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Found 6278 publications
Effects of Exercise Addiction and the COL1A1 Gene rs1800012 Polymorphism on Injury Susceptibility in Elite Female Volleyball Players
Publication Name: Genes
Publication Date: 2025-11-01
Volume: 16
Issue: 11
Page Range: Unknown
Description:
Objectives: The objective of this study was to separately examine the effects of exercise addiction and the Collagen Type I Alpha 1 Chain (COL1A1) gene rs1800012 G/T polymorphism on injury susceptibility in elite female volleyball players, and to test the hypothesis that the T allele, previously identified as a risk allele, is underrepresented in volleyball players compared to the general population. Methods: The study included 50 professional Turkish female volleyball players with documented injury data, along with 557 Turkish controls, 53 professional Russian volleyball players, and 810 Russian controls. The Turkish participants were enrolled in a case–control study, an injury study, and an exercise addiction study, whereas the Russian participants were enrolled solely in a case–control study. Results: Injured players had significantly higher scores in the Delay of Individual Social Needs and Conflict subscale of the Exercise Addiction Scale compared to their uninjured counterparts (p = 0.036). The random-effects meta-analysis revealed a significantly lower frequency of the COL1A1 T allele in volleyball players compared to controls (pooled OR = 0.63, 95% CI: 0.41–0.96, p = 0.031). Athletes who had not undergone surgery had a significantly higher frequency of the G allele compared to controls (89.2% vs. 78.7%, p = 0.037; OR = 2.23, 95% CI: 1.1–4.7). Among injured athletes, those carrying the GT genotype were significantly more likely to experience prolonged recovery (≥3 months) (57.1%) compared to those with the GG genotype (28.0%, p = 0.017). Conclusions: Exercise addiction and the COL1A1 rs1800012 T allele were associated with a higher incidence of injury in female volleyball players. The T allele was also associated with a longer recovery time following injury.
Open Access: Yes
INVESTIGATING THE ROLE OF ACTIVATION FUNCTIONS IN PREDICTING THE PRICE OF CRYPTOCURRENCIES DURING CRITICAL ECONOMIC PERIODS
Publication Name: Virtual Economics
Publication Date: 2024-12-31
Volume: 7
Issue: 4
Page Range: 64-91
Description:
Accurate cryptocurrency price forecasting is crucial due to the significant financial implications of prediction errors. The volatile and non-linear nature of cryptocurrencies challenges traditional statistical methods, revealing a gap in effective predictive modelling. This study addresses this gap by examining the impact of activation functions on neural network models during critical economic periods, specifically aiming to determine how optimising activation functions enhances accuracy in neural network models, including RNN, GRU, LSTM, and hybrid architectures. Using data from January 2016 to June 2022—encompassing stable periods, the COVID-19 pandemic, and the onset of the 2022 Ukraine conflict—we analysed price trends under various market conditions. Our methodology involved testing three activation functions (ReLU, sigmoid, and Tanh) across these models. Both univariate and multivariate analyses were conducted, with the latter incorporating additional metrics such as opening, highest, and lowest prices. The results indicate that optimising activation functions enhances prediction accuracy. Among the models, GRU demonstrated the highest accuracy, whereas RNN was the least efficient. Multivariate models outperformed univariate ones, highlighting the benefits of incorporating comprehensive data. Notably, the Tanh activation function led to the greatest improvements, particularly in underperforming models such as RNN. These findings underscore the critical role of activation function selection in enhancing the predictive power of neural networks for cryptocurrency markets. Optimising activation functions can lead to more reliable forecasts, facilitating better trading decisions and risk management. This study highlights activation functions as key parameters in neural network modelling, encouraging further exploration. Future research could investigate different economic periods and cryptocurrency behaviours to assess model robustness. Additionally, examining a broader range of cryptocurrencies may reveal whether the benefits of activation function optimisation are consistent across various assets. Incorporating external factors such as macroeconomic indicators or social media sentiment could further enhance models and improve forecasting accuracy.
Open Access: Yes
Equation-oriented thermodynamic optimisation of heat pump integration in industrial heat recovery systems: A system-level pathway to cost and emission reduction
Publication Name: Energy
Publication Date: 2025-10-30
Volume: 335
Issue: Unknown
Page Range: Unknown
Description:
Integrating heat pumps into large-scale electricity-to-heat industrial processes has proven highly successful in enhancing the utilisation of renewable energy and contributing to carbon emission reductions. However, most studies focus on overall system performance, overlooking the detailed thermal behaviour of the heat pump itself. This limits the adaptability of heat pumps in dynamic industrial settings. This work proposes an equation-oriented framework that enables flexible integration of thermodynamically detailed heat pump models into industrial heat recovery systems. A superstructure-based optimisation model is developed to minimise energy costs and enhance efficiency, considering process constraints, network layout, and heat pump performance. The model dynamically optimises heat pump operation and placement to enhance waste heat recovery and overall system integration. Moreover, the approach supports the integration of low-grade utilities to further improve the energy efficiency. The proposed framework is validated through an industrial-scale case study of a crude oil distillation process. Life cycle assessment is conducted to quantify potential environmental and economic benefits. Results show that integrating heat pumps into the system recovered 50.52 % of low-pressure steam, reducing the total operating cost and annual cost by 12.88 % and 12.42 %. Additionally, total net carbon emissions decreased by 28.70 %. Lower electricity prices increase heat pump use and economic benefits but also amplify rebound effects. Furthermore, although high-temperature heat pumps operating above 150 °C tend to increase capital expenditures, they unlock greater energy efficiency, thereby accelerating the industrial decarbonisation process.
Open Access: Yes
Corruption Perception in the Light of Green Transition Indicators
Publication Name: Sustainable Development and Green Innovation Managing Risk Through Interdisciplinary Approaches and Policy Strategies
Publication Date: 2025-10-27
Volume: Unknown
Issue: Unknown
Page Range: 219-236
Description:
Purpose: This study explores the relationship between green transition areas that promote sustainability and the perceived level of corruption across 41 countries. Need for the study: Corruption undermines sustainability efforts and environmental governance, creating a need to understand its interaction with green transition indicators. Methodology: The study uses data from the Bertelsmann Stiftung (BS) Sustainable Governance Indicators (SGI) 2022 report and Transparency International's Corruption Perceptions Index (CPI), deploying statistical methods to examine how environmental policy and participation in international treaties affect corruption. Findings: State performance in environmental policy significantly influences corruption perception, with effects enhanced by international cooperation. Gross greenhouse gas emissions emerge as the most influential indicator, negatively affecting corruption perception by increasing its presence. Practical implications: These findings call for integrating anti-corruption measures into environmental policy frameworks, fostering international collaboration, and enhancing transparency to advance sustainable development and reduce corruption risks.
Open Access: Yes
Dynamic regulation strategy of the SCO2 Brayton cycle system based on PCM and its instability evaluation model
Publication Name: Energy
Publication Date: 2025-10-15
Volume: 334
Issue: Unknown
Page Range: Unknown
Description:
The dynamic study of the Supercritical Carbon Dioxide (SCO2 ) Brayton cycle has received extensive attention from the industry in recent years. While various dynamic operating conditions occur intermittently within the system, some commonly used control methods are unable to adapt effectively to those situations. In this study, a dynamic model of the SCO2 Brayton cycle coupled with a printed circuit heat exchanger with embedded PCM, a storage tank, and a proportional-integral-derivative (PID) controller was developed and validated with the model, and then the control effects of the various control models were compared in terms of their control effectiveness under three typical variable operating conditions (periodic temperature fluctuation, load reduction and recovery, and reduced flow rate). In addition, the stability assessment of the SCO2 Brayton cycle was modeled. Compared to the basic SCO2 Brayton cycle, the PCM-PCHE reduces the amplitude of the total efficiency fluctuations by 44.8 %, and the integrated layout covering the printed circuit heat exchanger with embedded PCM, storage tank, and PID controller shows the best stability. Controlling the extraction ratio with a PID controller contributes more to the stability of the SCO2 Brayton cycle than controlling the condensate flow rate with a PID controller. In contrast, the printed circuit heat exchanger with an embedded PCM contributes more to the stability of the SCO2 Brayton cycle concerning the storage tank. Overall, the total control layout reduced the instability by about 40 % compared to the initial recompression layout, indicating that the PCM, storage tank, and PID controller greatly improved the stability of the SCO2 Brayton cycle.
Open Access: Yes
Evaluation of SLAM Methods for Small-Scale Autonomous Racing Vehicles †
Publication Name: Engineering Proceedings
Publication Date: 2025-01-01
Volume: 113
Issue: 1
Page Range: Unknown
Description:
Simultaneous Localization and Mapping (SLAM) is a critical component of autonomous navigation, enabling mobile robots to construct maps while estimating their location. In this study, we compare the performance of SLAM Toolbox and Cartographer, two widely used 2D SLAM methods, by evaluating their ability to generate accurate maps for autonomous racing applications. The evaluation was conducted using real-world data collected from a RoboRacer vehicle equipped with a 2D laser scanner and capable of providing odometry, operating on a small test track. Both SLAM methods were tested offline. The resulting occupancy grid maps were analyzed using quantitative metrics and visualization tools to assess their quality and consistency. The evaluation was performed against ground truth data derived from an undistorted photograph of the racetrack.
Open Access: Yes
Robust Control of a Quadcopter BLDC Motor: Comparative Analysis of PID and H∞ Controllers
Publication Name: International Journal of Automotive Science and Technology
Publication Date: 2025-12-17
Volume: 9
Issue: 1st Future of Vehicles Conf.
Page Range: 1-6
Description:
The aim of the present study was to investigate a control strategy designed for the BLDC (Brushless Direct Current) motor of a quadcopter-type drone, with particular emphasis on the precise and stable maintenance of altitude in a disturbed environment. Two different control methods were implemented and compared during the research: the classical PID (Proportional-Integral-Derivative) controller and the H∞ (H-infinity) control technique. The investigations were carried out along two approaches. On the one hand, a transfer function—reproduced from a previous study—was used as a possible reference, and tested in the MATLAB simulation environment. On the other hand, a custom-developed physical prototype with one degree of freedom was created, capable of vertical motion along a single axis, allowing for the examination of altitude control under real-world conditions. The purpose of the system was to maintain a predetermined hovering altitude even in the presence of external disturbances, such as artificially generated wind. During the design of the control algorithms, a state-space-based modeling approach was applied, and appropriate weighting functions were defined, with special attention given to robustness against disturbances, control accuracy, and energy-efficient operation. The simulation results showed that the H∞ controller reduced average power demand by 19.43% compared to PID control, while practical measurements demonstrated a 38% decrease in average power consumption. In addition, overshoot was reduced by 96% and oscillation amplitude by 86% under wind disturbance. The objective of the research was to examine the practical applicability of an advanced control method that can provide greater stability, reliability, and energy efficiency under varying environmental conditions compared to traditional solutions.
Open Access: Yes
Innovative wireless sensing for modal analysis and damage modeling of Petőfi Bridge
Publication Name: Results in Engineering
Publication Date: 2024-12-01
Volume: 24
Issue: Unknown
Page Range: Unknown
Description:
The historic Petőfi Bridge (1933), a steel truss structure in Győr, Hungary, exemplifies the vulnerability of truss-type bridges to both local and total collapse. This study introduces an innovative, low-cost, accurate, and scalable wireless sensing system (WSS) for Structural Health Monitoring (SHM), utilizing the Petőfi Bridge as a case study. The research details the architecture and workflow of the system, with experimental validations confirming the accuracy of measured acceleration responses. The main natural frequencies of the bridge were estimated by processing the collected data, showing a strong correlation with reference values obtained through conventional wired systems. A calibrated high-fidelity finite element model analyzed the sensitivity of bridge damage detection indicators. The study explores variations in vertical displacement, and modal frequencies, and validates an approach based on displacement influence lines (DILs). The findings indicate the varying efficacy of these indicators in detecting structural damage, providing critical insights for advancing SHM practices.
Open Access: Yes
Sorting for Sustainability: Harnessing Female Awareness of Zero Waste
Publication Name: Journal of Sustainability Research
Publication Date: 2024-12-01
Volume: 6
Issue: 4
Page Range: Unknown
Description:
Background: Sustainable Development Goal 12 focuses on sustainable consumption and production patterns. Females are more likely to adopt these sustainable consumption practices due to their environmental attitudes. The scope of the present research is to develop a Hungarian model that can provide a theoretical explanation for the formation, viability and empowerment of zero waste awareness among females as they are sensitive to the issue and may have sufficient knowledge about it. Methods: An online questionnaire was distributed in a university environment in Hungary, resulting in 160 responses after data cleaning. The model was constructed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Results: The results show that for females, the factors waste sorting and zero waste practicality account for 72.4% of the variance in zero waste awareness. The Beta values indicate that both effects are positive with the effect of the first (βZWS-ZWA = 0.523) being stronger than the second (βZWP-ZWA = 0.389). In addition, it can be concluded that women’s attitudes toward waste sorting have a strong positive impact (R2 = 0.542, βZWS-ZWP = 0.736) on zero waste practicality. Conclusions: The zero waste attitudes of female university students’ behavior are significantly related to the selective collection of waste and the practical use of old products. In addition, waste separation is a practical approach to environmental responsibility, as there is no need to dispose of all end-of-life products if they can be recycled. The model could help the government understand the factors and the mindset from a female perspective in order to partially support the decision-making process related to sustainability.
Open Access: Yes
