IRIS Università degli Studi dell'Aquila
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EVALUATION OF VISUAL-PERCEPTUAL ABILITIES IN BADMINTON ATHLETES
No full textPurpose: Visual-perceptual abilities play a pivotal role in sports
performance, particularly in disciplines requiring rapid decision
making and precise perception. In badminton, athletes have to follow fast-moving objects, anticipate opponent movements, and execute precise strokes. The present study aimed to assess and compare visual performance across a range of domains between competitive badminton players and age-matched controls. It was hypothesized that badminton expertise would be associated with superior performance on multiple visual and oculomotor function measures.
Methods: Seventy-two participants were recruited: 36 competitive
badminton players (21M/15F, age 22.9 ± 2.4 years, 13.2 ± 3.1 years
of practice) and 36 controls (21M/15F, age 22.3 ± 1.7 years). Visual
perceptual assessments were conducted using the Tetra system and
the EyeSwift Pro system and included: binocular visual acuity
(LogMAR), stereopsis (Wirt test), reaction time (ms), pursuit eye
movements, saccadic latency and velocity (ms), contrast sensitivity
(0.5–12 cpd), and fixation stability. Due to non-normal distributions
in most variables, Mann–Whitney U tests were employed for con
tinuous variables, with effect sizes calculated as r =|Z|/HN. Chi
square tests were used for categorical pursuit variables. Bonferroni
correction was applied to control for multiple comparisons.
Results: After Bonferroni correction, badminton players demon
strated significantly superior performance in five visual domains.
Visual acuity was markedly better in both left eye (- 0.085 ± 0.08
LogMAR, p\0.001, r = 0.528) and right eye (- 0.079 ± 0.76
LogMAR, p\0.001, r = 0.524). Reaction time showed the largest
effect (0.269 ± 0.058 vs 0.411 ± 0.072 s, p\0.001, r = 0.760).
Overall contrast sensitivity was superior (p\0.001, r = 0.414), and
right eye saccadic latency was reduced (p = 0.002, r = 0.364). No
significant differences were found in stereopsis (p = 0.149), left eye
saccadic parameters, fixation stability, saccadic velocity, or pursuit
movements after correction.
Conclusions: This comprehensive analysis provides evidence that
competitive badminton players possess superior visual abilities across multiple domains. These findings support the hypothesis that high level badminton participation is associated with enhanced visual performance, likely reflecting both self-selection of individuals with superior visual abilities and training-induced neuroplastic adaptations. The lack of group differences in saccadic peak velocity, despite shorter latencies in badminton players, may indicate that visual expertise in this population is primarily associated with faster initiation rather than alterations in the kinematic properties of eye
movements. Future longitudinal studies should investigate the relative contributions of predisposition versus training-induced adaptations
Modeling the mechanical behavior of coated masonry elements using surface stress theory
Full text linkThe Gurtin–Murdoch Surface Stress Model (SSM) is employed to model thin coatings of Steel Fiber Reinforced Mortar (SFRM) applied to masonry structures. This approach introduces a non-classical mechanical boundary condition, which expresses in-plane surface traction on the masonry facades in terms of surface stress and inertia. Finite Element (FE) analyses are performed within the elastic regime on coated masonry wall samples, both under static and dynamic loading conditions, to validate the accuracy of the theoretical model. Finally, a more realistic masonry structural system is analyzed to demonstrate the effectiveness of the proposed reinforcement and highlight the computational efficiency of the proposed surface model
Bone inflammation in postmenopausal women with type 2 diabetes or obesity in rela-tion to Wnt signaling and bone strength
No full textA mixed Cosserat and higher gradient formulation for fibrous tissues and biomaterials
No full textFibrous materials, including engineering composites and biological tissues, exhibit distinctive behaviors that can be characterized by melding concepts of Cosserat and higher gradient elasticities. In this work, we generalize higher gradient theories for fibrous materials by considering Cosserat effects. We use the principle of virtual power and the calculus of variations to obtain the balance laws and boundary conditions. For minimizing the total potential energy of the system, we find conditions for quasi-convexity, rank-one convexity, and Legendre-Hadamard inequalities that must be satisfied for solutions of the balance laws to be valid. Finally, we present a linearized formulation and show illustrative computational results. According to one example, Poynting effects arise from non-classical effects such as higher gradients and Cosserat effects
Experimental and numerical research of debonding defects detection in fiber metal laminates using low-power ultrasonic-induced thermography
No full textDebonding defects in fiber metal laminates (FMLs) pose a significant threat to structural reliability, necessitating efficient and non-destructive inspection methods. This study explores the use of low-power ultrasonic-induced thermography (LUIT) for rapid visualization of debonding defects in FMLs through combined experimental and numerical investigations. An inspection system was developed, incorporating bispectral analysis for the determination of optimized excitation frequencies, thereby enhancing the heat generated at defect locations to achieve improved detection performance. Infrared thermography was employed to monitor transient temperature evolution, and a contrast-based time-slice selection strategy was introduced to enhance defect visibility. Furthermore, a comprehensive numerical simulation framework integrating modal analysis, implicit dynamic simulation, and thermo-mechanical coupling was proposed to reveal the underlying heating mechanisms, focusing on frictional dissipation, viscoelastic damping, and plastic deformation. The combined results demonstrate the capability of LUIT to selectively heat debonding defects without damaging the material, with defect detectability strongly influenced by defect size, depth, and excitation timing. The findings demonstrate that LUIT offers a fast, safe, and non-destructive approach for reliable debonding defect detection in FML structures
Classification of “Ricotta” whey cheese from different milk and Designation of Origin-protected samples through infrared spectroscopy and chemometric analysis
Full text linkWhey cheeses are produced in various parts of the world, such as Portugal, Spain, and Turkey. In Italy, whey cheese goes under the name “ricotta”. This study investigates the classification of ricotta whey cheese derived from various milk sources (either protected designation of origin (PDO) or not) using an Attenuated Total Reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy combined with chemometric analysis. Employing the SPORT-LDA method, which can incorporate Variable Importance in Projection (VIP) analysis, 287 samples of ricotta cheese produced using milk from four different animals (sheep, cow, goat, and water buffalo) were classified according to the animal origin. This led to the correct classification of 97 % of the test samples (3 misclassified samples over 97). VIP analysis revealed that the spectral ranges of 3300–3100 cm−1, 2900–2800 cm−1, and 1700–1300 cm−1 are consistently relevant across all milk sources, thanks to the key molecular vibrations associated with protein structures, lipid content, and water. Eventually, the analysis was circumscribed to sheep ricotta cheeses, because some of these present the PDO quality mark. SIMCA was used to classify PDO samples with respect to the Non-PDO sheep ricotta individuals. The application of SIMCA to model class PDO led to 82.1 % of sensitivity and 82.7 % of specificity (in external validation). The findings underscore the robustness of ATR-FTIR spectroscopy and chemometrics in maintaining the integrity of PDO products and ensuring quality control
Roadmap for the development of machine learning-based interatomic potentials
Full text linkAn interatomic potential, traditionally regarded as a mathematical function, serves to depict atomic interactions within molecules or solids by expressing potential energy concerning atom positions. These potentials are pivotal in materials science and engineering, facilitating atomic-scale simulations, predictive material behavior, accelerated discovery, and property optimization. Notably, the landscape is evolving with machine learning transcending conventional mathematical models. Various machine learning-based interatomic potentials, such as artificial neural networks, kernel-based methods, deep learning, and physics-informed models, have emerged, each wielding unique strengths and limitations. These methods decode the intricate connection between atomic configurations and potential energies, offering advantages like precision, adaptability, insights, and seamless integration. The transformative potential of machine learning-based interatomic potentials looms large in materials science and engineering. They promise tailor-made materials discovery and optimized properties for specific applications. Yet, formidable challenges persist, encompassing data quality, computational demands, transferability, interpretability, and robustness. Tackling these hurdles is imperative for nurturing accurate, efficient, and dependable machine learning-based interatomic potentials primed for widespread adoption in materials science and engineering. This roadmap offers an appraisal of the current machine learning-based interatomic potential landscape, delineates the associated challenges, and envisages how progress in this domain can empower atomic-scale modeling of the composition-processing-microstructure-property relationship, underscoring its significance in materials science and engineering
Hydrophobic gold nanoparticles coupled with fluorescent dyes: A smart tool for optoelectronic applications
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Living Beyond the Edge: Impacts of Climate Change on Rock Lizards at the Niche Margin
Full text linkEctotherms are particularly threatened by climate change because they are strictly reliant on environmental conditions for homeostasis. Increasing environmental temperatures may approach the species' critical thermal maximum, with deleterious effects on individual thermoregulation capacities. This study tests the hypothesis developed in a recent work that under ongoing global warming populations living in sites at the warm edge of the species' thermal niche will suffer a disruption of the thermoregulation process, with detrimental effects at the individual and population level. We collected individual measurements and temperature data for Mediterranean endemic rock lizards, across the entire distribution range of the species and during two different sampling periods ~20 years apart to compare thermoregulation coefficient (C), body condition index (BCI) and population size under different climatic conditions. We found that C and BCI vary across space and time following a linear pattern along the thermal niche gradient (Niche Margin Effect, NME) until a threshold temperature, beyond which the NME is disrupted. This threshold temperature indicates the warm edge of the species' thermal niche. A slightly higher temperature marks the threshold at which we observed significant population declines over the 20-year study period in the warmest sites. This suggests a lagged response of population trends to climate warming. This study suggests a mechanism of disruption of homeostatic processes when the warm margin of the thermal niche is reached and indicates that individual parameters such as thermoregulation coefficient and body condition, rather than demographic trends, are key indicators for an early detection of population extinction risk. The multipopulation approach implemented in our study allows to identify the niche edge that underlies species' vulnerability to global warming, and to identify populations suffering negative effects of climate change before demographic collapse. This might allow to plan appropriate mitigation measures and management strategies to avoid local extinctions