Search Results (146,601)

The present study explores the application of RNNs for the prediction and propagation of flood waves along a section of the Bârsa River, Romania, as a fast alternative to classical hydraulic models, aiming to identify new ways to alert the population. Five neural architectures were analyzed as follows: S-RNN, LSTM, GRU, Bi-LSTM, and Bi-GRU. The input data for the neural networks were derived from 2D hydraulic simulations conducted using HEC-RAS software, which provided the necessary training data for the models. It should be mentioned that the input data for the hydraulic model are synthetic hydrographs, derived from the statistical processing of recorded floods. Performance evaluation was based on standard metrics such as NSE, $R^2$ MSE, and RMSE. The results indicate that all studied networks performed well, with NSE and $R^2$ values close to 1, thus validating their capacity to reproduce complex hydrological dynamics. Overall, all models yielded satisfactory results, making them useful tools particularly the GRU and Bi-GRU architectures, which showed the most balanced behavior, delivering low errors and high stability in predicting peak discharge, water level, and flood wave volume. The GRU and Bi-GRU networks yielded the best performance, with RMSE values below 1.45, MAE under 0.3, and volume errors typically under 3%. On the other hand, LSTM architecture exhibited the most significant instability and errors, especially in estimating the flood wave volume, often having errors exceeding 9% in some sections. The study concludes by identifying several limitations, including the heavy reliance on synthetic data and its local applicability, while also proposing solutions for future analyses, such as the integration of real-world data and the expansion of the methodology to diverse river basins thus providing greater significance to RNN models. The final conclusions highlight that RNNs are powerful tools in flood risk management, contributing to the development of fast and efficient early warning systems for extreme hydrological and meteorological events. Full article

Generative AI tools such as ChatGPT are reshaping educational practice, yet first-year teacher-education students often lack the prompt-engineering skills and confidence required to use them responsibly. This pilot study examined whether a concise three-session clinic on prompt engineering could simultaneously boost AI literacy and reduce technology anxiety in prospective teachers. Forty-five freshmen in a Peruvian teacher-education program completed validated Spanish versions of a 12-item AI-literacy scale and a 12-item technology-anxiety scale one week before and after the intervention; normality-checked pre–post differences were analysed with paired-samples t-tests, Cohen’s d, and Pearson correlations. AI literacy rose by 0.70 ± 0.46 points (t (44) = −6.10, p < 0.001, d = 0.91), while technology anxiety fell by 0.58 ± 0.52 points (t (44) = −3.82, p = 0.001, d = 0.56); individual gains were inversely correlated (r = −0.46, p = 0.002). These findings suggest that integrating micro-level prompt-engineering clinics in the first semester can help future teachers engage critically and comfortably with generative AI and guide curriculum designers in updating teacher-training programs. Full article

Electrospun nanofibrous membranes have gained considerable attention in bone tissue engineering due to their ability to mimic the extracellular matrix and provide a suitable environment for cell attachment and proliferation. This study investigates the fabrication, characterization, and biocompatibility of poly(L-lactic acid) (PLA)-based membranes enhanced with periclase (MgO) and gold nanoparticles (AuNPs). The membranes were fabricated using an optimized electrospinning process and subsequently characterized using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FT-IR), and contact angle measurements. Additionally, in vitro biodegradation studies in simulated body fluid (SBF) and cytocompatibility tests with osteoblast-like cells were conducted. The results demonstrated that the incorporation of MgO and AuNPs significantly influenced the structural and chemical properties of the membranes, improving their wettability and bioactivity. SEM imaging confirmed uniform fiber morphology with well-distributed nanoparticles. FT-IR spectroscopy indicated successful integration of bioactive components into the PLA matrix. Cytocompatibility assays showed that modified membranes promoted higher osteoblast adhesion and proliferation compared to pristine PLA membranes. Furthermore, biodegradation studies revealed a controlled degradation rate suitable for guided bone regeneration applications. These findings suggest that electrospun PLA membranes enriched with MgO and AuNPs present a promising biomaterial for GBR applications, offering improved bioactivity, mechanical stability, and biocompatibility. Full article

Three-dimensional trench electrode silicon detectors play an important role in particle physics research, nuclear radiation detection, and other fields. A novel polysilicon-fill-strengthened etch-through 3D trench electrode detector is proposed to address the shortcomings of traditional 3D trench electrode silicon detectors; for example, the distribution of non-uniform electric fields, asymmetric electric potential, and dead zone. The physical properties of the detector have been extensively and systematically studied. This study simulated the electric field, potential, electron concentration distribution, complete depletion voltage, leakage current, capacitance, transient current induced by incident particles, and weighting field distribution of the detector. It also systematically studied and analyzed the electrical characteristics of the detector. Compared to traditional 3D trench electrode silicon detectors, this new detector adopts a manufacturing process of double-side etching technology and double-side filling technology, which results in a more sensitive detector volume and higher electric field uniformity. In addition, the size of the detector unit is 120 µm × 120 µm × 340 µm; the structure has a small fully depleted voltage, reaching a fully depleted state at around 1.4 V, with a saturation leakage current of approximately $4.8\times {10}^{-10}\mathrm{A}$, and a geometric capacitance of about 99 fF. Full article

Reliable, non-destructive grading of fresh fruit requires simultaneous assessment of external morphology and hidden internal defects. Camera-based grading of fresh fruit using colorimetric (RGB) and near-infrared (NIR) imaging often misses subsurface bruising and cannot capture the fruit’s true shape, leading to inconsistent quality assessment and increased waste. To address this, we developed a 4D-grading pipeline that fuses visible and near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral imaging with structured-light 3D scanning to non-destructively evaluate both internal defects and external form. Our contributions are (1) flagging the defects in fruits based on the reflectance information, (2) accurate shape and defect measurement based on the 3D data of fruits, and (3) an interpretable, decision-tree framework that assigns USDA-style quality (Premium, Grade 1/2, Reject) and size (Small–Extra Large) labels. We demonstrate this approach through preliminary results, suggesting that 4D hyperspectral imaging may offer advantages over single-modality methods by providing clear, interpretable decision rules and the potential for adaptation to other produce types. Full article

Based on the panel data of daily meteorological stations and winter wheat yield in Henan Province from 2000 to 2023, this study comprehensively used the Mann–Kendall trend test, wavelet coherence analysis (WTC), and other methods to reveal the temporal and spatial evolution of extreme precipitation and its multi-scale stress mechanism on grain yield. The results showed the following: (1) Extreme precipitation showed the characteristics of ‘frequent fluctuation-gentle trend-strong spatial heterogeneity’, and the maximum daily precipitation in spring (RX1DAY) showed a significant uplift. The increase in rainstorm events (R95p/R99p) in the southern region during the summer is particularly prominent; at the same time, the number of consecutive drought days (CDDs > 15 d) in the middle of autumn was significantly prolonged. It was also found that 2010 is a significant mutation node. Since then, the synergistic effect of ‘increasing drought days–increasing rainstorm frequency’ has begun to appear, and the short-period coherence of super-strong precipitation (R99p) has risen to more than 0.8. (2) The spatial pattern of winter wheat in Henan is characterized by the three-level differentiation of ‘stable core area, sensitive transition zone and shrinking suburban area’, and the stability of winter wheat has improved but there are still local risks. (3) There is a multi-scale stress mechanism of extreme precipitation on winter wheat yield. The long-period (4–8 years) drought and flood events drive the system risk through a 1–2-year lag effect (short-period (0.5–2 years) medium rainstorm intensity directly impacted the production system). This study proposes a ‘sub-scale governance’ strategy, using a 1–2-year lag window to establish a rainstorm warning mechanism, and optimizing drainage facilities for high-risk areas of floods in the south to improve the climate resilience of the agricultural system against the background of climate change. Full article

Zoological environments aim to promote natural behaviours and optimal welfare conditions. Over the past decade, research on the use of artificial ultraviolet-B (UV-B) exposure has improved vitamin D₃ levels and reduced incidences of metabolic bone disease in diurnal primates; however, this has not been investigated in nocturnals. Aye-ayes (Daubentonia madagascariensis), nocturnal lemurs often housed indoors in zoos with little to no exposure to natural sunlight, have been reported to have low vitamin D₃ levels. This study aims to investigate the impacts of artificial UV-B as a supplemental healthcare strategy for aye-ayes, examining its influences on vitamin D₃ levels and positional sleeping behaviour. The 25-hydroxy-vitamin D₃ (25OHD₃) blood levels were tested before and after exposure to different levels of artificial UV-B and heat sources. Statistical analysis showed no correlation between UV-B and 25OHD₃ at group parameter levels. However, one individual showed a positive correlation. Sleeping position duration analysis showed a potential basking behaviour with the use of increased ear exposure and other thermoregulatory responses. Despite representing 8.06% of the European captive aye-aye population, these findings highlight the need for further research on vitamin D₃ parameters and responses to UV-B to optimise captive conditions and support the species’ long-term health. Full article

Organoids allow to model healthy and diseased human tissues. and have applications in developmental biology, drug discovery, and cell therapy. Traditionally cultured in immersion/suspension, organoids face issues like lack of standardization, fusion, hypoxia-induced necrosis, continuous agitation, and high media volume requirements. To address these issues, we developed an air–liquid interface (ALi) technology for culturing organoids, termed AirLiwell. It uses non-adhesive microwells for generating and maintaining individualized organoids on an air–liquid interface. This method ensures high standardization, prevents organoid fusion, eliminates the need for agitation, simplifies media changes, reduces media volume, and is compatible with Good Manufacturing Practices. We compared the ALi method to standard immersion culture for midbrain organoids, detailing the process from human pluripotent stem cell (hPSC) culture to organoid maturation and analysis. Air–liquid interface organoids (3D-ALi) showed optimized size and shape standardization. RNA sequencing and immunostaining confirmed neural/dopaminergic specification. Single-cell RNA sequencing revealed that immersion organoids (3D-i) contained 16% fibroblast-like, 23% myeloid-like, and 61% neural cells (49% neurons), whereas 3D-ALi organoids comprised 99% neural cells (86% neurons). Functionally, 3D-ALi organoids showed a striking electrophysiological synchronization, unlike the heterogeneous activity of 3D-i organoids. This standardized organoid platform improves reproducibility and scalability, demonstrated here with midbrain organoids. The use of midbrain organoids is particularly relevant for neuroscience and neurodegenerative diseases, such as Parkinson’s disease, due to their high incidence, opening new perspectives in disease modeling and cell therapy. In addition to hPSC-derived organoids, the method’s versatility extends to cancer organoids and 3D cultures from primary human cells. Full article

Conventional image encryption schemes struggle to meet the high security demands of medical images due to their large data volume, strong pixel correlation, and structural redundancy. To address these challenges, we propose a grayscale medical image encryption algorithm based on a novel 5-D memristor chaotic system. The algorithm integrates a Symmetric L-type Josephus Spiral Scrambling (SLJSS) module and a Dynamic Codon-based Multi-RNA Diffusion (DCMRD) module to enhance spatial decorrelation and diffusion complexity. Simulation results demonstrate that the proposed method achieves near-ideal entropy (e.g., 7.9992), low correlation (e.g., 0.0043), and high robustness (e.g., NPCR: 99.62%, UACI: 33.45%) with time complexity of $\mathcal{O}\left(11MN\right)$, confirming its effectiveness and efficiency for medical image protection. Full article

During large-scale pavement construction, the preparation of SBS-modified asphalt typically produces large amounts of harmful fumes. The emergence of deodorants can effectively alleviate the problem of smoke emissions during the asphalt manufacturing process. On the basis of ensuring the original road performance, exploring more suitable dosages and types of deodorant is urgently needed. Five commercial deodorants were evaluated using an asphalt smoke collection system, and UV-visible spectrophotometry (UV) was employed to screen the deodorants based on smoke concentration. Gas chromatography–mass spectrometry (GC-MS) was used to quantitatively analyze changes in harmful smoke components before and after adding two deodorants. Subsequently, the mechanisms of action of the two different types of deodorants were analyzed microscopically using fluorescence microscopy. Finally, the performance of bitumen and asphalt mixtures after adding deodorants was evaluated. The results showed that deodorant A (reactive type) and D (adsorption type) exhibited the best smoke suppression effects, with optimal addition rates of 0.6% and 0.5%, respectively. Deodorant A reduced benzene homologues by nearly 50% and esters by approximately 40%, while deodorant D reduced benzene homologues by approximately 70% and esters by approximately 60%, without producing new toxic gases. Both deodorants had a minimal impact on the basic properties of bitumen and the road performance of asphalt mixtures, with all indicators meeting technical specifications. This research provides a theoretical basis for the effective application of deodorants in the future, truly enabling a transition from laboratory research to large-scale engineering applications in the construction of environmentally friendly roads. Full article

Objective: The accurate visualization of root canal systems on periapical radiographs is critical for successful endodontic treatment. This study aimed to evaluate and compare the effectiveness of several image enhancement algorithms—including a novel Total Variation–Contrast-Limited Adaptive Histogram Equalization (TV-CLAHE) technique—in improving the detectability of root canal configurations in mandibular incisors, using cone-beam computed tomography (CBCT) as the gold standard. A null hypothesis was tested, assuming that enhancement methods would not significantly improve root canal detection compared to original radiographs. Method: A retrospective analysis was conducted on 60 periapical radiographs of mandibular incisors, resulting in 420 images after applying seven enhancement techniques: Histogram Equalization (HE), Contrast-Limited Adaptive Histogram Equalization (CLAHE), CLAHE optimized with Pelican Optimization Algorithm (CLAHE-POA), Global CLAHE (G-CLAHE), k-Caputo Fractional Differential Operator (KCFDO), and the proposed TV-CLAHE. Four experienced observers (two radiologists and two dentists) independently assessed root canal visibility. Subjective evaluation was performed using an own scale inspired by a 5-point Likert scale, and the detection accuracy was compared to the CBCT findings. Quantitative metrics including Peak Signal-to-Noise Ratio (PSNR), Signal-to-Noise Ratio (SNR), image entropy, and Structural Similarity Index Measure (SSIM) were calculated to objectively assess image quality. Results: Root canal detection accuracy improved across all enhancement methods, with the proposed TV-CLAHE algorithm achieving the highest performance (93–98% accuracy), closely approaching CBCT-level visualization. G-CLAHE also showed substantial improvement (up to 92%). Statistical analysis confirmed significant inter-method differences (p < 0.001). TV-CLAHE outperformed all other techniques in subjective quality ratings and yielded superior SNR and entropy values. Conclusions: Advanced image enhancement methods, particularly TV-CLAHE, significantly improve root canal visibility in 2D radiographs and offer a practical, low-cost alternative to CBCT in routine dental diagnostics. These findings support the integration of optimized contrast enhancement techniques into endodontic imaging workflows to reduce the risk of missed canals and improve treatment outcomes. Full article

Telomeres are protective DNA sequences located at chromosome ends, essential to maintaining genomic stability. This narrative review examines how maternal lifestyle factors during pregnancy influence fetal telomere length (TL). Positive associations have been identified between offspring’s TL and maternal consumption of nutrients such as vitamins C and D, folate, and magnesium. Additionally, adherence to a Mediterranean diet and regular physical activity during pregnancy are correlated with increased placental TL, supporting fetal genomic integrity. Conversely, maternal dietary patterns high in carbohydrates, fats, or alcohol, as well as exposure to triclosan and sleep-disordered breathing, negatively correlate with offspring’s TL. Maternal infections may also shorten TL through heightened inflammation and oxidative stress. However, evidence regarding the impact of other lifestyle factors—including maternal stress, smoking, caffeine intake, polyunsaturated fatty acid consumption, obesity, and sleep quality—remains inconsistent. Given that shorter telomere length has been associated with cardiovascular, pulmonary, and neurodegenerative diseases, as well as certain types of cancer, these findings highlight the vital importance of maternal health during pregnancy in order to prevent potential adverse effects on the fetus. Further studies are required to elucidate the precise timing, intensity, and interplay of these influences, enabling targeted prenatal interventions to enhance offspring health outcomes. Full article

This study was conducted to investigate the effects of puffed jujube powder (PJP) supplementation in the diet on the slaughter characteristics, growth performance, meat quality, and serum antioxidant capacity of Hainan Black (HB) goats. Twenty-four healthy male HB goats, three months old with an initial body weight of 15.12 ± 3.67 kg, were randomly divided into three groups: the 10% PJP group (basal diet plus 10% PJP); the 20% PJP group (basal diet plus 20% PJP); and the control group (basal diet only). After a 10-day adaptation period, a feeding trial was carried out for 90 days in an ad libitum diet environment. The results show that the final body weight of the 20% PJP group was markedly higher (p < 0.05) than that of the control group (22.58 ± 0.94 kg vs. 20.45 ± 1.01 kg). The average daily gain of the 20% PJP group was 83.44 ± 1.78 g/d, which was substantially greater (p < 0.05) than the 59.22 ± 2.13 g/d of the control group. The feed intake of the 20% PJP group was 713.10 ± 4.54 g/d, notably higher (p < 0.05) than the 498.20 ± 4.33 g/d of the control group. In terms of slaughter characteristics, the carcass weight of the 20% PJP group was 13.99 ± 1.22 kg, considerably heavier (p < 0.05) than the 11.79 ± 1.38 kg of the control group. The muscle weight of the 20% PJP group was 11.43 ± 1.42 kg, distinctly greater (p < 0.05) than the 9.59 ± 1.99 kg of the control group. The slaughter rate of the 20% PJP group was 42.41%, showing a notable increase (p < 0.05) compared with the 37.42% of the control group, and the net meat rate of the 20% PJP group was 34.65%, with a significant rise (p < 0.05) compared with the 30.43% of the control group. Regarding serum antioxidant capacity and meat quality, the activities of serum antioxidant enzymes, superoxide dismutase (SOD) and catalase (CAT), were conspicuously increased (p < 0.05) in the 20% PJP group. The meat shear force of the 20% PJP group was decreased by 12.9%, and the cooking loss was improved by 8.9% in comparison with the control group. In conclusion, the supplementation of 20% PJP in the diet was demonstrated to enhance the growth performance, improve the meat quality, and boost the antioxidant status of HB goats, thus presenting a feasible strategy for optimizing tropical goat production systems. Full article

Grapevine (Vitis vinifera L.) cultivation is an important agricultural sector worldwide. Its expansion into new areas, like Kazakhstan, brings significant phytosanitary risks. Viroids, such as grapevine yellow speckle viroid 1 (GYSVd-1) and hop stunt viroid (HSVd), are RNA pathogens that threaten vineyard productivity. They can cause a progressive decline through latent infections. Traditional diagnostic methods are usually targeted and therefore not suitable for thorough surveillance. In contrast, modern high-throughput sequencing (HTS) methods often face challenges due to their high costs and complicated sample preparation, such as ribosomal RNA (rRNA) depletion. This study introduces a simplified diagnostic workflow that overcomes these barriers. We utilized the latest Oxford Nanopore V14 cDNA chemistry, which is designed to prevent internal priming, by substituting a targeted oligo(dT)VN priming strategy to facilitate the sequencing of non-polyadenylated viroids from total RNA extracts, completely bypassing the rRNA depletion step and use of random oligonucleotides for c DNA synthesis. This method effectively detects and identifies both GYSVd-1 and HSVd. This workflow significantly reduces the time, cost, and complexity of HTS-based diagnostics. It provides a powerful and scalable tool for establishing strong genomic surveillance and phytosanitary certification programs, which are essential for supporting the growing viticulture industry in Kazakhstan. Full article

To enable intelligent inspection of underground cable systems, this study presents a gecko-inspired quadruped robot that integrates multi-degree-of-freedom motion with a deep learning-based visual detection system. Inspired by the gecko’s flexible spine and leg structure, the robot exhibits strong adaptability to confined and uneven tunnel environments. The motion system is modeled using the standard Denavit–Hartenberg (D–H) method, with both forward and inverse kinematics derived analytically. A zero-impact foot trajectory is employed to achieve stable gait planning. For defect detection, the robot incorporates a binocular vision module and an enhanced YOLOv8 framework. The key improvements include a lightweight feature fusion structure (SlimNeck), a multidimensional coordinate attention (MCA) mechanism, and a refined MPDIoU loss function, which collectively improve the detection accuracy of subtle defects such as insulation aging, micro-cracks, and surface contamination. A variety of data augmentation techniques—such as brightness adjustment, Gaussian noise, and occlusion simulation—are applied to enhance robustness under complex lighting and environmental conditions. The experimental results validate the effectiveness of the proposed system in both kinematic control and vision-based defect recognition. This work demonstrates the potential of integrating bio-inspired mechanical design with intelligent visual perception to support practical, efficient cable inspection in confined underground environments. Full article