Software Systems Research Articles

Nonaka and Takeuchi knowledge management model based on institutional and infrastructure factors

Purpose The purpose of this study is to investigate and analyze the knowledge management (KM) model of Nonaka and Takeuchi, focusing on institutional and infrastructure factors in a specific field of design offices in a product-oriented organization. In other words, this research does not intend to recreate the model of Nonaka and Takeuchi, but seeks to expand and modify this model according to the specific context and institutional and infrastructure factors that may specifically affect the effectiveness of the model. Design/methodology/approach This study used two distinct questionnaires, administered to the same set of respondents, to comprehensively address different dimensions of KM. The first questionnaire, focused on KM components, assessed aspects such as knowledge creation, sharing and utilization. The second questionnaire evaluated institutional and infrastructural factors critical to KM, covering dimensions like organizational culture, values, leadership, context, hardware, software and network systems. This dual-questionnaire approach is justified, as it allows for a detailed and differentiated analysis: one tool captures the operational aspects of KM, while the other explores the supporting infrastructure. This methodology ensures that the study accurately measures both the effectiveness of KM practices and the adequacy of the supporting environment, thus providing a robust assessment of the KM system. Findings This study identifies seven key factors influencing KM processes: organizational culture, values, leadership, context, hardware, software and network systems. These factors shape how knowledge is created, shared and used, and support proposed modifications to the Nonaka and Takeuchi KM model. Using the TOPSIS method, this study found that organizational context, culture and values rank above average, while KM policies are moderate, and information technology is below average in the design offices of a product-oriented organization in Tehran. Further research in different sectors could help validate these findings. Originality/value This study introduces a novel enhancement to the Nonaka and Takeuchi KM model by incorporating a comprehensive analysis of institutional and infrastructural factors. Unlike existing models, which primarily focus on generalized KM principles, this research uniquely integrates specific factors such as organizational culture, leadership and technological infrastructure. The originality of this work lies in its tailored approach for product-oriented organizations, offering a more precise and actionable framework for improving KM practices. This advancement not only deepens theoretical insights but also provides practical value by addressing the specific needs and dynamics of the target organizations.

Investigation of a novel Schiff base Catena-((μ6-(E)-2-((4-methoxy-2-oxidobenzylidene)ammonio)ethane-1-sulfonato potassium as a potential antibacterial agent.

Schiff bases, which have intriguing properties in many areas, have been studied extensively in recent years due to their structural properties and biological activities. In this research, a novel water-soluble Schiff base complex, Catena-((μ6-(E)-2-((4-methoxy-2-oxidobenzylidene) ammonio) ethane-1-sulfonato potassium, C10H14KNO6S (CMOAESP), was synthesized by a one-step condensation reaction of 2-hydroxy-4-methoxy benzaldehyde and taurine with the yield of 65%, 0.333g. Spectral analysis of water-soluble crude product showed equilibria keto-enol tautomerism, by a resulting Zwitterionic form of the structure. The ADMET prediction showed that the CMOAESP obeys Lipinski's rule and was in bioavability range. The molecular docking results showed an inhibition ability for 1JIJ and MBT1 proteins which play an important role in antibacterial studies. The experimental end theoretical calculations were in a good agreement that CMOASP has inhibition efficiency against Escherichia coli and has inhibition at high concentrations against Staphylococcaceae aureus. The WinGX software system SHELXS direct technique was used to solve the structure, and SHELXL full-matrix least-squares approach on F2 was used to refine the results. The Gaussian 09W program was used to carry out the DFT calculations. The gap values for CMOAESP were calculated by using the B3LYP/6- 311 + + G(d,p) method in order to predict its reactivities and behaviors in the gas phase. The frontier orbitals, LUMO and HOMO together with some global parameters as electronegativity (μ), chemical potential (χ), hardness (η), electrophilicity index (ω), and softness (S) values were predicted from DFT calculations.

Metamorphic Relation Generation: State of the Art and Research Directions

Metamorphic testing has become one mainstream technique to address the notorious oracle problem in software testing, thanks to its great successes in revealing real-life bugs in a wide variety of software systems. Metamorphic relations, the core component of metamorphic testing, have continuously attracted research interests from both academia and industry. In the last decade, a rapidly increasing number of studies have been conducted to systematically generate metamorphic relations from various sources and for different application domains. In this article, based on the systematic review on the state of the art for metamorphic relations’ generation, we summarize and highlight visions for further advancing the theory and techniques for identifying and constructing metamorphic relations, and discuss promising research directions in related areas.

Self-Designing Software

Exploring ways to include a software system as an active member of its own design team, able to reason about its own design and to synthesize better variants of its own building blocks as it encounters different deployment conditions.

A Roadmap for Integrating Sustainability into Software Engineering Education

The world faces escalating crises: record-breaking temperatures, widespread fires, severe flooding, increased oceanic microplastics, and unequal resource distribution. Academia introduces courses around sustainability to meet the new demand, but software engineering education lags behind. While software systems contribute to environmental issues through high energy consumption, they also hold the potential for solutions, such as more efficient and equitable resource management. Yet, sustainability remains a low priority for many businesses, including those in the digital sector. Business as usual is no longer viable. A transformational change in software engineering education is urgently needed. We must move beyond traditional curriculum models and fully integrate sustainability into every aspect of software development. By embedding sustainability as a core competency, we can equip future engineers not only to minimise harm but also to innovate solutions that drive positive, sustainable change. Only with such a shift can software engineering education meet the demands of a world in crisis and prepare students to lead the next generation of sustainable technology. This paper discusses a set of challenges and proposes a customisable education roadmap for integrating sustainability into the software engineering curricula. These challenges reflect our perspective on key considerations, stemming from regular, intensive discussions in regular workshops among the authors and the community, as well as our extensive research and teaching experience in the field.

A Comprehensive Life Cycle Carbon Footprint Assessment Model for Electric Power Material Warehouses

Electric power material warehouses are critical to optimizing power grid supply chains and reducing carbon emissions, aiding the power sector’s decarbonization and climate goals. Nevertheless, to our knowledge, there are no comprehensive assessments of the life cycle carbon emissions associated with storage warehouses, so the emission reduction potential of the ever-increasing number of automated technologies is still unknown. This study presents an extensive life cycle carbon footprint assessment model tailored for electric power material warehouses, and it encompasses both traditional and automated frameworks. Utilizing a process-based life cycle assessment (LCA) methodology, carbon emissions across five distinct stages are examined: storage buildings and facilities, loading and unloading, transportation, packaging, and information management systems. For this purpose, warehouses in Jiangsu Province, China, are employed as a case study. The results show that automating warehouses can achieve a reduction in total carbon emissions of 42.85% compared with traditional warehouses, with total life cycle emissions of 39,531.26 tCO2, and the transportation stage is identified as the predominant contributor. This research not only offers actionable recommendations for strategies, including renewable energy integration, intelligent control systems, and standardized packaging protocols, but also establishes a framework for future investigations of refining carbon accounting methodologies—particularly in underexplored domains such as packaging.

Enhancing Software Security: A Research-Driven Automation Framework

With the ever-growing dependency on software in critical systems such as healthcare, finance, transportation, and defense, among many others, the need for robust security in software has never been greater. Breaches of security, in which an undetected vulnerability was often the culprit, lead to severe financial loss, loss of reputation, and even legal action for organizations and end-users. While technology has considerably improved, conventional security practices have repeatedly have failed to address the rapid growth of complexity and dynamic nature in modern software systems. The paper presents a critical requirement for an organized and active approach toward software security for its lifetime. We propose an automation framework driven by research that responds to these challenges by fitting into the tight cooperation of security testing tools in order to automate the detection and mitigation of vulnerabilities: it engenders a continuous improvement culture of security. This framework will be tailored to support Agile development and DevOps workflows, seamlessly embedding security in the rapid, iterative cycles of development. This framework will allow an organization to measure and improve quantitatively its security practices over time by harnessing actionable metrics and insight.

Evolution of Diagnostic Medical Physics Enterprise.

The roles and responsibilities of radiation safety officers (RSO), medical health physicists (MHP) and diagnostic medical physicists (DMP) have evolved significantly over the past 20 years. With the availability of enterprise software systems and aggregated data platforms for various radiologic healthcare systems, the roles of these professions are expanding beyond their original scopes in managing the Radioactive Materials License (RSO, MHP) and Machine Specific Physics Testing (DMP). Workers in medical radiation safety are transitioning from siloed workers working within their specific disciplines as new emerging technology and clinical care require these roles to evolve. This paper aims to demonstrate the value in embracing the change in these roles to better serve the patients and occupational workers RSOs, MHPs, and DMPs serve. As medical physics enterprise solutions evolve, so will the relationships between these valuable stakeholders.

Mechanochromic Chameleon Packaging Based on Polydiacetylene.

We demonstrated a mechanochromic chameleon packaging that quantitatively visualizes damage based on the polydiacetylene blue-to-red color transition. The applied pressures on the damage can be conveniently read by taking a photograph via a homemade mobile app called the "Pressure Analysis App". The key aspects of the development were 1) the adjustment of the sensitivity by adding guest molecules into the PDA matrix, 2) quantitative calibration, and 3) the accurate reading of the pressure from RGB images based on the calibration. The force sensitivity of polydiacetylene on cellulose was characterized in the range of 30-100 nN (2.59-8.86 MPa) at the nanoscale by dual friction force/fluorescence microscopy, and in the range of 0.7-2.2 N (0.11-0.35 MPa) at the macroscopic scale by a friction tester. The scanning speed was found to be one of the key parameters, where the force sensitivity above 50 mm/s was 6.45 times larger than that below 10 mm/s. The developed mechanochromic packaging system can be used for transporting electronics and medical tools, such as vaccine vials, food, etc., more safely and reliably in the future.

A 3D Model-Based Framework for Real-Time Emergency Evacuation Using GIS and IoT Devices

Advancements in 3D modelling technology have facilitated more immersive and efficient solutions in spatial planning and user-centred design. In healthcare systems, 3D modelling is beneficial in various applications, such as emergency evacuation, pathfinding, and localization. These models support the fast and efficient planning of evacuation routes, ensuring the safety of patients, staff, and visitors, and guiding them in cases of emergency. To improve urban modelling and planning, 3D representation and analysis are used. Considering the advantages of 3D modelling, this study proposes a framework for 3D indoor navigation and employs a multiphase methodology to enhance spatial planning and user experience. Our approach combines state-of-the art GIS technology with a 3D hybrid model. The proposed framework incorporates federated learning (FL) along with edge computing and Internet of Things (IoT) devices to achieve accurate floor-level localization and navigation. In the first phase of the methodology, Quantum Geographic Information System (QGIS) software was used to create a 3D model of the building’s architectural details, which are required for efficient indoor navigation during emergency evacuations in healthcare systems. In the second phase, the 3D model and an FL-based recurrent neural network (RNN) technique were utilized to achieve real-time indoor positioning. This method resulted in highly precise outcomes, attaining an accuracy rate over 99% at distances of no less than 10 metres. Continuous monitoring and effective pathfinding ensure that users can navigate safely and effectively during emergencies. IoT devices were connected with the building’s navigation software in Phase 3. As per the performed analysis, it was observed that the proposed framework provided 98.7% routing accuracy between different locations during emergency situations. By improving safety, building accessibility, and energy efficiency, this research addresses the health and environmental impacts of modern technologies.

31W Linear broadband 3.4 to 4.4 GHZ high power class-j GaN HEMT amplifier

The recent upsurge in wireless communication systems requiring high-power transmitters for numerous applications such as electronic warfare (EW), RADAR, Satellite and optical communications has further underscored the importance of linear broadband high-power Class-J power amplifiers. This paper proposes a 31W linear broadband 3.4 to 4.4 GHz high-power Class-J GaN HEMT(gallium nitride high electron mobility transistor)amplifier. The power amplifier was designed based on Cree's commercially available 10WGaN HEMT power transistor device (CGHV40010F) using Keysight Advanced Design System (ADS) software and simulated. The transistor was biased withadrain supply voltage of 48V at aquiescent drain-to-source current of 0.58A,which makes the power transistor suitable for high voltage transmitter operations and foreclosed the need for voltage upgrade, thereby reducing thecost of operation. The power amplifier (PA) operates from 3.4 to 4.4 GHz with a centre frequency of 3.9 GHz. The PA has an output power of 31W, drain efficiency of 36.3%, power added efficiency of 35.3% and power gain of 12.9 dB at an input power of 32 dBm. The PA small signal gain stood at 10.6 dB at acentre frequency of 3.9 GHz. The PA maintained a peak envelope power of 56.2W at aninput power of 31 dBm at atwo-tone Frequency of 3.895 GHz. The proposed PA will find applications in wireless communications, military and aviation transmitters.

Beyond Cohesion and Coupling: Integrating Control Flow in Software Modularization Process for Better Code Comprehensibility

As software systems evolve to meet the changing needs of users, understanding the source code becomes a critical step in the process. Clustering techniques, also known as modularization techniques, offer a solution to breaking down complex source code into smaller, more manageable parts. This facilitates improved analysis and understanding of the software’s structure. However, the effectiveness of clustering algorithms in code understanding heavily relies on the chosen criteria. While existing methods typically consider cohesion, coupling, and balance between clusters, we argue that these criteria alone may not fully satisfy one of the primary objectives of clustering, which is to enhance understanding. This is because spaghetti-like structures can be created even when these criteria are satisfied. To address this issue, we introduce two new criteria incorporating program control flow to regulate cluster dependencies. By controlling the uniformity of input and output directions, as well as the distribution of inputs and outputs, clustering algorithms can generate clusters that are more developer-friendly and easier to comprehend. We provide intuitive explanations and real-world projects to demonstrate the effectiveness of our approach, and also incorporate feedback from academics and expert programmers. This paper reveals that integrating these new criteria into existing clustering algorithms enables developers to gain deeper insights into the structure of software systems. This, in turn, leads to better design decisions and improved developer understanding of the source code.

Let’s CHAT About Artificial Intelligence for Students With Disabilities: A Systematic Literature Review and Meta-Analysis

Researchers have explored artificial intelligence (AI) applications across educational contexts; however, there is a lack of meta-analysis focused on students with disabilities (SWDs). This study examined the overall effect of AI-based interventions on SWDs’ learning outcomes in 29 (quasi-)experimental studies conducted globally. We used cultural historical activity theory (CHAT) to explore how the effect was moderated by factors, including participant-, AI-, AI-SWD interaction-, intervention-, and methodology-related characteristics. Results indicated a medium effect (Hedge’s g = 0.588) of interventions operating through robots, computer software, and intelligent VR systems. There were no statistically significant moderators. Regardless, this study contributes to a holistic understanding of historical dimensions of AI applications for SWDs and offers critical theoretical implications for future investigations. We call for more rigorous research to explore AI that not only ensures accessibility but also promotes opportunities for SWDs to take an agentic role in participating in and contributing to AI-mediated learning activities.

The First Fifth-Generation District Heating and Cooling System in Kazakhstan: Planning and Design

This paper focuses on the potential for integrating Geographic Information System (GIS) software into Fifth-Generation District Heating and Cooling (5GDHC) systems to promote efficient and sustainable energy management, particularly in Kazakhstan. By reviewing the key literature, we identify three main areas where GIS software enhances the planning of 5GDHC systems: decision-making in the context of energy market regulations, operational data utilization, and modeling/simulations for technical design. The technical design emphasizes the role of heat pumps, ultra-low temperature district heating (ULTDH) networks, and end-user buildings. Previous research has explored various methodologies for integrating network and demand-side strategies, developing sustainable district heating and cooling (DHC) systems, and mapping urban areas suitable for DHC deployment. However, none has presented an open-source model incorporating GIS-based decision-making in designing 5GDHC systems. This study, for the first time, addresses this gap through a case study conducted in the Northern Industrial Zone of Karaganda, Kazakhstan, demonstrating how GIS-enhanced modeling can be effectively applied in a developing, industry-driven economy. We outline the mathematical framework for comparing existing simulation tools and developing a custom model suited to the region’s needs. Additionally, we discuss validation and calibration methods, which remain underexplored in the current literature. The proposed model incorporates waste heat recovery from local sources, including nearby wastewater treatment plants, showcasing a sustainable energy solution for the industrial park. The results indicate that a well-structured 5GDHC system, supported by GIS tools, can markedly enhance energy efficiency and sustainability, presenting a scalable and adaptable approach for other regions in Kazakhstan and beyond.

Assessment of proprioceptive and kinesthetic memory in shoulder joint using KEMTAI software system

<p style="text-align: justify;">Proprioception and kinesthesia refer to the sense of joint position and movement, assessable through joint position sense (JPS). We evaluated the potential of the KEMTAI software system in tracking and quantifying shoulder movement by examining 40 subjects (ages 22-68) divided into three age groups. Subjects, blindfolded, performed shoulder flexion, stopped on voice command and by their own at predefined angles measured by the software. Our findings indicated no significant differences in JPS accuracy across age groups, although precision improved with external cues, and a decline in JPS memory over short intervals was observed, suggesting further exploration is needed.</p>

A Comprehensive Review of Intravenous Oncology Drug Preparation in Pharmacy: Safety, Efficiency, Innovations, and Stability

Introduction: Intravenous (IV) administration of oncology drugs is a critical component of cancer treatment, providing rapid and controlled delivery of therapeutic agents. The preparation of these drugs involves intricate processes that require stringent safety protocols, efficient workflows, and innovative technologies to ensure patient safety and therapeutic efficacy. This review aims to provide a comprehensive overview of current practices and advancements in the preparation of intravenous oncology drugs within pharmacy settings, focusing on safety, efficiency, innovation, and drug stability. Safety: Safety is paramount in the preparation of intravenous oncology drugs, given the hazardous nature of chemotherapeutic agents. Adherence to guidelines such as USP <797> and USP <800> is essential to minimize risks of contamination and exposure. Strategies to enhance safety include the use of personal protective equipment (PPE), engineering controls like biological safety cabinets (BSCs) and compounding aseptic containment isolators (CACIs), and rigorous training and education for pharmacy staff. Historical incidents, such as the New England Compounding Center contamination, underscore the critical need for strict safety protocols. Efficiency: Efficiency in drug preparation involves optimizing processes to meet high demand while maintaining safety and quality. Current methodologies include prescription verification, com-pounding, quality control, and dispensing. Technological advancements, such as automated compounding devices (ACDs) and pharmacy management software, have significantly improved efficiency by reducing preparation time and minimizing errors. However, balancing efficiency with safety remains a challenge, requiring careful resource allocation, ongoing staff training, and compliance with safety standards. Innovative Technologies: The integration of cutting-edge technologies, such as robotics, automation, and artificial intelligence (AI), has revolutionized the preparation of intravenous drugs. Robotic systems enhance precision and reduce human error, while advanced aseptic techniques and AI-driven systems optimize dosing and workflow. Future trends include the potential use of 3D printing, nanotechnology, and blockchain to further improve the safety, efficiency, and traceability of drug preparation processes. Stability: Maintaining the stability of compounded drugs is crucial to ensuring their efficacy and safety. Factors such as storage conditions, handling procedures, and compatibility with diluents and containers can significantly impact drug stability. Guidelines like USP <797> provide detailed recommendations for maintaining stability. Research on stabilizing agents, improved packaging, and real-time monitoring systems continues to advance the field, addressing stability challenges and enhancing patient outcomes. Conclusion: This review highlights the critical importance of safety, efficiency, innovation, and stability in the preparation of intravenous oncology drugs. Adhering to stringent safety protocols, optimizing workflows, embracing innovative technologies, and ensuring drug stability are essential for improving patient outcomes and enhancing pharmacy practices. Future research should focus on integrating emerging technologies, standardizing protocols, providing ongoing education, and implementing real-time monitoring systems to further advance the field. By addressing current challenges and embracing new solutions, the preparation of intravenous oncology drugs can achieve greater heights in patient safety and treatment efficacy.

Research and design of multiple gas mixing system in modified atmosphere packaging

Despite the abundant production of fruits and vegetables in Xinjiang, there is an increasing trend in waste rates. Gas-controlled packaging techniques are employed post-harvest to enhance freshness and extend shelf life. However, the multi-gas mixing system at the core of this equipment often encounters challenges such as insufficient stability, limited precision, high costs, and inadequate intelligence. In this context, we have developed and designed a multi-gas mixing system for gas-conditioned packaging. The system integrates Internet of Things technology, uses a programmable controller as the core, proposes a ternary gas distribution model based on the ideal gas equation and Dalton’s law of partial pressures, and utilizes RS-485 bus, TCP/IP protocol, among others. This ensures communication between the equipment and data transmission with the cloud server while enabling remote control of the gas mixing and blending process via a mobile phone terminal. The system runs stably through testing, with the average relative deviations of CO2 and O2 gas concentrations being 0.86% and 0.72%, respectively. This fulfills the technical prerequisites for achieving a gas concentration precision of less than 1%, addressing challenges related to inadequate precision in gas blending, unstable performance, and limited visual representation. Moreover, it significantly reduces equipment costs and operational complexities while serving as a valuable reference for advancing multivariate gas mixing and blending technology in Xinjiang’s fruit and vegetable gas-conditioned packaging.

New Approaches to Determining the D/H Ratio in Aqueous Media Based on Diffuse Laser Light Scattering for Promising Application in Deuterium-Depleted Water Analysis in Antitumor Therapy

The development of affordable and reliable methods for quantitative determination of stable atomic nuclei in aqueous solutions and adjuvant agents used in tumor chemotherapy is an important task in modern pharmaceutical chemistry. This work quantified the deuterium/prothium isotope ratio in aqueous solutions through an original two-dimensional diffuse laser scattering (2D-DLS) software and hardware system based on chemometric processing of discrete interference patterns (dynamic speckle patterns). For this purpose, 10 mathematical descriptors (di), similar to QSAR descriptors, were used. Correlation analysis of bivariate “log di—D/H” plots shows an individual set of multi-descriptors for a given sample with a given D/H ratio (ppm). A diagnostic sign (DS) of differentiation was established: the samples were considered homeomorphic if 6 out of 10 descriptors differed by less than 15% (n ≥ 180). The analytical range (r = 0.987) between the upper (D/H ≤ 2 ppm) and lower (D/H = 180 ppm) limits for the quantification of stable hydrogen nuclei in water and aqueous solutions were established. Using the Spirotox method, a «safe zone» for protozoan survival was determined between 50 and 130 ppm D/H. Here, we discuss the dispersive (DLS, LALLS) and optical properties (refractive index, optical rotation angle) of the solutions with different D/H ratios that define the diffuse laser radiation due to surface density inhomogeneities. The obtained findings may pave the way for the future use of a portable, in situ diffuse laser light scattering instrument to determine deuterium in water and aqueous adjuvants.

Assessing the Global Sensitivity of RUSLE Factors: A Case Study of Southern Bahia, Brazil

Global sensitivity analysis (GSA) of the revised universal soil loss equation (RUSLE) factors is in its infancy but is crucial to rank the importance of each factor in terms of its non-linear impact on the soil erosion rate. Hence, the goal of this study was to perform a GSA of each factor of RUSLE for a soil erosion assessment in southern Bahia, Brazil. To meet this goal, three non-linear topographic factor (LS factor) equations alternately implemented in RUSLE, coupled with geographic information system (GIS) software and a variogram analysis of the response surfaces (VARSs), were used. The results showed that the average soil erosion rate in the Pardo River basin was 25.02 t/ha/yr. In addition, the GSA analysis showed that the slope angle which is associated with the LS factor was the most sensitive parameter, followed by the cover management factor (C factor) and the support practices factor (P factor) (CP factors), the specific catchment area (SCA), the sheet erosion (m), the erodibility factor (K factor), the rill (n), and the erosivity factor (R factor). The novelty of this work is that the values of parameters m and n of the LS factor can substantially affect this factor and, thus, the soil loss estimation.

Stress, physical activity, and mindfulness practices among youth amidst COVID-19

IntroductionThe COVID-19 pandemic has exacerbated stress and anxiety among young people, particularly university students, impacting their mental well-being and daily life. Given the rise in social isolation and economic uncertainty, the adoption of mindfulness practices such as sophrology, meditation, and yoga becomes essential for improving their mental health. This study aims to evaluate the impact of these practices on stress levels and their effect on engagement in physical activities among youths.MethodThis study employed a mixed methods design to assess the impact of different wellness and mindfulness practices on stress levels and physical activity (PA) engagement among university students. Quantitative data were gathered electronically from 218 students at the University of Rouen and the university of Paris-Cité through validated questionnaires, including custom tools on sports and mindfulness practices and the Perceived Stress Scale (PSS). The sample consisted mainly of young adults aged 18 to 35, with a majority of 170 female and 48 male participants. Qualitative insights were gathered through semi-structured interviews with three directors of the university's sports and physical activities department (SUAPS), as well as four wellness program instructors. Data analysis involved statistical techniques using Statistical Analysis System (SAS) software for quantitative data, while qualitative data were analyzed thematically using Sphinx software, a tool for textual analysis. Ethical approval for the study was obtained, and confidentiality of all participants was maintained throughout the research.Results and conclusionThe COVID-19 pandemic had significant effects on French university students’ PA, mental health, and stress levels. Lockdowns led to a decline in sports practices for many, while others adapted by increasing their engagement in fitness and wellness practices. The majority of participants (64.68%) reported moderate levels of stress. A significant correlation was found between motivations for mental health support and stress management, and higher levels of stress (p = 0.0000 and p = 0.0024, respectively). Regular participation in wellness activities was associated with lower stress (p = 0.0193). The findings reinforce the idea that incorporating wellness practices into educational environments can strengthen students’ mental resilience and overall well-being, equipping them with essential tools to effectively cope with future stressors.