Search Results (984)

Object detection in degraded environments such as low-light and nighttime conditions remains a challenging task, as conventional computer vision techniques often fail to achieve high precision and robust performance. With the increasing adoption of deep learning, this paper aims to enhance object detection under such adverse conditions by proposing an improved version of YOLOv11, named DRF-YOLO (Degradation-Robust and Feature-enhanced YOLO). The proposed framework incorporates three innovative components: (1) a lightweight Cross Stage Partial Multi-Scale Edge Enhancement (CSP-MSEE) module that combines multi-scale feature extraction with edge enhancement to strengthen feature representation; (2) a Focal Modulation attention mechanism that improves the network’s responsiveness to target regions and contextual information; and (3) a self-developed Dynamic Interaction Head (DIH) that enhances detection accuracy and spatial adaptability for small objects. In addition, a lightweight unsupervised image enhancement algorithm, Zero-DCE (Zero-Reference Deep Curve Estimation), is introduced prior to training to improve image contrast and detail, and Generalized Intersection over Union (GIoU) is employed as the bounding box regression loss. To evaluate the effectiveness of DRF-YOLO, experiments are conducted on two representative low-light datasets: ExDark and the nighttime subset of BDD100K, which include images of vehicles, pedestrians, and other road objects. Results show that DRF-YOLO achieves improvements of 3.4% and 2.3% in mAP@0.5 compared with the original YOLOv11, demonstrating enhanced robustness and accuracy in degraded environments while maintaining lightweight efficiency. Full article

Background/Objectives: The Sox transcription factor family is critical for gonadal development and sex differentiation in animals, yet its roles in chelonians, particularly in the Chinese soft-shelled turtle (Pelodiscus sinensis), have rarely been investigated. Methods: This study cloned and analyzed the cDNA sequences of Sox3 and Sox30 genes from P. sinensis, examining their amino acid sequences and structural properties. Real-time quantitative PCR (RT-qPCR) was used to assess the expression of these two genes in different adult tissues and at various stages of embryonic gonadal development. Additionally, the effects of exogenous hormones (17β-estradiol, E₂ and 17α-Methyltestosterone, MT) on the expression of Sox3 and Sox30 were also investigated. Results: The results indicated that Sox3 showed significantly elevated expression in female gonads, kidney, brain, liver, lung, spleen, and muscle relative to male counterparts, displaying a female-biased expression pattern. In contrast, Sox30 showed a male-biased pattern, with higher expression in male gonads, spleen, muscle, brain, and liver than in females, showing expression. Both genes were expressed at low levels. Exogenous hormone treatments revealed that MT significantly downregulated Sox3 expression in female embryos, whereas E₂ significantly enhanced Sox3 expression in male embryos. Furthermore, MT treatment significantly upregulated Sox30 expression in female embryos, and E₂ treatment also significantly increased Sox30 expression in male embryos. Conclusions: These findings suggest that Sox3 and Sox30 play crucial roles in the gonadal development of P. sinensis, with Sox3 potentially involved in ovarian development and Sox30 in testicular maturation. Both genes are regulated by exogenous hormones, highlighting their importance in sex differentiation and gonadal development. This study provides valuable theoretical insights for further exploration of the molecular mechanisms of sex regulation in reptiles. Full article

Objective: This study aimed to evaluate the diagnostic accuracy of two cone beam computed tomography (CBCT) devices using 18 imaging modalities in detecting root fractures—vertical, horizontal, and oblique—in teeth with intracanal post systems. Materials and methods: Ninety-six were extracted; single-rooted mandibular premolars were endodontically treated and restored with Bundle, Reforpost, or Splendor Single Adjustable posts. Controlled fractures of different types were induced using a universal testing machine. Each tooth was scanned with NewTom 7G and NewTom Go (Quantitative Radiology, Verona, Italy) under nine imaging protocols per device; varying in dose and voxel size, yielding 1728 CBCT images. Three observers (a professor of endodontics; a specialist; and a postgraduate student in endodontics) independently evaluated the images. Results: Observers demonstrated almost perfect agreement (κ ≥ 0.81) with the gold standard in fracture detection using NewTom 7G. No significant differences were found in sensitivity, specificity, or accuracy across voxel size and dose parameters for both devices in detecting fracture presence (p > 0.05). Similarly, both devices displayed comparable performance in identifying horizontal and oblique fractures (p > 0.05). However, in NewTom Go, regular and low doses with different voxel sizes showed reduced sensitivity and accuracy in detecting vertical fractures across all post systems (p ≤ 0.05). Conclusions: NewTom 7G, with its advanced detector system and smaller voxel sizes, provides superior diagnostic accuracy for root fractures. In contrast, NewTom Go displays reduced sensitivity for vertical fractures at lower settings. Clinical relevance: CBCT device selection and imaging protocols significantly affect the diagnosis of vertical root fractures. Full article

Anti-tank landmines endanger post-conflict recovery. Detecting camouflaged TM-62 landmines in low-altitude unmanned aerial vehicle (UAV) imagery is challenging because targets occupy few pixels and are low-contrast and often occluded. We introduce a single-class anti-tank dataset and a YOLOv5 pipeline augmented with a SAHI-based small-object stage and Weighted Boxes Fusion. The evaluation combines COCO metrics with an operational operating point (score = 0.25; IoU = 0.50) and stratifies by object size and occlusion. On a held-out test partition representative of UAV acquisition, the baseline YOLOv5 attains mAP@0.50:0.95 = 0.553 and AP@0.50 = 0.851. With tuned SAHI (768 px tiles, 40% overlap) plus fusion, performance rises to mAP@0.50:0.95 = 0.685 and AP@0.50 = 0.935—ΔmAP = +0.132 (+23.9% rel.) and ΔAP@0.50 = +0.084 (+9.9% rel.). At the operating point, precision = 0.94 and recall = 0.89 (F1 = 0.914), implying a 58.4% reduction in missed detections versus a non-optimized SAHI baseline and a +14.3 AP@0.50 gain on the small/occluded subset. Ablations attribute gains to tile size, overlap, and fusion, which boost recall on low-pixel, occluded landmines without inflating false positives. The pipeline sustains real-time UAV throughput and supports actionable triage for humanitarian demining, as well as motivating RGB–thermal fusion and cross-season/-domain adaptation. Full article

Background/Objective: One of the life stages that affects the consolidation of habits and health is the university stage. This transition to adulthood is associated with a decrease in physical activity, increasing the risk of cardiovascular disease. This study describes lifestyle habits related to physical activity level, diet quality, and body composition in nursing students and analyzes cardiovascular risk using the ABSI-z index. Methods: We conducted a cross-sectional study with 296 students from the Faculty of Nursing of Albacete (Spain). Physical activity was assessed via the IPAQ-SF. Body composition was measured by bioimpedance, from which BMI and ABSI-z scores were obtained as indicators of cardiovascular risk. The eating patterns of the participants were analyzed. Results/Discussion: The active students had significantly better body composition, with greater fat-free mass and muscle mass than the sedentary students, both in men (p = 0.037 and p = 0.046, respectively) and in women (p = 0.002 and p = 0.007). These findings corroborate evidence of the protective role of physical activity in maintaining metabolic health. The analysis of the ABSI-z score revealed different patterns in the distribution of body fat. High ABSI values were associated with greater abdominal girth (p < 0.001) and visceral fat (p < 0.001) in women, confirming its usefulness as an early marker of cardiovascular risk in university students. In contrast, the fulfillment of healthy dietary criteria was low, especially in the consumption of legumes (19%) and fish (25.9%). Conclusions: Regular physical activity is a determining factor in the body composition of university students, and ABSI is a good indicator of cardiovascular risk. Full article

Background and Objectives: The anesthetic nerve block test is a surgical technique that can assist in the differential diagnosis of forefoot pain. The MTP joint, enclosed by its capsule, may act as a sealed cavity with predictable contrast dispersion, whereas the IM space, lacking clear boundaries and containing bursae and the plantar digital nerve, favors diffuse spread. Due to the high rate of false positives in suspected cases of Morton’s neuroma with the anesthetic block current procedure in the intermetatarsal space, the aim of this study was to propose an alternative to the current procedure. Material and Methods: Six fresh cadaveric feet were used. Under ultrasound guidance, the 2nd–4th MTP joints received stepwise intra-articular injections of radiopaque contrast. The third common digital nerve was injected within the third intermetatarsal space. Standard radiographs were obtained to assess distribution and proximal spread. Results: A volume of 0.3 mL was sufficient to fully reach the intra-articular cavity and potentially induce effective localized anesthesia. When the third common digital plantar nerve was injected in an anatomically healthy region, the contrast medium showed a proximal diffusion pattern extending up to the mid-diaphyseal level of the third and fourth metatarsal bones. On radiographs, the intra-articular infiltration lines appear sharply demarcated, supporting the interpretation of the metatarsophalangeal joint as a sealed compartment. Conclusions: Low intra-articular anesthetic volumes may yield targeted effects, while Morton’s neuroma injections spread proximally, risking loss of diagnostic specificity; this technique may improve decision-making accuracy and reduce failures. Full article

Sustainable production also involves analyzing greenhouse gas (GHG) emissions throughout the entire cultivation and processing cycle. The emissions balance for different sugar beet varieties is a key element of environmental assessment in sustainable production systems. It is consistent with the objectives of the European Green Deal and aims to decarbonize agri-food technology. This study aims to assess and compare GHG emissions associated with the cultivation of three sugar beet variants (Viola, Jaromir, and Pulitzer) taking into account their technological and quality characteristics. The varieties were selected based on their registration in the National Register and their importance in agricultural practice in Poland, as well as their contrasting technological profiles, which allow for the assessment of the relationship between raw material quality and GHG balance. The study combines life cycle assessment (LCA) with physiological parameters such as CO₂ assimilation, sugar content, yield, fuel consumption, and fertilizer use. The aim is to identify the correlation between the technological value of a variety and its environmental impact. It has been shown that genotypic characteristics have a significant impact on both yield and emissions. The Viola and Jaromir varieties showed a favorable balance between photosynthetic efficiency and greenhouse gas emissions, while the Pulitzer variety, despite low emissions per kilogram of product, showed poorer yield performance. The importance of using integrated assessment methods combining production efficiency, environmental efficiency, and crop quality was emphasized. Such an approach is essential for the development of sustainable agricultural practices in line with the EU’s climate neutrality goals. Further research is needed to optimize agrotechnical strategies tailored to the requirements of individual varieties, contributing to climate-resilient and environmentally friendly crop production. Full article

The rising penetration of electric vehicles is driving huge demand for lithium batteries, making low-carbon manufacturing a critical objective. This goal is challenged by insufficient production scheduling flexibility and the neglect of carbon-reduction technologies. To address these challenges, this paper develops a low-carbon planning methodology for lithium battery plant energy systems by leveraging manufacturing chain flexibilities. First, a lithium battery energy–carbon material modeling approach is developed that accounts for process production delays and intermediate product storage to capture schedulable process energy consumption patterns. A nitrogen–oxygen coupling production framework is introduced to facilitate oxygen-enriched combustion technology application, while energy recovery pathways are incorporated given the high energy consumption of the formation stage. Subsequently, a process scheduling-driven planning model for lithium battery industrial integrated energy systems (IIES) is developed. Finally, the planning model is validated through four contrasting case studies and systematically evaluated using multi-criteria decision analysis (MCDA). The results demonstrate three principal conclusions: (1) incorporating process scheduling effectively enhances process energy flexibility and reduces total system costs by 19.4%, with MCDA closeness coefficient improving from 0.257 to 0.665; (2) oxygen-enriched combustion increases maximum combustion and carbon capture (CCS) rates from 90% to 95%, reducing carbon tax to 40.5% of the baseline; (3) energy recovery on the basis of process scheduling further reduces costs and carbon emissions, with battery recovery achieving an additional 30.2% cost reduction compared to 24.1% for heat recovery, and MCDA identifies this integrated approach as the optimal solution with a closeness coefficient of 0.919. Full article

Objective: Medical Visual Question Answering (Med-VQA), a key technology that integrates computer vision and natural language processing to assist in clinical diagnosis, possesses significant potential for enhancing diagnostic efficiency and accuracy. However, its development is constrained by two major bottlenecks: weak few-shot generalization capability stemming from the scarcity of high-quality annotated data and the problem of catastrophic forgetting when continually learning new knowledge. Existing research has largely addressed these two challenges in isolation, lacking a unified framework. Methods: To bridge this gap, this paper proposes a novel Evolvable Clinical-Semantic Alignment (ECSA) framework, designed to synergistically solve these two challenges within a single architecture. ECSA is built upon powerful pre-trained vision (BiomedCLIP) and language (Flan-T5) models, with two innovative modules at its core. First, we design a Clinical-Semantic Disambiguation Module (CSDM), which employs a novel debiased hard negative mining strategy for contrastive learning. This enables the precise discrimination of “hard negatives” that are visually similar but clinically distinct, thereby significantly enhancing the model’s representation ability in few-shot and long-tail scenarios. Second, we introduce a Prompt-based Knowledge Consolidation Module (PKC), which acts as a rehearsal-free non-parametric knowledge store. It consolidates historical knowledge by dynamically accumulating and retrieving task-specific “soft prompts,” thus effectively circumventing catastrophic forgetting without relying on past data. Results: Extensive experimental results on four public benchmark datasets, VQA-RAD, SLAKE, PathVQA, and VQA-Med-2019, demonstrate ECSA’s state-of-the-art or highly competitive performance. Specifically, ECSA achieves excellent overall accuracies of 80.15% on VQA-RAD and 85.10% on SLAKE, while also showing strong generalization with 64.57% on PathVQA and 82.23% on VQA-Med-2019. More critically, in continual learning scenarios, the framework achieves a low forgetting rate of just 13.50%, showcasing its significant advantages in knowledge retention. Conclusions: These findings validate the framework’s substantial potential for building robust and evolvable clinical decision support systems. Full article

Adequate intake of fruits and vegetables (F + V) supports healthy growth and development in children, yet many New Zealand children do not meet national dietary recommendations, and methods to evaluate intake require good reliability. Objectives: To establish the validity and reliability of a modified 24 h multiple pass recall (MPR) for evaluating F + V and carotenoid intakes in children aged 9–13 years. The reliability of the Veggie Meter^® (VM^®), a non-invasive reflection spectrometer to estimate skin carotenoid scores and derive blood carotenoid concentrations, was also examined. Methods: Thirty-two children (20 boys, 12 girls) completed three 24 h MPRs and parent-assisted weighed food diaries (WFDs) on randomised weekdays and weekends. Skin carotenoid scores were assessed using the VM^®. The validity of the MPR was evaluated against WFDs using log-transformed Pearson correlations and mean x-axis bias. The reliability was assessed by the coefficient of variation (CV) and Pearson correlations. Results: Participants did not meet recommended F + V intakes (5–5.5 servings/day): MPR (mean fruit 1.3 servings/day; vegetables 2.0), WFD (fruit 1.3; vegetables 1.9). The MPR was a valid tool to estimate fruit and vegetable daily servings (combined-day Pearson coefficients > 0.71) with only trivial–small standardized mean bias-offset vs. WFD; however, the reliability was poor for the MPR-estimated carotenoid intake (CV 126%) and F + V intake. In contrast, the VM^® was reliable (Pearson correlation 0.97–0.99) with low measurement error (CV 4.0–5.2%). Conclusions: The modified 24 h MPR was valid but unreliable for estimating F + V and carotenoid intake. The VM^® demonstrated high reliability as a biomarker of skin carotenoid status in children. Full article

Background/Objectives: We provide a framework for determining how far into the future the spatiotemporal dynamics of tumor growth can be accurately predicted using routinely available magnetic resonance imaging (MRI) data. Our analysis is applied to a coupled set of reaction-diffusion equations describing the spatiotemporal development of tumor cellularity and vascularity, initialized and constrained with diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI data, respectively. Methods: Motivated by experimentally acquired murine glioma data, the rat brain serves as the computational domain within which we seed an in silico tumor. We generate a set of 13 virtual tumors defined by different combinations of model parameters. The first parameter combination was selected as it generated a tumor with a necrotic core during our simulated ten-day experiment. We then tested 12 additional parameter combinations to study a range of high and low tumor cell proliferation and diffusion values. Each tumor is grown for ten days via our model system to establish “ground truth” spatiotemporal tumor dynamics with an infinite signal-to-noise ratio (SNR). We then systematically reduce the quality of the imaging data by decreasing the SNR, downsampling the spatial resolution (SR), and decreasing the sampling frequency, our proxy for reduced temporal resolution (TR). With each decrement in image quality, we assess the accuracy of the calibration and subsequent prediction by comparing it to the corresponding ground truth data using the concordance correlation coefficient (CCC) for both tumor and vasculature volume fractions, as well as the Dice similarity coefficient for tumor volume fraction. Results: All tumor CCC and Dice scores for each of the 13 virtual tumors are >0.9 regardless of the SNR/SR/TR combination. Vasculature CCC scores with any SR/TR combination are >0.9 provided the SNR ≥ 80 for all virtual tumors; for the special case of high-proliferating tumors (i.e., proliferation > 0.0263 day⁻¹), any SR/TR combination yields CCC and Dice scores > 0.9 provided the SNR ≥ 40. Conclusions: Our systematic evaluation demonstrates that reaction-diffusion models can maintain acceptable longitudinal prediction accuracy—especially for tumor predictions—despite limitations in the quality and quantity of experimental data. Full article

Smart polyester materials with embedded near-infrared (NIR) functionalities offer a promising pathway for low-cost, covert tagging, and object identification. In this study we present the development and characterization of polyester packaging surfaces printed with spectrally matched twin dyes that are invisible under visible light but selectively absorbed in the NIR region. The dye patterns were applied using a Direct-to-Film transfer (DTF) method onto polyester substrates. To validate their optical behavior, we applied a dual measurement approach. Laboratory grade NIR absorbance spectroscopy was used to characterize the spectral profiles of the twin dyes in the 400–900 nm range. A custom photodiode-based detection system was constructed to evaluate the feasibility of low-cost, embedded NIR absorbance sensing. Results from both methods show correlation in absorbance contrast between the dye pairs, confirming their suitability for spectral tagging. The developed materials were evaluated in a real-world detection scenario using commercially available NIR cameras. Under dark field conditions with edge illuminated planar lighting, the twin dye patterns were successfully recognized through custom software, enabling non-contact identification and spatial localization of the NIR codes. This work presents a low-cost, scalable approach for smart packaging applications based on optical detection of actively illuminated twin dyes using accessible NIR imaging systems. Full article

With the development of infrared remote sensing technology and the deployment of satellite constellations, infrared video from orbital platforms is playing an increasingly important role in airborne target surveillance. However, due to the limitations of remote sensing imaging, the aerial targets in such videos are often small in scale, low in contrast, and slow in movement, making them difficult to detect in complex backgrounds. In this paper, we propose a novel detection network that integrates inter-frame residual guidance with spatio-temporal feature enhancement to address the challenge of small object detection in infrared satellite video. This method first extracts residual features to highlight motion-sensitive regions, then uses a dual-branch structure to encode spatial semantics and temporal evolution, and then fuses them deeply through a multi-scale feature enhancement module. Extensive experiments show that this method outperforms mainstream methods in terms on various infrared small target video datasets, and has good robustness under low-signal-to-noise-ratio conditions. Full article

Background/Objectives: Despite their low incidence, popliteal artery aneurysms (PAAs) are the most common aneurysms of the peripheral arteries and carry a high risk of limb loss. The optimal treatment, either with open (OR) or endovascular repair (ER), remains debated due to the lack of high-level evidence. Methods: In accordance with STROBE guidelines, we conducted a retrospective observational study with a prospective follow-up. All patients presenting with a PAA who underwent elective OR in the Vascular and Endovascular Surgery Unit of Agostino Gemelli Hospital (Rome, Italy) over the last four years were enrollved. Urgent and endovascular cases were excluded. Clinical examination, Doppler ultrasound (DUS), and contrast-enhanced computed tomography angiography (CTA) were performed preoperatively. Clinical and DUS follow-up was performed at 1, 3, 6, and 12 months postoperatively and annually thereafter. Endpoints were the primary, primary assisted, and secondary patency calculated using a Kaplan–Maier estimate based on the “first event” (arterial stenosis, occlusion, or reintervention) after the procedure. Amputation rate and overall mortality were also assessed. The results were compared with the success and complication rates reported in contemporary endovascular series. Results: Overall, 62 open interventions for popliteal artery aneurysms were performed during the study period; 49 patients (100% male, 70.3 SD ± 8.8 years) were included for a total of 52 PAAs treated electively (median diameter 30.5 mm, range 20–75; 92.3% fusiform). Aneurysm involved P1 segment in 38.5% of cases (20), P2 in 48.1% of cases (25), and P3 in 13.5% of cases (7). Two runoff vessels were present in most patients (37, 71.2%). Surgery consisted of the aneurysm’s exclusion through ligation and autologous vein or prosthetic bypass (25, 48.1%) or aneurysmectomy and interposition graft or end-to-end anastomosis (27, 51.9%). At a mean follow-up of 18 months (SD ± 17.7), the primary, the primary assisted, and the secondary patency were 94.3%, 100%, and 100% respectively. No minor nor major amputations and no deaths were reported. Conclusions: In the endovascular era, our results highlight that regardless the specific characteristics—including age, comorbidities, and aneurysm anatomy—OR provides excellent early and mid-term outcomes with high patency and low complication rate compared with contemporary endovascular series reported in the literature. Full article

Chemical fertilizers are commonly used to supply phosphorus and other nutrients to crops, but due to high affinity of soils for P fixation, over-application of P fertilizer is common, which may result in groundwater and surface water pollution. To increase P use efficiency, different strategies, including different fertilizer formulations and types, have been developed. Two struvite-based fertilizers, Crystal Green^® (CG) and Crystal Green Pearl^® (CGP), are touted as environmentally safe, because they are insoluble in water but soluble in organic acids exuded from crop roots. The objective of this study was to assess fate and transport of P from diammonium phosphate (DAP), CG, and CGP through two loam soils with a significant difference in their initial P content. Two loamy soils, one collected from an experimental field receiving fertilizer continuously since 1985 and one from an adjacent area receiving no fertilizer, and a pure sand control were packed in 5 cm diameter and 5 cm long columns. Several grains equivalent to approximately 80 mg P from each fertilizer were imbedded at the bottom of the column. Distilled water was passed through the soil columns from the bottom at a relatively constant rate, and the outflow was collected every two hours using a fraction collector. Outflow samples from each treatment combination were analyzed for P by the colorimetric method, and the amount of P retained by the soils along the column at the end of the water application was determined by the nitric acid digestion method. Approximately 91% of P in DAP, 34% in CG, and only 3.8% in CGP was transported through the sand column. In contrast, the amounts of P transported were approximately 42.2% for DAP, 6.4% for CG, and 0.4% for CGP through the high-P soil and 22.4% for DAP, 0.6% for CG, and almost zero for CGP through the low-P soil. Overall, the results show a high solubility and transport for DAP, very low transport for CGP, and somewhat low to medium transport for CG fertilizers. In addition, the results show that even the high-P soil that has received fertilizer for about 40 years has the capacity to fix significant amounts of P. Full article