VIT-AP University

Very-large-scale integration (VLSI) remains the foundation of modern digital systems; however, continued CMOS scaling is increasingly limited by power dissipation, leakage current, device variability, interconnect overhead, and rising design complexity. These challenges have motivated the search for next-generation computing paradigms and new electronic design automation methodologies beyond conventional transistor-based design. In this context, quantum computing and reversible logic provide a promising framework for information-preserving computation, resource-aware synthesis, and emerging post-CMOS design flows. Since arithmetic logic units are fundamental components of digital datapaths, a quantum arithmetic logic unit serves as a meaningful benchmark for studying synthesis, optimization, decomposition, and verification in a quantum-aware VLSI setting. In this work, a quantum arithmetic logic unit is presented in IBM Qiskit, integrating reversible logic optimization, modular arithmetic and logic-unit construction, Clifford + T mapping, representative functional verification, and noise-aware simulation.The proposed arithmetic unit achieves a quantum cost of 21, corresponding to a 4.55% reduction relative to the selected arithmetic comparison baseline. At the complete-architecture level, the proposed QALU uses 12 reversible gates, five constant inputs, 13 garbage outputs, and a quantum cost of 39 while supporting 16 operation modes. Relative to the selected comparison baseline, the proposed design reduces gate count by 25.00% and quantum cost by 11.36%, while increasing the number of supported operations by 14.29%. These improvements are accompanied by trade-offs of 25.00% more constant inputs and 18.18% more garbage outputs.These percentages are specific to the selected baseline because previously reported designs differ in their architectures, supported functions, gate libraries, and cost assumptions; therefore, the comparison should not be interpreted as demonstrating universal superiority. In addition, representative Qiskit Aer simulations assess the response of the selected logic-unit configuration to separately applied bit-flip, depolarizing, amplitude-damping, and phase-damping noise channels. This preliminary synthetic-noise analysis complements the structural and functional evaluations but does not constitute hardware-calibrated validation or general evidence of noise resilience. Collectively, these evaluations provide a software-level, implementation-oriented design workflow relevant to emerging quantum and VLSI design methodologies.

Accurate diagnosis of spinal lesions relies on clear and high-quality medical images obtained from X-ray, magnetic resonance imaging (MRI), and computed tomography (CT). In clinical practice, these images are often affected by noise, low contrast, imaging artifacts, and variations in acquisition settings. Such limitations can obscure spinal anatomical structures and reduce the accuracy of both clinical assessment and computer-aided image analysis. Consequently, image enhancement has become an essential preprocessing step for lesion detection, segmentation, and other automated image analysis tasks. This paper presents a comprehensive structured review of recent advances in spinal image enhancement by analyzing studies published between 2016 and 2025. The review is conducted by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The reviewed studies encompass conventional image processing methods, machine learning (ML) techniques, deep learning (DL) approaches, including convolutional neural networks (CNNs), U-Net variants, generative adversarial networks (GANs), and Transformer models. For systematic comparison, the selected studies are categorized according to imaging modality, enhancement technique, and clinical application. The reviewed studies evaluate image enhancement using quantitative measures such as the Structural Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR). However, relatively few studies investigate whether these improvements consistently translate into enhanced lesion detection, segmentation accuracy, or overall diagnostic performance. This finding emphasizes the importance of evaluating enhancement techniques using clinically relevant downstream tasks rather than relying solely on image quality metrics. Furthermore, this review summarizes the strengths and limitations of existing enhancement approaches and discusses current challenges, including limited dataset diversity, poor cross-dataset generalization, inconsistent evaluation protocols, insufficient model interpretability, reproducibility issues, and limited end-to-end clinical validation. Finally, future research work is presented to support the development of reliable, efficient, and clinically deployable AI-assisted spinal imaging systems.

Following the successful vitrification and characterization of LiCoO2–P2O5 glasses containing 20–40 mol% LiCoO2 (5 mol% increments), the present study reports X-ray photoelectron spectroscopy (XPS) results and then focuses on their dielectric properties, ac/dc conductivity, and the examination of their suitability for solid-state batteries. XPS O 1 s results indicated that the amount of non-bridging oxygens increased with LiCoO2 content in the glasses, consistent with a network depolymerization effect. The presence of Co2+ and Co3+ was also verified by XPS; estimates based on the Co 2p3/2 satellites region indicated an increase in Co3+ concentration within ∼26–30% of total cobalt with increasing LiCoO2 content. The dielectric parameters, ac conductivity (measured from 4 Hz to 8 MHz and temperatures from 306 to 633 K) and dc conductivity in the same temperature range were found to increase, while the electrical impedance decreased with LiCoO2 content. Electrical modulus analysis and Cole-Cole plots revealed dipolar relaxation, with activation energy decreasing as LiCoO2 increased. This relaxation is ascribed to complexes of octahedrally coordinated Co2+ ions and surrounding oxygen ions. At higher LiCoO2 levels the conductivity (both ac and dc) is dominated by ionic contribution, whereas at lower concentrations, a polaronic contribution via electron hopping among Co2+ and Co3+ ions seemed to be significant. Overall, the results identify the higher-LiCoO2 glasses as promising candidates for further investigation as glassy solid-electrolyte materials, while the lower-LiCoO2 compositions may warrant investigation for electrode-related applications. Direct electrochemical measurements, including ionic transference, electrochemical stability, and cell-level cycling, are required to establish practical suitability for solid-state battery applications.

The uncontrolled release of dyes and pathogens from textile effluents demands multifunctional materials for water remediation. In this study, TiO2 and 1%, 3%, and 5% Ce-doped TiO2 nanoparticles were synthesised via a Sol-Gel method. Structural and elemental analyses confirmed anatase-phase nanoparticles with successful Ce incorporation, mixed Ce3+/Ce4+ states, and oxygen-vacancy formation. Ce doping reduced the band gap from 3.11 eV (TiO2) to 2.92 eV (3% Ce-TiO2), accompanied by pronounced photoluminescence quenching. Among the synthesized samples, 3% Ce-TiO2 demonstrated superior photocatalytic performance. The catalyst efficiently degraded various cationic and anionic dyes, as well as real textile wastewater, achieving degradation efficiencies of 97% under UV irradiation and 94% under sunlight, while retaining its stability over five cycles. Treated wastewater showed reduced toxicity in Vigna radiata seed germination assays. The material also demonstrated antibacterial activity against Staphylococcus aureus and Escherichia coli, highlighting its potential for sustainable textile wastewater treatment.

The aim of this study was to investigate the simultaneous influence of B4C, BN and SiC reinforcement and heat treatment on the mechanical and tribological behavior of Al 7075 composite materials produced through Inert Gas Assisted Stir Casting. The developed composites showed a significant reduction in material density of 0.96