CMR University

PurposeThis study aims to investigate the impact of metaverse applications on apparel design and retail, focusing on Generation Z consumers' purchase intentions. It examined how immersive experience quality, social interaction and digital fashion trend awareness influenced consumer behavior in metaverse-based apparel retail environments.Design/methodology/approachA quantitative research design was used, with primary data collected from 323 Gen Z respondents using a structured survey and purposive sampling. Key constructs were measured using validated five-item Likert scales. Data analysis was conducted through Structural Equation Modeling in AMOS, ensuring model fit, reliability and validity. Construct scales were adapted from established sources with rigorous pretesting for metaverse-specific contexts, and robustness checks (e.g. bootstrapping) confirmed result stability.FindingsThe results indicated that immersive experience quality was the strongest predictor of purchase intention, followed by social interaction and digital fashion trend awareness. Demographic factors, such as gender and age, also significantly moderated purchase behavior. The findings underscored the importance of creating engaging, interactive and trend-aware virtual environments to stimulate Gen Z's digital fashion consumption. Path analyses revealed mediation effects via organism states (e.g. emotional engagement), extending beyond prior descriptive models.Originality/valueThis study offers the originality by empirically testing an integrated model that extends the Stimulus-Organism-Response framework with Uses and Gratifications Theory and Social Identity Theory. Unlike prior work, which often examines these elements in isolation (immersion alone in Kim, 2025), this research holistically assesses their combined effects on Gen Z's purchase intentions in metaverse apparel retail a gap in the digital fashion literature.

Fitness training enhances endurance in soccer players. The study aimed to determine the effect of a Motophysic Fitness (MPFIT) training program on the physical and technical skills of twenty youth soccer players with an average age 20±1 years, height 1.71 ± 0.5 m, and weight 64.3 ± 5.7 kg. It consisted of a 12-week intervention period during the off-season. The MPFIT training was designed to improve physical fitness in terms of endurance, taking into account the players' positional differences. Yo-Yo Intermittent Recovery Test Level-1 (Yo-YoIRT1) was implemented to measure endurance before and after training. The outcome of Yo-YoIRT1 was assessed in terms of total distance covered in meters, the level achieved and estimated VO2max. Maximum heart rate was also measured to analyse the impact of MPFIT training. The MPFIT regime offered an average of 2% increase in fitness level of the players in all positions. Z-test revealed that significance p-values for the level achieved and VO2max were determined to be p=0.004 and p=0.02, respectively. The study provided substantial evidence supporting the viability of MPFIT regime as an innovative form of high-intensity training and implemented by individual players for self-assessment and by trainers for enhancing the soccer player fitness.

This study presents a novel, to the best of our knowledge, ultra-wideband nanobiosensor based on a double-negative (DNG) metamaterial perfect absorber for early cancer detection through exosomal biomarker analysis. Our biosensor operates across a broad frequency range from 70 THz to 3 PHz, exhibiting near-unity absorption, i.e., exceeding 99%, and angular and polarization insensitivity, i.e., providing polarization-independent absorption across the full spectrum of polarization angles (0° to 90°), ensuring stable performance under both transverse electric (TE) and transverse magnetic (TM) polarized waves. Of particular interest is its performance in the near-infrared (NIR) region (70–400 THz), where the sensor’s DNG characteristics manifest through simultaneously negative permittivity and permeability, enhancing field confinement and sensitivity. This spectral window is especially conducive to label-free, non-invasive detection of circulating exosomes, critical indicators of early stage oncogenesis. The sensor is constructed using a tri-layer metal–insulator–metal (MIM) architecture comprising nickel (Ni) layers and a silicon dioxide (SiO 2 ) dielectric spacer. The design leverages the plasmonic and thermal stability properties of Ni and the low optical attenuation of SiO 2 to achieve optimal absorption and structural robustness. Electromagnetic simulations demonstrate strong electric and magnetic resonances, producing significant near-field enhancements. These improve the detection of subtle dielectric changes associated with exosomal binding events. The sensor maintains high absorption efficiency across oblique incidence angles and various polarization states, making it suitable for real-world biomedical diagnostic applications. By focusing on the NIR regime where tissue transparency and molecular vibrational modes intersect, the proposed biosensor enables the discrimination between cancer-derived exosomes and their normal counterparts, as confirmed through spectral and field distribution analyses. The demonstrated performance highlights the sensor’s promise for next-generation photonic platforms targeting early cancer diagnostics, with potential extension to environmental monitoring and energy harvesting technologies.

This study reports the design, fabrication, and experimental investigation of 3D-printed honeycomb structures subjected to drop-weight impact testing. Hexagonal honeycomb structures were designed using CAD software and fabricated using Fused Deposition Modeling (FDM) with PLA (Polylactic Acid) material. The primary objectives were to analyze energy absorption capacity, deformation characteristics, and failure mechanisms under controlled dynamic impact loading. Drop-weight impact tests were conducted at three distinct heights (1.0 m, 1.5 m, and 2.0 m), with a striker mass of 63.6 kg, systematically evaluating different impact energy levels. Force-displacement behavior and post-impact failure modes were documented to assess structural response. Results demonstrated that the honeycomb structure absorbed 624 J, 936 J, and 1248 J of energy at 1.0 m, 1.5 m, and 2.0 m drop heights, respectively, with corresponding displacements of 28–32 mm, 33–39 mm, and 45–50 mm. Specific energy absorption (SEA) values increased from 9.81 J/kg to 19.62 J/kg with increasing impact height. Progressive cell wall buckling and densification were identified as primary deformation mechanisms. This work contributes to understanding the performance of polymer-based cellular structures under dynamic impact loading and provides a foundation for optimization in crashworthy applications in aerospace, automotive, and protective equipment sectors.

In the present era, the use of cloud environment for communication, storage, application software, infrastructure, etc., has increased tremendously. The use of cloud environment in our everyday activities has increased the need for secure, covert and classified data transfer. Different techniques such as steganography, watermarks, cryptography etc., provide security to critical data in the cloud environment. Video steganography, one of the steganography methods often face the limitation of handling transcoding, compression, and file format conversion in the cloud environment. In this paper authors have proposed a framework to implement video steganography as a service in the cloud environment that supports scalable, modular and robust microservice for secure data communication. The proposed framework includes identifying eligible pixels, data embedding and compression of video as independent services. The proposed framework implements high payload recovery rates while achieving imperceptibility in cloud workflows. Diverse video sets, UCF101 were used to evaluate the proposed framework. The study proposes a framework that achieves an effective balance between capacity, robustness, and efficiency. Thus, the framework discussed in this paper provides a practical foundation for secure and confidential data communication in cloud environments.