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Menstrual Cycle and Hormonal Contraceptive Symptom Severity and Frequency in Athletic Females
Get PDFThe purpose of this study was to determine symptom severity and frequency in female exercisers and athletes from a diverse range of sports who have a menstrual cycle (MC) or use hormonal contraceptives (HCs). An additional aim was to explore the perceived impact of MC/HC use upon exercise and sport performance. In total, 604 self-identifying female athletes and exercisers (M = 29.4 years, SD = 9.0) from 85 sports/activities completed a survey which included: sport/exercise participation, bleeding characteristics, HC use, symptom severity/frequency, symptom management strategies, menstrual product use, and perceived impact of MC/HC use on exercise performance. The data were subject to mixed-methods analysis. Over one third (n = 225; 37.25%) of participants reported current HC use. Ninety-five percent (95.36%) of participants experienced symptoms related to MC or HC use. Physiological, psychological, and affective symptoms were all among the most prevalent. The most frequently noted severe and very severe symptoms for all participants, MC and HC users, were abdominal cramps (36.92%, 39.32%, and 32.89%, respectively), mood changes (26.16%, 25.07%, and 28.00%, respectively), and tiredness (25.33%, 25.59%, and 24.89%, respectively). Symptom impact was self-managed through medical and/or other (cognitive/behavioral) strategies. Qualitative content analysis of the data produced four overarching themes: (a) the impact of symptoms, (b) menstrual stigma and taboos, (c) protective factors, and (d) coping strategies. In conclusion, menstruation is a multifaceted, unique experience that impacts upon sport/exercise performance. Practitioners should consider athletes’ distinct needs, including the frequency of occurrence and severity of their symptomatic experiences, when facilitating menstruation-supportive training, avoiding a “one-size fits-all” approach
Dynamic spillover effects and interconnectedness of DeFi assets, commodities, and Islamic stock markets during crises
Get PDFDecentralized Finance (DeFi) assets, commodities, and Islamic stock market cointegration are affected by technological innovations, market dynamics, investor behavior, and crises. This study investigates the dynamics of returns and volatility for three DeFi assets, six commodities, and three Islamic stock markets from December 2019, to March, 2023, and identifies higher spillover effects during crises. Links among the Cross-DeFi, commodity, and Islamic markets significantly influence returns and volatility during crises. Notably, the commodities index emerged as a pivotal and substantial transmitter of risk during the Russian-Ukraine war crisis, with Emerging Markets (EM) being a key recipient. However, during the COVID-19 pandemic, livestock indices assume the role of prominent risk-return spillover receivers. The findings indicate robust returns and volatility interconnected between DeFi assets and Islamic markets with a moderate level of connectivity among commodity groups. WDI, ACWI, and EM explained 75 % of the variance observed during crisis episodes. This study formulates strategic portfolio management within and between connectedness among return volatilities by highlighting the stability of DeFi assets, the diversification potential in commodities, and a balanced option in Islamic markets. Our study provides a deep and insightful understanding of the stakeholders across markets during crises
Transparent RFID tag wall enabled by artificial intelligence for assisted living
Get PDFCurrent approaches to activity-assisted living (AAL) are complex, expensive, and intrusive, which reduces their practicality and end user acceptance. However, emerging technologies such as artificial intelligence and wireless communications offer new opportunities to enhance AAL systems. These improvements could potentially lower healthcare costs and reduce hospitalisations by enabling more effective identification, monitoring, and localisation of hazardous activities, ensuring rapid response to emergencies. In response to these challenges, this paper introduces the TransparentRFIDTag Wall (TRT-Wall), a novel system taht utilises a passive ultra-high frequency (UHF) radio-frequency identification (RFID) tag array combined with deep learning for contactless human activity monitoring. The TRT-Wall is tested on five distinct activities: sitting, standing, walking (in both directions), and no-activity. Experimental results demonstrate that the TRT-Wall distinguishes these activities with an impressive average accuracy of 95.6% under four distinct distances (2, 2.5, 3.5 and 4.5 m) by capturing the RSSI and phase information. This suggests that our proposed contactless AAL system possesses significant potential to enhance elderly patient-assisted living
Evaluation and Structural Optimisation of 0.6 m Impulse Turbine in Dolphin Wave Energy Conversion Device Through Computational Fluid Dynamics and Generative Design
Get PDFIn this paper, the performance of an adapted design of a 0.6 m impulse turbine in a new wave energy conversion device—the Dolphin device—is evaluated. This study is focused on developing an optimised structure in order to maximise the potential of the device and provide a lightweight and robust novel design. For this purpose, initial studies on the system involved 2D CFD simulations combined with parametric optimisation, which validated the use of the turbine system with water as the working fluid. The obtained component geometries were then used for the creation of a 3D CFD model, which was tested in a set-up dynamic simulation environment. Subsequently, the performance of the system was evaluated through the use of referenced experimental analyses. By taking into account the loading conditions present at the blades, as well as the inherent typical loads caused by the rotational speed of the turbine, the system was then optimised using generative design processes. Through the applied methodology, the performance of the turbine was predicted to be 61.79%. Moreover, the generative design optimisation showed a reduction in mass of 60.226% for the blade structure and 69.523% for the rotor structure
Development of a Digital Health Intervention for the Secondary Prevention of Cardiovascular Disease (INTERCEPT): Co-Design and Usability Testing Study
Get PDFBackground: Secondary prevention is an important strategy to reduce the burden of cardiovascular disease (CVD), a leading cause of death worldwide. Despite the growing evidence for the effectiveness of digital health interventions (DHIs) for the secondary prevention of CVD, the majority are designed with minimal input from target end users, resulting in poor uptake and usage.Objective: This study aimed to optimize the acceptance and effectiveness of a DHI for the secondary prevention of CVD through co-design, integrating end users’ perspectives throughout.Methods: A theory-driven, person-based approach using co-design was adopted for the development of the DHI, known as INTERCEPT. This involved a 4-phase iterative process using online workshops. In phase 1, a stakeholder team of health care professionals, software developers, and public and patient involvement members was established. Phase 2 involved identification of the guiding principles, content, and design features of the DHI. In phase 3, DHI prototypes were reviewed for clarity of language, ease of navigation, and functionality. To anticipate and interpret DHI usage, phase 4 involved usability testing with participants who had a recent cardiac event (<2 years). To assess the potential impact of usability testing, the System Usability Scale was administered before and after testing. The GUIDED (Guidance for Reporting Intervention Development Studies in Health Research) checklist was used to report the development process.Results: Five key design principles were identified: simplicity and ease of use, behavioral change through goal setting and self-monitoring, personalization, system credibility, and social support. Usability testing resulted in 64 recommendations for the app, of which 51 were implemented. Improvements in System Usability Scale scores were observed when comparing the results before and after implementing the recommendations (61 vs 83; P=.02).Conclusions: Combining behavior change theory with a person-based, co-design approach facilitated the development of a DHI for the secondary prevention of CVD that optimized responsiveness to end users’ needs and preferences, thereby potentially improving future engagement
Timber properties of species with potential for wider planting in Great Britain
Get PDFDiversifying the range of tree species planted in Great Britain is an important goal in adapting to climate change and increasing the resilience of British forests. The wood properties and utilisation potential of less widely planted species are important considerations for forest managers but, for many species, there is limited relevant information available on their properties, especially for construction timber. This study examined the main physical and mechanical properties of eight species: European silver fir, Pacific silver fir, grand fir, Caucasian fir, Serbian spruce, Japanese red cedar, sycamore and silver birch. Sample material was obtained from a mixture of experimental trials, demonstration plots and normal forest stands in the age range 40–60 years. Measurements of wood density, bending stiffness and bending strength were made on structural-sized samples and indicative EN 338 strength classes were estimated. Theresults suggested that European silver fir, Pacific silver fir and Serbian spruce could all potentially be graded into the C16 strength class with a near 100% yield, while grand fir would be limited to the C14 strength class. Japanese red cedar fell below C14, limited by strength, density and stiffness. Caucasian fir was limited by strength to about C14. When silver birch and sycamore were graded against the softwood ‘C’ strength classes, they met the requirements of C40 and C20 respectively. Neither species, however, graded well in the hardwood ‘D’ strength classes. More testing is required for formal grading assignment, as these preliminary indications are based on sampling that is not fully representative of future scaled up commercial production
Microwave Devices and Circuits for Advanced Wireless Communication: Design and Analysis
No full textThis book offers a comprehensive overview of design and analysis of microwave devices and circuits for 5G and beyond wireless communication systems. It focuses on modern microwave antennas, filters, metamaterials, and MIMO systems. It includes a design approach based on Artificial Intelligence and the practical use of microwave devices and circuits in commercial, medical, and military applications.Microwave Devices and Circuits for Advanced Wireless Communications: Design and Analysis explores the performance of microwave devices and circuits by highlighting the difficulties encountered by researchers and designers such as latency, interoperability, wireless coexistence, data streaming, safety, security, and privacy. The book explores the most important aspects of antenna design, including radiation pattern control, impedance matching with bandwidth improvement, and gain enhancement. It also examines different categories of metasurfaces, including frequency-selective surfaces (FSS) and electromagnetic bandgap (EBG) structures, and their distinct roles in antenna design. Additionally, the book examines concepts such as ultra-wideband (UWB) radar for 5G millimeter wave applications, and advanced techniques such as synthetic aperture radar (SAR), beam-forming, compressed sensing, and diffraction tomography for enabling high-resolution imaging across wider application areas. The authors also present an overview on applying machine learning (ML) techniques to advanced wireless communication for signal-processing tasks such as signal denoising, equalization, and modulation recognition. They then discuss the potential significance of UAV communication systems in achieving seamless connection, quality of service (QoS), as well as the difficulties and potential remedies involved in building dependable networks using UAVs. Throughout the book the authors offer a critical assessment of the strengths and limitations of each topic and approach presented, thus providing valuable guidance for future research in this exciting field
Evolved Open-Endedness in Cultural Evolution: A New Dimension in Open-Ended Evolution Research
Get PDFThe goal of Artificial Life research, as articulated by Chris Langton, is “to contribute to theoretical biology by locating life-as-we-know-it within the larger picture of life-as-it-could-be” (1989, p. 1). The study and pursuit of open-ended evolution in artificial evolutionary systems exemplify this goal. However, open-ended evolution research is hampered by two fundamental issues: the struggle to replicate openendedness in an artificial evolutionary system, and the fact that we only have one system (genetic evolution) from which to draw inspiration. We argue that cultural evolution should be seen not only as another real-world example of an open-ended evolutionary system, but that the unique qualities seen in cultural evolution provide us with a new perspective from which we can assess the fundamental properties of, and ask new questions about, open-ended evolutionary systems, especially in regard to evolved open-endedness and transitions from bounded to unbounded evolution. Here we provide an overview of culture as an evolutionary system, highlight the interesting case of human cultural evolution as an open-ended evolutionary system, and contextualise cultural evolution by developing a new framework of (evolved) open-ended evolution. We go on to provide a set of new questions that can be asked once we consider cultural evolution within the framework of open-ended evolution, and introduce new insights that we may be able to gain about evolved open-endedness as a result of asking these questions
An artificial neural network (ANN) approach for early cost estimation of concrete bridge systems in developing countries: the case of Sri Lanka
Get PDFPurposeThe Government’s investment in infrastructure projects is considerably high, especially in bridge construction projects. Government authorities must establish an initial forecasted budget to have transparency in transactions. Early cost estimating is challenging for Quantity Surveyors due to incomplete project details at the initial stage and the unavailability of standard cost estimating techniques for bridge projects. To mitigate the difficulties in the traditional preliminary cost estimating methods, there is a requirement to develop a new initial cost estimating model which is accurate, user friendly and straightforward. The research was carried out in Sri Lanka, and this paper aims to develop the artificial neural network (ANN) model for an early cost estimate of concrete bridge systems.Design/methodology/approachThe construction cost data of 30 concrete bridge projects which are in Sri Lanka constructed within the past ten years were trained and tested to develop an ANN cost model. Backpropagation technique was used to identify the number of hidden layers, iteration and momentum for optimum neural network architectures.FindingsAn ANN cost model was developed, furnishing the best result since it succeeded with around 90% validation accuracy. It created a cost estimation model for the public sector as an accurate, heuristic, flexible and efficient technique.Originality/valueThe research contributes to the current body of knowledge by providing the most accurate early-stage cost estimate for the concrete bridge systems in Sri Lanka. In addition, the research findings would be helpful for stakeholders and policymakers to propose policy recommendations that positively influence the prediction of the most accurate cost estimate for concrete bridge construction projects in Sri Lanka and other developing countries
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