Search Results (4,664)

A low-cost, high-robust, high-gain preamplifier is fabricated in a 65 nm CMOS for Hall sensors. A semi-open loop that combines an optimized differential–difference amplifier with a simplified open-loop amplifier is proposed to achieve stringent transconductance matching, with the same DC and AC conditions. A two-stage reconfigurable structure, together with an embedded offset-accumulation elimination scheme, relieves open-loop stress and achieves both high fidelity and accurate gain. The experimental results show that the preamplifier has a variable gain of 34.6–46.6 dB and a gain error no more than 0.12% under process/voltage/temperature variations and without error calibration, at the cost of an active area of 0.076 mm² and a current dissipation of 0.7 mA under a 2.5–3.3 V supply. Specifically, both the loop topology and the transconductance match are different from the existing works. Full article

This study investigates the 55%Al-Zn-Si coating system. Using microstructural characterization and thermodynamic simulation, we systematically analyzed its microstructure formation, solidification behavior, and the regulatory effects of Cr, Nb, and V micro-alloying elements. The results show that the typical coating consists of a primary α-Al dendritic skeleton and an interdendritic Zn-rich eutectic phase, exhibiting a characteristic spangle morphology. The addition of Si is crucial. By participating in the formation of a Fe-Al-Si ternary compound layer, it effectively suppresses the intense reaction at the Fe/Al interface, providing essential conditions for the sufficient growth of the outer Al-rich dendrites and the formation of a continuous transition layer. Thermodynamic analysis further clarifies that the coating solidification follows three distinct stages: precipitation of the primary α-Al phase, an Al-Si binary eutectic reaction, and a final Al-Zn-Si ternary eutectic transformation. Regarding micro-alloying, this study reveals the specific roles of different elements: Cr significantly refines the transition layer structure, promoting its transformation from coarse lamellae into a fine and uniform morphology; V tends to combine with Al to form high-melting-point enriched regions, inhibiting the growth of Fe-Al intermetallics and reducing the thickness of the brittle transition layer by approximately 50%; conversely, the addition of Nb disrupts the normal solidification sequence, inducing abnormal segregation of Al-rich and Si-rich phases, which compromises the homogeneity and integrity of the coating structure. Through an in-depth analysis of the fundamental solidification mechanism and micro-alloying effects, this research provides an important theoretical basis for optimizing the microstructure of hot-dip Al-Zn sheets via precise composition design and micro-alloying strategies. Full article

The ambient stability of ambient-processed lead-free perovskite absorbers remains a critical challenge toward scalable, eco-friendly photovoltaics. Herein, we systematically investigate the time-dependent structural and morphological evolution of drop-cast ambient-processed Cs₃Sb₂I₉ thin films, being a potential non-toxic and stable solar absorber candidate (energy bandgap ~2 eV) for solar cells, stored under uncontrolled ambient condition (~60% Relative humidity) for 28 days. Sequential X-ray diffraction (XRD) and surface morphology analyses using scanning electron microscope (SEM) reveal that the films preserve their trigonal P3̅m1 phase throughout aging, confirming phase stability. Moderate moisture exposure may induce partial recrystallization and subtle structural reorganization, possibly including minor c-axis realignment, leading to reduced lattice strain and improved crystallite coherence. Even after prolonged aging, no secondary phases or micro-cracks are detected, underscoring the slow degradation kinetics and robust Sb–I bonding that stabilize the layered [Sb₂I₉]³⁻ dimers. The late-stage increase in diffraction intensity and partial recovery of crystallographic parameters could indicate transient structural reorganization, potentially associated with moisture-mediated reordering within an overall degradation pathway. These observations suggest some degree of morphological persistence and structural tolerance of Cs₃Sb₂I₉ under ambient conditions, rather than complete stability. This behavior offers useful insights into ambient processing and the long-term reliability of lead-free perovskite photovoltaics. Full article

Women’s advancement into leadership roles remains uneven in many post-socialist labor markets despite high levels of female education and workforce participation. While prior research has emphasized structural barriers and national institutional conditions, less is known about how firm-level organizational environments shape women’s evaluations of leadership as a viable career pathway. This study aims to examine how firm type shapes women’s managerial aspirations across career stages in post-socialist Mongolia. Using cross-sectional survey data from 191 employed women in Ulaanbaatar, aspiration patterns were compared across three organizational contexts: foreign-owned firms, domestic private firms, and public-sector organizations. Career aspirations were operationalized as three states—high aspiration, constrained aspiration, and low aspiration—to capture differences between leadership motivation and perceived feasibility. Pearson’s chi-square tests and Cramér’s V were used to assess associations between firm type, career stage, and aspiration categories. The results show that women in foreign-owned firms are more likely to sustain leadership aspirations, whereas constrained and low aspirations are more prevalent in domestic private firms and the public sector, particularly at mid-career stages. These findings suggest that leadership aspirations reflect organizationally shaped feasibility assessments rather than individual motivation alone, and that firm type operates as a critical meso-level opportunity structure within shared post-socialist institutional conditions. Full article

Colletotrichum species are among the most destructive phytopathogens worldwide, with appressorium-mediated penetration representing a critical stage in host infection. Targeting this morphogenetic transition offers a promising strategy for sustainable disease control by interfering with the infection process rather than solely inhibiting fungal growth. In this study, chitosan–κ-carrageenan nanoparticles (CS–κ-CRG) without and with lysozyme (CS–κ-CRG/Lz) were synthesized, characterized, and evaluated for their ability to inhibit appressorium formation in Colletotrichum siamense, a strain exhibiting low sensitivity to chitosan. The nanoparticles showed monodisperse size distributions, with hydrodynamic diameters of 503 and 333 nm for CS–κ-CRG and CS–κ-CRG/Lz, respectively, positive surface charges of approximately +26 mV, spherical morphology, and a lysozyme encapsulation efficiency of 63%. Both formulations significantly reduced conidial viability and delayed germination, inducing morphological alterations such as conidial swelling, hyphal deformation, and vacuolization. Fluorescence microscopy using calcofluor white and propidium iodide revealed disturbances in cell wall organization and loss of membrane integrity. Both nanomaterials markedly affected appressorium development in a concentration- and formulation-dependent manner. Notably, CS–κ-CRG/Lz showed stronger suppression of appressorium formation, whereas at 200 µg·mL⁻¹, CS–κ-CRG nanoparticles stimulated appressorium formation, suggesting that sublethal nanoparticle stress may trigger compensatory or hyper-pathogenic responses. These findings highlight the potential and complexity of utilizing chitosan-based nanomaterials for phytopathogen management and emphasize the importance of mechanistic and dose–response evaluations before field application. Full article

SARS-CoV-2, the causative agent of COVID-19, emerged in late 2019 and rapidly developed into a global health crisis. In this study, we analysed 173,194 SARS-CoV-2 genomes from the GISAID database to explore the intra-continental dynamics and distribution of variants across Africa between 2020 and 2024. We have identified 1377 distinct lineages, which were classified by clade to assess associations with infection and mortality rate. So, we conducted a Shannon entropy analysis to confirm the diversity and we applied a Correspondence Analysis (CA). Our findings revealed that one of the deadliest in Africa during the Delta wave, lineage AY.45 predominated in the South Africa cluster, whereas AY.34.1 drove transmission in the Atlantic West Africa cluster, underscoring regional heterogeneity. Furthermore, early in the pandemic, men exhibited a 39% higher risk of infection compared to women (aOR: 1.39, 95% CI [1.34–1.45]), particularly in association with clade G. By contrast, later stages were dominated by clade GRA, which disproportionately affected the elderly (≥70 years; aOR: 1.39, 95% CI [1.33–1.45]) and children (0–9 years; aOR: 1.26, 95% CI [1.20–1.33]). Our analysis highlighted that the pandemic on the African continent unfolded as a mosaic of epidemics shaped by diverse variants and regional epidemiological contexts. These findings emphasize the importance of genomic surveillance to capture local epidemic signatures and inform region-specific public health strategies. Full article

Accurate and efficient classification of hematological malignancies from peripheral blood smear (PBS) images remains challenging due to the scarcity of annotated datasets, staining variability, and subtle morphological differences among blood cancer subtypes. To address these limitations, this study proposes an Advanced Lightweight Deep Learning (ALDL) framework for the multi-class classification of Acute Lymphoblastic Leukemia (ALL) across four clinically significant stages: Benign, Pro-B, Pre-B, and Early Pre-B. The framework integrates EfficientNetV2-S with Convolutional Block Attention Modules (CBAM) to enhance spatial and channel-wise feature refinement. At the same time, Focal Loss is employed to mitigate class imbalance by prioritizing hard-to-classify samples. A robust preprocessing pipeline, including CLAHE contrast enhancement, Reinhard stain normalization, and data augmentation, improves feature visibility and dataset generalization. Lesion segmentation is performed using RGB-based thresholding and watershed overlay, followed by lesion-level cropping to ensure consistency across inputs. Experimental evaluations on the ALL-DB dataset demonstrate the superior performance of the proposed method, achieving an average accuracy of 96.11%, an F1-score of 95.99%, and an AUC of 0.9875. Comparative analyses against MobileNetV3, ResNet50, DenseNet121, VGG16, and InceptionV3 confirm that the proposed segmentation-guided EfficientNetV2-S + CBAM + Focal Loss framework consistently outperforms conventional CNN architectures across both 70:30 and 60:40 train–test splits. Furthermore, a detailed investigation of color spaces (RGB, HSV, LAB, and HED) indicates that RGB yields the most reliable segmentation and classification results. At the same time, HED enhances lesion visualization at the expense of higher computational cost. The proposed ALDL framework demonstrates strong potential for real-world application as a computer-aided diagnostic (CAD) system for early leukemia detection, offering improved diagnostic reliability, reduced error rates, and practical scalability for clinical environments. Full article

Silicon carbide (SiC) MOSFETs are promising for high-efficiency, high-power-density power conversion owing to their high breakdown capability, fast switching speeds, and low switching losses. However, parasitic parameters can cause severe voltage/current overshoot and oscillation during high-speed switching, leading to electromagnetic interference and degraded performance. To address this issue, this study analyzes the mechanisms of current overshoot during turn-on and voltage overshoot during turn-off, and presents an adaptive active gate driver chip based on a three-stage driving current control strategy. By identifying key switching intervals and regulating segmented gate-drive current, the proposed chip can effectively suppress overshoot while reducing the switching loss. During turn-on, cross-cycle switching point regulation based on Miller plateau tracking is proposed to achieve adaptive control under different operating conditions, while the turn-off control is realized by peak sampling of the drain–source voltage. The chip was fabricated in the 180 nm BCD process. Compared with a conventional passive driver, the proposed driver reduces turn-on loss by 35.1% at 400 V/40 A under a dv_DS/dt of 4.8 V/ns and reduces turn-off loss by 33.2% under a v_DS overshoot of nearly 50 V. These results show that the proposed chip improves SiC MOSFET switching performance and provides a practical gate-driving solution. Full article

Background: Weight loss and skeletal muscle wasting are frequent in cancer and may influence treatment tolerance and outcomes. Computed tomography (CT) based body composition analysis at the third lumbar vertebra (L3) is an accurate method to quantify skeletal muscle in routine oncology care. Methods: We performed a multicenter retrospective cohort study including 202 adults with locally advanced (stage IB–III) gastric cancer treated in four Portuguese hospitals (January 2020–December 2022). Skeletal muscle area (SMA) was assessed on baseline CT at the L3 vertebral level, using Data Analysis Facilitation Suite (DAFS) software v3.11.2, and skeletal muscle index (SMI) was subsequently calculated. Patients with low muscle quantity were classified as sarcopenic (below sex-specific SMI mean). We evaluated associations with relapse-free survival (RFS), overall survival (OS), FLOT chemotherapy dose-limiting toxicities (DLTs), and postoperative complications after gastrectomy. Results: Mean age was 69 years, 65% had ECOG PS 0, 53% received FLOT chemotherapy protocol. Mean SMI was 49.6 cm²/m² in males and 40.9 cm²/m² in females and correlated positively, though moderately, with BMI (p < 0.01; r = 0.424). Sarcopenia was not significantly associated with RFS (p = 0.186) or OS (p = 0.168) at 30-month follow-up. Although numerical differences were observed (64% vs. 56% of patients did not relapse and 74% vs. 63% were alive, for non-sarcopenic vs. sarcopenic patients). Sarcopenia was associated with a higher risk of DLTs (p = 0.021; OR 2.56, 95% CI 1.15–5.73) and postoperative complications (p = 0.024; OR 2.16, 95% CI 1.11–4.21). Conclusions: Sarcopenia significantly increases the risk of chemotherapy toxicity and postoperative complications in locally advanced gastric cancer. However, its effect on OS and RFS was not statistically significant at 30-month follow-up. Standardization of CT-based sarcopenia cut-offs remains a major barrier to clinical implementation. Full article

The global poultry hatching industry faces severe challenges of resource waste and animal ethics issues due to the routine culling of day-old male chicks. Meanwhile, early sex identification of 4-day-incubated chicken embryos is limited by low accuracy, as embryos at this stage have weak, low-contrast blood vessels that are highly susceptible to interference from the eggshell’s texture. To address these issues, this paper proposes a non-destructive early sex identification method for chicken embryos based on an improved MobileViT-V3 model. Taking the lightweight hybrid architecture MobileViT-V3 as the backbone, we embedded a Micro Feature Enhancement module (MFE-Module) in Stage 3 to strengthen the extraction of fine vascular details, and a Multi-Scale Adaptive Attention Fusion module (MSAAF-Module) in Stage 4 to realize adaptive weighted screening of multi-source features. Experiments on the self-constructed dataset of 4-day-incubated embryos show that the improved model achieves a test set classification accuracy of 92.26%, with an F1-score of 92.15%, a recall rate of 92.12%, and a Kappa coefficient of 0.845. It outperforms mainstream models such as YOLOv12, ShuffleNetV2, ConvNeXt-T, ResNet, and Swin-ViT, with only 2.98 M parameters and an inference speed of 97.6 FPS, well exceeding the 30 FPS real-time requirement of industrial sorting lines and showing high potential for practical industrial deployment. This method provides a new scheme for non-destructive, high-precision, and high-efficiency early sex identification in poultry hatching. Full article

Stone coal is an important vanadium-bearing resource and a potential source of rare earth elements (REEs). Previous studies have mainly focused on the bulk occurrence, resource potential, and leaching behavior of V or REEs in stone coal, whereas the microscale spatial relationships between V and REEs and their evolution during leaching remain poorly constrained. In this study, three representative stone coal samples were analyzed by synchrotron radiation micro-X-ray fluorescence (μXRF) to characterize the microscale distributions of V and REEs in raw samples and corresponding leaching residues. Pearson correlation analysis was further used to quantify changes in V–REE spatial relationships during leaching. The results showed that V–REE relationships were generally weak and were modified to different extents after leaching. In the GZ sample, the V–Eu correlation coefficient decreased from 0.63 to 0.34, indicating that the migration of V and REEs was not fully synchronized. The three samples also showed different REE distribution tendencies after leaching: GZ showed partial transfer of REEs to the leachate with residual retention, PX showed mixed behavior with appreciable retention in the residue, whereas PZ retained REEs predominantly in the residue. These results suggest that the integrated utilization of V and REEs in stone coal can be better achieved through a staged recovery route, in which the REE recovery pathway is determined according to their actual distribution between the leachate and the residue after V leaching. This study provides a microscale basis for the comprehensive utilization of coal-related critical metal resources. Full article

The increasing demand for platinum group metals (PGMs) and critical base metals (BMs) underscores the critical roles these metals play in renewable energy and advanced technologies, enabling more efficient, environmentally sustainable operations. A hydrometallurgical approach to Au, Pd, and Pt tailings, derived from the glycine leaching of low-grade nickel and iron sulfide flotation concentrates, is investigated. The proposed process evaluates two glycine-based systems: glycine combined with KMnO₄ and catalyzed by cyanide under starvation conditions. Leaching with glycine in the presence of KMnO₄ (72 h, 25% solids, 60 °C, pH 11, dissolved oxygen 10 ppm, 126.7 kg/t glycine, and 7 kg/t KMnO₄) achieved extraction efficiencies of up to 66.7% Au, 89.1% Pd, and 95.8% Pt. In comparison, the cyanide-starved glycine system (72 h, 30% solids, 60 °C, pH 11, dissolved oxygen 20 ppm, 98.5 kg/t glycine, and 3.3 kg/t cyanide) resulted in up to 80.8% Au, 78.3% Pd, and 14.3% Pt. Activated carbon and Amberlite resin demonstrated selective adsorption of Au and PGMs. For activated carbon, Au adsorption exhibited a non-linear dependence on carbon dosage, reaching a maximum of 77.61% at 20 g/L, then decreasing to 50.85% at 25 g/L, and finally increasing to 65.04% at 30 g/L, indicating variable adsorption behavior. In contrast, Amberlite resin exhibited more consistent, progressive adsorption with increasing dosage. Au adsorption remained high across all conditions, increasing from 88.06% at 10 g/L to 99.67% at 30 g/L. Similarly, Pd and Pt adsorption improved significantly with resin dosage, reaching maximum values of 81.32% and 83.36% at 25 g/L, respectively, followed by a slight decline at 30 g/L. Implementing a two-stage process using carbon + resin (30 g/L) increased PGM recovery, achieving 99.89% Au, 81.8% Pd, and 92.4% Pt. Elution tests showed that Au (61.97%) and Pd (60.55%) were desorbed efficiently using thiourea (2% w/v) and HCl (0.5 M), whereas Pt elution proved difficult and required alternative strategies. The findings confirm glycine-based technologies as a promising, environmentally friendly alternative to conventional methods and provide a basis for further process development and optimization. Full article

Background: Thymic epithelial tumors (TETs) are rare neoplasms of the anterior mediastinum, ranging from indolent thymomas to aggressive thymic carcinomas. Increasing evidence suggests that genetic alterations contribute to their pathogenesis and biological behavior. GTF2I, TP53, and NOTCH1 are particularly interesting among the potential genes due to their central roles in transcriptional regulation, cell-cycle control, and oncogenic signaling. Methods: In this study, 150 TET samples from Vietnamese patients were classified according to WHO guidelines and the Masaoka–Koga staging system. Genotyping was conducted on 139 high-quality samples using Sanger sequencing targeting exon 15 of GTF2I, exon 7 of TP53, and exon 34 of NOTCH1. The potential impact of these variants was predicted using the in silico MutationTaster2025 and CADD v1.7 tools. Statistical analyses were also conducted to assess associations between variants and tumor subtypes. Results: Our study identified a total of 17 variants across GTF2I, TP53, and NOTCH1, in which the c.1271T>A variant in the GTF2I hotspot, predicted to be deleterious, was identified in 14.1% of indolent thymomas and showed a significant association with this subtype group (odds ratio: 0.048, adjusted p-value = 0.014). In contrast, previously unreported variants in TP53 (c.772G>A) and NOTCH1 (c.7546T>G) were also computationally predicted to be deleterious and were significantly enriched in aggressive subtypes, with ORs of 15.1 (adjusted p-value = 0.01) and 18.4 (adjusted p-value = 0.026), respectively. Conclusion: These hypothesis-generating findings suggest that variations in GTF2I, TP53, and NOTCH1 may serve as candidate molecular markers for distinguishing thymoma subtypes and assessing patient risk. To date, this is the first targeted hotspot screening study of GTF2I, TP53, and NOTCH1 variants in TETs within the Vietnamese population. Full article

Studying zooplankton in freshwater ecosystems is crucial for ecological research, providing insight into ecosystem health, biodiversity, and water quality. This study focuses on developing a hybrid approach for studying and analyzing zooplankton communities using machine learning and human expert analysis. The goal of the study was to automate the labor-intensive process of zooplankton analysis as part of a long-term Lake Baikal monitoring program (since 1945), while maintaining continuity with traditional methods. A software and algorithmic system were developed to automate the analysis: images were processed using a two-stage pipeline (object detection using YOLO V11, classification using metric learning and visual transformers), and complex cases and new species were sent to specialists for verification. Over 240,000 images from 811 samples were processed, and models are updated using verified data to adapt to seasonal changes. An updatable database of labeled zooplankton images suitable for statistical analysis and research has been created. A comparison of manual and machine analysis revealed no significant differences in species composition, with accurate detection in 87% of images. This approach allows for scalable monitoring and the accumulation of labeled data arrays for the development of computer vision methods and the assessment of the state of Lake Baikal’s ecosystem. Full article

Background/Objectives: Vascular calcification and arterial stiffness are common in chronic kidney disease (CKD). Gla-rich protein (GRP) is a vitamin K-dependent protein implicated in mineral biology, but clinical evidence across CKD stages is limited. We evaluated associations of serum GRP with vascular calcification (VC) burden and arterial stiffness across CKD stages, including hemodialysis, compared with controls. Methods: In this prospective observational study, 185 adults were enrolled: controls (n = 61), individuals with CKD stage IIIb–IV (n = 61), and individuals with CKD stage V on hemodialysis (HD) (n = 63). Abdominal aortic calcification was assessed by the Kauppila score, and arterial stiffness was assessed by oscillometric pulse wave velocity (PWV). Serum GRP, FGF-23, and β-Klotho (KLb) were measured by ELISA. Non-parametric group comparisons and Bonferroni-corrected Spearman correlations were used. Results: GRP differed across groups (p < 0.001), showing a non-linear pattern with the lowest values in CKD IIIb–IV. PWV and Kauppila score increased across CKD stages (both p < 0.001). After Bonferroni correction, GRP correlated with KLb (ρ = 0.720) and FGF-23 (ρ = 0.625), but not with PWV or Kauppila score. In multivariable analyses, GRP showed a statistically significant but modest association with PWV and Kauppila score. Conclusions: In this CKD spectrum cohort, serum GRP was associated with CKD-MBD biochemical markers (KLb and FGF-23) much more strongly than with vascular phenotypes; its associations with vascular calcification burden and arterial stiffness were modest in multivariable modelling, supporting GRP as a marker of the CKD-MBD biochemical profile rather than a strong surrogate of vascular phenotype. Full article