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Do cheaters prosper? Effect of externally supplied momentum during resistance training on measures of upper body muscle hypertrophy.
Get PDFExercise technique, defined as the controlled execution of bodily movements to ensure an exercise effectively targets specific muscle groups while minimizing the risk of injury, is a resistance training (RT) variable frequently highlighted as critical to successful RT program outcomes, with proper technique suggested to play a role in maximizing muscle development. This study examined the effects of externally applied momentum on RT-induced muscular adaptations in the upper extremities. Thirty young adults were recruited to participate in a within-participant design, with one limb randomly allocated to perform biceps curls and triceps pushdowns using strict form (STRICT) and the other using external momentum (CHEAT). Participants completed four sets of each exercise with 8-12 repetitions until momentary muscular failure, twice a week for eight weeks. We obtained pre-post proximal and distal measures of muscle thickness for the elbow flexors and extensors, and assessed circumference changes in the upper arms. Data were analyzed in a Bayesian framework including both univariate and multivariate mixed effect models with random effects. Differences between conditions were estimated as average treatment effects, with inferences based on posterior distributions and Bayes Factors (BFs). Results showed similar between-conditions increases for all muscle thickness sites as well as circumference measures, generating consistent support for the null hypothesis (BF = 0.06 to 0.61). Volume load was markedly greater for CHEAT compared to STRICT across each week of the intervention. In conclusion, the use of external momentum during single-joint RT of the upper extremities neither helped nor hindered hypertrophy of the target muscles
A systematic review of simulation models in medicine supply chain management: current state and emerging trends.
Get PDFSimulation modelling has widely been applied in healthcare supply chain management, focusing on blood and vaccine supply chains with less attention on the medicine supply chains. This study presents a systematic review of studies applying simulation methods, namely agent-based modelling, discrete event simulation, and system dynamics, to address problems in the medicine supply chain. We adopt the Search, Appraisal, Synthesis, and Analysis (SALSA) approach to collect data from three databases (Scopus, Web of Science, and PubMed) from 2000 to 2023. 320 journal publications qualified for the initial screening and filtration and were extracted for further analysis. Only 31 studies met the inclusion criteria, with the first publication identified in 2010 and the last in 2023. The paper shows the usefulness of applying simulation in identifying medicine supply chain bottlenecks pertaining to stockouts (19%, n = 6), and falsified or counterfeit (16%, n = 5). System dynamics was the most applied approach with 42% (n = 13) and 6% (n = 2) employing a hybrid simulation approach. 32% (n = 10) of the studies reported verification and validation at either a conceptual or operational level with insufficient data from the real-world system reported as a challenge. The study suggests a gradually increasing interest in simulation applications in medicine supply chains informing decision-making. Combining multiple simulation approaches is recommended to address complex medicine supply chain issues, such as availability. In order to understand the usefulness of the model in decision-making, more effort is needed to validate developed models
Knee flexion range of motion does not influence muscle hypertrophy of the quadriceps femoris during leg press training in resistance-trained individuals.
Get PDFThis study investigated the effect of knee flexion range of motion (ROM) during the leg press exercise on quadriceps femoris muscle hypertrophy in resistance-trained individuals. Twenty-three participants (training age: 7.2 ± 3.5 years) completed a within-participant design, performing four sets of unilateral leg presses to momentary failure twice weekly for eight weeks. In one leg, knee flexion range of motion (ROM) was fixed at approximately 5–100°, while for the other leg, participants used their maximum individualized ROM (5–154 ± 7.8°). Quadriceps muscle thickness was assessed via B-mode ultrasonography at the proximal, central, and distal regions of the mid- and lateral thigh. Bayesian analyses were conducted to quantify treatment effects and provide inferential estimates using credible intervals and Bayes Factors (BF). Univariate and multivariate analyses indicated "moderate" (BF = 0.14 to 0.22) and "extreme" (BF<0.01) evidence in support of the null hypothesis, respectively. Within-condition analyses revealed small-to-medium hypertrophic adaptations in both conditions, with absolute increases ranging from 1.08 mm to 1.91 mm. These findings suggest that both knee flexion ROMs are similarly effective for promoting quadriceps femoris muscle hypertrophy over a relatively short training-period in resistance-trained individuals
Investigating intersectionality and its influence on information behaviours of women and immigrant digital entrepreneurs in Nigeria: overcoming social inequalities through information strategies.
Get PDFThis study investigates how intersecting social identities shape the information behaviours of women and immigrant digital entrepreneurs in Nigeria, addressing systemic inequalities through information practices. Using a qualitative approach, the research analyses interviews with 26 digital entrepreneurs, including seven marginalized women and immigrant entrepreneurs, employing grounded theory and critical realism. Findings reveal that gender, marital status, sexual orientation, religion and socioeconomic status create multilayered barriers to information. Conversely, technology, online communities including WhatsApp groups and mutual support networks emerge as critical enablers, fostering agency and resilience. The study introduces Socio-Informational Stratification (SIS), a mid-range theory highlighting how marginalized entrepreneurs navigate stratified information environments, repositioning themselves despite structural constraints. Through bridging micro-level lived experiences with macro-level structural forces, this study advances understanding of how marginalized groups leverage information to challenge systemic inequities in Nigeria's evolving digital entrepreneurship environment
Competency, understanding and the role of explanation in AI-driven education.
No full textThe increasing use of artificial intelligence within educational practice raises many important questions about the future role of pedagogical concepts long considered fundamental. One such example is the notion that understanding comes about through forms of explanation. Given the lack of transparency in current generative AI models, it is reasonable to ask what impact this will have on the need for explanations within teaching and what this means for its relationship to student understanding. Will the widespread use of generative AI technologies result in enhanced learning opportunities or does it mean that students will simply offload crucial parts of the learning process without any compensatory benefits? While research in Artificial Intelligence in Education (AIEd) continues to grow, there remains a significant gap in incorporating educational research perspectives. Most AIEd research is dominated by those with an engineering background, focusing heavily on technological design and development. This engineering-centric approach may often overlook the viewpoints of educational researchers and teachers, leading to a narrow understanding of AI’s role in educational settings. This paper takes a distinctly educational research perspective, examining how AI-driven tools may be shaped to enhance learning, understanding, and competency in contemporary education
Entrepreneurship in the Arab world.
No full textEntrepreneurship in the Arab World is a pioneering academic reader and research companion offering an in-depth exploration of entrepreneurship in the Arab world. Edited by leading scholars with deep regional expertise, the book addresses the cultural, institutional, religious and socio-economic dynamics shaping entrepreneurial activity in Arab countries. With contributions from local and international experts, the book provides a rich, contextualized analysis across a broad spectrum of topics, including women's entrepreneurship, youth entrepreneurship, social innovation, family enterprises, digital entrepreneurship, green entrepreneurship, Islam and entrepreneurship and more. This book is designed for university students, educators, researchers, business support agencies, international aid agencies, and policy-makers working in or focused on supporting entrepreneurship in the Arab world. Its structured chapters include case studies, key learning points, and discussion questions to enhance teaching and learning. The book fills a critical gap in contextualized entrepreneurship education resources by offering a tailored, region-specific deep dive. It promotes culturally relevant learning, provides practical insights for students and practitioners and offers policy recommendations for fostering inclusive and sustainable entrepreneurship. This essential text will support the growing regional movement towards economic diversification and youth empowerment and serve as a benchmark for future research and pedagogy in Arab entrepreneurship studies
Multi-scale infinite element analysis of GFRP pipe stiffness: effect of fibre volume fraction.
Get PDFThis study employs a multi-scale finite element analysis (FEA) to investigate the mechanical behaviour of a Glass Fibre-Reinforced Polymer (GFRP) pipe under diametral compression. A Representative Volume Element (RVE) was used to generate homogenised material properties for three fibre volume fractions (FVF) of 30%, 55% and 70%. These properties were implemented in a macro-scale model of FRP ring tested as per ASTM D2412. Results demonstrate a significant positive correlation between fibre content, structural stiffness, and ultimate strength, validating the multi-scale approach and providing key insights for composite pipe design
Adaptive double pulse dual coprime frequency diverse array MIMO radar for enhanced range, angle and doppler estimation.
Get PDFIn this paper, we propose a Double Pulse-based Dual Coprime Frequency Diverse Array Multiple Input Multiple Output (DCFDA-MIMO) radar for enhanced target parameter estimation, including range, angle, and Doppler. The proposed model employs an unstructured approach for parameter estimation using the recently developed DCFDA-MIMO radar, which has garnered significant attention due to its superior target resolution compared to traditional Frequency Diverse Array MIMO (FDA-MIMO) radar. Because most conventional designs rely on a structured approach using a single pulse, conventional FDA-MIMO radar suffers from increased computational complexity due to multiple signal classification (MUSIC) and strong coupling between range and angle parameters. To address these challenges, we introduce an efficient, low-complexity method that effectively reduces range-angle coupling and improves target parameter estimation. Unlike existing techniques, the proposed approach uses the Double Pulse method, transmitting the first pulse without frequency increments to estimate the angle. In contrast, the second pulse incorporates suitable frequency increments to estimate range and Doppler separately by incorporating the estimated angle information. Monte Carlo simulations validate that the proposed DCFDA-MIMO-based Double Pulse method significantly improves target parameter estimation in terms of signal-to-noise ratio (SNR), signal-to-interference-and-noise ratio (SINR), and Cramér–Rao lower bound (CRLB) compared to existing array structures
Digitalisation and green strategies: a systematic review of the textile, apparel and fashion industries.
No full textThe textile, apparel, and fashion (TAF) industries are vital to national economies, providing employment and fostering global economic development. On the other hand, TAF industries contribute to approximately 20% of global pollution. The rise of Industry 4.0 (I4.0) technologies—including the Internet of Things (IoT), Artificial Intelligence (AI), and robotics—aims to enhance production efficiency and resource management. However, this transition brings several challenges, such as potential disruptions from automation, concerns regarding energy efficiency, and escalating sustainability demands. In response, Industry 5.0 (I5.0) emphasises the integration of human-centric and sustainable practices, encouraging collaboration between humans and machines. While some existing studies highlight the potential of these technologies as enablers of the circular economy (CE), they often fall short of comprehensively linking these technologies to specific operational and strategic elements of CE. Furthermore, they do not sufficiently address how these digital tools fit within a broader sustainability framework in the context of CE principles. This review study aims to explore how digital transformation through I4.0 and I5.0 technologies can enhance circular economy practices in the TAF industries while alleviating the environmental and social challenges associated with industrial growth. The study examined 42 peer-reviewed studies from 2013 to 2023, employing a descriptive and theoretical literature review methodology to analyse the strategies, impacts, and challenges of digitalisation and green transition in the TAF industries. Findings reveal a significant disparity between firms in the Global North, which focus on technology advancement, and those in the Global South, facing implementation barriers. The study advocates for an approach that contextualises the integration of I4.0 and I5.0 technologies, ensuring that sustainable production practices align with regional needs
Generating realistic benchmarks for dynamic truck and trailer scheduling using Gaussian Copulas.
Get PDFAcademic research in dynamic optimisation uses benchmark generators to artificially simulate controlled and reproducible changing-environments to systematically compare algorithmic performance under uncertainty. However, due to the scarcity or difficulty in acquiring real-world data, benchmarks often fail to incorporate real-world features, such as problem constraints or the time-linkage property, where previously made decisions influence future events. This study introduces a Gaussian Copula-based real-world data-driven synthetic data generation model for Dynamic Truck and Trailer Scheduling Problem (DTTSP). The model offers a realistic, privacy-preserving DTTSP benchmark instance generator, which can be used to recreate the dynamism, constraints, heterogeneity, and time-linkage of logistics and supply chain operations. This work examines the utility, fidelity, and privacy of the suggested model in four workday case studies from a local transportation company. The conducted experiments demonstrate the systematical application of Gaussian Copulas to produce accurate, useful, and secure DTTSP benchmark instances that capture the statistical properties and correlation of variables, as well as the temporal patterns, in the original annual data. Nevertheless, the utility analysis of the conditional sampling indicates that there is still room for improvement in the modelling process
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