering, Science and Technological Trends
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Firewall Technology Testing in Pakistan: The Fine Line Between National Security and Freedom of Expression
Get PDFConcerns have been raised over the international trend of relying on firewall technology for cybersecurity and digital censorship, especially in Pakistan. Firewalls are important to protect critical infrastructure, but can also be used to restrict access to information as state-controlled devices. In this article, we critically examine Pakistan’s firewall deployment, investigating whether it intended to promote national security or online freedom. This study applies qualitative analysis, through economic, legal, and technological assessment of firewall policies in Pakistan, especially in the light of the amendment of the Prevention of Electronic Crimes Act (PECA) in 2025, which was in the course of writing this article, and the implications of this on the economic, political and social life of the country. It also draws comparative insights from global cybersecurity models, including China and Iran, to analyze Pakistan’s trajectory of digital governance. The key findings highlight that Pakistan’s firewall policies have increasingly been used as a means of controlling the internet; laws are unclear and can be used to limit free speech and media. Firewall-based censorship also has hidden economic costs, which now reach $1.62 billion in 2024. Implications of this research suggest that digital rights and cybersecurity should be balanced in the policies. Key to preventing Pakistan’s cybersecurity efforts from eroding democracy and economic growth is transparent firewall governance and independent judicial oversight. Without such reforms, Pakistan runs the risk of digital isolation, loss of investment, and online freedoms. The findings add to the ongoing debate about cybersecurity law, digital human rights, and technology in government
The Human Rights Implications of Scientific Progress: A Case Study on Gene Editing and Disability Rights
Get PDFGene editing tools like CRISPR-Cas9 hold great promise for treating genetic diseases but also raise important ethical concerns, especially regarding disability rights. While gene editing can eliminate inherited diseases, it could also worsen ableism and widen social divides by reinforcing discrimination against people with disabilities. This article will talk about the ethical challenges of gene editing, focusing on the impact on marginalized groups, such as the Deaf community, who see their conditions as part of their identity rather than something to be fixed. The research will focus on practical examples, like gene therapy for sickle cell disease and editing embryos for hearing impairments, and highlight the limited access to these technologies, which could deepen inequality. It calls for stronger global guidelines that include input from disability communities to prevent the technology from reinforcing social divisions. The results show that without clear limits, gene editing may lead to a society that values genetic traits over diversity and human dignity, urging policies that promote fairness and inclusion
Electrochemical Biosensors for Real-Time Oxidative Stress Monitoring in Saliva
Get PDFOxidative stress, resulting from an imbalance between reactive oxygen species and antioxidant defences, is a critical factor in the onset and progression of numerous diseases, including cancer, cardiovascular conditions, and neurological disorders. Early detection of oxidative stress biomarkers is essential for timely diagnosis and effective treatment. Saliva has emerged as a highly attractive biofluid for this purpose due to its non-invasive, easily accessible, and cost-effective collection. Recent advancements in electrochemical biosensors have significantly enhanced the sensitivity, selectivity, and reliability of detecting oxidative stress indicators in saliva. These innovative sensing platforms enable real-time monitoring of key biomarkers at low concentrations, offering great potential for clinical and point-of-care applications. However, challenges such as sensor stability, biofouling, and interference from complex salivary components remain to be addressed to ensure robust performance in practical settings. This review summarises the latest developments in electrochemical biosensing of salivary oxidative stress biomarkers, highlights existing limitations, and discusses prospective strategies to overcome current barriers. The continued evolution of this technology promises to facilitate early disease detection and improve patient outcomes through accessible and precise oxidative stress monitoring
Density Functional Theory: A Quantum Mechanical Framework for Novel Materials Design
Get PDFDensity Functional Theory (DFT) has become a fundamental principle of contemporary materials research, providing a quantum mechanical framework for the examination of matter at the electronic level. By changing the many-body problem into electron density, DFT makes it possible to make precise predictions of structural, electronic, and catalytic properties based on basic principles. Because it can make predictions, it has sped up the discovery of semiconductors, catalysts, and energy storage materials, which means we don\u27t have to rely on expensive experiments as much. At the same time, projects like the Materials Project show how important it is for high-throughput computational design. Even if there are problems with the cost of processing and the accuracy of the results, new developments like hybrid methods, machine learning integration, and new quantum computing technologies keep making it more useful. So, DFT is not only a basic theoretical tool, but it is also a real driver of innovation in the creation of new materials
Review of Smart Edible Films and Coatings for Perishable Foods and Future of Smart Packaging
Get PDFoai:ojs2.journals.scopua.com:article/8The focus of this review article is smart edible films and coatings and also to elaborates the future of smart packaging for perishable foods. The galaxy of smart packaging is expanding in research and concepts at a quick pace. A number of proposals and preliminary solutions to food preservative issues were produced using recently developed technologies and advanced methods, such as molecular biology and nanotechnology. The study highlights several novel sustainable packaging solutions that must take into account the need to minimize environmental effects, reduce losses, and ensure food safety and quality. Food packaging contributes to waste production in addition to being essential for maintaining food during transportation and storage from farm to table. By lowering the need for chemicals and preservatives, current food packaging systems strive to prolong the shelf life of perishable foods while simultaneously preventing quality deterioration. A number of techniques and strategies, such as oxygen scavenging and antimicrobial technologies, are linked to the creation of modified films
Natural Disaster Prediction and Mitigation through Machine Learning
Get PDFFlooding remains a major natural disaster affecting Pakistan\u27s provinces of Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan, with increasing severity due to climate change and human activities. This research explores the application of machine learning techniques to enhance flood prediction accuracy for the years 2025 to 2030. The study utilises historical hydro-meteorological data, including rainfall, temperature, and vegetation indices, to train four machine learning models: Decision Tree, Random Forest, Linear Regression, and Support Vector Machine (SVM). Standard evaluation metrics such as precision, recall, F1-score, and mean squared error (MSE) are used to assess model performance. Results show that Random Forest and SVM outperform the other models in terms of both accuracy and generalizability. These models effectively identify high-risk flood zones across the studied provinces. The findings demonstrate the potential of data-driven approaches to support early warning systems, enabling better disaster preparedness, resource allocation, and mitigation planning. This research highlights how machine learning can play a critical role in reducing flood-related risks and enhancing resilience against future natural disasters in Pakistan
First-Principles Study of Cubic CsSrF₃: Effects of Li Doping on Structural, Electronic and Optical Properties
Get PDFIn this work, the structural, electronic, optical, and elastic properties of cubic fluoro-perovskite CsSrF₃ and its lithium-doped derivatives (Cs₁₋ₓLiₓSrF₃, x = 0–1) are systematically investigated using first-principles density functional theory (DFT) calculations utilizing the generalized gradient approximation using the Perdew–Burke–Ernzerhof (GGA-PBE) functional. To evaluate the structural stability, the total energy is fitted to the Birch–Murnaghan equation of state, resulting in equilibrium lattice constants of 5.000 Å for Pristine CsSrF₃ and 5.076 Å for the doped composition (x = 1). The electronic band structure study shows that Pristine CsSrF₃ has an indirect bandgap of 5.543 eV, which gradually narrows to 4.011 eV with full lithium substitution. Li-induced changes in electronic states close to the Fermi level are responsible for this trend. The valence and conduction bands are primarily controlled by the F-p and Sr-s orbitals, respectively, according to Density of States (DOS) studies. Optical properties demonstrate higher tunability with the doping of lithium, the refractive index varies between 1.78 and 1.40 eV, and the reflectivity decreases from 0.27 eV to 0.10 eV. These characteristics indicate considerable amounts of potential for photovoltaic and UV applications. Mechanical investigation shows anisotropic and ductile behaviour, with predicted bulk modulus values ranging from −9.890 GPa (Pristine) to −17.311 GPa (x = 1), demonstrating a softening effect with increased Li concentration. Ultimately, the findings highlight the potential of Pristine CsSrF₃ and its Li-doped concentrations for the implementation into energy-harvesting and next-generation optoelectronic systems
Twisted Bilayer Graphene at the Magic Angle: A Review of Highly Correlated Physics and Unconventional Superconductivity
Get PDFA novel platform for researching topological quantum phenomena, unusual superconductivity, and strongly coupled electron physics is Twisted Bilayer Graphene (TBG) at the “Magic Angle” (~1.05°). Two graphene layers are rotated to this exact angle to form a moiré superlattice, which produces flat electronic bands that significantly improve electron-electron interactions. This results in a rich phase diagram with non-Fermi liquid behaviour, correlated insulators, and superconductivity. This review covers the theoretical foundations, experimental results, and unanswered concerns about magic-angle TBG, including significant challenges like twist angle control, disorder effects, and the interaction of strain and electrical characteristics. Beyond basic research, TBG has great technological potential, with potential applications in neuromorphic devices, ultra-sensitive sensors, and quantum computing (e.g., topological qubits). This system provides a novel approach to comprehending high-temperature superconductivity and achieving next-generation quantum technologies by fusing insights from correlated physics with device engineering
AI/ML-Driven Design and Optimisation of Quantum Dots: A Perspective Toward Intelligent Materials Discovery
Get PDFQuantum dots (QDs), nanoscale semiconductors with size-dependent and tunable optoelectronic properties, are central to next-generation technologies spanning displays, photovoltaics, bioimaging, and quantum information systems. However, their synthesis and optimisation remain challenging due to the intricate interplay of reaction parameters and nonlinear physicochemical interactions. The integration of artificial intelligence (AI) and machine learning (ML) is redefining this landscape, enabling predictive design, autonomous synthesis control, and accelerated discovery across the QD domain. This Perspective highlights the conceptual advances and methodological innovations driving AI/ML-assisted QD research, emphasising achievements in data-driven modelling, synthesis optimisation, and materials informatics. Persistent challenges, including data scarcity, model transparency, and limited generalizability, are critically examined, alongside emerging strategies toward physics-informed and autonomous discovery frameworks. We propose that the convergence of intelligent algorithms and human expertise will catalyse a paradigm shift from empirical experimentation toward rational, self-evolving materials design in quantum dot science
Assessment and Critical Review of PM0.1 Pollution in Pakistan
Get PDFParticulate matter (PM) is among the most significant air pollutants globally, with severe implications for environmental integrity, human health, and climate stability. Among its various fractions, ultrafine particles (PM0.1, particles with an aerodynamic diameter ≤ 0.1 μm) are gaining increasing attention due to their high surface area-to-mass ratio, deep pulmonary penetration, and potential to translocate into systemic circulation and vital organs. This paper presents a comprehensive critical review of PM0.1 assessment in Pakistan, emphasising its sources, spatiotemporal distribution, measurement limitations, and health consequences. Despite the mounting evidence of air quality degradation in Pakistan, data on PM0.1 remain scarce and fragmented. The few available studies indicate that urban centres such as Lahore, Karachi, Islamabad, and Faisalabad exhibit ultrafine particle concentrations substantially higher than international safety benchmarks. Anthropogenic activities, including vehicular emissions, industrial combustion, biomass burning, and construction dust, are dominant contributors. This review identifies key gaps in current research, highlighting the lack of long-term monitoring, standardised methodologies, and toxicological assessments specific to PM0.1 exposure in local populations. It further stresses the urgent need for policy integration, investment in high-resolution monitoring technologies, and public health interventions. Overall, the assessment underscores that PM0.1 pollution in Pakistan poses an emerging environmental health crisis that remains scientifically underexplored and administratively underprioritized