Search Results (203)

To elucidate how exogenous regulators mitigate the impact of mechanical leaf damage on maize, field experiments were conducted on two sowing dates (S1, S2) using two cultivars (XY335, ZD958). Severe leaf damage at the six-leaf stage significantly reduced kernel number, ear number, and 100-kernel weight, causing yield losses of 21.9–48.9%. Foliar application of melatonin (MT), brassinolide (BR), and urea (UR) substantially alleviated these losses, increasing yield by 14.1–52.2% compared to damaged controls, with UR and BR being most effective, especially in ZD958. These regulators restored leaf area index (LAI) by promoting leaf width and delaying senescence, improved photosynthetic performance (Pn, Gs, Ci, and Tr), enhanced post-silking dry matter accumulation by up to 31%, and accelerated grain filling through increased maximum and mean filling rates. Structural equation modeling confirmed that kernel number and 100-kernel weight were the primary yield determinants. These findings reveal the physiological mechanisms underlying damage recovery and demonstrate the potential of targeted regulator applications—urea as a cost-effective option, brassinolide for improving kernel number under sustained stress, and melatonin for broad resilience. This study provides not only theoretical evidence but also a feasible strategy for mitigating yield loss in maize production under field conditions where leaf damage commonly occurs. Full article

The historic mortuary at Zagreb’s Mirogoj Cemetery, built in 1886, sustained moderate damage during the 2020 Mw 5.3 earthquake. Aiming to preserve heritage value while meeting Croatia’s Level 4 seismic safety requirements, the structure was assessed using in situ and laboratory tests followed by macro-element modeling with 3Muri software. The study evaluated four scenarios: (A) post-earthquake damaged state, (B) reinforcement with new masonry and RC walls, (C) partial fiber-reinforced cementitious matrix (FRCM) plastering, and (D) systematic FRCM plastering. Results show that Case B improved Ultimate Limit State (ULS) scaling factors from 0.64/0.56 to 0.92/0.90 (X/Y), while Case D raised them to 1.03/1.17, satisfying Eurocode 8 and national renovation criteria. Systematic FRCM application improved story shear capacity by up to 57% and shifted failure modes from brittle shear to ductile rocking. Partial plastering proved insufficient, highlighting the need for comprehensive global retrofitting. While the solution is minimally invasive and reversible, uncertainties remain regarding long-term durability and out-of-plane performance. This hybrid retrofitting strategy offers a replicable model for heritage masonry buildings in seismically active regions. Full article

This study investigates the mechanical behavior of water-washable photosensitive resins used in masked stereolithography (mSLA) 3D printing, evaluating the effect of post-curing time (0, 5, 10, 30, and 60 min) and printing orientation (Flat [XY], Vertical [Z], and On-edge [XZ]) on the material characteristics. Specimens were manufactured according to ISO 527-2 type 1B and ISO 178 standards for tensile and bending tests, respectively. A Matlab algorithm was developed to automate the processing of experimental data. This tool enabled the extraction of parameters to fit distinct mathematical models for the elastic (linear) and nonlinear (polynomial) regimes, allowing the material response to be characterized at different curing times and print orientations. These models were implemented in Ansys Workbench for comparison with experimental results. The results show that increasing the post-curing time from 0 to 60 min raises the elastic modulus from 964.5 to 1892.4 MPa in the Flat [XY] orientation and from 774 to 1661.2 MPa in the Vertical [Z] orientation for tensile testing. In bending testing, the Flat [XY] orientation presented the best mechanical properties, while the Vertical [Z] and On-edge [XZ] orientations showed similar behavior. The numerical simulations adequately reproduced the experimental results, validating the developed constitutive models. Finally, a stress–strain correlation model is presented that enables estimation for any post-curing time between 0 and 60 min. This study provides essential data for optimizing 3D printing processes and developing structural applications with photopolymer resins. Full article

Recent advances in artificial intelligence (AI) have transformed ophthalmic diagnostics, particularly for retinal diseases. In this prospective, non-randomized study, we evaluated the performance of an AI-based software system against conventional clinical assessment—both quantitative and qualitative—of optical coherence tomography (OCT) images for diagnosing diabetic macular edema (DME). A total of 700 OCT exams were analyzed across 26 features, including demographic data (age, sex), eye laterality, visual acuity, and 21 quantitative OCT parameters (Macula Map A X-Y). We tested two classification scenarios: binary (DME presence vs. absence) and multiclass (six distinct DME phenotypes). To streamline feature selection, we applied paraconsistent feature engineering (PFE), isolating the most diagnostically relevant variables. We then compared the diagnostic accuracies of logistic regression, support vector machines (SVM), K-nearest neighbors (KNN), and decision tree models. In the binary classification using all features, SVM and KNN achieved 92% accuracy, while logistic regression reached 91%. When restricted to the four PFE-selected features, accuracy modestly declined to 84% for both logistic regression and SVM. These findings underscore the potential of AI—and particularly PFE—as an efficient, accurate aid for DME screening and diagnosis. Full article

Bats are great models for studying repetitive DNAs due to their compact genomes and extensive chromosomal rearrangements. Here, we investigated the repetitive DNA content of two phyllostomid bat species, Artibeus lituratus (2nn = 30♀/31♂) and Carollia perspicillata (2n = 20♀/21♂), both harboring a multiple XY₁Y₂ sex chromosome system. Satellite DNA (satDNA) libraries were isolated and characterized, revealing four and ten satDNA families in A. lituratus and C. perspicillata, respectively. These sequences, along with selected microsatellites, were in situ mapped onto chromosomes in both species and phylogenetically related taxa. SatDNAs showed strong accumulation in centromeric and subtelomeric regions, especially pericentromeric areas. Cross-species mapping with C. perspicillata-derived probes indicated terminal localization patterns in other bat species, suggesting conserved distribution. Microsatellites co-localized with 45S rDNA clusters on the neo-sex chromosomes. Additionally, genomic hybridization revealed a male-specific signal on the Y₁ chromosome, pointing to potential sex-linked repetitive regions. These findings confirm that bat genomes display relatively low amounts of repetitive DNA compared to other mammals and underscore the role of these elements in genome organization and sex chromosome evolution in phyllostomid bats. Full article

With the growing adoption of 3D stacked memory structures, precise alignment and overlay control have become critical for multi-layer overlay accuracy. The metrology accuracy and stability of alignment marks are crucial to ensuring optimal alignment and overlay performance. This study systematically investigates the contributions of two key alignment parameters—Wafer Quality (WQ) and Alignment Position Deviation (APD)—to the alignment model residue in 3D structures. Through experimental and simulation approaches, we analyze the interplay between WQ, APD and overlay performance. Results reveal that APD exhibits a stronger correlation with uncorrectable model residue, particularly under global process variations such as etch non-uniformity. Furthermore, APD sensitivity varies directionally (X/Y direction marks) and spatially (wafer edge versus center), highlighting the need for targeted mark designs in process-sensitive zones. These findings provide actionable insights for optimizing alignment strategies, mark designs and process monitoring throughout R&D, technology development and high-volume manufacturing phases. Full article

This study proposes a deep learning-based method to improve overlay alignment precision in laser direct writing systems. Alignment errors arise from multiple sources in nanoscale processes, including optical aberrations, mechanical drift, and fiducial mark imperfections. A significant portion of the residual alignment error stems from the interpretation of mark coordinates by the vision system and algorithms. Here, we developed a convolutional neural network (CNN) model to predict the coordinates calculation error of 66,000 sets of computer-generated defective crosshair marks (simulating real fiducial mark imperfections). We compared 14 neural network architectures (8 CNN variants and 6 feedforward neural network (FNN) configurations) and found a well-performing, simple CNN structure achieving a mean squared error (MSE) of 0.0011 on the training sets and 0.0016 on the validation sets, demonstrating 90% error reduction compared to the FNN structure. Experimental results on test datasets showed the CNN’s capability to maintain prediction errors below 100 nm in both X/Y coordinates, significantly outperforming traditional FNN approaches. The proposed method’s success stems from the CNN’s inherent advantages in local feature extraction and translation invariance, combined with a simplified network architecture that prevents overfitting while maintaining computational efficiency. This breakthrough establishes a new paradigm for precision enhancement in micro–nano optical device fabrication. Full article

In this study, four types of fall detection systems for seniors living alone using x-y scatter and Doppler range images measured from frequency-modulated continuous wave (FMCW) millimeter-wave (mmWave) sensors were introduced. Despite advancements in fall detection, existing long short-term memory (LSTM)-based approaches often struggle with effectively distinguishing falls from similar activities of daily living (ADLs) due to their uniform treatment of all time steps, potentially overlooking critical motion cues. To address this limitation, an attention mechanism has been integrated. Data was collected from seven participants, resulting in a dataset of 669 samples, including 285 falls and 384 ADLs with walking, lying, inactivity, and sitting. Four LSTM-based architectures for fall detection were proposed and evaluated: Raw-LSTM, Raw-LSTM-Attention, HOG-LSTM, and HOG-LSTM-Attention. The histogram of oriented gradient (HOG) method was used for feature extraction, while LSTM networks captured temporal dependencies. The attention mechanism further enhanced model performance by focusing on relevant input features. The Raw-LSTM model processed raw mmWave radar images through LSTM layers and dense layers for classification. The Raw-LSTM-Attention model extended Raw-LSTM with an added self-attention mechanism within the traditional attention framework. The HOG-LSTM model included an additional preprocessing step upon the RAW-LSTM model where HOG features were extracted and classified using an SVM. The HOG-LSTM-Attention model built upon the HOG-LSTM model by incorporating a self-attention mechanism to enhance the model’s ability to accurately classify activities. Evaluation metrics such as Sensitivity, Precision, Accuracy, and F1-Score were used to compare four architectural models. The results showed that the HOG-LSTM-Attention model achieved the highest performance, with an Accuracy of 95.3% and an F1-Score of 95.5%. Optimal self-attention configuration was found at a 2:64 ratio of number of attention heads to channels for keys and queries. Full article

Introduction: Pediatric prosthetic knee joints must be appropriately scaled from adult designs to ensure proper gait biomechanics. However, direct dimensional scaling without considering the biomechanical implications may lead to functional discrepancies. This study aimed to evaluate whether using a linear scaling factor can effectively adapt a knee for pediatric use. The study assessed whether such an approach yields a viable pediatric prosthetic knee joint by applying a fixed scaling factor and analyzing the resultant knee geometry. Methods: The linear scaling factor was determined based on the pylon tube diameter, a key constraint in compact pediatric knee design. Given a pediatric pylon diameter of 22 mm, the length of the tibial link was set to 22 mm, yielding a scaling factor of 0.6875 when compared to the adult-sized knee. This scaling factor was used to determine the dimensions of the pediatric four-bar (scaled) knee joint. Static geometric analysis was conducted using GeoGebra^® to model the lower-body segment lengths. The knee joint’s performance was evaluated based on stance and swing phase parameters. These metrics were compared between the scaled knee and a commercial pediatric knee. Results: The geometric analysis revealed that while using the linear scaling factor maintained proportional relationships, certain biomechanical parameters deviated from the expected pediatric norms. The scaled knee achieved a toe clearance of 13.5 mm compared to 19.7 mm in the commercial design and demonstrated a swing-phase heel clearance of 11.6 mm versus 13.3 mm, maintaining negative x/y ratios at heel contact and showing significant stability in push-off moments, while the stance flexion angle remained within an acceptable range. The heel contact and push-off ratios (x/y) were found to be comparable, with the scaled model achieving values of −1.21 and −0.59, respectively. The stance flexion angle measured 10.6°, closely aligning with the commercial reference. Conclusions: Using a linear scaling factor provides a straightforward method for adapting adult prosthetic knee designs to pediatric use. However, deviations in key biomechanical parameters indicate that further experimental study may be required to validate the applicability of the scaled knee joint for pediatric users. Future work should explore dynamic simulations and experimental validations to refine the design further and ensure optimal gait performance. Full article

Nile tilapia, as an ideal model for studying sex differentiation, is a popular farmed fish worldwide with a stable XX/XY sex-determination system. In tilapia, ovarian differentiation is triggered by estradiol-17β (E2) production in undifferentiated gonads. In a previous study, we suggested that follicle-stimulating hormone (FSH) signaling might be involved in ovarian differentiation in Nile tilapia. In this study, we further investigated the role of FSH signaling in ovarian differentiation via aromatase expression, which converts testosterone to E2. Masculinization of XX fry by aromatase inhibitor or 17α-methyltestosterone leads to suppression of fshr expression. Feminization of XY fry by E2 treatment increased fshr expression from 15 days after hatching, when E2 treatment was terminated. XX tilapia developed ovaries harboring aromatase expression if fsh and fshr were double knockdowns by morpholino-oligo injections. Finally, the transcriptional activity in the upstream region of the aromatase gene (cyp19a1a) was further increased by FSH stimulation when HEK293T cells were co-transfected with foxl2 and ad4bp/sf1. Collectively, this study suggests that the role of FSH signaling is not critical in tilapia ovarian differentiation; however, FSH signaling may have a compensatory role in ovarian differentiation by increasing cyp19a1a transcription in cooperation with foxl2 and ad4bp/sf1 in Nile tilapia. Full article

Free-form surface polishing is a key process in precision machining within high-end manufacturing, where optimizing the polishing trajectory directly influences both processing quality and efficiency. Traditional trajectory planning methods for free-form surface polishing in high-curvature regions suffer from issues such as a lack of precision, low trajectory continuity, and inefficiency. This paper proposes an improved trajectory planning method based on curvature characteristics, incorporating dynamic partitioning and boundary smoothing algorithms. These methods dynamically adjust according to surface curvature, enhancing processing efficiency and surface quality. Additionally, a hybrid optimization framework combining a genetic algorithm (GA) and local search (LS) is proposed to address the challenges of balancing global optimization with local fine-tuning in traditional trajectory planning methods. These challenges often result in large errors, low machining efficiency, and unstable surface quality. The method optimizes the overall trajectory distribution through a global search using GA while locally refining the high-curvature regions with LS. This combination improves trajectory uniformity and smoothness, and the results demonstrate significant increases in machining efficiency and accuracy. Finally, the feasibility of the trajectory planning method was verified through motion simulation. This paper also provides a detailed description of the mathematical modeling, algorithm implementation, and simulation analysis of the XY-3-RPS hybrid robot for trajectory optimization, offering both a theoretical foundation and engineering support for its application in free-form surface polishing. Full article

Achieving a stable color output across wide temperature ranges in automotive LED applications is challenging, especially when using cost-sensitive chips with limited computational resources. This study proposes an improved temperature model that integrates Fourier heat conduction and thermal resistance concepts to more accurately capture self-heating and power dissipation effects. To accommodate the constraints of low-cost automotive-grade microcontrollers (MCUs), the associated optical algorithm is converted from floating-point to a 16.16 fixed-point format, reducing both memory usage and computational overhead. Experimental results conducted from −40 °C to 120 °C show that the improved model predicts LED temperatures within 5 °C of measured values, reducing errors by up to 30% compared to conventional PN-junction-based methods. Furthermore, by comparing the chromaticity points generated under the new and traditional models—and implementing an additional three-duty-cycle offset at 1% brightness—the improved approach reduces chromaticity drift by approximately 0.0052 in the CIE 1931 xy color space. These findings confirm the superior stability and accuracy of the new model for both thermal management and chromaticity compensation, offering a cost-effective solution for automotive LED systems requiring precise color control under constrained MCU resources. Full article

This paper presents a comprehensive investigation into the phenomenon of gamut boundary distortion that occurs during the gamut conversion process in LED full-color display systems. This phenomenon is influenced by the electro-optical transfer function. First, a CIE-xyY colorimetric framework specifically designed for LEDs is developed and established as the foundation for gamut conversion in LED applications. Next, the principles of gamut conversion based on this model are detailed. Additionally, a set of indices, including the Laplacian operator, entropy function, and magnitude of deviation of distorted color points, is integrated to form a comprehensive descriptive methodology. This methodology enables a thorough quantification of distribution patterns and effectively illustrates the outcomes of distortion. The findings of this research are significant for improving color conversion strategies and enhancing the color performance of display devices, making meaningful contributions to related fields. Full article

This study tackles the challenge of splitting and merging in parametric active contours or snakes. The proposed method comprises three stages: (1) fully 4-connected interpolation, (2) snake splitting, and (3) snakes merging. For this purpose, first, the coordinates of snake points are separated into two corrupted 1D signals, with missing X/Y samples in the signals representing missing snakes’ coordinates. These missing X/Y samples are estimated using a constrained Tikhonov regularisation model, ensuring fully 4-connected snakes. Next, crossing points are identified by plotting snake points onto a raster matrix, detecting overlaps where multiple snake points occupy the same raster cell. Finally, snakes are split or merged by extracting snake points between crossing snake points that form a loop using a heuristic approach. Experimental results on the boundary detection of enamel in Micro-CT images and coronary arteries’ lumen in CT images demonstrate the proposed method’s ability to handle contour splitting and merging effectively. Full article

This publication presents the results of research on selected quality features of sample models made using 3D printing technology from the Powder Bed Fusion (PBF) group and a material based on aluminum powder. Two quality areas were analyzed: tensile strength and geometric surface structure. Strength tests of thin-walled models were carried out for samples with four given thicknesses of 1, 1.4, 1.8, and 2 mm and four printing directions, namely, three in the XZ plane and one in the XY plane. The measurement of the geometric structure was carried out using optical measuring devices and by taking into account the assessment of roughness and waviness parameters. Using scanning electron microscopy (SEM), an analysis of the fracture of samples after rupture was carried out and the surface was assessed for technological defects created in the manufacturing process. The test results showed that for thin-walled sample models, there are certain technological limitations regarding the minimum sample thickness in the manufacturing process and that the strength of thin-walled models in relation to “solid” samples depends on both the sample thickness and the printing direction. Roughness parameters that determine functional quality characteristics such as friction and wear were determined and also showed a dependence on the printing direction. Full article