Search Results (19,262)

To address the inefficiency of traditional concrete crack detection methods and the heavy reliance of supervised learning on extensive labeled data, in this study, an intelligent assessment method of concrete damage based on pseudo-label semi-supervised learning and fractal geometry theory is proposed to solve two core tasks: one is binary classification of pixel-level cracks, and the other is multi-category assessment of damage state based on crack morphology. Using three-channel RGB images as input, a dual-path collaborative training framework based on U-Net encoder–decoder architecture is constructed, and a binary segmentation mask of the same size is output to achieve the accurate segmentation of cracks at the pixel level. By constructing a dual-path collaborative training framework and employing a dynamic pseudo-label refinement mechanism, the model achieves an F1-score of 0.883 using only 50% labeled data—a mere 1.3% decrease compared to the fully supervised benchmark DeepCrack (F1 = 0.896)—while reducing manual annotation costs by over 60%. Furthermore, a quantitative correlation model between crack fractal characteristics and structural damage severity is established by combining a U-Net segmentation network with the differential box-counting algorithm. The experimental results demonstrate that under a cyclic loading of 147.6–221.4 kN, the fractal dimension monotonically increases from 1.073 (moderate damage) to 1.189 (failure), with 100% accuracy in damage state identification, closely aligning with the degradation trend of macroscopic mechanical properties. In complex crack scenarios, the model attains a recall rate (Re = 0.882), surpassing U-Net by 13.9%, with significantly enhanced edge reconstruction precision. Compared with the mainstream models, this method effectively alleviates the problem of data annotation dependence through a semi-supervised strategy while maintaining high accuracy. It provides an efficient structural health monitoring solution for engineering practice, which is of great value to promote the application of intelligent detection technology in infrastructure operation and maintenance. Full article

Soil salinization and selenium (Se) deficiency threaten global food security. This study developed a composite bioinoculant combining ACC deaminase-producing Serratia liquefaciens and biogenically synthesized nano-selenium (SeNPs) to alleviate saline–alkali stress and enhance Se nutrition in rice (Oryza sativa L.). A strain of S. liquefaciens with high ACC deaminase activity was isolated and used to biosynthesize SeNPs with stable physicochemical properties. Pot experiments showed that application of the composite inoculant (S3: S. liquefaciens + 40 mmol/L SeNPs) significantly improved seedling biomass (fresh weight +53.8%, dry weight +60.6%), plant height (+31.6%), and root activity under saline–alkali conditions. S3 treatment also enhanced panicle weight, seed-setting rate, and grain Se content (234.13 μg/kg), meeting national Se-enriched rice standards. Moreover, it increased rhizosphere soil N, P, and K availability and improved microbial α-diversity. This is the first comprehensive demonstration that a synergistic bioformulation of ACC deaminase PGPR and biogenic SeNPs effectively mitigates saline–alkali stress, enhances soil fertility, and enables safe Se biofortification in rice. Full article

This paper presents a novel harmonic-selective clocking scheme that facilitates concurrent downconversion of spectrally distant radio frequency (RF) signals using a single low-frequency local oscillator (LO) in an N-path receiver architecture. The proposed scheme selectively generates LO harmonics aligned with multiple RF bands, enabling simultaneous downconversion without modification of the passive mixer topology. The receiver employs a 4-path passive mixer configuration to enhance harmonic selectivity and provide flexible frequency planning.The architecture is implemented on a printed circuit board (PCB) and validated through comprehensive simulation and experimental measurements under continuous wave and modulated signal conditions. Measured results demonstrate a sensitivity of $-55\mathrm{dBm}$ and a conversion gain varying from $-2.5\mathrm{dB}$ to $-9\mathrm{dB}$ depending on the selected harmonic pair. The receiver’s performance is further corroborated by concurrent (dual band) reception of real-world signals, including a GPS signal centered at 1575 MHz and an LTE signal at 1179 MHz, both downconverted using a single 393 MHz LO. Signal fidelity is assessed via Normalized Mean Square Error (NMSE) and Error Vector Magnitude (EVM), confirming the proposed architecture’s effectiveness in maintaining high-quality signal reception under concurrent multiband operation. The results highlight the potential of harmonic-selective clocking to simplify multiband receiver design for wireless communication and global navigation satellite system (GNSS) applications. Full article

Background/Objectives: Rib fracture detection holds critical importance in the field of medical image processing. Methods: In this study, two different data augmentation methods, traditional data augmentation (Albumentations) and focused data augmentation (focused augmentation), were compared using computed tomography (CT) images for the detection of rib fractures on YOLOv8n, YOLOv8s, and YOLOv8m models. While the traditional data augmentation method applies general transformations to the entire image, the focused data augmentation method performs specific transformations by targeting only the fracture regions. Results: The model performance was evaluated using the Precision, Recall, mAP@50, and mAP@50–95 metrics. The findings revealed that the focused data augmentation method achieved superior performance in certain metrics. Specifically, analysis on the YOLOv8s model showed that the focused data augmentation method increased the mAP@50 value by 2.18%, reaching 0.9412, and improved the recall value for fracture detection by 5.70%, reaching 0.8766. On the other hand, the traditional data augmentation method achieved better results in overall precision metrics with the YOLOv8m model and provided a slight advantage in the mAP@50 value. Conclusions: The study indicates that focused data augmentation can contribute to achieving more reliable and accurate results in medical imaging applications. Full article

The objective of this study was to evaluate the feasibility and efficacy of the ultrasound-guided thoracolumbar erector spinae plane (TL-ESP) block in standing horses. A total of 24 injections (n = 12) were performed at the L1 level using either 0.1 mL/kg of saline solution (SS group) or 2% lidocaine (LID group). The block feasibility was assessed based on needle visualization and injection time, while efficacy was evaluated through craniocaudal and dorsoventral (DV) spread using the pinprick technique over 270 min. Desensitization was observed at least once in 100% of horses in the LID group and in 75% in the SS group (p = 0.001). However, in the SS group, desensitization was primarily limited to the Th18 metamer at the 2 cm DV position, with a shorter duration compared to the LID group. The block onset occurred at 22.5 (11.25–60) min in the LID group and at 5 (5–30) min in the SS group (p = 0.069). The number of affected metamers was significantly higher in the LID group (2 [¹,²,³]) compared to the SS group (1 [1–2.25], p = 0.014). At the 2 cm DV point, the end of the block effect occurred at 135 (120–210) min in the LID group and at 60 (3.75–60) min in the SS group (p = 0.001). Needle visualization was excellent in 95.8% of cases, and the mean injection time was 2.5 (2–3) min. These findings confirm that the TL-ESP block is a feasible technique in standing horses. However, its effect is predominantly localized to dorsal dermatomes with a limited ventral spread. Future studies evaluating larger volumes and multiple injection sites are warranted to enhance its clinical applicability. Full article

Plasma-activated water (PAW), enriched with reactive oxygen and nitrogen species (RONS), presents oxidative and antimicrobial characteristics with potential in cosmetic applications. This study examined the effects of two PAW formulations—nitrate-rich (PAW-N) and peroxide-rich (PAW-P)—on human hair types classified as straight (Type 1), wavy (Type 2), and coily/kinky (Type 4). The impact of PAW on hair structure and chemistry was evaluated using Fourier-transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), UV–Vis spectrophotometry, and physicochemical analyses of the liquids (pH, ORP, conductivity, and TDS). PAW-N, with high nitrate content (~500 mg/L), low pH (2.15), and elevated conductivity (6244 µS/cm), induced significant damage to porous hair types, including disulfide bond cleavage, protein oxidation, and lipid degradation, as indicated by FTIR and EDS data. SEM confirmed severe cuticle disruption. In contrast, PAW-P, containing >25 mg/L of hydrogen peroxide and exhibiting milder acidity and lower ionic strength, caused more localized and controlled oxidation with minimal morphological damage. Straight hair showed greater resistance to both treatments, while coily and wavy hair were more susceptible, particularly to PAW-N. These findings suggest that the formulation and ionic profile of PAW should be matched to hair porosity for safe oxidative treatments, supporting the use of PAW-P as a gentler alternative in hair care technologies. Full article

Carbon deposits on the crown of engine pistons can markedly reduce combustion efficiency and shorten service life. Conventional cleaning techniques often fail to simultaneously ensure a high carbon removal efficiency and maintain optimal surface integrity. To enable efficient and precise carbon removal, this study proposes the application of hybrid laser cleaning—combining continuous-wave (CW) and pulsed lasers—to piston carbon deposit removal, and employs response surface methodology (RSM) for multi-objective process optimization. Using the N52B30 engine piston as the experimental substrate, this study systematically investigates the combined effects of key process parameters—including CW laser power, pulsed laser power, cleaning speed, and pulse repetition frequency—on surface roughness (Sa) and carbon residue rate (RC). Plackett–Burman design was employed to identify significant factors, the method of the steepest ascent was utilized to approximate the optimal region, and a quadratic regression model was constructed using Box–Behnken response surface methodology. The results reveal that the Y-direction cleaning speed and pulsed laser power exert the most pronounced influence on surface roughness (F-values of 112.58 and 34.85, respectively), whereas CW laser power has the strongest effect on the carbon residue rate (F-value of 57.74). The optimized process parameters are as follows: CW laser power set at 625.8 W, pulsed laser power at 250.08 W, Y-direction cleaning speed of 15.00 mm/s, and pulse repetition frequency of 31.54 kHz. Under these conditions, the surface roughness (Sa) is reduced to 0.947 μm, and the carbon residue rate (RC) is lowered to 3.67%, thereby satisfying the service performance requirements for engine pistons. This study offers technical insights into the precise control of the hybrid laser cleaning process and its practical application in engine maintenance and the remanufacturing of end-of-life components. Full article

Timely and accurate monitoring of crop nitrogen (N) status is essential for precision agriculture. UAV-based hyperspectral remote sensing offers high-resolution data for estimating plant nitrogen concentration (PNC), but its cost and complexity limit large-scale application. This study compares the performance of UAV hyperspectral data (S185 sensor) with simulated multispectral data from DJI Phantom 4 Multispectral (P4M), PlanetScope (PS), and Sentinel-2A (S2) in estimating winter wheat PNC. Spectral data were collected across six growth stages over two seasons and resampled to match the spectral characteristics of the three multispectral sensors. Three variable selection strategies (one-dimensional (1D) spectral reflectance, optimized two-dimensional (2D), and three-dimensional (3D) spectral indices) were combined with Random Forest Regression (RFR), Support Vector Machine Regression (SVMR), and Partial Least Squares Regression (PLSR) to build PNC prediction models. Results showed that, while hyperspectral data yielded slightly higher accuracy, optimized multispectral indices, particularly from PS and S2, achieved comparable performance. Among models, SVM and RFR showed consistent effectiveness across strategies. These findings highlight the potential of low-cost multispectral platforms for practical crop N monitoring. Future work should validate these models using real satellite imagery and explore multi-source data fusion with advanced learning algorithms. Full article

The worldwide increase in antifungal resistance, particularly in Candida sp., requires the exploration of novel therapeutic agents. Natural compounds have been a rich source of antimicrobial molecules, where peptides constitute the class of the most bioactive components. Therefore, this study looks into the target-specific binding efficacy of insect-derived antifungal peptides (n = 37) as possible alternatives to traditional antifungal treatments. Using computational methods, namely the HPEPDOCK and HDOCK platforms, molecular docking was performed to evaluate the interactions between selected key fungal targets, lanosterol 14-demethylase, or LDM (PDB ID: 5V5Z), secreted aspartic proteinase-5, or Sap-5 (PDB ID: 2QZX), N-myristoyl transferase, or NMT (PDB ID: 1NMT), and dihydrofolate reductase, or DHFR, of C. albicans. The three-dimensional peptide structure was modelled through the PEP-FOLD 3.5 tool. Further, we predicted the physicochemical properties of these peptides through the ProtParam and PEPTIDE 2.0 tools to assess their drug-likeness and potential for therapeutic applications. In silico results show that Blap-6 from Blaps rhynchopeter and Gomesin from Acanthoscurria gomesiana have the most antifungal potential against all four targeted proteins in Candida sp. Additionally, a molecular dynamics simulation study of LDM-Blap-6 was carried out at 100 nanoseconds. The overall predictions showed that both have strong binding abilities and are good candidates for drug development. In in vitro studies, Gomesin achieved complete biofilm eradication in three out of four Candida species, while Blap-6 showed moderate but consistent reduction across all species. C. tropicalis demonstrated relative resistance to complete eradication by both peptides. The present study provides evidence to support the antifungal activity of certain insect peptides, with potential to be used as alternative drugs or as a template for a new synthetic or modified peptide in pursuit of effective therapies against Candida spp. Full article

Introduction: Biodegradable Temporizing Matrix (BTM) is a new synthetic dermal substitute suitable for wound closure and tissue regeneration. The data in paediatric population remain limited. The study purpose is to review the indications for BTM application in paediatric patients; evaluate the short-term and long-term results, including complications and functional outcomes, as well as to share some unique observations regarding the use of BTM in paediatric population. Patients and Methods: Patients undergoing reconstructive surgery and BTM application during the last three years were included. Data collected included patient demographics, primary diagnosis, previous surgical management, post-operative complications and final outcomes. BTM was used in 32 patients. The indications varied including epidermolysis bullosa (n = 6), burns (n = 4), trauma (n = 7), infection (n = 4), ischemia or necrosis (n = 11). Results: The results were satisfying with acceptable aesthetic and functional outcomes. Complications included haematomaunderneath the BTM leading to BTM removal and re-application (n = 1), BTM infection (n = 1) and split-thickness skin graft failure on top of BTM requiring re-grafting (n = 2). Conclusions: BTM can be a good alternative to large skin grafts, locoregional flaps or even free flaps. The big advantages over other dermal substitutes or skin grafts are that BTM is less prone to infection and offers excellent scarring by preserving the normal skin architecture. Specifically in children, BTM might not require grafting, resulting in spontaneous healing with good scarring. In critically ill patients, BTM reduces the operation time and there is no donor site morbidity. BTM should be considered in the reconstructive ladder when discussing defect coverage options in children and young people. Full article

Strawberries are highly perishable fruits prone to postharvest losses due to defects, diseases, and uneven ripening. This study proposes a deep learning-based approach for automated quality assessment using the YOLOv8n object detection model. A custom dataset of 5663 annotated strawberry images was compiled, covering eight quality categories, including anthracnose, gray mold, powdery mildew, uneven ripening, and physical defects. Data augmentation techniques, such as rotation and Gaussian blur, were applied to enhance model generalization and robustness. The model was trained over 100 and 200 epochs, and its performance was evaluated using standard metrics: Precision, Recall, and mean Average Precision (mAP). The 200-epoch model achieved the best results, with a mAP50 of 0.79 and an inference time of 1 ms per image, demonstrating suitability for real-time applications. Classes with distinct visual features, such as anthracnose and gray mold, were accurately classified. In contrast, visually similar categories, such as ‘Good Quality’ and ‘Unripe’ strawberries, presented classification challenges. Full article

Hydrogels are widely known for their ability to increase soil water retention and for their potential slow nutrient release mechanism. They have been constantly improved to meet the growing demand for sustainability in agriculture. Research focused on the development of biodegradable hydrogels, produced from industrial cellulose waste, are an ecological and efficient alternative soil ameliorant for the improvement of agricultural land. The objective of this study was to evaluate the impacts of two types of hydrogel (processed in a glass reactor versus a twin-screw extruder) on soils with different textures (clay and sandy loam), testing their water retention capacity, nitrogen leaching, and effects on seed germination. The methodology included the evaluation of water retention capacity at different pressures with different hydrogel addition rates in the soil, leaching tests in columns filled with soil and hydrogel layers, and germination tests of sorghum and corn. The results indicated that the addition of hydrogel significantly improved water retention, especially in sandy loam soils. The hydrogels also reduced nitrogen leaching, acting as nitrification inhibitors and limiting the conversion of ammonium to nitrate, with greater effectiveness in clayey soils. In the tested formulations, it was observed that the hydrogel doses applied to the columns favored nitrogen retention in the region close to the roots, directly influencing the initial stages of germination. This behavior highlights the potential of hydrogels as tools for directing nutrients in the soil profile, indicating that adjustments to the C:N ratio, nutrient release rate, and applied doses can optimize their application for different crops. Full article

Enhancing the specificity and applicability of PCR-based genome-walking methods is highly desirable. A new and universal genome-walking tool, called center degenerated walking-primer PCR (CDWP-PCR), is presented in this study. CDWP-PCR involves adopting a center degenerated walking primer (cdWP) in the secondary/tertiary round of amplification. This cdWP is generated by degenerating the seven central nucleotides of the normal walking primer (nWP) used in primary PCR to NNNNNNN (where N includes the bases A, T, C, and G). Clearly, a partially complementary structure is formed between the two primers. Accordingly, the primary CDWP-PCR non-target products defined by the nWP are diluted in secondary/tertiary CDWP-PCR, as these non-targets have difficulty in annealing with the cdWP; conversely, the primary target product can still be efficiently amplified. The working performance of the proposed CDWP-PCR is verified through cloning of the unknown flanks of three known genes. All the clear DNA bands in the tertiary CDWP-PCRs are confirmed to be correct, and the largest DNA band is 8.0 kb. Overall, CDWP-PCR can be considered as a reliable supplement to existing genome-walking methods. Full article

The aim of this study was to analyze how recombinant rabbit NGF (Nerve Growth Factor) encapsulated in chitosan (rrβNGFch) affects sperm viability, motility, capacitation, acrosome reaction (AR), kinetic traits, and apoptosis after 30 min and 2 h of storage. Specific intracellular signaling pathways associated with either cell survival, such as protein kinase B (AKT) and extracellular signal-regulated kinases 1/2 (ERK1/2), or programmed cell death, such as c-Jun N-terminal kinase (JNK), were also analyzed. The results confirmed the effect of rrβNGFch on capacitation and AR, whereas a longer storage time (2 h) decreased all qualitative sperm traits. AKT and JNK did not show treatment-dependent activation and lacked a correlation with functional traits, as shown by ERK1/2. These findings suggest that rrβNGFch may promote the functional activation of sperm cells, particularly during early incubation. The increase in capacitation and AR was not linked to significant changes in pathways related to cell survival or death, indicating a specific action of the treatment. In contrast, prolonged storage negatively affected all sperm parameters. ERK1/2 activation correlated with capacitation, AR, and apoptosis, supporting its role as an NGF downstream mediator. Further studies should analyze other molecular mechanisms of sperm and the potential applications of NGF in assisted reproduction. Full article

Hydrogels, especially Polyvinyl alcohols, have received extensive attention as alternative materials for articular cartilage. Aiming at the problems such as low strength and poor toughness of polyvinyl alcohol hydrogels in practical applications, an enhancement and modification strategy is proposed. Sodium alginate fibers were introduced into polyvinyl alcohol hydrogel network through physical blending and freezing/thawing methods. The prepared composite hydrogels exhibited a three-dimensional porous network structure similar to that of human articular cartilage. The mechanical and tribological properties of hydrogels have been significantly improved, due to the multiple hydrogen bonding interaction between sodium alginate fibers and polyvinyl alcohol. Most importantly, under a load of 2 N, the friction coefficient of the PVA/0.4SA hydrogel can remain stable at 0.02 when lubricated in PBS buffer for 1 h. This work provides a novel design strategy for the development of high-performance polyvinyl alcohol hydrogels. Full article