Search Results (1,453)

Kazakhstan is one of the world’s major wheat producers and exporters, playing an important role in regional and global food security. However, increasing quality requirements in domestic and export markets have exposed limitations in the country’s capacity to consistently supply high-quality spring bread wheat (Triticum aestivum L.). This review aims to assess the current status of spring wheat grain quality in Northern Kazakhstan, identify the main factors driving its variation, and outline pathways for quality improvement. The analysis is based on published literature, official statistics, national quality standards, and recent data on wheat production, grading, breeding systems, agronomic practices, and trade patterns. The review reveals that wheat production is dominated by medium-quality grain (primarily class 3), while high-quality classes suitable for premium and improver markets represent a small share. Compared with major exporters such as Canada, the United States, and Australia, Kazakh wheat is generally inferior across key quality parameters. Structural constraints include the limited integration of quality assessments within breeding programs, insufficient laboratory infrastructure, weak agroecological zoning by quality classes, and suboptimal agronomic management, particularly regarding nitrogen use. Environmental heterogeneity and climate change further influence the yield–quality balance. Overall, the findings suggest that improving wheat grain quality in Kazakhstan will require coordinated advances in breeding, agronomy, institutional capacity, and market alignment, enabling a gradual shift toward a more competitive, quality-oriented wheat production system. Full article

Background: Radiotherapy (RT) combined with androgen deprivation therapy (ADT) is a standard treatment for non-metastatic high-risk (HR) prostate cancer (PC). However, the benefit of elective nodal irradiation (ENI) in clinically node-negative (cN0) patients, although suggested, remains controversial, particularly in the elderly. We report the outcomes of elderly HR PC patients treated with prostate-only RT (PORT) and ADT in a “real-word” setting. Methods: Between 2016 and 2022, 43 consecutive elderly patients (median age 76 years) with HR- or very HR-PC according to NCCN criteria version 1.2026 (cN0, cT3-cT4 and/or ISUP Grade Group 4–5 and/or PSA serum levels at diagnosis ≥ 20 ng/mL) were treated at our institution. All patients were staged with abdominal MRI or CT and bone scan; nineteen patients (44.2%) also underwent 68Ga-PSMA-11 or 18F-fluorocholine PET/CT. All patients received PORT (predominantly moderate hypofractionation, 67.5–70 Gy in 25–28 fractions) and ADT (median duration 24 months). To ensure consistency, all oncological endpoints—Biochemical Failure-Free Survival (BFFS; Phoenix criteria), Disease-Free Survival (DFS), Metastasis-Free Survival (MFS), Prostate Cancer-Specific Survival (PCSS), and Overall Survival (OS)—were calculated from a unified time-zero (initiation of first oncological treatment). DFS was defined as a composite endpoint including biochemical failure, radiological recurrence, or initiation of salvage therapy. Results: at a median follow-up of 60 months, no patient reached the Phoenix threshold, resulting in a 100% 5- and 7-year BFFS. However, 4 patients (9.3%) experienced radiological recurrence detected via PET/CT before reaching the nadir + 2 threshold, yielding an estimated 5-year and 7-year DFS of 94.7% and 71.8%, respectively. The 5- and 7-year MFS was of 97.6% and 88.7%, respectively. Seven deaths occurred, all non-PC related, resulting in a 5-year OS of 86.7% and a Prostate Cancer-Specific Survival of 100%. Gastrointestinal toxicity was notably low (no acute or late G3-G4 events). Conclusions: Our findings suggest that PORT, when combined with long-term ADT and modern staging, provides excellent disease control and a favorable safety profile in elderly HR PC patients. Given the high rate of competing mortality in this population, treatment de-escalation via PORT appears to be a clinically reasonable strategy. These results are hypothesis-generating and warrant validation in prospective randomized trials. Full article

‘Mollar de Elche’ pomegranate is highly valued for its sweet flavor but faces significant commercial hurdles due to pale coloration and sensitivity to postharvest disorders. This study investigates the impact of preharvest foliar applications of L-α-amino acids, applied alone (AA) or combined with 2.5% sorbitol (Sor–AA), on secondary metabolism and physiological resilience, defined here as the fruit’s capacity to maintain metabolic homeostasis and stabilize antioxidant pigments during cold storage (7 °C). Our results show that both treatments triggered a substantial shift in secondary metabolism, doubling anthocyanin concentrations at harvest and effectively overcoming the cultivar’s color deficit. While the AA treatment maximized fruit quantity per tree, the Sor–AA combination achieved the highest total yield (83.58 ± 6.82 kg) and individual fruit weight (469.00 ± 16.00 g) through a ‘metabolic bypass’ that optimizes energy use. Crucially, the physiological resilience of the fruit was uniquely bolstered by the Sor–AA treatment, which was the only strategy to stabilize anthocyanin levels (~108 mg L⁻¹) and maximize free ellagic acid in the husk (371.72 mg kg⁻¹) throughout 42 days of storage. Multivariate PCA (explaining 79.79% of variance) confirmed that the synergy of amino acids and sorbitol triggers systemic metabolic reprogramming. Consequently, this targeted agronomic approach could provide significant economic benefits by increasing the proportion of export-grade fruit and extending the commercial window for the pomegranate sector. Full article

Diabetic retinopathy (DR) is the largest cause of permanent vision loss in the working-age population, making automated grading critical for timely therapeutic intervention. While recent deep learning algorithms have improved feature discrimination, modern state-of-the-art systems have two fundamental drawbacks. First, most models rely on standard Convolutional Neural Networks, which struggle to capture long-range relationships and lack semantic reasoning, resulting in visual findings that do not correlate with clinical knowledge. Second, present approaches often consider grading as a nominal classification or a pure ordinal regression task, failing to strike a compromise between high classification accuracy and severity-consistent predictions (Quadratic Weighted Kappa). To address these challenges, we propose Dual-SwinOrd, a novel framework that integrates a hierarchical Vision Transformer with a semantically guided dual-head mechanism. Specifically, we use a Swin Transformer backbone to extract hierarchical features, effectively capturing global retinal structures. To handle diverse lesion scales, we incorporate a Progressive Lesion-aware Kernel Attention (PLKA) module and a Semantic Prior Modulation (SPM) module guided by PubMedCLIP, bridging the gap between visual features and medical linguistic priors. In addition, we propose a Dual-Head learning strategy that decouples the optimization objective into two parallel streams: a Classification Head to maximize diagnostic accuracy and an Ordinal Regression Head (DPE) to enforce rank-consistency. This design effectively mitigates the trade-off between precision and ordinality. Extensive experiments on the APTOS 2019 and DDR datasets demonstrate that Dual-SwinOrd achieves state-of-the-art performance, yielding an Accuracy of 87.98% and a Quadratic Weighted Kappa (QWK) of 0.9370 on the APTOS 2019 dataset, as well as an Accuracy of 86.54% and a QWK of 0.9040 on the DDR dataset. Full article

Pegmatites with miarolitic cavities have not previously been reported from the Larsemann Hills, East Antarctica, and their age and origin remain poorly constrained. We report the first geochemical and geochronological data for fluorapatite from a newly discovered pegmatite with miarolitic cavities in the Larsemann Hills. Large Fe-rich fluorapatite crystals (up to 5 cm) contain abundant oriented monazite-(Ce) inclusions and display elevated REE (1397–7966 ppm), relatively high Y (945–4192 ppm), and low Sr (52.2–83.5 ppm). Their trace-element signatures plot within the fields of partial melts, high-grade metamorphic rocks, and evolved fluid-rich magmatic systems. U–Pb dating of fluorapatite yields concordant ages of 519 ± 4 Ma (ID-TIMS) and 521 ± 31 Ma (LA-ICP-MS), indicating crystallization during the D₄ stage of the Pan-African orogeny. The isotopic equilibrium between apatite and monazite inclusions suggests synchronous formation and late-stage fluid overprinting. Combined geological, geochemical, and isotopic evidence shows that the pegmatite formed in situ as a product of anatexis of the Broknes paragneisses and evolved within a volatile-rich magmatic–hydrothermal system. These results provide the first direct age constraints on pegmatites with miarolitic cavities in Antarctica and shed new light on the final stages of East Gondwana assembly. Full article

Speech enhancement through denoising is essential for maintaining signal intelligibility and quality in biometric speaker verification pipelines that operate in acoustically adverse conditions. Despite the proliferation of deep learning (DL) architectures for speech denoising, simultaneously optimizing noise attenuation, perceptual fidelity, and speaker-identity preservation remains an open problem. We address this gap by benchmarking three architecturally distinct DL-based enhancement models—Wave-U-Net, CMGAN, and U-Net—on three independent, domain-diverse corpora (SpEAR, VPQAD, and Clarkson) that the models never encountered during training and by introducing commercial-grade VeriSpeak speaker-verification scores as a biometric evaluation dimension absent from prior comparative studies. Our experiments reveal a clear three-way trade-off: U-Net achieves the highest signal-to-noise ratio (SNR) gains (+61.44% on SpEAR, +67.05% on VPQAD, +235.3% on Clarkson) but sacrifices naturalness; CMGAN yields the best perceptual evaluation of speech quality (PESQ) values (3.33, 1.35, and 2.50, respectively), favoring listening-comfort applications; and Wave-U-Net delivers the strongest biometric fidelity (VeriSpeak improvements of +11.63%, +30.22%, and +29.24%) while offering competitive perceptual quality. These results highlight that model selection must be driven by the target deployment scenario and provide actionable guidance for improving biometric verification robustness under real-world noise. Full article

Improving the energy efficiency of the building envelope is critical for global decarbonization, yet a gap remains in the comprehensive thermophysical characterization of carbon-enhanced Expanded Polystyrene (EPS). This study evaluates the impact of expansion ratios and moisture content on the thermal behavior of two commercial EPS grades, EPS-A (12.7 ± 0.5 kg/m³) and EPS-B (16.0 ± 1.1 kg/m³), investigating the counterintuitive role of graphite (1.4–1.8 wt.%) in enhancing the thermal insulation properties. Thermal conductivity and diffusivity were independently determined via Transient Plane Source (TPS) and Heat Flow Meter (HFM) methods across a 10–50 °C range, while specific heat capacity (c_p) was analyzed using HFM and Differential Scanning Calorimetry (DSC) through the sapphire comparison method and Temperature-Modulated DSC (TOPEM^®). Methodologically, it was found that standard HFM protocols are unsuitable for c_p determination in low-density foams, yielding an average relative error of ±29%; conversely, the sapphire comparison method provided the most reliable results in agreement with theoretical expectations. Results indicate that the efficacy of graphite as a radiative shield is closely coupled with cellular morphology, proving significantly more effective in the higher expansion grade (EPS-A, 70 wt.% open porosity) than in the denser EPS-B. Furthermore, 30-day water immersion tests revealed that the higher open porosity of EPS-A facilitates increased water uptake of 144 ± 17 wt.% (compared to 97 ± 7 wt.% for EPS-B), causing the geometric densities of the two grades to converge and fundamentally altering thermal transport mechanisms. The study concludes that accurate thermal modeling of carbon-enhanced insulation requires careful selection of testing parameters, particularly when accounting for moisture-induced degradation in high-porosity systems. Full article

Engagement is essential in informal learning contexts, as it fosters meaningful learning, personal relevance, and sustained motivation. However, engagement is a complex construct that requires diverse methodological approaches for accurate assessment. This study empirically examines a multi-method approach, combining questionnaires, log file analyses, and observations, in the context of a tablet-based educational program developed for an exhibition on mobility and traffic. A total of 307 tenth-grade students from 21 classes at twelve state high schools participated in self-regulated learning activities during the museum visit. Findings reveal that each method offers distinct insights: questionnaires capture students’ self-reported engagement, log files track behavioral patterns, and observations provide qualitative evidence of interaction quality. Each method provides valuable, specific insights into student engagement. Thus, integrating multiple approaches yields a more comprehensive understanding of engagement. These results underscore the importance of methodological pluralism and critical reflection when interpreting research findings from different methodological sources in informal learning environments. Full article

Accurate and non-destructive evaluation of grape quality is crucial for intelligent viticulture, yet most existing approaches address cultivar classification and soluble solid content (SSC) prediction as independent tasks based on single-modality data, limiting robustness and practical applicability. This study proposes DualStream-RTNet, a unified multimodal deep learning framework that simultaneously performs grape cultivar classification and SSC prediction by integrating RGB-HSV fused images and PCA-compressed hyperspectral spectra. The dual-stream architecture enables the complementary learning of external chromatic–textural cues and internal physicochemical information, while a Transformer-enhanced fusion module strengthens global representation and cross-modal correlation. A dataset of 864 berries from five grape cultivars was used to validate the model. DualStream-RTNet achieved 93.64% classification accuracy, outperforming ResNet18 and other CNN baselines, and produced more compact and consistent confusion-matrix patterns. For SSC prediction, it consistently yielded the highest performance across cultivars, with R2p values up to 0.9693 and RMSE as low as 0.2567, surpassing the PLSR, SVR, LSTM, and Transformer regression models. These results demonstrate the superiority of the proposed framework in capturing both visual and spectral characteristics. DualStream-RTNet provides an efficient and scalable solution for comprehensive grape quality assessment, offering strong potential for real-time sorting, precision grading, and smart agricultural applications. Full article

Research using latent profile analysis (LPA) has yielded inconsistent results regarding the number of personality profiles among athletes, the specific configuration of the Big Five traits, and their interpretation. This study seeks to explore personality types by excluding additional variables from the LPA model, aiming to assess how well personality profiles are universal (independent of gender and cultural context) and can predict academic achievement in student athletes. A cross-sectional study was conducted using a paper-and-pencil questionnaire among 424 student athletes from two universities in Poland and Ukraine. The average age of participants was 20 years old (M = 20.01; SD = 2.48), 62% were male, 53% lived in Poland, and 58% studied Sports Sciences vs. 42% Physical Education. The Mini-International Personality Item Pool (Mini-IPIP) was used to assess the Big Five personality traits, and grade point average (GPA) was used to measure students’ academic achievements in the last semester. The LPA identified four personality profiles: (1) Restrained Neurotic (Profile 1, 32%), Open Extravert (Profile 2, 42%), Competitive Neurotic (Profile 3, 17%), and Cooperative Perfectionist (Profile 4, 8%). Profiles 1, 3, and 4 showed similarly low levels of emotional stability, extraversion, and intellect but differed significantly in agreeableness and conscientiousness. Gender and country differences across athletes representing specific profiles were also noted. Profile 2 showed the strongest link with academic achievement. Hierarchical multiple linear regression showed that LPA profiles explained only 2% of GPA variance, compared to Big Five personality traits (9%) and demographic variables, such as sex, country, and study major (8%), which were also included in the following steps in the regression model, explaining only 9% and 8%, respectively. Most student athletes (52%) with personality profiles 1 (Restrained Neurotic), 3 (Competitive Neurotic), and 4 (Cooperative Perfectionist) may require psychological training to better cope with negative emotions and stress arising in competitive and academic settings. Profile 2 (Open Extravert) seems to be the most adaptive and potentially successful personality type. Personality types are, at least to some extent, related to gender and country of residence. More cross-cultural research is required to further verify the types of athletic personalities. Full article

Background/Objectives: Retrospective analysis of the safety of contrast-enhanced ultrasound in children. Methods: A retrospective analysis was conducted on children who underwent contrast-enhanced ultrasound (CEUS) examinations at the Children’s Hospital of Chongqing Medical University from 2019 to 2025. Adverse reactions were classified into three grades (mild, moderate, and severe) based on severity. Following the pharmacological classification, the types of adverse reactions are divided into “Type A reactions” and “Type B reactions” and further classified into immediate and delayed reactions according to the timing of occurrence. Results: This study included 1604 pediatric patients who underwent a total of 1924 intravenous CEUS examinations. Seven patients experienced adverse reactions, yielding an overall adverse reaction incidence rate of 0.436% (95% Confidence Interval: 0.18–0.90%). Among these, six reactions were mild (6/7, 85.71%), and one was moderate (1/7, 14.29%). Among the seven patients, 16 clinical manifestations were recorded, comprising 12 type B reactions (12/16, 75%) and 4 type A reactions (4/16, 25%). Furthermore, all adverse reactions were classified as immediate onset. Conclusions: Under the conditions of this study, CEUS demonstrated good safety in the pediatric population, with no serious adverse events observed. Full article

Structural optimization of the cathode flow field is a viable approach to homogenize multi-physical field distributions and boost the output of air-cooled proton exchange membrane fuel cells (PEMFCs). This work develops a three-dimensional non-isothermal model to systematically evaluate the performance of graded flow channel designs. The results indicate that the graded structure promotes fluid transport in the central zone, thereby improving oxygen distribution uniformity at the gas diffusion layer/catalyst layer (GDL/CL) interface. Compared to the traditional parallel flow channel (with an average oxygen mass fraction of 0.051% and a uniformity index of 0.779), this configuration yields a 6.4% increase in the average oxygen mass fraction and a 0.96% enhancement in distribution uniformity. However, increased gradient flow reduces the flow velocity within the channels and raises the operating temperature, posing challenges for water and thermal management. The curved channel design, featuring longer channels at the ends and shorter channels in the center, compensates for the uneven air supply caused by the fan, thus balancing the flow distribution. Among the tested configurations, the 10° curved structure exhibits optimal performance, achieving the best compromise between gas distribution and liquid water removal. It effectively promotes oxygen diffusion and uniform water distribution, significantly alleviating mass transfer polarization and yielding a more uniform interface temperature distribution due to evaporative cooling. Both excessively small and large curvature angles lead to performance degradation, primarily due to inadequate water removal and flow separation, accompanied by excessive pressure drop, respectively. In contrast, the 10° curved channel strikes an optimal balance, offering significant advantages in overall cell performance and water–thermal management, which provides critical guidance for optimizing PEMFC flow field designs. Full article

Diet is a key modulator of the gut microbiota, thereby influencing host physiology. Microbial colonization begins early in life, influenced by maternal sources, mode of birth, diet, and environmental exposures, and stabilizes into an adult-like microbiome during early childhood. This maturation yields a microbial ecosystem dominated by Firmicutes and Bacteroidetes that contributes to host physiological homeostasis. Gut microorganisms function as an integrated metabolic system that transforms dietary substrates into bioactive metabolites, including short-chain fatty acids (SCFAs), amino acid-derived compounds, and microbial lipids. These metabolites regulate glucose and lipid metabolism, intestinal barrier integrity, and immune modulation. Although many metabolic functions are conserved, their activity is shaped by diet, microbial cross-feeding, and local intestinal conditions, enabling functional specialization within the gut. Disruption of this system, known as dysbiosis, is associated with alterations in microbial diversity and metabolic output that have been linked to metabolic diseases, including obesity and related disorders. Evidence from experimental models and observational studies suggests that these associations may involve interconnected inflammatory and metabolic mechanisms, such as impaired intestinal barrier function, low-grade inflammation, and altered dietary energy harvest; however, causal relationships in humans remain incompletely understood. Beyond peripheral effects, the gut microbiome influences host metabolism via the gut–brain axis, a bidirectional network that integrates neural, endocrine, immune, and metabolic signaling. Microbiota-derived metabolites and gut hormone modulation contribute to appetite regulation, energy balance, and glucose homeostasis, while central neuroendocrine signaling can reciprocally shape the intestinal microbial niche. Collectively, these findings highlight the gut microbiome as a central regulator of host metabolism, whose disruption may contribute to the development of metabolic disease. Full article

The steel frame-shear wall composite system has excellent lateral resistance performance in prefabricated steel structure buildings. However, the traditional steel plate concrete shear wall is prone to early buckling of the steel plate and concentrated interface damage under cyclic loading, which limits its energy dissipation capacity. This study presents a steel plate-enhanced reinforced concrete shear wall (SPRCSW) with an internal corrugated steel plate and double-layer steel mesh working together and conducts a selection study based on finite element analysis. Under the same design conditions, the peak bearing capacity in the positive and reverse directions of the SPRCSW is increased by approximately 55.4% and 46.9%, respectively, compared to the ordinary reinforced concrete shear wall, with a ductility coefficient reaching 6.08. The stiffness decline is mild, and the hysteretic curve is complete. Then, this paper forms an SR-SPRCSW composite structural system by combining the new shear wall with a steel frame using semi-rigid joints. Through the comparison of the finite element analysis and low-cycle reverse loading test results of the SR-SPRCSW structure, it is verified that the overall structural system shows good agreement in hysteretic response, skeleton curve characteristics, and failure mode under both research methods, with the peak shear bearing capacity error of less than 1% and the overall bearing capacity deviation controlled within 8%. On this basis, the key parameters of the semi-rigid joints in the SR-SPRCSW structure are analyzed. The results show that the strengthening of the “top and bottom + double web” angle steel joint can raise the peak bearing capacity of the SR-SPRCSW structure by approximately 26.1% and the yield displacement by approximately 29.5%; increasing the strength grade and diameter of high-strength bolts can heighten the initial stiffness and bearing capacity of the overall structure, but ductility slightly decreases; the thickness of the angle steel has a significant impact on the stiffness and deformation capacity of the structure, and a recommended range of values with better comprehensive performance is provided. The findings offer valuable insights for designing seismic-resistant semi-rigid steel frames with steel plate reinforced concrete shear walls and optimizing their parameters. Full article

This study investigates the interplay between Portland cement strength class (32.5, 42.5, and 52.5) and fiber/cement ratio (ranging from 1/2 to 1/5 by weight) to optimize the physical-mechanical and thermal performance of cement-bonded fiberboards. The experimental data revealed a distinct trade-off: while reducing the fiber content towards a 1/5 ratio significantly improved flexural strength and dimensional stability through matrix densification, it inevitably compromised thermal insulation. Among the binders evaluated, the 42.5 strength class emerged as the most effective option, outperforming the 32.5 class and, notably, offering a more balanced profile than the 52.5 class. The highest stiffness was recorded with the 42.5 cement at a 1/5 ratio (modulus of elasticity (MOE): 5902 ± 532 N/mm²; modulus of rupture (MOR): 12.49 ± 0.6 N/mm²), yielding performance metrics comparable to the 1/4 ratio (MOR: 12.78 N/mm²). Furthermore, this formulation demonstrated superior moisture resistance, achieving water absorption (WA) values as low as 18.9%. Thermal conductivity (TC) measurements at 20 °C confirmed that while fiber-rich mixtures (1/2 ratio) favored insulation, the 42.5 cement at a 1/4 ratio maintained a competitive conductivity value (λ = 0.1625 W/mK), lower than that of the 52.5 grade, thereby striking a critical balance between structural integrity and thermal efficiency. Statistical analyses (Two-way ANOVA, p < 0.05) corroborated the significant influence of both cement type and mix ratio. Microstructural insights from Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) suggest that the superior performance of the 42.5 cement is associated with optimized hydration kinetics and a well-graded particle size distribution (D50 = 14.80 µm), which together facilitated effective fiber encapsulation. Full article