Search Results (6,937)

Accurate postharvest quality evaluation of soybeans is essential for preserving product value and meeting industry standards. Traditional inspection methods are often inconsistent, labor-intensive, and unsuitable for high-throughput operations. This study presents a non-destructive soybean classification approach using a simplified reflectance-mode hyperspectral imaging system equipped with a single light source, eliminating the complexity and maintenance demands of dual-light configurations used in prior studies. A spectral–spatial data fusion strategy was developed to classify harvested soybeans into four categories: normal, split, diseased, and foreign materials such as stems and pods. The dataset consisted of 1140 soybean samples distributed across these four categories, with spectral reflectance features and spatial texture attributes extracted from each sample. These features were combined to form a unified feature representation for use in classification. Among multiple machine learning classifiers evaluated, Linear Discriminant Analysis (LDA) achieved the highest performance, with approximately 99% accuracy, 99.05% precision, 99.03% recall and 99.03% F1-score. When evaluated independently, spectral features alone resulted in 98.93% accuracy, while spatial features achieved 78.81%, highlighting the benefit of the fusion strategy. Overall, this study demonstrates that a single-illumination HSI system, combined with spectral–spatial fusion and machine learning, offers a practical and potentially scalable approach for non-destructive soybean quality evaluation, with applicability in automated industrial processing environments. Full article

External lighting is essential for autonomous inspections of concrete structures in low-light environments. However, previous studies have primarily relied on uniformly diffused lighting to illuminate images and faced challenges in detecting complex crack patterns. This paper proposes two novel algorithms that use directional lighting to classify concrete defects. The first method, named fused neural network, uses the maximum intensity pixel-level image fusion technique and selects the maximum intensity pixel values from all directional images for each pixel to generate a fused image. The second proposed method, named multi-channel neural network, generates a five-channel image, with each channel representing the grayscale version of images captured in the Right (R), Down (D), Left (L), Up (U), and Diffused (A) directions, respectively. The proposed multi-channel neural network model achieved the best performance, with accuracy, precision, recall, and F1 score of 96.6%, 96.3%, 97%, and 96.6%, respectively. It also outperformed the FusedNet and other models found in the literature, with no significant change in evaluation time. The results from this work have the potential to improve concrete crack classification in environments where external illumination is required. Future research focuses on extending the concepts of multi-channel and image fusion to white-box techniques. Full article

Background/Objectives: The application of additive manufacturing in medicine, and specifically in personalised medicine, has achieved notable development. This article aims to present the results and benefits of applying a comprehensive methodology to simulate, plan, and manufacture customised three-dimensional medical prosthetic devices for use in surgery to restore bone structures with congenital and acquired malformations. Methods: To digitally reconstruct a bone structure in three dimensions from a medical image, a segmentation process is developed to correlate the anatomical model. Then, this model is filtered using a post-processing step to generate stereolithography (STL) files, which are rendered using specialised software. The segmentation of tomographic images is achieved by the specific intensity selection, facilitating the analysis of compact and soft tissues within the anatomical region of interest. With the help of a thresholding algorithm, a three-dimensional digital model of the anatomical structure is obtained, ready for printing the required structure. Results: The described cases demonstrate that the use of anatomical test models, cutting guides, and customised prostheses reduces surgical time and hospital stay, and achieves better aesthetic and functional results. Using materials such as polylactic acid (PLA) for presurgical models, appropriate resins for cutting guides, and biocompatible materials such as polyether ether ketone (PEEK) or polymethylmethacrylate (PMMA) for prostheses, the described improvements are achieved. Conclusions: The achievements attained demonstrate the feasibility of applying these techniques, their advantages and their accessibility in Ecuador. They also reinforce the ideas of personalised medicine in the search for medical treatments and procedures tailored to the needs of each patient. Full article

Human perception of urban streetscapes plays a crucial role in shaping human-centered urban planning and policymaking. Traditional studies on safety perception often rely on labor-intensive field surveys with limited spatial coverage, hindering large-scale assessments. To address this gap, this study constructs a street safety perception dataset for Wuhan, classifying street scenes into three perception levels. A convolutional neural network model based on transfer learning is developed, achieving a classification accuracy of 78.3%. By integrating image-based prediction with spatial clustering and correlation analysis, this study demonstrates that safety perception displays a distinctly clustered and uneven spatial distribution, primarily concentrated along major arterial roads and rail transit corridors by high safety levels. Correlation analysis indicates that higher safety perception is moderately associated with greater road grade, increased road width, and lower functional level while showing a weak negative correlation with housing prices. By presenting a framework that integrates transfer learning and geospatial analysis to connect urban street imagery with human perception, this study advances the assessment of spatialized safety perception and offers practical insights for urban planners and policymakers striving to create safer, more inclusive, and sustainable urban environments. Full article

Due to the shortage of construction aggregates, carbonate rock aggregates—including mainly limestone aggregates—have long been used in structural concrete in many countries worldwide. On the other hand, earlier tests on the shear fracture toughness of concretes with limestone aggregates were very limited and were even abandoned for many years. For the above reasons, in this paper, completely new fracture toughness tests were performed according to the mode II fracture for limestone concretes with different grain size distributions. Two types of aggregate grain were used, i.e., two with maximum grain sizes of 8 mm (M1 series concrete) and 16 mm (M2 series concrete). During the experiments, the critical stress-intensity factor (K_IIc) and critical unit work of failure (J_IIc) were determined. Based on the conducted studies, it was found that higher values of fracture mechanics parameters were noted as the grain sizes of the aggregate used increased. The increases in the analyzed fracture mechanics parameters were noticeably greater in the M2 series concrete compared to the results for the M1 series concrete, specifically by 27% for K_IIc and 35% for J_IIc. In addition to macroscopic tests, detailed microstructural analyses of the ITZ area between the coarse aggregate grains and the cement matrix were conducted. Based on the captured images, it was determined that, in the M1 series concrete, the contacts between the aggregate grains and the cement paste exhibit a loose structure with visible microcracks. In contrast, the M2 series concrete showed no visible damages within the ITZ area itself nor at their displacement at a distance of approximately a few μm away from this area. This microstructure of both materials resulted in the M1 series concrete being more prone to rapid and sudden fracture propagation, leading to its brittle behavior during the fracture process. In contrast, the large, well-developed limestone aggregate grains in the M2 series concrete facilitated improved stress transfer beyond the ITZ area into the cement matrix, preserving the continuity of the material structure and consequently leading to quasi-plastic behavior of the concrete during the fracture process. The novelty and utilitarianism of the research undertaken result from the fact that exploring the properties of concretes with limestone aggregates using mode II fracture is an important aspect of evaluating the durability and safety of concrete structures subjected mainly to shear forces. Full article

Durian is a major tropical crop in Southeast Asia, but its yield and quality are severely impacted by a range of pests and diseases. Manual inspection remains the dominant detection method but suffers from high labor intensity, low accuracy, and difficulty in scaling. To address these challenges, this paper proposes EN-YOLO, a novel enhanced YOLO-based deep learning model that integrates the EfficientNet backbone and multimodal attention mechanisms for precise detection of durian pests and diseases. The model removes redundant feature layers and introduces a large-span residual edge to preserve key spatial information. Furthermore, a multimodal input strategy—incorporating RGB, near-infrared and thermal imaging—is used to enhance robustness under variable lighting and occlusion. Experimental results on real orchard datasets demonstrate that EN-YOLO outperforms YOLOv8 (You Only Look Once version 8), YOLOv5-EB (You Only Look Once version 5—Efficient Backbone), and Fieldsentinel-YOLO in detection accuracy, generalization, and small-object recognition. It achieves a 95.3% counting accuracy and shows superior performance in ablation and cross-scene tests. The proposed system also supports real-time drone deployment and integrates an expert knowledge base for intelligent decision support. This work provides an efficient, interpretable, and scalable solution for automated pest and disease management in smart agriculture. Full article

Medical image segmentation is crucial for disease diagnosis, as precise results aid clinicians in locating lesion regions. However, lesions often have blurred boundaries and complex shapes, challenging traditional methods in capturing clear edges and impacting accurate localization and complete excision. Small lesions are also critical but prone to detail loss during downsampling, reducing segmentation accuracy. To address these issues, we propose a novel adaptive scale thresholding network (AdSTNet) that acts as a post-processing lightweight network for enhancing sensitivity to lesion edges and cores through a dual-threshold adaptive mechanism. The dual-threshold adaptive mechanism is a key architectural component that includes a main threshold map for core localization and an edge threshold map for more precise boundary detection. AdSTNet is compatible with any segmentation network and introduces only a small computational and parameter cost. Additionally, Spatial Attention and Channel Attention (SACA), the Laplacian operator, and the Fusion Enhancement module are introduced to improve feature processing. SACA enhances spatial and channel attention for core localization; the Laplacian operator retains edge details without added complexity; and the Fusion Enhancement module adapts concatenation operation and Convolutional Gated Linear Unit (ConvGLU) to improve feature intensities to improve edge and small lesion segmentation. Experiments show that AdSTNet achieves notable performance gains on ISIC 2018, BUSI, and Kvasir-SEG datasets. Compared with the original U-Net, our method attains mIoU/mDice of 83.40%/90.24% on ISIC, 71.66%/80.32% on BUSI, and 73.08%/81.91% on Kvasir-SEG. Moreover, similar improvements are observed in the rest of the networks. Full article

Aqueous singlet oxygen (¹O₂) sensitization is of high interest due to its wide application in bio-imaging and photodynamic therapy. For organic photosensitizers like porphyrin derivatives, surfactant-assisted micelles have been intensively explored for dispersing hydrophobic sensitizers in aqueous phase; however, they can suffer from poor long-term stability. In this work, palladium octaethylporphyrin (PdOEP)-embedded silica particles were prepared with assistance from Tween micelles, and their corresponding application in aqueous ¹O₂ sensitization was explored. With assistance from Tween 80 at a >3 mg/mL concentration, superior (>95%) solubilization of PdOEP was observed in aqueous solution, leading to a high ¹O₂ quantum yield (Φ_Δ ≈ 93%). By optimizing the synthesis conditions, >95% of micellar PdOEP was embedded into silica particles, exhibiting comparable Φ_Δ (up to 70%) to micellar systems by effectively suppressing PdOEP aggregation in particles. The PdOEP-embedded silica particles exhibited dramatically enhanced long-term stability (more than one year) compared to corresponding micelles with a half-life of ~38 days. In addition, aqueous ¹O₂ sensitization by PdOEP-embedded silica particles was demonstrated upon two-photon excitation in a near-infrared regime (λ_ex = 1030 nm), highlighting the great potential of this method for future biological applications. Full article

Antioxidants have drawn much interest owing to their capacity to shield the human body from reactive oxygen species (ROS). Therefore, it is essential to develop a quick and easy assay for the evaluation of antioxidants and for imaging their distribution in food. Herein, we describe a fluorescence measurement platform for assessing and visualizing antioxidant capacity. Our method is based on using the composite of graphene quantum dots (GQDs) with Fe³⁺ (Fe³⁺-GQDs) as a reagent for evaluating and imaging the antioxidant capacity in foods using a fluorescence turn-off–on strategy. The fluorescence of GQDs was found to be selectively quenched with Fe³⁺ at pH 3.5. Upon addition of an antioxidant, Fe³⁺ is reduced to Fe²⁺, and the fluorescence of GQDs is regained. Next, we investigated the fluorescence intensity after the reaction of Fe³⁺-GQDs with seven typical antioxidants, and it showed excellent sensitivity down to 0.60 µM of antioxidant. Next, using Fe³⁺-GQDs as a reagent, we developed a paper-based fluorescence imaging method for antioxidants in foods. Furthermore, we analyzed the distribution of antioxidant capacity on cucumber and carrot slices (tips, central parts, and shoulders). Next, the antioxidant capacity of cucumber and carrot slice extracts was measured, and the results were consistent with the fluorescence imaging results of the intact slices. Full article

Amid growing demands for heritage conservation and precision urban governance, this study proposes a multimodal framework to analyze tourist perception and behavior in Macau’s Historic Centre. We integrate geotagged social media images and text, ultra-wideband (UWB) pedestrian trajectories, and a LiDAR-derived 3D digital twin to examine the interplay among spatial configuration, movement, and affect. Visual content in tourist photos is classified with You Only Look Once (YOLOv8), and sentiment polarity in Weibo posts is estimated with a fine-tuned Bidirectional Encoder Representations from Transformers (BERT) model. UWB data provide fine-grained trajectories, and all modalities are georeferenced within the digital twin. Results indicate that iconic landmarks concentrate visual attention, pedestrian density, and positive sentiment, whereas peripheral sites show lower footfall yet strong emotional resonance. We further identify three coupling typologies that differentiate tourist experiences across spatial contexts. The study advances multimodal research on historic urban centers by delivering a reproducible framework that aligns image, text, and trajectory data to extract microscale patterns. Theoretically, it elucidates how spatial configuration, movement intensity, and affective expression co-produce experiential quality. Using Macau’s Historic Centre as an empirical testbed, the findings inform heritage revitalization, wayfinding, and crowd-management strategies. Full article

Background/Objectives: Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive fibrosing interstitial disease that incurs significant healthcare costs due to diagnostic and treatment needs. This study aimed to estimate healthcare expenses related to IPF diagnosis, treatment, and follow-up, including factors affecting overall expenditure. Methods: This retrospective cohort study included 276 IPF patients from a tertiary hospital (2013–2022). Diagnostic and treatment costs were analyzed, including antifibrotic medications (pirfenidone and nintedanib), diagnostic tests (pulmonary function tests and performance evaluation tests), and interventions (fiberoptic bronchoscopy, imaging modalities). Costs in Turkish Lira were converted to United States dollars. Statistical analysis was performed using non-parametric tests to evaluate expenditure correlations with demographic, clinical, and treatment parameters, which included the Mann–Whitney and Spearman Rank Correlation tests when appropriate. Results: The median healthcare expenditure was USD 429.1 (9.13–21,024.57). Inpatient costs (USD 582.67; USD 250.22 to USD 1751, 25th and 75th percentile, respectively) were higher than outpatient costs (USD 192.36; USD 85.75 to USD 407.47, 25th and 75th percentile, respectively). Antifibrotic regimens did not differ significantly in cost or duration (Z = 0.657; p = 0.511) (mean pirfenidone duration: 1.1 ± 1.0 years; mean nintedanib duration: 0.6 ± 0.9 years). Diagnostic tests, particularly pulmonary function tests (PFT) (p: 0.001, Rho: 0.337), diffusing capacity of the lungs for carbon monoxide (DLCO) (p: 0.001, Rho: 0.516), and high-resolution computed tomography (HRCT) (p: 0.001, Rho: 0.327), were the primary drivers of costs. Longer treatment duration was positively correlated with expenditure (Rho: 0.264, p: 0.001 and Rho: 0.247, p: 0.006 for pirfenidone and nintedanib, respectively) while age showed a weak negative correlation (Rho = −0.184, p = 0.002). Gender and type of antifibrotic regimen did not show any significant effect on costs. Discussion: Diagnostic and follow-up testing were the main contributors to costs, driven by reimbursement requirements and the progressive nature of IPF. Antifibrotic medications, although expensive, provided clinical stability, potentially reducing hospitalization needs but increasing long-term care expenses. Variations in healthcare systems affect expenditures, with Turkey’s universal coverage lowering costs compared to Western countries. The study’s main limitations include being a single-center, retrospective study and its inability to include comorbidities and disease severity in the statistical analysis. Conclusions: IPF management is resource-intensive, with diagnostic tests and follow-up driving costs independent of demographics and treatment modality. Anticipating higher expenditures with prolonged survival and evolving treatment options is crucial for healthcare budget planning. Preparation of healthcare policies accordingly to these observations, which must include an overall increase in cost due to treatment duration and survival, remains a crucial aspect of budget control. Full article

Background and Objectives: Total body irradiation (TBI) remains a cornerstone of conditioning for allogeneic haematopoietic stem-cell transplantation (HSCT). Whereas early research debated the need for irradiation, contemporary investigations focus on optimising dose, fractionation and delivery techniques. Material and Methods: We synthesised six decades of evidence, spanning from single-fraction cobalt treatments to modern helical tomotherapy and intensity-modulated total-marrow/lymphoid irradiation (TMI/TMLI). To complement the literature, we reported our institutional experience on 77 paediatric and adult recipients treated with conventional extended-source-to-skin-distance TBI at the University Hospital Policlinico “G. Rodolico–San Marco” between 2015 and 2025. Results: According to literature data, fractionated myeloablative schedules, typically 12 Gy in 6 fractions, provide superior overall survival and lower rates of severe graft-versus-host disease (GVHD) compared with historical single-dose regimens. Conversely, reduced-intensity protocols of 2–4 Gy broaden HSCT eligibility for older or comorbid patients with acceptable toxicity. Conformal planning reliably decreases mean lung dose without compromising engraftment, and early-phase trials are testing selective escalation to 16–20 Gy or omission of TBI in molecularly favourable cases. With regard to our institutional retrospective series, 92% of patients completed a 12-Gy regimen with only transient grade 1–2 nausea, fatigue or hypotension; all transplanted patients engrafted, and no grade ≥ 3 radiation pneumonitis occurred. Conclusions: Collectively, the published evidence and our experience support TBI as an irreplaceable component of HSCT conditioning and suggest that coupling it with advanced imaging, organ-sparing dosimetry and molecular response monitoring can deliver safer, more personalised therapy in the coming decade. Full article

The upper Mapocho River basin, located in central Chile, has been affected by numerous landslides in the past, which may become more frequent due to a projected increase in intense precipitation events in the context of climate change. Against this background, this study aimed to analyze the ground deformation associated with an active landslide area in the Yerba Loca basin using the SBAS–DInSAR technique with PAZ and Sentinel-1 images acquired during two time periods, 2019–2021 and 2018–2022, respectively. Using PAZ imagery, the estimated vertical displacement velocity (subsidence) was as high as 9.6 mm/year between 2019 and 2021 in the area affected by the Yerba Loca multirotational slide in August 2018. Analysis of Sentinel-1 images indicated a vertical displacement velocity reaching −94 mm/year between 2018 and 2022 in the Yerba Loca landslide, suggesting continued activity in this area. It, therefore, may collapse again soon, affecting tourism services and the local ecosystem. By focusing on a mountainous region, this study demonstrates the usefulness of radar imagery for investigating landslides in remote or hard-to-reach areas, such as the mountain sector of central Chile. Full article

This study addresses the need for efficient and non-destructive monitoring of the nutrient status of hardy kiwi (Actinidia arguta), a plantation crop native to East Asia. Traditional nutrient monitoring methods are labor-intensive and often destructive, limiting their practicality in precision agriculture. To overcome these challenges, we deployed a rotary-wing unmanned aerial vehicle (UAV) equipped with a multispectral camera to capture monthly images of 10 hardy kiwi orchards in South Korea from June to October 2019. We extracted spectral bands (i.e., red, red-edge, green, and near-infrared) to generate normalized difference vegetation index and canopy chlorophyll content index maps, which were correlated with in situ chlorophyll measurements using a chlorophyll meter. Strong positive correlations were observed between vegetation indexes and actual chlorophyll content, with canopy chlorophyll content index achieving the highest predictive accuracy (average correlation coefficient > 0.84). Regression models based on multispectral data enabled reliable estimation of leaf chlorophyll across months and regions, with an average RMSE of 3.1. Our results confirmed that UAV-based multispectral imaging is an effective, scalable approach for real-time monitoring of nutrient status, supporting timely, site-specific fertilizer management. This method has the potential to enhance fertilizer efficiency, reduce environmental impact, and improve the quality of hardy kiwi cultivations. Full article

In response to the instability fluctuations and erosion characteristic changes in pantograph-catenary system (PCS) arcs induced by humidity variations in an open environment, a single-variable controlled experimental approach based on multi-source data fusion is proposed. This study innovatively establishes a humidity-controlled reciprocating current-carrying arc initiation test platform, integrating digital image processing with the dynamic analysis of multi-physics sensor signals (current, voltage, temperature). The study quantitatively evaluates the arc motion characteristics and the erosion effects on the frictional contact pair under different relative humidity levels (30%, 50%, 70%, and 90%) with a DC power supply (120 V/25 A). The experimental data and analysis reveal that increasing humidity results in higher contact resistance and accumulated arc energy, with arc stability first improving and then decreasing. At low humidity, arc behavior is more intense, and the erosion rate is faster. As humidity increases, the electrode wear transitions from adhesive wear to electrochemical wear, accompanied by copper transfer. The results suggest that the arc stability is optimal at moderate humidity (50% RH), with a peak current-carrying efficiency of 66% and a minimum loss rate of 14.5%. This threshold offers a vital theoretical framework for the optimization and risk assessments of PCS design. Full article