Search Results (413)

Ongoing global disruptions, including pandemics, geopolitical tensions, and climate-driven events, have exposed vulnerabilities in healthcare supply chains (HSCs). This study examines how artificial intelligence (AI) is reshaping HSCs to improve agility, resilience, and sustainable performance. Using a systematic literature review with PRISMA-style screening across Scopus and Web of Science, the study is complemented by bibliometric analysis and latent Dirichlet allocation topic modeling to analyze peer-reviewed articles. The results indicate an exponential increase in AI-enabled HSC research, concentrated in a small number of journals and spanning a globally diverse author community. Three dominant thematic clusters emerged: (1) sustainability-oriented supply chain design, (2) disruption and resilience management, and (3) healthcare-focused digital transformation. Across these themes, AI, digital twins, Internet of Things, and simulation are evolving from efficiency tools to strategic enablers of decision intelligence, supporting real-time sensing, scenario analysis, and proactive risk mitigation. The study highlights a convergence of “triple transformation” in which digitalization, resilience, and sustainability are increasingly co-dependent capabilities in HSCs. However, persistent barriers exist, including data quality issues, legacy systems, workforce skill gaps, limited model interpretability, and incomplete governance frameworks, which constrain large-scale adoption. The findings indicate a need for longitudinal and multi-method studies on human–AI collaboration, trust calibration, and leadership in AI-enabled HSCs. This study provides practical guidance for healthcare organizations looking to leverage AI in developing agile, resilient, and sustainable supply chain ecosystems. Full article

Soccer is the most widely practiced sport globally, but is also associated with a high incidence of lower limb injuries. Among multiple risk factors, soccer footwear represents a crucial biomechanical interface affecting traction, proprioception, and joint loading. This narrative review aims to explore how each component of modern soccer footwear impacts performance and injury risk, with a focus on evidence-based functional customization. A comprehensive narrative review of available literature was conducted across PubMed, Scopus, and Web of Science, integrating biomechanical, clinical, and materials science studies. We included studies concerning the structures composing soccer technical footwear. Conical studs were associated with reduced rotational stiffness and lower joint torque, while bladed studs enhanced linear traction but increased ACL strain risk. Upper materials, such as knitted fabrics and engineered mesh, improve proprioception and thermal regulation but show trade-offs in durability and protection. Soleplate stiffness influenced load distribution and performance: increased stiffness improves sprinting but compromises multidirectional agility. Fatigue and proprioception were modulated by insole and soleplate synergy. Soccer footwear should be seen as a clinical and performance tool requiring evidence-based customization. Advances in material technology, 4D foot scanning, and plantar pressure mapping enable functional matching between footwear and athlete characteristics. Translating these insights into player-specific footwear designs may reduce injury rates and enhance on-field performance. Full article

This protocol details an optimized step-by-step procedure for performing the Seahorse XF Cell Mito Stress Test on human umbilical vein endothelial cells (HUVECs) using the Agilent Seahorse XF Pro Analyzer. Designed to address practical challenges often overlooked in standard manuals, the method preserves the native adherent state of HUVECs—a key in vitro model in vascular aging (VA) research—enabling real-time, label-free measurement of mitochondrial respiration and glycolytic function without cell detachment. The workflow is presented chronologically, covering instrument preparation, cell seeding, compound loading, assay execution, and post-assay normalization, with integrated notes and troubleshooting tips refined through hands-on experience based on the official manuals. This protocol aims to set up a detailed, rearranged standard workflow to improve experimental efficiency, reduce operator error, and support reproducible and well-organized metabolic profiling of HUVECs in aging and cardiovascular studies. Full article

Integrated control systems (Supervisory Control and Data Acquisition–SCADA and Manufacturing Execution Systems—MES) constitute the backbone of Industry 4.0; however, research on their implementation remains scarce. This study analyzes the opportunities and challenges of modernizing these systems within the context of the Brazilian industry. A survey of 101 experts was conducted, with results analyzed via Friedman and Holm–Sidak nonparametric tests to establish a clear hierarchy of factors. Findings reveal that while economic efficiency, productivity gains, and real-time remote access represent the most significant opportunities, they are countered by critical structural challenges: obsolete machinery and inadequate infrastructure. These challenges significantly inflate implementation costs and highlight the reality of technological obsolescence that is typical of emerging economies. By applying the Resource-Based View (RBV), this research frames digital integration as a strategic competitive capability rather than a mere technical upgrade. Practically, the study provides a roadmap for industrial leaders to balance digital agility expectations with pragmatic operational constraints. These insights offer a foundation for successful digital transformation, delivering actionable value for academics, industrial managers, and policymakers. Full article

Accurately estimating story points in Agile Scrum environments remains a challenging task, as traditional models often struggle to capture the complex relationships between user stories and their corresponding effort estimations. In this study, we leverage Gemini’s embedding representations to enhance the modeling of user stories within a story point estimation dataset. To improve prediction performance, we propose GemSP, an ensemble regression model that integrates two complementary regression techniques applied to the Gemini embeddings. Our approach aims to exploit the rich semantic representations of user stories while benefiting from the robustness of ensemble learning. Experimental results show that, when instantiated with Gemini embeddings, the proposed GemSP framework achieves lower prediction error than selected baseline models (GPT-2, Deep-SE, and GPT2SP) under cross-project evaluation on JIRA datasets. These results illustrate the practical benefit of decoupling semantic representation learning from regression, enabling effective integration of stronger embedding models within lightweight ensemble predictors. Full article

Background: Reaction time and coordination are key performance components in team sports such as handball, particularly during the developmental years. Integrating visual and cognitive stimuli through smart technologies has been shown to facilitate motor skill development in young athletes. Methods: This study evaluated the effects of a BlazePod-based training protocol on reaction time, visuomotor coordination, movement quickness, and change-of-direction performance in junior male handball players aged 12–14 years. Thirty-two athletes (mean age = 13.37 ± 0.29 years) were randomly assigned to an experimental group (n = 16), in which the traditional neuromotor/coordination block of regular practice was replaced with BlazePod-based drills three times per week for eight weeks, or to a control group (n = 16), which trained the same capacities with traditional handball-specific exercises without technology. Training frequency (3 sessions/week), session duration (90 min), and the workload of the 30 min neuromotor block were matched between groups. Motor performance was assessed using four tests: Focus Reactions, Fast Feet, Clap Challenge, and the Agility T-Test. Paired- and independent-samples t-tests were applied to compare pre- and post-intervention scores. Results: The experimental group showed significant within-group improvements in Focus Reactions (p = 0.002) and AgilTT_ShuffleLeft (p = 0.014), whereas the control group showed no improvements and a small but significant worsening in Focus Reactions. Between-group comparisons at post-test revealed significant differences in favor of the experimental group for Fast Feet (p = 0.036), Clap Challenge (p = 0.008), AgilTT_Overall (p < 0.001), and AgilTT_SprintBack (p = 0.003). Conclusions: The integration of BlazePod technology into handball training produced measurable improvements in reaction speed and lateral agility among junior players. These findings suggest that technology-assisted neuromotor training represents a viable training modality that can replace a traditional neuromotor block within youth handball practice while maintaining overall training dose. Full article

Technological advances have influenced and changed cultural heritage in the galleries, libraries, archives, and museums (GLAM) sector by facilitating new forms of experimentation and knowledge exchange. In this context, this paper explores the evolving practice of archaeological facial depiction using AI-powered deepfake avatar creator software programs, such as Epic Games’ MetaHuman Creator (MHC), which offer new affordances in terms of agility, realism, and engagement, and build upon traditional workflows involving the physical sculpting or digital modelling of faces from the past. Through a case-based approach, we illustrate these affordances via real-world applications, including four-dimensional portraits, multi-platform presentations, Augmented Reality (AR), and enhanced audience interaction. We consider the limitations and challenges of these digital avatar systems, such as misrepresentation or cultural insensitivity, and we position this advanced technology within the broader context of digital heritage, considering both the technical possibilities and ethical concerns around synthetic representations of individuals from the past. Finally, we propose that the use of MHC is not a replacement for current practice, but rather an augmentation, expanding the potential for storytelling and public learning outcomes in the GLAM sector, as a result of increased efficiency and new forms of public engagement. Full article

Human Capital Agility is increasingly recognized as a critical capability for achieving sustainable project success in the highly dynamic construction sector, yet an original and empirically testable Human Capital Agility model rooted in Human Capital theory is still lacking. This study aims to develop and validate a Human Capital Agility framework that integrates Leadership Agility and Knowledge Management and to construct a hierarchical roadmap for the gradual development of Human Capital Agility. Using a multi-method design, survey data from 141 construction professionals were analyzed with Partial Least Squares Structural Equation Modeling to test the structural relationships among Knowledge Management, Leadership Agility, Human Capital Agility, Sustainable Project Success, and the moderating role of Firm Size, while expert judgments from nine practitioners were modeled using Modified Total Interpretive Structural Modeling to derive the internal hierarchy of Human Capital Agility components. The results show that Leadership Agility is a dominant driver of Human Capital Agility and that Human Capital Agility significantly enhances Sustainable Project Success, whereas the direct effect of tacit knowledge on Leadership Agility is not supported. The hierarchical model maps nine key components of Human Capital Agility into six levels, separating foundational drivers such as attitudes and predisposition from higher-level outcome capabilities such as generative behavior, responsiveness, adaptability, and resilience. These findings provide an integrated and empirically grounded Human Capital Agility model that offers both a causal explanation and a practical roadmap for strengthening human capital capabilities in construction projects. Full article

The capacity of the United Kingdom (UK) to prosecute technology-enabled financial and economic crime (FEC) is increasingly shaped by the Collingridge dilemma. Even though the dilemma was broadly conceptualized in technology governance, its application to prosecutorial and enforcement practice, evidentiary standards, and criminal liability attribution represents uncharted scholarly territory. Through socio-legal mixed methods combining doctrinal analysis, case studies, and comparative analysis, the paper shows how the dilemma’s two horns or pillars (i.e., early epistemic uncertainty and late institutional inertia) manifest in criminal law and regulatory contexts. The paper finds that just like the European Union and United States, the UK criminal enforcement ecosystem exhibits both horns across cryptocurrency, algorithmic trading, artificial intelligence (AI), and fintech domains. By integrating supplementary theories such as responsive regulation, precautionary principles and technological momentum, the study advances a socio-legal framework that explains enforcement inertia and doctrinal gaps in liability attribution for emerging technologies. The paper demonstrates how epistemic uncertainty and institutional entrenchment shape enforcement outcomes and proposes adaptive strategies for anticipatory governance including technology-literate capacity building, anticipatory legal reform, and data-driven public-private coordination. These recommendations balance ex-ante legal clarity (reducing uncertainty) with ex-post enforcement agility (overcoming entrenchment) to provide a normative framework for navigating the Collingridge dilemma in FEC prosecution. Full article

Scaling Agile in industrial software projects is a process control problem that must balance governance, scalability, and adaptability while keeping decisions auditable. We present a hybrid fuzzy multi-criteria decision-making (MCDM) framework that combines Fuzzy Analytic Hierarchy Process (FAHP) for uncertainty-aware weighting with a tunable VIKOR–PROMETHEE ranking stage. Weighting and ranking are kept distinct to support traceability and parameter sensitivity. A three-layer hierarchy organizes twenty-two criteria across organizational, project, group, and framework levels. In a single-enterprise validation with two independent expert panels (n = 10 practitioners), the tuned hybrid achieved lower rank error than single-method baselines (mean absolute error, $\mathrm{MAE}$ = 1.03; Spearman $\rho$ = 0.53) using pre-specified thresholds and a transparent $\alpha +\beta$ = 1 control. The procedure is practical for process governance: elicit priorities, derive fuzzy weights, apply the hybrid ranking, and verify stability with sensitivity analysis. The framework operationalizes modeling, optimization, control, and monitoring of scaling decisions, making trade-offs explicit and reproducible in industrial settings. Full article

Background and Objectives: Lower-extremity injuries are common among female athletes; however, their multifactorial predictors remain insufficiently understood. Given the interplay between physiological and psychological readiness in athletic performance, identifying the factors that influence lower limb performance is crucial for effective injury prevention. This study aimed to evaluate the predictive effects of physiological (VO₂peak, anaerobic power, agility, and isokinetic strength) and psychological (resilience and self-efficacy) variables on functional performance related to risk of injury. Materials and Methods: This cross-sectional study included 60 athletes with a mean age of 24.5 ± 6.90 years and mean body mass index of 23.12 ± 3.6 kg/m² (range: 16–30 kg/m²). The testing protocol included anthropometric measurements, the Lower Extremity Functional Test (LEFT), Wingate anaerobic cycling test, assessments of aerobic capacity, isokinetic muscle strength, and jumping performance (Single-Leg Hop [SLH] and Standing Long Jump [SLJ] tests). Psychological assessments included the General Self-Efficacy Scale (GSES) and a resilience questionnaire. A hierarchical regression analysis was performed. Results: The participants trained 5 ± 2 days per week and had 42 ± 39 months of sports experience. The mean VO_2peak was 40.82 ± 5.8 mL·kg⁻¹·min⁻¹, relative anaerobic peak power was 7.53 ± 1.92 W/kg, and fatigue index was 60.63 ± 15.41%. The mean isokinetic knee extension and flexion torque were 184.55 ± 44.60 N·m and 95.08 ± 21.44 N·m, respectively, with a flexion-to-extension ratio of 53.5%. The mean LEFT completion time was 160 ± 22 s. The participants demonstrated moderate resilience (BRS = 21 ± 4) and good self-efficacy (GSES = 33 ± 7.5). Among the psychological variables, GSES exhibited a modest negative correlation with LEFT (r = −0.28, p = 0.02). No significant associations were found between LEFT and psychological resilience. Longer LEFT completion times were associated with lower VO_2peak, mean power, and jump distance (p < 0.01). In the final model (R² = 0.58, p = 0.02), SLH (β = −0.54), VO_2peak (β = −10.32), and GSES (β = −0.70) were the strongest independent predictors of LEFT performance. Conclusions: SLH distance, VO_2peak, and general self-efficacy are key predictors of functional performance on the LEFT among female athletes. These factors may serve as practical indicators for identifying athletes who could benefit from targeted injury prevention programs. Full article

The purpose of this study was to develop and validate an integrated model explaining how AI-enabled knowledge integration and digital ecosystem connectivity influence knowledge innovation capability through the mediating role of knowledge agility and the moderating roles of digital trust and organizational learning culture. Grounded in the Knowledge-Based View (KBV) and Dynamic Capability Theory (DCT), this research seeks to understand how technological and cultural enablers jointly drive exploratory, exploitative, and adaptive innovation. A quantitative cross-sectional research design was employed, and data were collected from 243 professionals working in knowledge-intensive organizations. Measurement scales were adapted from previous studies, and data analysis was conducted through structural equation modeling, using SmartPLS 4. Reliability, validity, and path analyses were performed to test the hypothesized relationships among constructs. The results indicated that AI-enabled knowledge integration and digital ecosystem connectivity significantly enhance knowledge agility, which in turn positively affects knowledge innovation capability. The mediation tests confirmed the role of knowledge agility, while digital trust and organizational learning culture were confirmed to strengthen the relationship between knowledge agility and innovation capability. This study contributes to theory by integrating technological, organizational, and cultural perspectives into a unified model of digital innovation. Practically, it guides organizations in leveraging AI systems, digital connectivity, and learning culture to foster sustainable innovation. Full article

Youth soccer requires an integrated approach combining technical–tactical, physical, and psychological components to enhance performance and long-term engagement. Although Repeated Linear Sprint Training (LRST) and Repeated Change of Direction Speed (RCOD) training are widely used to improve fitness, direct comparisons of their effects on physical performance and perceptual responses in adolescent players remain limited. This study compared the effects of an 8-week LRST versus RCOD training program on physical performance, perceived exertion, and enjoyment in youth soccer players. Twenty-six male players were randomly assigned to an LRST group (n = 13) or an RCOD group (n = 13). Both groups completed two weekly sessions of their assigned training in addition to regular soccer practice. Pre- and post-intervention assessments included acceleration and sprint speed, change-of-direction (COD) performance (T-Half Test [THT], Illinois Agility Test [IAT]), lower-limb power (Five-Jump Test [5JT], Squat Jump [SJ], Countermovement Jump [CMJ]), and endurance-intensive fitness. Enjoyment and session-RPE were recorded after each training session. Both groups improved across all physical measures (main effect of time, p < 0.0001). Significant time × group interactions favored RCOD for THT (~1.6%), IAT (~1.1%), 5JT (~2.3%), CMJ (~5.2%), and SJ (~6.3%), with no overall main effect of group. Enjoyment was consistently higher in the RCOD group (p < 0.0001), while session-RPE did not differ between groups. In youth soccer, both LRST and RCOD effectively enhance physical performance. However, RCOD appears more effective for improving pre-planned COD and explosive performance while eliciting greater enjoyment without increasing perceived exertion. Incorporating structured RCOD training alongside linear sprint work may represent a practical strategy to optimize physical development and sustain player engagement. Full article

Background: This study examines how AI-driven metaverse integration enhances sustainable manufacturing performance in Jordan’s industrial sector, with particular emphasis on the mediating role of digital supply chain resilience. Grounded in resource orchestration theory (ROT), the research explains how digital twin systems, predictive AI analytics, and virtual collaboration technologies jointly support sustainability through improved supply chain agility, responsiveness, and continuity. Methods: Data were collected from 500 industrial managers, of which 415 valid responses were analyzed using partial least squares structural equation modeling (PLS-SEM). Results: The findings indicate that AI-powered metaverse dimensions have significant and positive effects on sustainable manufacturing performance, both directly and indirectly through digital supply chain resilience. The mediation analysis confirms that resilience serves as a critical mechanism linking metaverse-based technology adoption to sustainability outcomes. Conclusions: The study highlights the strategic importance of integrating advanced digital and virtual technologies into supply chains to address sustainability challenges, particularly in emerging economies such as Jordan. By extending resource orchestration theory to the metaverse context, this research contributes to theory development and offers practical insights for industrial managers seeking to leverage digital transformation as a source of sustainable competitive advantage. Full article

Research laboratories in universities face a complex challenge: they must manage multiple projects, diverse teams, and tight deadlines, often with limited resources. While the business world has long used agile and quality management tools to navigate such complexity, these methods are surprisingly rare in academic research. In this study, we set out to bridge this gap. We implemented a combined management model, blending agile Scrum practices with proven quality tools like the Ishikawa diagram and PDCA cycle, within a pharmaceutical sciences research lab. Over a six-month period, we diagnosed key issues, created a structured action plan, and introduced an online platform to monitor progress continuously. Our approach led to a significant increase in productivity, with 65% of targeted articles being published or submitted and 75% of general lab activities completed. Perhaps just as importantly, communication improved dramatically, and the lab successfully met all its institutional deadlines. We conclude that this hybrid framework is not just a theoretical idea but a practical and powerful innovation. It provides a tangible blueprint for other research groups looking to enhance their productivity, streamline communication, and build a more adaptive and effective research culture in the face of academic complexity. Full article