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Search Results (111,759)

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19 pages, 3781 KiB  
Article
Validation of Atmospheric Wind Fields from MIGHTI/ICON: A Comprehensively Comparative Analysis with Meteor Radars, FPI and TIMED/TIDI
by Dini Gong, Shengyang Gu, Yusong Qin, Na Li, Yiding Chen, Wei Yuan and Yafei Wei
Remote Sens. 2025, 17(5), 794; https://doi.org/10.3390/rs17050794 (registering DOI) - 24 Feb 2025
Abstract
The Michelson interferometer for global high-resolution thermospheric imaging (MIGHTI) aboard the NASA ionospheric connection (ICON) satellite offers extensive atmospheric wind field data for mid-latitude regions and has recently released its version 5 (v05) data. We conducted a comprehensive comparison and validation of MIGHTI [...] Read more.
The Michelson interferometer for global high-resolution thermospheric imaging (MIGHTI) aboard the NASA ionospheric connection (ICON) satellite offers extensive atmospheric wind field data for mid-latitude regions and has recently released its version 5 (v05) data. We conducted a comprehensive comparison and validation of MIGHTI v05 level 2.2 data for the period from December 2019 to October 2022, covering all MIGHTI data in orbit. In a comparison of raw wind speeds, MIGHTI demonstrates good agreement with the ground-based Fabry–Pérot interferometer (FPI), meteor radars, and the space-borne instrument TIMED Doppler interferometer (TIDI). However, some differences still exist. Comparisons with meteor radars revealed differences attributable to observational altitude, day–night variations, and latitude distribution. Below 100 km, MIGHTI and meteor radar exhibit excellent consistency (r = 0.819 for zonal and r = 0.782 for meridional winds). Day–night differences are minimal, with closer amplitude values observed at night. MIGHTI shows stronger correlations with low-latitude meteor radar, with coefficients of 0.859 (zonal) and 0.891 (meridional) at Ledong. The meridional wind correlation is better in low-latitude regions, in contrast to mid-latitudes. Similar observations were made in a comparison with FPI, emphasizing the need for caution when considering the meridional wind component of MIGHTI at observational boundaries (~40 °N). In addition to comparing raw wind speed data, we analyzed the amplitude of fluctuations extracted by MIGHTI and TIDI by employing the least squares method to extract planetary waves. The results indicate that both TIDI and MIGHTI observe the same fluctuation events, but TIDI extracts larger fluctuation amplitudes than MIGHTI. Finally, we present, for the first time, the spatial structure of a five-day wave that occurred in March 2020. Full article
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11 pages, 1211 KiB  
Article
Aberrant Expression Levels of Androgen Receptor and SRD5A2 in Epididymal Epithelial Cells of Crossbred Infertile Cattle–Yak
by Manita Wittayarat, Kimika Kawanishi, Haruka Ohata, Megumi Nagahara, Rentsenkhand Sambuu, Otgonjargal Sambuu, Maki Hirata, Fuminori Tanihara, Masayasu Taniguchi, Takeshige Otoi and Yoko Sato
Animals 2025, 15(5), 660; https://doi.org/10.3390/ani15050660 (registering DOI) - 24 Feb 2025
Abstract
Although yaks and cattle belong to the same Bovinae subfamily and have the same number of chromosomes, hybrid males are sterile because of the inactivation or abnormality of gene expression related to the production of healthy normal sperm. Recently, the analysis of gene [...] Read more.
Although yaks and cattle belong to the same Bovinae subfamily and have the same number of chromosomes, hybrid males are sterile because of the inactivation or abnormality of gene expression related to the production of healthy normal sperm. Recently, the analysis of gene expression not only in the testis but also in the epididymis has offered hints about the mechanism of infertility, because the epididymis supports the maturation of sperm in acquiring the capacity of fertilisation. Sperm maturation processes have been thought to be androgen-dependent, and the androgen receptor (AR) can be activated by dihydrotestosterone converted from plasma testosterone by the 5α-reductase isoform 2 (SRD5A2) in epididymal cells. In the present study, we investigated the immuno-expression levels of the AR and SRD5A2 in the epithelial cells of the hybrid cattle–yak epididymal caput in comparison with yak samples using image analysis. Epididymal tissues from yaks (1–3 years of age) and hybrid cattle–yaks (2 years of age) were used in this study. In yaks, AR signal intensity did not show any changes in epididymal epithelial cells during maturation. However, in 2-year-old hybrid cattle–yaks, AR signal intensity was significantly higher in the principal cells of the epididymis compared to that of yaks of the same age, indicating that hybrid sterility is not likely related to AR deficiency in the epididymal epithelium. On the other hand, SRD5A2 signal intensity was stable during maturation in the epithelial cells of the yak epididymis. However, the epididymal SRD5A2 signal intensity in the epithelial cells of the hybrid cattle–yak was lower than that of the yak. This suggests that a deficiency in SRD5A2 production in the epididymis may result in hybrid infertility, as it can subsequently cause incomplete AR signal transduction and altered spermatozoa physiology. Full article
(This article belongs to the Section Animal Reproduction)
25 pages, 5576 KiB  
Article
MultiDiffEditAttack: A Multi-Modal Black-Box Jailbreak Attack on Image Editing Models
by Peihong Chen, Feng Chen and Lei Guo
Electronics 2025, 14(5), 899; https://doi.org/10.3390/electronics14050899 (registering DOI) - 24 Feb 2025
Abstract
In recent years, image editing models have made notable advancements and gained widespread use. However, these technologies also present significant security risks by enabling the creation of Not Safe For Work (NSFW) content. This study introduces MDEA (MultiDiffEditAttack), an innovative multi-modal black-box jailbreak [...] Read more.
In recent years, image editing models have made notable advancements and gained widespread use. However, these technologies also present significant security risks by enabling the creation of Not Safe For Work (NSFW) content. This study introduces MDEA (MultiDiffEditAttack), an innovative multi-modal black-box jailbreak attack framework designed to evaluate and challenge the security of image editing models. MDEA leverages large language models and genetic algorithms to generate adversarial prompts that modify sensitive vocabulary structures, thereby bypassing prompt filters. Additionally, MDEA employs transfer learning to optimize input image features, effectively bypassing post-hoc safety checks. By integrating prompt attacks and safety checker attacks, MDEA utilizes a multimodal attack strategy to target image editing models in a black-box setting. Experimental results demonstrate that MDEA significantly improves the attack efficiency against image editing models compared to current black-box methods. These results demonstrate the effectiveness of MDEA in multi-modal attacks and reveal numerous vulnerabilities in current defense mechanisms. Full article
(This article belongs to the Special Issue Security and Privacy for AI)
20 pages, 8937 KiB  
Article
The Flexural Performance of Underground Combined Walls
by Chunchao Chen and Shihai Chen
Buildings 2025, 15(5), 728; https://doi.org/10.3390/buildings15050728 (registering DOI) - 24 Feb 2025
Abstract
Connecting diaphragm walls as permanent components of underground spaces in relation to basement sidewalls is an effective method for enhancing structural stability, reducing structural footprint, and improving waterproofing performance. To investigate the influence of connection methods between diaphragm walls and sidewalls on the [...] Read more.
Connecting diaphragm walls as permanent components of underground spaces in relation to basement sidewalls is an effective method for enhancing structural stability, reducing structural footprint, and improving waterproofing performance. To investigate the influence of connection methods between diaphragm walls and sidewalls on the mechanical performance of combined walls and to determine the differences in mechanical behavior between combined and composite walls, four–point bending experiments were conducted based on static loading systems and digital imaging technology. The cracking characteristics, strain response, load–bearing capacity, displacement ductility, and interface mechanical behavior of a combined wall with interface roughening and rebar anchoring, a combined wall with shear grooves, and a composite wall with a high–density polyethylene waterproof layer were comparatively analyzed. The results showed that for the combined walls with interface roughening and rebar anchoring or with shear grooves, through–thickness cracks extended across the interface, with no interfacial slipping failure observed. The combined wall with shear grooves exhibited noticeable through–thickness cracks. For the composite wall, cracks were staggered on both sides of the interface, with significant interface slipping failure. Compared to the composite wall, the combined walls demonstrated superior overall performance with fewer cracks. Additionally, the load–bearing capacity and displacement ductility of the combined wall with interface roughening and rebar anchoring were significantly higher than those of the combined wall with shear grooves and the composite wall. The composite wall exhibited the lowest load–bearing capacity, while the combined wall with shear grooves demonstrated the least displacement ductility. Full article
(This article belongs to the Section Building Structures)
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24 pages, 1122 KiB  
Review
From Cadavers to Neural Networks: A Narrative Review on Artificial Intelligence Tools in Anatomy Teaching
by Srinivasa Rao Sirasanagandla, Sharmila Saran Rajendran, Sreenivasulu Reddy Mogali, Yassine Bouchareb, Noushath Shaffi and Adham Al-Rahbi
Educ. Sci. 2025, 15(3), 283; https://doi.org/10.3390/educsci15030283 - 24 Feb 2025
Abstract
The application of artificial intelligence (AI) in anatomy teaching is gaining attention due to its potential to support personalized learning and its ability to provide customized, real-time feedback. While the potential impact of complete AI integration in medical education remains unclear, there is [...] Read more.
The application of artificial intelligence (AI) in anatomy teaching is gaining attention due to its potential to support personalized learning and its ability to provide customized, real-time feedback. While the potential impact of complete AI integration in medical education remains unclear, there is a suspicion that it could revolutionize pedagogical and assessment practices. Traditional anatomy teaching strategies that use donated human resources hinder continuous learning due to accessibility and ethical challenges. Existing resources, such as anatomy atlases, may not provide knowledge of spatial relationships. AI-powered applications enable students to access more flexible and accessible learning material beyond physical classrooms. This review critically evaluates current advances and the possible impacts of AI in learning anatomy based on the reported empirical original studies. Additionally, it recognizes the challenges and provides possible solutions for them. Most of the initiatives to integrate AI in anatomy teaching are directed towards the development of customized anatomy chatbots and their integration with virtual reality (VR). Although the crucial role of medical imaging in the anatomy curriculum is recognized, currently, no AI application has been developed to target this field. This review discusses the currently available AI tools for anatomy teaching. Additionally, the knowledge gaps and future directions of AI in medical education, especially anatomy education, are also discussed. With the present advances in AI technologies, their application in anatomical education is still deficient. This review paper provides an overview of recent tools used in anatomy teaching and learning. Full article
15 pages, 3020 KiB  
Article
Multi-Channel Cellytics for Rapid and Cost-Effective Monitoring of Leukocyte Activation
by Hojin Cheon, Samir Kumar, Inha Lee, Sanghoon Shin, Hyeji Jang, Young-Sun Lee, Myung-Hyun Nam, Hyun Sik Jun and Sungkyu Seo
Biosensors 2025, 15(3), 143; https://doi.org/10.3390/bios15030143 - 24 Feb 2025
Abstract
Morphological changes in leukocytes are valuable markers for diseases and immune responses. In our earlier work, we presented Cellytics, a device that uses lens-free shadow imaging technology (LSIT) to monitor natural killer cell activity. Here, we present an improved Cellytics system that has [...] Read more.
Morphological changes in leukocytes are valuable markers for diseases and immune responses. In our earlier work, we presented Cellytics, a device that uses lens-free shadow imaging technology (LSIT) to monitor natural killer cell activity. Here, we present an improved Cellytics system that has been upgraded to a four-channel configuration to achieve higher throughput while maintaining robust reproducibility for rapid and cost-effective leukocyte analysis. The performance of this multi-channel Cellytics system was improved through refinements to the micro-pinhole chip. Etched pinholes provided better image resolution and clarity compared to drilled pinholes. To stimulate leukocytes, we used an activation stimulator cocktail (ASC) and quantified the resulting morphological changes using shadow-based metrics, including peak-to-peak distance (PPD) and maxima-to-minima standard deviation (MMD-SD). In addition, we developed a new leukocyte activation parameter (LAP) to specifically assess these activation-induced morphological changes. After ASC stimulation, leukocytes showed significantly increased PPD and LAP values and decreased MMD-SD compared to non-activated leukocytes. These results are consistent with the results of the flow cytometric analysis. These results emphasize the potential of Cellytics for the rapid and accurate assessment of leukocyte activation and provide a valuable tool for both clinical diagnostics and basic immunological research. Full article
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27 pages, 2992 KiB  
Article
HiSTENet: History-Integrated Spatial–Temporal Information Extraction Network for Time Series Remote Sensing Image Change Detection
by Lu Zhao, Ling Wan, Lei Ma and Yiming Zhang
Remote Sens. 2025, 17(5), 792; https://doi.org/10.3390/rs17050792 (registering DOI) - 24 Feb 2025
Abstract
Time series remote sensing images (TSIs) offer essential data for time series remote sensing image change detection with remote sensing technology advances. However, most existing methods focus on bi-temporal images, lacking the exploration of temporal information between images. This presents a significant challenge [...] Read more.
Time series remote sensing images (TSIs) offer essential data for time series remote sensing image change detection with remote sensing technology advances. However, most existing methods focus on bi-temporal images, lacking the exploration of temporal information between images. This presents a significant challenge in effectively utilizing the rich spatio-temporal and object information inherent to TSIs. In this work, we propose a History-Integrated Spatial–Temporal Information Extraction Network (HiSTENet), which comprehensively utilize the spatio-temporal information of TSIs to achieve change detection of continuous image pairs. A Spatial-Temporal Relationship Extraction Module is utilized to model the spatio-temporal relationship. Simultaneously, a Historical Integration Module is introduced to fuse the objects’ characteristics across historical temporal images, while leveraging the features of historical images. Furthermore, the Feature Alignment Fusion Module mitigates pseudo changes by computing feature offsets and aligning images in the feature space. Experiments on SpaceNet7 and DynamicEarthNet demonstrate that HiSTENet outperforms other representative methods, achieving a better balance between precision and recall. Full article
(This article belongs to the Section Remote Sensing Image Processing)
29 pages, 22956 KiB  
Article
Numerical Investigation of Natural Light Transmission Through Fiber Optics
by Taher Maatallah, Mussad Alzahrani, Ahmad Almatar, Faisal Wahab and Sajid Ali
Energies 2025, 18(5), 1103; https://doi.org/10.3390/en18051103 - 24 Feb 2025
Abstract
Fiber optics is a cutting-edge technology with boundless potential for transmitting natural light inside buildings. Imaging Solar concentrators are very efficient in focusing light within the approximate numerical aperture of fiber optics. The proof-of-concept of fiber optics concentration daylight systems was investigated and [...] Read more.
Fiber optics is a cutting-edge technology with boundless potential for transmitting natural light inside buildings. Imaging Solar concentrators are very efficient in focusing light within the approximate numerical aperture of fiber optics. The proof-of-concept of fiber optics concentration daylight systems was investigated and elaborated for only single-mode step-index fibers, and none of the previous studies had explored the full sun spectrum meticulously, the overall transmission efficiency, and the luminous output of such a system. The present research elaborates a detailed and exclusive numerical investigation of multi-mode-indexed fiber optics daylight systems. The proposed design consists of subsequent optical stages that focus light into the fiber optic cable, filter unwanted infrared wavelength radiation, and uniformly collimate visible light onto the fiber optics. The ray path and ray power intensities were traced and computed using the ray tracing technique. The obtained simulation results demonstrated an overall optical transmission efficiency of 32% along a 10 m length. The luminous efficacy of visible light transmission was evaluated based on the average illuminance levels inside buildings, indicating a substantial indoor lighting enhancement of 92 lumens/watt. The proof-of-concept was validated by building a laboratory scale of the proposed system; the tests have shown the technical feasibility of the system and the effective material integrity for practical applications Full article
(This article belongs to the Section G: Energy and Buildings)
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22 pages, 2072 KiB  
Article
Clinical Assessment of Dairy Goats’ Udder Health Using Infrared Thermography
by Vera Korelidou, Zeljana Grbovic, Dejan Pavlovic, Isidora Simovic, Marko Panic, Anastasios Temenos and Athanasios I. Gelasakis
Animals 2025, 15(5), 658; https://doi.org/10.3390/ani15050658 - 24 Feb 2025
Abstract
This study aimed to evaluate the capacity of infrared thermography (IRT) to be used for the in situ clinical assessment of udder health status across lactation in goats. Two epidemiological studies were designed, with 106 purebred Skopelos goats being prospectively monitored over one [...] Read more.
This study aimed to evaluate the capacity of infrared thermography (IRT) to be used for the in situ clinical assessment of udder health status across lactation in goats. Two epidemiological studies were designed, with 106 purebred Skopelos goats being prospectively monitored over one lactation in the first study and 132 goats of the same breed from a second farm being enrolled in the second, cross-sectional study. Goats were categorized based on the clinical status of each udder half (healthy, fibrotic, both fibrotic and asymmetric, asymmetric, swollen supra-mammary lymph nodes, and abscessed). Skin surface temperature values of teats (TSST) and udder halves (USST), as well as temperature variations between different types of abscesses, based on the stage of their development (superficial developed, superficial fully mature, drained), and the symmetrical sites of the non-affected udder halves, were evaluated. Mixed linear regression analyses indicated that fibrosis, particularly when accompanied by asymmetry, resulted in a decrease of 0.2, 0.3, and 0.3 °C (p < 0.05) and of 0.6, 0.9, and 1.4 °C (p < 0.001) in the maximum, mean, and minimum USST, respectively. Recording season significantly affected USST and TSST (p < 0.001), with both of them increasing between February and August. Additionally, TSST appeared to be an unreliable indicator of udder health status, while abscesses exhibited distinct temperature patterns based on their developmental stage. It is concluded that IRT has the potential to be used on site for the detection of temperature alterations associated with chronic udder health issues, yet future studies on a larger and more diverse population of goats with various udder health conditions is needed to confirm its extensive applicability under real-world conditions. Full article
(This article belongs to the Special Issue Ruminant Health: Management, Challenges, and Veterinary Solutions)
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20 pages, 2090 KiB  
Article
Adsorptive Uptake of Acetaminophen by Agricultural Waste-Derived Hydrochar: Kinetics, Isotherms, and Characterization Studies
by Zaidun Naji Abudi, Rasha Al-Saedi and Alkhafaji R. Abood
Sustainability 2025, 17(5), 1923; https://doi.org/10.3390/su17051923 - 24 Feb 2025
Abstract
In this paper, we investigated a hydrochar-derived agricultural waste (AWHC) as a sustainable adsorbent, modified with three types of modification methods (by layer double hydroxides (AWHC-LDH (Mg-Al)), chemical activation method by KOH (AWHC-KOH) and H3PO4 (AWHC-H3PO4), [...] Read more.
In this paper, we investigated a hydrochar-derived agricultural waste (AWHC) as a sustainable adsorbent, modified with three types of modification methods (by layer double hydroxides (AWHC-LDH (Mg-Al)), chemical activation method by KOH (AWHC-KOH) and H3PO4 (AWHC-H3PO4), and then we used all four different types to remove acetaminophen (ACT) from synthetic solution. The maximum removal of ACT was 87%, 88%, 96%, and 97% for AWHC, AWHC-LDH (Mg-Al), AWHC-KOH, AWHC-H3PO4, respectively, at pH of 4 for AWHC-LDH (Mg-Al) and 6 for others, with a contact time of 120 min, initial concentration of 80 mg/L, adsorbent dose of 1.1 g, and speed of 200 rpm. The pseudo-second-order kinetic model could fit the adsorption process better (R2 = 0.953, 0.944, 0.924, and 0.934). The Langmuir model had the highest R2 for AWHC (0.952), AWHC-LDH (Mg-Al) (0.997), and AWHC-KOH (0.941), indicating its suitability for those hydrochars, while Freundlich isotherm had the highest R2 for AWHC-H3PO4 (0.946). The characterization results showed that LDH (Mg-Al) and KOH as modifications could effectively make the mesoporous structure. At the same time, H3PO4 developed a macroporous structure, shown by the scanning electron microscopy image supported by the Brunauer–Ettring–Teller and X-ray diffraction findings. The AWHC-LDH (Mg-Al) and AWHC-KOH exhibited better crystallinity and functional groups within the hydrochar matrix. Converting agricultural waste into practicable and sustainable materials for the environment’s benefit is a meaningful topic addressed in this paper. Full article
31 pages, 10322 KiB  
Article
SinGAN-Labeler: An Enhanced SinGAN for Generating Marine Oil Spill SAR Images with Labels
by Bin Wang, Lei Chen, Dongmei Song, Weimin Chen and Jintao Yu
J. Mar. Sci. Eng. 2025, 13(3), 422; https://doi.org/10.3390/jmse13030422 - 24 Feb 2025
Abstract
Deep learning-based SAR oil spill detection faces significant challenges due to limited labeled training data. To address this, we propose SinGAN-Labeler, an enhanced framework that generates high-quality synthetic SAR oil spill images and their labels from minimal input. The model integrates an adaptive [...] Read more.
Deep learning-based SAR oil spill detection faces significant challenges due to limited labeled training data. To address this, we propose SinGAN-Labeler, an enhanced framework that generates high-quality synthetic SAR oil spill images and their labels from minimal input. The model integrates an adaptive module to automate scale parameter optimization, accelerating training, and a hybrid attention module combining spatial, channel, and global contextual mechanisms to enhance feature extraction. By leveraging multi-scale training with diverse receptive fields, the generated images retain critical structural details while ensuring diversity. Experiments demonstrate that detection models trained on synthetic data achieve performance comparable to those using real images. Notably, expanding data sets by fivefold (from 5, 10, and 15 baseline images) improves the UNet++ model’s IoU by 78.2%, 58.5%, and 22.5%, respectively. These results validate SinGAN-Labeler’s capability to mitigate data scarcity and enhance oil spill detection accuracy, particularly under extreme sample limitations. Full article
(This article belongs to the Section Marine Pollution)
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21 pages, 351 KiB  
Review
Beyond the Surface: Nutritional Interventions Integrated with Diagnostic Imaging Tools to Target and Preserve Cartilage Integrity: A Narrative Review
by Salvatore Lavalle, Rosa Scapaticci, Edoardo Masiello, Valerio Mario Salerno, Renato Cuocolo, Roberto Cannella, Matteo Botteghi, Alessandro Orro, Raoul Saggini, Sabrina Donati Zeppa, Alessia Bartolacci, Vilberto Stocchi, Giovanni Piccoli and Francesco Pegreffi
Biomedicines 2025, 13(3), 570; https://doi.org/10.3390/biomedicines13030570 - 24 Feb 2025
Abstract
This narrative review provides an overview of the various diagnostic tools used to assess cartilage health, with a focus on early detection, nutrition intervention, and management of osteoarthritis. Early detection of cartilage damage is crucial for effective patient management. Traditional diagnostic tools like [...] Read more.
This narrative review provides an overview of the various diagnostic tools used to assess cartilage health, with a focus on early detection, nutrition intervention, and management of osteoarthritis. Early detection of cartilage damage is crucial for effective patient management. Traditional diagnostic tools like radiography and conventional magnetic resonance imaging (MRI) sequences are more suited to detecting late-stage structural changes. This paper highlights advanced imaging techniques, including sodium MRI, T2 mapping, T1ρ imaging, and delayed gadolinium-enhanced MRI of cartilage, which provide valuable biochemical information about cartilage composition, particularly the glycosaminoglycan content and its potential links to nutrition-related factors influencing cartilage health. Cartilage degradation is often linked with inflammation and measurable via markers like CRP and IL-6 which, although not specific to cartilage breakdown, offer insights into the inflammation affecting cartilage. In addition to imaging techniques, biochemical markers, such as collagen breakdown products and aggrecan fragments, which reflect metabolic changes in cartilage, are discussed. Emerging tools like optical coherence tomography and hybrid positron emission tomography–magnetic resonance imaging (PET-MRI) are also explored, offering high-resolution imaging and combined metabolic and structural insights, respectively. Finally, wearable technology and biosensors for real-time monitoring of osteoarthritis progression, as well as the role of artificial intelligence in enhancing diagnostic accuracy through pattern recognition in imaging data are addressed. While these advanced diagnostic tools hold great potential for early detection and monitoring of osteoarthritis, challenges remain in clinical translation, including validation in larger populations and integration into existing clinical workflows and personalized treatment strategies for cartilage-related diseases. Full article
(This article belongs to the Special Issue Applications of Imaging Technology in Human Diseases)
15 pages, 461 KiB  
Article
Presence of Pain Shows Greater Effect than Tendon Structural Alignment During Landing Dynamics
by Silvia Ortega-Cebrián, Diogo C. F. Silva, Daniela F. Carneiro, Victor Zárate, Leonel A. T. Alves, Diana C. Guedes, Carlos A. Zárate-Tejero, Aïda Cadellans-Arróniz and António Mesquita Montes
J. Funct. Morphol. Kinesiol. 2025, 10(1), 74; https://doi.org/10.3390/jfmk10010074 (registering DOI) - 24 Feb 2025
Abstract
Background/Objectives: Eccentric loading during landing is considered a key factor in the development of patellar tendinopathy and is associated with stiff landings and patellar tendinopathy. This study aims to investigate the relationship between tendon structure, presence of pain, and sex differences in [...] Read more.
Background/Objectives: Eccentric loading during landing is considered a key factor in the development of patellar tendinopathy and is associated with stiff landings and patellar tendinopathy. This study aims to investigate the relationship between tendon structure, presence of pain, and sex differences in landing kinematics and kinetics during countermovement jumps (CMJ) and tuck jump tests (TJT) in professional volleyball players. Methods: Professional volleyball players aged 18 to 30 years old (14 females and 25 males) participated in a cross-sectional study. Data included the Victorian Institute of Sport Assessment Patellar Tendon (VISA-P) questionnaire; patellar tendon ultrasound characterization tissue (UTC) scans, in order to identify groups with misaligned tendon fibers (MTF) or aligned tendon fibers (ATF); and biomechanical assessments for CMJ and TJT. The joint angle (JA) at the lower limb was measured at peak ground reaction force (peak_vGRF) and maximal knee flexion (max_KF). A general linear model was used to evaluate joint JA differences between tendon alignment, pain, and sex variables. Sample t-tests compared peak_vGRF, load time, load rate, and area based on tendon alignment, pain presence, sex, and jump. The statistical significance of p-value is >0.05, and the effect size (ES) was also calculated. Results: The MTF group revealed decreased knee JA during TJT at peak_vGRF (p = 0.01; ES = −0.66) and max_KF (p = 0.02; ES = −0.23). The presence of pain was associated with increased JA during the CMJ, particularly at peak_vGRF and max_KF for trunk, hip, and ankle joints. Females showed decreased peak_vGRF than males. Landing with misaligned tendon fibers showed longer load times compared to aligned tendon fibers (p = 0.021; ES = −0.80). The TJT exhibited a greater load rate than the CMJ (p = 0.00; ES = −0.62). Conclusions: Pain is a critical factor influencing greater JA during landing, particularly at the trunk, hip, and ankle joints in CMJ. Misaligned tendon fibers compromise landing dynamics by increasing trunk JA during TJT. Kinetics varied significantly by sex and jump type, while pain and tendon structure revealed limited differences. Full article
(This article belongs to the Special Issue Physical Activity for Optimal Health)
20 pages, 4004 KiB  
Article
Utilizing the Attention Mechanism for Accuracy Prediction in Quantized Neural Networks
by Lu Wei, Zhong Ma, Chaojie Yang, Qin Yao and Wei Zheng
Mathematics 2025, 13(5), 732; https://doi.org/10.3390/math13050732 (registering DOI) - 24 Feb 2025
Abstract
Quantization plays a crucial role in deploying neural network models on resource-limited hardware. However, current quantization methods have issues like the large accuracy loss and poor generalization for complex tasks. These issues pose obstacles to the practical application of deep learning and large [...] Read more.
Quantization plays a crucial role in deploying neural network models on resource-limited hardware. However, current quantization methods have issues like the large accuracy loss and poor generalization for complex tasks. These issues pose obstacles to the practical application of deep learning and large language models in smart systems. The main problem is our limited understanding of quantization’s effect on accuracy, and there is also a need for more effective approaches to evaluate the performance of the quantized models. To address these concerns, we develop a novel method that leverages the self-attention mechanism. This method predicts a quantized model’s accuracy using a single representative image from the test set. It utilizes the transformer encoder and decoder to perform this prediction. The prediction error of the quantization accuracy on three types of neural network models is 2.44%. The proposed method enables rapid performance assessment of the quantized models during the development stage, thereby facilitating the optimization of the quantization parameters and promoting the practical application of neural network models. Full article
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22 pages, 26752 KiB  
Article
Mapping Urban Tree Species by Integrating Canopy Height Model with Multi-Temporal Sentinel-2 Data
by Yang Yao, Xiaoke Wang, Haiming Qin, Weimin Wang and Weiqi Zhou
Remote Sens. 2025, 17(5), 790; https://doi.org/10.3390/rs17050790 (registering DOI) - 24 Feb 2025
Abstract
(1) Background: Urban tree species mapping is crucial for ecosystem service evaluation and sustainable urban strategy development. However, due to the spectral similarity among dominant urban tree species, spectral data alone are insufficient for high-accuracy classification. (2) Methods: We present an approach that [...] Read more.
(1) Background: Urban tree species mapping is crucial for ecosystem service evaluation and sustainable urban strategy development. However, due to the spectral similarity among dominant urban tree species, spectral data alone are insufficient for high-accuracy classification. (2) Methods: We present an approach that integrates the high-precision Canopy Height Model (CHM), generated from Ziyuan-3 (ZY3) stereo images, with multi-temporal Sentinel-2 data, for mapping 23 dominant urban tree species in Shenzhen. We primarily employed a random forest classifier using combinations of spectral bands, vegetation indices, and structural features, with subsets refined through Variance Inflation Factor (VIF) screening. We compared different models with different combinations of features, with or without the inclusion of CHM data. (3) Results: This study found that integrating VIF-screened seasonal Sentinel-2 spectral data with vegetation indices and structural metrics (Cop_DEM and ZY3_Cop_CHM) yielded an overall accuracy of 89.2%. Notably, ZY3_Cop_CHM emerged as the most influential predictor in the model. Additionally, the incorporation of ZY3_CHM data enhanced the classification accuracy by 7.1% and improved the accuracy by 4.8% compared with the use of ALOS_CHM. The species-specific F1 accuracy of a tree varies under different models and feature combinations, which underscores the need for tailored model tuning and an increase in overall model performance. Conclusions: These results indicate that integrating the ZY3_CHM data with multi-temporal Sentinel-2 data can accurately map the dominant urban tree species, suggesting its potential applicability in other urban environments. Full article
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