Search Results (1,393)

Rolling bearing fault diagnosis under complex and noisy operating conditions requires not only high diagnostic accuracy but also interpretability that can be quantitatively verified against physically meaningful excitation structures. However, many existing deep learning approaches rely on a single time–frequency (TF) representation and provide limited, non-verifiable links between model decisions and the original vibration patterns. To address this issue, we propose MBT-XAI, a multi-wavelet TF fusion network with a Token-to-Spectrum Traceback (TST) mechanism for structure-preserving, physics-consistent interpretability. Three complementary wavelets, namely Morlet, Mexican Hat, and Complex Morlet, are used to construct multi-view TF representations, which are encoded into RGB channels and adaptively fused via cross-channel attention within a Transformer backbone. TST maps patch-token attributions back to the TF domain, enabling quantitative evaluation of physics consistency through overlap-based metrics. Experiments on the public CWRU dataset and an industrial IMUST dataset show that MBT-XAI achieves 98.13 ± 0.24% and 96.23 ± 0.31% accuracy at SNR = 0 dB, outperforming the strongest baseline by 2.83% and 2.43%, respectively. Under AWGN contamination, MBT-XAI maintains 95.44 ± 0.38%/93.45 ± 0.47% accuracy on CWRU and 95.80 ± 0.33%/92.91 ± 0.51% accuracy on IMUST at SNR = −2/−4 dB. Under colored-noise contamination, the proposed method also preserves robust performance under pink and brown noise at the same SNR levels. Quantitative interpretability evaluation further indicates high alignment between salient frequency regions and theoretical fault-characteristic bands, with IoU = 80.21 ± 0.86% and Coverage = 91.70 ± 0.63%. In addition, MBT-XAI requires 10.393 M parameters and 10.678 GFLOPs, with an inference latency of 14.7 ms per sample (batch size = 1) on an NVIDIA GeForce RTX 3060 GPU. These results suggest that multi-wavelet TF modeling with attention-based fusion and TF-level traceback provides an accurate, robust, and physics-consistent framework for intelligent bearing fault diagnosis. Full article

Recent advances in ear biometrics have yielded increasingly accurate detection and recognition methods, driven by the ear’s uniqueness and permanence as a non-invasive biometric modality. Nonetheless, several limitations persist, including computationally demanding models, inconsistent evaluation metrics, and portable systems restricted by manual capture and limited datasets. To address these challenges, we developed a lightweight, video-based ear biometric system implemented on the Raspberry Pi 5. The system integrates You Only Look Once Version 12 (YOLOv12) for ear detection, EfficientNet-4 for feature extraction, and k-Nearest Neighbors (k-NNs) for recognition. Its robust hardware platform combines Raspberry Pi 5 with the Raspberry Pi AI Camera and AI HAT+. To train, fine-tune, and optimize YOLOv12 and EfficientNet-4, we used the Visual Geometry Group (VGG)Face-Ear dataset for training and the Unconstrained Ear Recognition Challenge 2019 dataset for validation, with k-NN employed for classification. The system is evaluated for classification accuracy and system-level performance. 13 participants, comprising 10 enrolled and three unenrolled subjects, participated in testing the system. The enrolled participants registered in the system were correctly identified, whereas unenrolled participants were excluded and rejected. The system achieved 92.31% accuracy, 95.45% precision, 96.97% recall, and an F1-score of 0.95, confirming the feasibility of deploying advanced ear biometric methods on embedded, resource-constrained devices. Full article

Low-orbit thermal infrared bidirectional whisk-broom imaging offers wide-swath coverage and high spatial resolution for monitoring moving targets such as aircraft, but large scan angles and terrain undulation cause non-rigid geometric distortion and radiometric inconsistency between forward and backward scans. These effects generate strong clutter in difference images and degrade small and weak target detection. To address this problem, we propose an infrared small target detection method that fuses accurate registration and weighted difference. First, we propose a hybrid multi-scale registration algorithm that achieves coarse affine registration through sparse feature–point matching and then iteratively corrects nonlinear deformations by integrating a global grayscale-driven force with a local sparse-feature-guided force, yielding a registration error of 0.3281 pixels. On this basis, a multi-scale weighted convolutional morphological difference algorithm is proposed. A novel dual-structure hollow top-hat transform is constructed to accurately estimate the background, and a multi-directional convolution mechanism is introduced to effectively suppress anisotropic edge clutter and enhance target saliency. Experiments on SDGSAT-1 thermal infrared bidirectional whisk-broom data show an SCRG of 18.27, and a detection rate of 91.2% when the false alarm rate is below 0.15%. The method outperforms representative competing algorithms and provides a useful reference for space-based aerial moving target detection. Full article

Non-invasive assessment of oocyte quality remains a challenge in assisted reproductive technology (ART). Through their bidirectional communication with the gamete, cumulus cells (CCs) act as a functional mirror of oocyte competence; however, the specific angiogenic signature within this microenvironment is still poorly understood. In the present study, we performed RNA-seq on CCs from healthy oocyte donors and infertile patients, utilizing a multi-pipeline bioinformatic approach (STAR-Cufflinks, TopHat-HTSeq, and HISAT2-StringTie) to establish a high-confidence, exploratory transcriptomic profile. A set of 234 differentially expressed genes (DEGs) consistently identified across pipelines was obtained, with functional enrichment highlighting blood vessel morphogenesis and angiogenesis as primary drivers of transcriptomic divergence between groups. RT-qPCR validation in individual samples confirmed statistically significant differences for ANKRD22 (upregulated) and E2F7 (downregulated) in infertile patients, while other angiogenesis-related genes, including ANGPT1, ANGPT2 and THBS1, showed consistent but non-significant expression trends, suggesting alterations in angiogenesis-related processes within the follicular microenvironment. These findings support the presence of coordinated angiogenesis-related alterations in cumulus cells and provide a basis for future studies exploring their potential relevance in oocyte competence and ART outcomes. Full article

Accurate segmentation of structural cracks is a core prerequisite for quantifying crack parameters, assessing damage severity, and providing early warning of structural safety. However, different types of structures exhibit significant individual variations in features such as color, texture, and brightness. Consequently, commonly used image segmentation algorithms struggle to establish a universal mathematical model, making it challenging to robustly identify and precisely segment crack targets amidst multi-feature disparities. To address the issue, this paper proposes a crack-segmentation algorithm based on bimodal image fusion and brightness piecewise linear enhancement (CSA-BB), and further enables parameter extraction and crack monitoring. The algorithm utilizes the complementary properties of visible-light and pseudo-color images for bimodal image fusion, thereby enhancing the detailed features of cracks. Furthermore, a brightness piecewise linear function has been devised that automatically selects appropriate parameters for image enhancement of structural cracks across varying background brightness. Subsequently, the crack region is effectively segmented using the bottom-hat transform and the OTSU algorithm. Ultimately, the crack’s safety level is determined from the acquired crack parameters, thereby enabling effective monitoring and assessment of the crack development process. In this paper, the proposed method achieves the best segmentation performance with a Dice coefficient of 0.4511 and a Jaccard index of 0.2981. Compared to the second-best algorithm, it yields significant improvements of 26.9% and 34.5%, respectively, demonstrating higher consistency with the ground truth. Moreover, superior computational efficiency and robustness are achieved, fulfilling the operational demands of real-world engineering environments. Full article

Rhodesain is a cysteine protease that plays a key role in the life cycle of Trypanosoma brucei rhodesiense, an endemic parasite in sub-Saharan Africa and responsible for Human African Trypanosomiasis (HAT), a disease that can be fatal if not treated promptly. Due to the limitations associated with current HAT pharmacological therapy, the search for new targets for the development of antitrypanosomal agents is urgently needed; in this context, rhodesain represents a promising therapeutic target. In this study, new chalcones were synthesized and tested against rhodesain. Given their affinity for the trypanosomal cysteine protease (K_i values in the micromolar range), chalcone 1a was selected to evaluate its effect in combination with the nutraceutical curcumin. The Combination Index (CI) was calculated using Chou and Talalay’s method. The analysis of the CI calculated at different f_a values of enzyme inhibition for the combination curcumin + 1a showed promising results. For all f_a values, the CI is less than one, indicating a synergistic effect when chalcone 1a is combined with curcumin. In particular, at the most significant f_a value (0.90), corresponding to 90% of enzyme inhibition, the CI value is 0.1781, indicating a strong synergism between the synthetic drug and the nutraceutical. The combined use of curcumin and chalcone 1a led to an enhancement of rhodesain inhibitory activity, resulting in a strong synergistic effect and supporting further investigation of this combination. Full article

The derivations presented in this paper suggest an intimate relationship between geometry and the electroweak sector at the Planck scale. A Lorentz-invariant maximally symmetric stochastically perturbed spacetime transformed to spherical coordinates reveals an emergent Schwarzschild metric, entirely a statistical structure of stochastic spacetime. Similarly, the transition from a maximally symmetric universe with a complex $SU\left(2\right)$ scalar doublet $\varphi$, comprising four independent real scalar fields with a zero vacuum expectation value (VEV), to spherical coordinates at the Planck scale reveals the spontaneously broken electroweak (EW) sector. Working in the unitarity gauge, the resulting EW potential can be simultaneously mapped in space at the Planck scale and across the EW sector. In space, the resulting EW potential includes a deep well within the Schwarzschild sphere and a shallow well just outside corresponding to an accretion disk. The same potential mapped in the EW space provides an entire family of possible sombrero hat potentials with fourth-order coupling specific to a point in space. At the minimum points of the potential in space, inside the Schwarzschild sphere and at the accretion disk, the $\lambda$ corresponding to the Standard Model (SM) fourth-order coupling is instead derived as $\frac{\lambda }{5}$. The factor of $\frac{1}{5}$ is a simple consequence of the conservation of the EW VEV and the fact that the SM formulation of the EW potential does not account for situations where the perturbations in $\varphi$ dominate. A more general formulation of the EW potential restores the SM quartic coupling and preserves $\lambda$ in space. An emergent Higgs field inside the Schwarzschild black hole is found to directly relate to the stochastic spacetime fields normalized by the Schwarzschild radius. The corresponding Higgs vacuum has both a ground and excited state and the possibility of both positive and negative vacuum entropy. Finally, the scalar-field VEV degeneracy in EW space of the metastable Higgs vacuum appears instead differentiated in space with possible probability, tunneling, and entropy implications. Full article

The jet structure plays an important role in both the prompt and afterglow emission phases of gamma-ray bursts (GRBs). Whether GRB jets are better described by uniform (top-hat) or structured models remains an open question. We use the afterglowpy Python package to numerically model the late X-ray afterglow light curves of a large sample of long and short GRBs, and apply the Bayesian Information Criterion (BIC) to compare the performance of top-hat and Gaussian structured jet models. Within our adopted modeling framework, we find that the top-hat model is preferred by the BIC for ∼78.9% (150/190) of long GRBs and 70% (7/10) of short GRBs. GRB 180205A and GRB 140515A exhibit $\Delta$BIC < 2 for all three model comparisons, indicating that top-hat, Gaussian, and power-law jets provide equivalent fits to their afterglow light curves. This large-sample analysis suggests that uniform jets may be more common than structured jets in the observed GRB population, although this conclusion is subject to the limitations of our model assumptions and the BIC-based model selection criterion. Furthermore, we find that the best-fit distributions of observer angle ${\theta }_{\mathrm{obs}}$, electron energy fraction ${ϵ}_e$, and isotropic equivalent energy $E_0$ differ significantly between the top-hat and Gaussian jet models, with ${\theta }_{\mathrm{obs}}$ showing the most pronounced distinction. Full article

Suramin is a century-old polysulfonated naphthylurea that remains a first-line treatment for early-stage human African trypanosomiasis (HAT). Remarkably, despite its age, suramin continues to draw attention because of its unusually broad spectrum of biological activities. Historically known as an antagonist of purinergic (P2) receptors and an inhibitor of extracellular enzymes, suramin has more recently been shown to interact with a range of intracellular and mitochondrial proteins. These include succinate dehydrogenase, the ADP/ATP carrier (AAC), the aspartate/glutamate carriers AGC1 and AGC2, carnitine O-acetyltransferase (CRAT), and the ATP-Mg/Pi carrier (APC2). Across these targets, suramin displays sub-micromolar to low-micromolar potencies, largely driven by electrostatic complementarity between its highly anionic sulfonate groups and basic nucleotide- or anion-binding regions of proteins. This extensive polypharmacology helps explain the diverse biological effects reported for suramin and supports its use as a valuable pharmacological probe of mitochondrial transport and metabolism. At the same time, its largeness and high negative charge limit oral bioavailability and brain penetration, prompting efforts to develop simplified analogues. This review brings together chemical, biological, and structural perspectives on suramin, highlighting opportunities for drug repurposing, transporter-focused drug design, and a better understanding of mitochondrial toxicity. Full article

Ultra-high-strength steel sheets were joined by forge joining during hot stamping. This study investigated the influence of punch cross-sectional shape and punch tip inclination shape on joint strength through experiments and finite element simulation, with applications in hat bending. The experiments systematically evaluated various punch geometries by varying the punch’s cross-sectional shape and the aspect ratio of rectangular punches. A second set of experiments focused on the influence of punch tip inclination shape. These experiments examined a rectangular punch with a slope. Joint strength is primarily assessed by measuring the tensile shear load. Finite element simulation was used to analyze joining mechanisms, investigating contact pressure and surface expansion rate distribution. The results from the experiments consistently indicated that, for a constant cross-sectional area, punch shapes with a larger punch perimeter on the upper sheet yielded a higher tensile shear load, though the changing inclination shape of the rectangular punch tip did not lead to an observed improvement in joint strength. Finite element simulation analysis revealed that punch shapes promoting a uniform distribution of contact pressure and surface expansion rate across the joint area tended to exhibit higher joint strength compared with the same punch cross-sectional area but less uniform distribution, a tendency that was more pronounced for the distribution of contact pressure than for the surface expansion rate. Full article

Accurate genealogical records are essential in livestock breeding for maintaining genetic diversity, preventing inbreeding, and mapping of economically important traits in beef production. This study aimed to assess parent–offspring relationships within South African Bonsmara and Nguni cattle populations using both traditional pedigree records and genomic data. Hair samples from 119 Nguni and 311 Bonsmara cattle were genotyped using the BovineSNP50 array, and these were imputed to Illumina BovineHD BeadChip using updated SNP coordinates from the assembly genome (ARC—UCSD 1.2). Quality control and data filtering were performed using PLINK v1.9, while relationship inference was conducted using KING v2.2.8 and PLINK v1.9 software for principal component analysis, IBD metrics and Mendelian error-based exclusion. Categories of relatedness through network relationship analysis revealed a predominance of half-sibling relationships in both breeds, with 2317 such relationships identified in Nguni and 1221 in Bonsmara. Inference of parent–offspring pairs showed discrepancies with the recorded pedigrees, with 49 inferred pairs compared to 47 recorded pairs in Nguni, and 62 inferred pairs compared to 75 pairs recorded in Bonsmara. Relationships based on IBD using PLINK with a ‘PI-HAT’ threshold greater than 0.45 revealed unique parent–offspring inferences that differed from those obtained using KING v2.2.8. Phylogenetic network analysis assigned each individual’s genomic origin independent of the pedigree records, supporting the efficiency of SNP data for genetic assignment. These results demonstrated that SNP-based pedigree verification can accurately identify parent–offspring and half-sibling relationships, providing a reliable foundation for recombination analysis and supporting precise trait mapping and informed selection in breeding programs. Full article

Liquid metal embrittlement (LME) during hot stamping of Zn-coated high-strength steels poses significant challenges to the long-term durability of automotive components. This study investigates how ~30 μm deep LME cracks affect the mechanical behavior of Zn-coated high-strength boron steel. LME-free flat specimens were compared with hat-shaped specimens containing LME cracks. While tensile strength and ductility exhibited minimal changes, the high-cycle fatigue limit (R = −1, 10⁷ cycles) decreased by 10.9% from 550 MPa to 490 MPa in hat-shaped specimens. Fractographic examination revealed distinct stress-dependent crack initiation mechanisms: at high stress amplitudes (≥690 MPa), LME cracks competed with intrinsic substrate defects but did not dominate fatigue failure. In contrast, at moderate-to-low stress amplitudes (≤630 MPa), LME cracks dominated fatigue degradation through a multi-site crack initiation tendency. El Haddad analysis positioned these cracks at the short-to-long crack transition boundary (l ≈ l₀). Preliminary fracture mechanics analysis reveals that conventional single-crack LEFM models systematically overestimate the fatigue threshold stress for LME-affected specimens, a discrepancy qualitatively attributed to the high surface density and morphological complexity of LME crack networks and to chemically assisted grain boundary weakening induced by liquid Zn infiltration—effects not captured by standard fracture mechanics frameworks. These results establish the stress-dependent mechanisms governing LME crack-induced fatigue degradation and provide a mechanistic basis for the development of more accurate fatigue life prediction methods for Zn-coated hot-stamped high-strength steels. Full article

Platforms often fail to incorporate the needs of white hats who prefer non-material incentives when designing reward schemes. To study incentive design under private preference information, this paper develops a dynamic game with incomplete information and examines how appointing communications specialists can facilitate truthful preference disclosure and improve the platform’s incentive strategy. The results indicate that the platform’s decision depends on the white hats’ net utility from participation, white hats’ reputational losses, and the platform’s prior probability that white hats participate. When the platform appoints communications specialists, white hats disclose their preference information truthfully once their net utility from participation exceeds a threshold. Under this condition, the platform can identify their preference types and match incentive types to white hats’ preferences. Under misaligned signaling, where white hats use material (non-material) incentives to signal non-material (material) preferences, the platform has no incentive to appoint communications specialists. Full article

This study elucidates the regulatory mechanisms of methoxy substitution and photoexcitation on the antioxidant properties of pterostilbene (PTE) versus resveratrol (RES), employing a combined approach of multi-reference calculations, density functional theory (DFT), time-dependent DFT (TD-DFT), and molecular docking. Spectral analysis indicates that trans isomers exhibit a significant redshift (~13 nm) and have oscillator strengths more than double those of cis isomers. A pivotal difference in photoisomerization kinetics was identified: methoxy substitution drastically lowers the isomerization barrier for RES, indicating that PTE is more readily photoisomerized. Regarding radical scavenging, thermodynamic data confirm that Hydrogen Atom Transfer (HAT) and Radical Adduct Formation (RAF) are spontaneous pathways; notably, the O1 site of trans-PTE serves as the optimal hydrogen donor. Conceptual DFT (CDFT) analysis reveals that photoexcitation triggers a dramatic electronic reconfiguration, particularly for cis-PTE, whose ionization potential in the S1 state drops sharply to 4.66 eV, accompanied by an increased softness of 0.38 eV⁻¹, rendering it a highly potent electron donor. Furthermore, molecular docking demonstrates that trans-PTE robustly occupies the Keap1 Kelch pocket (binding energy: −7.478 kcal/mol) to inhibit Nrf2 binding via its favorable planar geometry. Full article