Search Results (3,598)

In the Chondrichthyes Raja asterias and Myliobatis aquila and in the Teleost Sparus aurata, the appendicular skeleton of the pectoral fins (including the calcified structures of the mouth in M. aquila) was investigated to find out how the specific skeletal segments were formed and stiffened over the course of evolution, not only with regard to the adaptation of the ontogenesis of the cartilage “anlagen” to the mechanical requirements of locomotion in the water column, but also to the specific feeding habits (durophagy) of M. aquila. The morphology of the pectoral fins of the three species showed a different layout, characterized by the geometry of the basic units (aligned tesserae and calcified radial columns), which provide varied flexibility of the pectoral fins, suggesting an adaptation to the “pelagic” and “benthic” locomotion patterns in the environment where the species live. The morphology of the calcified structures in the mouth of M. aquila showed the presence of two different masticatory systems: the first (external) with the rows of teeth resting on the maxillary and mandibular arches, and the second (internal, in the oral cavity) with the symphyseal plates specialized for durophagy. Chemical–physical analyses revealed that the calcified cartilage matrix of the Chondrichthyes fin rays, teeth and durophagy plates is stiffened by the same Ca₃(PO₄)₂ mineral phase deposed in the organic matrix of the Teleost S. aurata fins (with the characteristic SEM morphological texture of calcified bone matrix). The hitherto unknown presence of two different chewing systems in M. aquila documents an evolutionary adaptation to nutritional requirements that can be explained by two hypotheses: the coexistence of two functioning systems in current specimens, allowing for the ingestion of harder and softer prey (or plant food), or the persistence of a rudimentary dentition that is no longer used (vestigial dentition). Furthermore, the texture of the calcified matrix in teleost fishes, as observed by scanning electron microscopy, may indicate a bone-like organic matrix substrate, similar to that found in endochondral ossification. Full article

This study examines how diabetes mellitus and physiological aging influence the nanomechanical behavior of rat rib cortical bone using combined static and dynamic nanoindentation. Ribs from young control, old, and streptozotocin-induced diabetic rats were analyzed to quantify both intrinsic and frequency-dependent mechanical properties. Static nanoindentation revealed markedly higher hardness and elastic modulus in the diabetic group (0.47 ± 0.22 GPa and 9.53 ± 3.03 GPa, respectively) compared to controls (0.11 ± 0.03 GPa and 3.21 ± 0.51 GPa; p < 0.001). The modulus-to-hardness ratio, an indicator of fracture toughness, was reduced from 30.34 in controls to 20.45 in diabetics, suggesting increased stiffness but greater brittleness. Dynamic nanoindentation (0–4.5 Hz) demonstrated significant aging-related changes in the storage and loss moduli (p < 0.001), while the loss factor (tan δ < 1) and viscosity remained similar across groups, indicating predominantly solid-like behavior. These results show that diabetes stiffens bone tissue through matrix-level alterations, whereas aging primarily affects its viscoelastic damping capacity. The combined static–dynamic nanoindentation protocol provides a robust framework for distinguishing disease- and age-related bone degradation at the tissue scale. Translationally, the findings help explain why bones in diabetic or elderly individuals may fracture despite normal mineral density, underscoring the need to assess bone quality beyond conventional densitometry. Full article

With the development of remote sensing technologies, the volume of remote sensing data is growing dramatically, making efficient management and retrieval of large-scale remote sensing images increasingly important. Recently, deep hashing for content-based remote sensing image retrieval (CBRSIR) has attracted significant attention due to its computational efficiency and high retrieval accuracy. Although great advancements have been achieved, the imbalance between easy and difficult image pairs during training often limits the model’s ability to capture complex similarities and degrades retrieval performance. Additionally, distinguishing images with the same Hamming distance but different categories remains a challenge during the retrieval phase. In this paper, we propose a novel deep relevance hashing (DRH) for remote sensing image retrieval, which consists of a global hash learning model (GHLM) and a local hash re-ranking model (LHRM). The goal of GHLM is to extract global features from RS images and generate compact hash codes for initial ranking. To achieve this, GHLM employs a deep convolutional neural network to extract discriminative representations. A weighted pairwise similarity loss is introduced to emphasize difficult image pairs and reduce the impact of easy ones during training. The LHRM predicts relevance scores for images that share the same Hamming distance with the query to reduce confusion in the retrieval stage. Specifically, we represent the retrieval list as a relevance matrix and employ a lightweight CNN model to learn the relevance scores of image pairs and refine the list. Experimental results on three benchmark datasets demonstrate that the proposed DRH method outperforms other deep hashing approaches, confirming its effectiveness in CBRSIR. Full article

(1) Background: This research investigates the application of Artificial Intelligence (AI), particularly biomimetic convolutional neural networks (CNNs), for the automatic classification of gastrointestinal (GI) polyps in endoscopic images. The study combines AI and Transfer learning techniques to support early detection of colorectal cancer by enhancing diagnostic accuracy with pre-trained models; (2) Methods: The Kvasir dataset, comprising 4000 annotated endoscopic images across eight polyp categories, was used. Images were pre-processed via normalisation, resizing, and data augmentation. Several CNN architectures, including state-of-the-art optimized ResNet50, DenseNet121, and MobileNetV2, were trained and evaluated. Models were assessed through training, validation, and testing phases, using performance metrics such as overall accuracy, confusion matrix, precision, recall, and F1 score; (3) Results: ResNet50 achieved the highest validation accuracy at 90.5%, followed closely by DenseNet121 with 87.5% and MobileNetV2 with 86.5%. The models demonstrated good generalisation, with small differences between training and validation accuracy. The average inference time was under 0.5 s on a computer with limited resources, confirming real-time applicability. Confusion matrix analysis indicates that common errors frequently occur between visually similar classes, particularly when reviewed by less-experienced medical physicians. These errors underscore the difficulty of distinguishing subtle features in gastrointestinal imagery and highlight the value of model-assisted diagnostics; (4) Conclusions: The obtained results confirm that Deep learning-based CNN architectures, combined with Transfer learning and optimisation techniques, can classify accurately endoscopic images and support medical diagnostics. Full article

Despite advancement in skin engineering, native skin grafting remains the gold standard in clinical settings. We have previously demonstrated that a platelet-derived hydrogel (PG) can act as a scaffold to engineer a semi-mature bilaminar human skin equivalent (PG-HSE). In this study, PG-HSE was grafted on full thickness wounds in athymic mice. PG-HSE was compared with native skin autografts and a clinically proven bilaminar skin graft that utilises a single layer NovoSorb^® polyurethane biodegradable temporising matrix (plus plasma) as the scaffold (BTM-HSE). The graft analysis revealed PG-HSE-grafted wounds were fully epidermised in two weeks and the level of inflammatory markers, CXCl1, CXCl2, IL1β, and IL-6 transcripts, in grafts were at similar levels to their levels in autografts. This coincided with higher expression of COL1A2, COL3A1, and COL5A1 transcripts in PG-HSE grafts, compared to autografts and BTM-HSE grafts. Moreover, a higher deposition of both Col I and Col III was detected in the PG-HSE graft wound bed, when compared to the BTM-HSE graft wound bed. Conversely, BTM-HSE grafts showed a higher level of integrins, ITGA2, ITGA3, ITGA5, ITGA6, ITGAV, and ITGB1, at the RNA level, suggesting a stronger cell–scaffold interaction. In summary, we have shown although both PG and single layer BTM foam (plus plasma) are effective scaffolds for skin engineering, some key aspects of wound repair, including a reduction in inflammation and an increase in collagen deposition, are achieved with the platelet-derived hydrogel. The long-term effect of these scaffolds on wound scarring remains to be investigated. Full article

Coral reef ecosystems are biodiversity hotspots that provide essential ecological and environmental services but are increasingly threatened by anthropogenic pressure and climate change. Effective conservation of reef systems within Marine Protected Areas (MPAs) can be enhanced using spatially explicit approaches that integrate habitat mapping and ecological metrics at seascape scales. In this study, we characterized the benthic seascape of Cayo Arenas and identified optimal priority conservation zones in one of the core zones of the recently established Southern Gulf of Mexico Reefs National Park (SGMRNP). In July 2023, ground-truthing was performed to quantify the cover of sand, calcareous matrix, macroalgae, hard corals and octocorals. Cluster analysis of quantitative data and ecological similarity between classes was used to identify the main benthic habitat classes. Object-based and supervised classification algorithms on a PlanetScope image were used to construct a thematic map of the benthic reef system. Based on the thematic map, habitat connectivity, β-diversity, patch compactness, and availability for commercial species were estimated. In addition, a benthic change analysis (2017–2013), based on the spectral characteristics of PlanetScope images, was performed. The layers obtained were then used to perform an iterative weighted overlay analysis (WOA) using 126 combinations. Six main habitat classes, with different coverages of hard corals, calcareous matrix, macroalgae, and sand, were identified. Habitats with calcareous matrix and sandy substrates dominated the seascape. High habitat compactness, connectivity, and β-diversity values were observed, suggesting habitat stability and ecologically dynamic areas. Based on the WOA, eight optimal priority areas for conservation were recognized. These areas are characterized by heterogeneous habitats, moderate coral cover, and high connectivity. We provide a spatially explicit approach that can strengthen conservation planning within the SGMRNP and other MPAs, particularly by assisting zonation and sub-zonation processes. Full article

In the context of increasing urban night lighting, the phenomenon of light trespass in residential areas is becoming increasingly serious, affecting the night comfort and circadian rhythm of residents. Aiming at this problem, this paper takes the night lighting of activity places in old multi-story residential areas of Shijingshan, Beijing, as the research object, and proposes a research framework integrating parametric modeling, multi-objective optimization, correlation analysis, and scheme decision-making, aiming to trade off the two objectives of maximizing the night lighting of the activity places and minimizing indoor light intrusiveness. The study first establishes a parametric model based on Rhino and Grasshopper, combines the NSGA-II algorithm with multi-objective optimization simulation to obtain the Pareto optimal solution, analyzes the correlation between the design variables and the objective function by the Spearman method, and finally assists in the scheme decision-making by K-means clustering. The results showed that the streetlight heights (SH), distance between buildings and streetlights (DBS), and streetlight matrix types (SMT) were the key factors affecting lighting performance, which should be emphasized in the actual lighting design. Secondly, the Cluster2 solution set optimally performs the two objective functions. The 18th individual of Generation 15 (Gen. 15 Ind. 18) and Gen. 31 Ind. 42 are recommended, providing practical guidance for night lighting design in residential areas. The innovation of this study lies in applying multi-objective optimization and K-means clustering to optimize the night lighting environment in micro-spaces within old multi-story residential areas in cities, offering new insights for lighting design in similar scenarios. Full article

We investigate the quantum dynamics of entanglement and fidelity in the hyperfine structure of hydrogen atoms under dephasing noise, modeled via the Lindblad master equation. The effective Hamiltonian captures the spin–spin interaction between the electron and proton, with dephasing incorporated through local Lindblad operators. Analytical solutions for the time-dependent density matrix are derived for various initial states, including separable, partially entangled, and maximally entangled configurations. Entanglement is quantified using the concurrence, while fidelity measures the similarity between the evolving state and the initial state. Numerical results demonstrate that entanglement exhibits oscillatory decay modulated by the dephasing rate, with anti-parallel spin states displaying greater robustness compared to parallel configurations, often leading to entanglement sudden death. Fidelity dynamics reveal similar damped oscillations, underscoring the interplay between coherent hyperfine evolution and environmental dephasing. These insights elucidate strategies for preserving quantum correlations in atomic systems, with implications for quantum information processing and metrology. Full article

Jiangsu Province is an important economic province on the eastern coast of China, revealing the spatial–temporal characteristics, dynamic degree, and transition direction of land use/cover change, and its main driving factors are significant for the effective use of land resources and the promotion of regional human–land coordinated development. Based on land use data of Jiangsu Province from 2000 to 2020, this study investigates the spatiotemporal evolution characteristics of land use/cover using the dynamics model and the transfer matrix model, and examines the influence and interaction of the driving factors between human activities and the natural environment based on 10-factor data using Geodetector. The results showed that (1) In the past 20 years, the type of land use/cover in Jiangsu Province primarily comprises cropland, water, and impervious, with the land use/cover change mode mainly consisting of a dramatic change in cropland and impervious and relatively little change in forest, grassland, water, and barren. (2) From the perspective of the dynamic rate of land use/cover change, the single land use dynamic degree showed that impervious is the only land type whose dynamics have positively increased from 2000 to 2010 and 2010 to 2020, with values of 3.67% and 3.03%, respectively. According to the classification of comprehensive motivation, the comprehensive land use motivation in Jiangsu Province in each time period from 2000 to 2010 and 2010 to 2020 is 0.46% and 0.43%, respectively, which belongs to the extremely slow change type. (3) From the perspective of land use/cover transfer, Jiangsu Province is mainly characterized by a large area of cropland transfer (−7954.30 km²) and a large area of impervious transfer (8759.58 km²). The increase in impervious is mainly attributed to the transformation of cropland and water, accounting for 4066.07 km² and 513.73 km² from 2010 to 2020, which indicates that the non-agricultural phenomenon of cropland in Jiangsu Province, i.e., the process of transforming cropland into non-agricultural construction land, is significant. (4) From the perspective of driving factors, population density (q = 0.154) and night light brightness (q = 0.156) have always been important drivers of land use/cover change in Jiangsu Province. The interaction detection indicates that the land use/cover change is driven by both socio-economic factors and natural geographic factors. (5) In response to the dual pressures of climate change and rapid urbanization, coordinating the multiple objectives of socio-economic development, food security, and ecological protection is the fundamental path to achieving sustainable land use in Jiangsu Province and similar developed coastal areas. By revealing the characteristics and driving factors of land use/cover change in Jiangsu Province, this study provides qualitative and quantitative theoretical support for the coordinated decision-making of economic development and land use planning in Jiangsu Province, specifically contributing to sustainable land planning, climate adaptation policy-making, and the enhancement of community well-being through optimized land use. Full article

The flat peach, an important commercial crop in the 143rd Regiment of Shihezi, China, is overwintered using plastic film mulching. Flat peaches are cultivated to boost the local temperate rural economy. The development of accurate maps of the spatial distribution of flat peach plantations is crucial for the intelligent management of economic orchards. This study evaluated the performance of pixel-based and object-based random forest algorithms for mapping flat peaches using the GF-1 image acquired during the overwintering period. A total of 45 variables, including spectral bands, vegetation indices, and texture, were used as input features. To assess the importance of different features on classification accuracy, the five different sets of variables (5, 15, 25, and 35 input variables and all 45 variables) were classified using pixel/object-based classification methods. Results of the feature optimization suggested that vegetation indices played a key role in the study, and the mean and variance of Gray-Level Co-occurrence Matrix (GLCM) texture features were important variables for distinguishing flat peach orchards. The object-based classification method was superior to the pixel-based classification method with statistically significant differences. The optimal performance was achieved by the object-based method using 25 input variables, with an overall accuracy of 94.47% and a Kappa coefficient of 0.9273. Furthermore, there were no statistically significant differences between the image-derived flat peach cultivated area and the statistical yearbook data. The result indicated that high-resolution images based on the overwintering period can successfully achieve the mapping of flat peach planting areas, which will provide a useful reference for temperate lands with similar agricultural management. Full article

Background/Objectives: Gingival tissue deficiencies present significant treatment challenges. We investigated three xenogeneic collagen scaffolds—Fibro-Gide, FibroMATRIX, and Mucoderm—with and without human gingival MSCs for soft tissue augmentation. Methods: The study assessed scaffold properties (mechanical properties and micro-CT structure), cytocompatibility, ex vivo vascular growth stimulation (CAM-test), and in vivo effects in rabbit model. Results: All scaffolds were cytocompatible and maintained MSC viability via extract and contact cytotoxicity tests. Fibro-Gide showed the highest porosity at 78.5%, followed by FibroMATRIX at 64.3%, while Mucoderm had the lowest porosity at 33.2%. Mucoderm exhibited the greatest stiffness due to its dense structure, contrasting with the more similar mechanical properties of Fibro-Gide and FibroMATRIX. In an ex vivo HET-Cam model of the angiogenic response, Fibro-Gide exhibited reduced blood vessel length and blood flow rate compared to FibroMATRIX and Mucoderm. In vivo, Mucoderm resorbed completely, FibroMATRIX demonstrated optimal partial degradation, and Fibro-Gide retained most of its collagen structure. Conclusions: The FibroMATRIX with MSCs combination showed particularly promising results for enhancing tissue thickness and vascularization, suggesting this approach could significantly improve gingival regeneration outcomes. Full article

The tumor microenvironment (TME) comprises neoplastic and stromal cells, and extracellular matrix elements, all engaging in a complex interplay that ultimately dictates tumorigenesis, cancer progression, and therapeutic response. While extensive research on the TME has been conducted in human oncology, data on its veterinary counterpart, particularly in feline mammary tumors (FMTs), are still scarce. In this review, we explore current understanding of feline mammary carcinoma (FMC) microenvironment, focusing on tumor necrosis, fibrosis, angiogenesis, adipose tissue tumor-associated inflammation, extracellular vesicles, and epithelial–mesenchymal transition (EMT) and their prognostic implications. In FMC, remodeling of collagen fibers, cancer-associated fibroblasts (CAFs), regulatory T cells (Tregs) and elevated serum leptin have been associated with poor prognosis, whereas stromal cytotoxic T cells correlate with more favorable outcomes. By contrast, findings on necrosis and pro-angiogenic factors remain inconsistent, and research on extracellular vesicles (EVs) is still in its early stages. This review presents insights from human breast cancer (HBC) that further support and elucidate the potential relevance of these TME components. As FMCs are highly aggressive tumors, a deeper understanding of their microenvironment could not only improve prognostic accuracy but also uncover novel therapeutic targets. Furthermore, due to their similarities, FMCs offer a potential valuable spontaneous model for HBC, particularly for the aggressive triple-negative phenotypes. Full article

With the rapid development of China’s tourism industry, the homogenization of regional tourism images has become a growing concern. To address this, this study quantifies the similarities and differences in tourism image perception across China’s 31 provinces, focusing on 350 5A-level destinations, analyzing 757,046 tourist reviews collected from Ctrip.com in 2024. Using a three-dimensional framework (cognitive, affective, and overall image), we analyze social media data through natural language processing, random forest regression, and social network analysis. Key findings include the following: (1) most comments are positive, with Jiangsu and Chongqing showing high cognitive image similarity but low overall similarity; (2) cognitive image significantly impacts affective image, especially through unique tourism resources; (3) an inter-provincial similarity–difference matrix reveals significant perceptual differences among provinces. This study provides a novel methodological approach for multidimensional image evaluation and offers crucial empirical insights for regional policy-making aimed at optimizing land and tourism resource allocation, balancing regional disparities, and promoting sustainable land use and development across China. Full article

In this paper, the evaluation of the mechanical performance of novel, designed topologically optimized shin pads with advanced materials will be conducted with the aid of Finite Element Analysis (FEA) to assess the endurance of the final structure on impact phenomena extracted from actual real-life data acquired from contact sports. The main focus of the developed prototype is to have high-enough energy absorption capabilities and vibration isolation properties, crucial for the development of trustworthy protective equipment. The insertion of advanced materials with controlled weight fractions and lattice geometries aims to strategically improve those properties and provide tailored characteristics similar to the actual human skeleton. The final design is expected to be used as standalone protective equipment for athletes or as a protective shield for the development of human lower limb prosthetics. In this context, computational investigation of the dynamic mechanical response was conducted by replicating a real-life phenomenon of the impact during a contact sport in a median condition of a stud kick impact and an extreme case scenario to assess the dynamic response under shock-absorption conditions and the final design’s structural integrity by taking into consideration the injury prevention capabilities. The results demonstrate that the proposed lattice geometries positively influence the injury prevention capabilities by converting a severe injury to light one, especially in the gyroid structure where the prototype presented a unified pattern of stress distribution and a higher reduction in the transmitted force. The incorporation of the PA-12 matrix reinforced with the reused ground tire rubber results in a structure with high enough overall strength and crucial modifications on the absorption and damping capabilities vital for the integrity under dynamic conditions. Full article

Molecularly imprinted polymer (MIP) biosensors offer an attractive strategy for selective biomolecule detection, yet imprinting proteins with structural fidelity remains a major challenge. In this work, we present a rationally designed electrochemical biosensor for matrix metal-loproteinase-8 (MMP-8), a key salivary biomarker of periodontal disease. By integrating graphene oxide (GO) with electropolymerized poly(eriochrome black T, EBT) films on screen-printed carbon electrodes, the partially reduced GO interface enhanced electrical conductivity and facilitated the formation of well-defined poly(EBT) films with re-designed polymerization route, while template extraction generated artificial antibody-like sites capable of specific protein binding. The MIP-based electrodes were comprehensively validated through morphological, spectroscopic, and electrochemical analyses, demonstrating stable and selective recognition of MMP-8 against structurally similar interferents. Complementary density functional theory (DFT) modeling revealed energetically favorable interactions between the EBT monomer and catalytic residues of MMP-8, providing molecular-level insights into imprinting specificity. These experimental and computational findings highlight the importance of rational monomer selection and nanomaterial-assisted polymerization in achieving selective protein imprinting. This work presents a systematic approach that integrates electrochemical engineering, nanomaterial interfaces, and computational validation to address long-standing challenges in protein-based MIP biosensors. By bridging molecular design with practical sensing performance, this study advances the translational potential of MIP-based electrochemical biosensors for point-of-care applications. Full article