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关键词： galaxies: clusters: general   galaxies: clusters: intracluster medium   cosmology: observations   large-scale structure of Universe  

摘要： We present the weak-lensing mass calibration and constrain the relation between the stellar mass of the brightest cluster galaxy (BCG), halo mass, and redshift (M-star,M- BCG-M-z) for a sample of 124 galaxy clusters and groups at redshift 0.1 < z < 0.8 from the first Data Release of the eROSITA All-Sky Survey (eRASS1), using data from the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The cluster survey is conducted by the eROSITA X-ray telescope aboard the Spectrum-Roentgen-Gamma (SRG) space observatory. The cluster sample is X-ray-selected and optically confirmed with a negligibly low contamination rate (approximate to 5%). On the basis of individual clusters, the shear profiles g(+) of 96 clusters are derived using the HSC Three-Year (HSC-Y3) weak-lensing data, while the BCG stellar masses M-star,M- BCG of 101 clusters are estimated using the SED template fitting to the HSC five-band (grizY) photometry. The observed X-ray photon count rate C-R is used as the mass proxy, based on which individual halo masses M are obtained at the given C-R in a population modelling, while accounting for systematic uncertainties in the weak-lensing modelling through a simulation-calibrated weak-lensing mass-to-halo-mass (M-WL-M-z) relation. The count rate (C-R-M-z) and BCG stellar mass (M-star,M- BCG-M-z) relations are simultaneously constrained in forward modelling and population modelling. In agreement with the results based on the weak-lensing data from the DES and KiDS surveys, we obtain a C-R-M-z relation with a self-similar redshift scaling and a mass trend that is steeper than the self-similar prediction. We cannot simultaneously place stringent constraints on the power-law indices of the mass (B-BCG) and redshift (gamma(BCG)) trends, due to the parameter degeneracy arising from the sample selection and the limited sample size. By adopting an informative prior on gamma(BCG) to break the B-BCG-gamma(BCG) degeneracy, we obtain a M-star,M- BCG-M-z relation with the mass slop

关键词： Microprocessors   Transistors   Resistance   Hamming distances   Nonvolatile memory   FeFETs   Voltage control   Logic   Discharges (electric)   Symbols   Approximate search   content addressable memory (CAM)   multi-state Hamming distance (MSHD)   pattern matching   resistive random-access memory (RRAM)  

摘要： The multi-state Hamming distance (MSHD) is a crucial metric for evaluating the similarity of symbolic sequences in data-intensive search applications, such as genomic analysis. MSHD search is performed by comparing inputs against database entries, which can be efficiently accelerated by content-addressable memories (CAMs), such as multi-level cell (MLC) RRAM CAMs. However, designing MLC RRAM-based MSHD CAM faces critical challenges in area efficiency, primarily due to large CAM cells, complex MSHD computing circuits, and bulky variation-compensating input circuits. To address these issues, we propose three techniques to develop M(3)CAM, an MLC RRAM-based multi-bit CAM (MCAM) supporting in-memory operation of MSHD. First, we propose a 5T1R MCAM cell with MLC RRAM to support dense symbol matching. Second, we propose an MSHD in-memory operation circuit with only three transistors to support dense MSHD computation. Third, we propose a feedback-driven adaptive input DAC to enable minimal area-overhead compensation for RRAM variation. Compared to the state-of-the-art, the proposed M(3)CAM reduces MCAM cell area by 74.2%, and reduces MSHD computing circuit transistors by 20%, while expanding the MSHD search range to 16x .

关键词： Calmodulin   Calmodulin mutant CaM(D130G)   Cardiac L-type calcium channel   Long QT syndrome  

摘要： Recent studies have identified a significant association between mutations in Calmodulin (CaM), a pivotal calcium-sensing protein, and the pathogenesis of LQTS. CaM interacts with various cellular proteins, notably the myocardial L-type calcium channel (LTCC), where the Cav1.2 channel serves as the principal subtype in cardiac myocytes. The CaM_D130G mutant is specifically linked to the development of Long QT Syndrome (LQTS). This study aimed to investigate the altered binding of CaM_D130G mutants to Cav1.2 channels, clarifying their role in LQTS pathogenesis.

关键词： triple negative breast neoplasms   breast neoplasms   magnetic resonance imaging   diagnosis   computer-assisted   disease-free survival  

摘要： Background/Objectives: To identify preoperative MRI features using computer-assisted diagnosis (CAD) that are associated with invasive disease-free survival (IDFS) and distant metastasis-free survival (DDFS) in patients with primarily operable triple-negative breast cancer (TNBC). Methods: This retrospective study was approved by the institutional review board with informed consent was waived. Between January 2012 and December 2014, 74 consecutive women with primary TNBC (mean age, 51 years;range, 29-77 years) who underwent preoperative MRI were included and followed until August 2021. Dynamic contrast-enhanced and T2-weighted images were obtained using 3T scanners. Peritumoral edema and central necrosis were evaluated retrospectively. CAD was used to extract 3D diameters, angiovolume, and kinetic parameters, and kinetic heterogeneity was calculated. Cox proportional hazards models were used to assess associations between MRI features and IDFS and DDFS, adjusting for clinicopathologic factors. Results: During a median follow-up of 80.9 months, 12 patients developed invasive disease, and 8 developed distant metastasis. In multivariable analysis, peak enhancement (hazard ratio [HR], 1.40;95% confidence interval [CI], 1.06-1.84;p = 0.019) and angiovolume (HR, 2.86;95% CI, 1.26-6.47;p = 0.012) were independently associated with IDFS, whereas angiovolume (HR, 2.47;95% CI: 1.28-4.78;p = 0.007) was independently associated with DDFS. Conclusions: Preoperative CAD-derived MRI features, particularly peak enhancement and angiovolume, were associated with IDFS in TNBC patients whereas angiovolume alone was associated with DDFS.

关键词： Brain tumor classification   Explainable AI (XAI)   Convolutional Neural Networks (CNN)   Grad-CAM  

摘要： Detecting Brain Tumors is essential in medical imaging, as early and accurate diagnosis significantly improves treatment decisions and patient outcomes. Convolutional Neural Networks have demonstrated high efficiency in this domain, but their lack of interpretability remains a significant drawback for clinical adoption. This study explores the integration of Explainability techniques to enhance transparency in CNN-based classification and improve model performance through advanced optimization strategies. The primary research question addressed is how to improve the accuracy, generalization, and interpretability of CNNs for brain tumor Detection. While previous studies have demonstrated the effectiveness of deep learning for tumor detections, challenges such as class imbalance and overfitting of CNNs persist. To bridge this gap, we employ different dynamic learning rate modifiers, perform architectural enhancements, and apply XAI techniques, including Grad-CAM and LIME. Our experiments are conducted on three publicly available multiclass tumor datasets to ensure the generalizability of the proposed approach. Among the tested architectures, the enhanced ResNet model consistently outperformed others across all datasets, achieving the highest test accuracy, ranging from 99.36% to 99.65%. The techniques such as unfreezing layers, integrating various blocks, pooling, and dropout layers enhanced feature refinement and reduced overfitting. By incorporating XAI, we improve model interpretability, ensuring that clinically relevant regions in MRI scans are highlighted. These advancements contribute to highly reliable AI-assisted diagnostics, addressing significant challenges in medical image classification.

关键词： Acetabular dysplasia   Alternative to periacetabular osteotomy   Femoro acetabular impingement   Hip arthroscopy   Labral/chrondral repair  

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关键词： Explainable   Artificial intelligence   Deep learning   Interpretability  

摘要： Deep learning models, particularly convolutional neural networks (CNNs), have achieved remarkable success in solving complex computer vision problems. However, their lack of interpretability poses challenges for adoption in high-stakes domains. To address this, numerous saliency methods have been proposed to generate visual explanations of CNNs' decision processes. Existing methods often suffer from low explanation quality, high computational cost, or a lack of theoretical foundation. In this work, we introduce SHARPEN-CAM, a novel visual explanation method that adopts a hierarchical "reunion-redistribution" strategy to assign importance coefficients to activation maps. SHARPEN-CAM first reunites similar activation maps into groups and calculates SHAP values as group coefficients. It then redistributes these group coefficients to individual activation maps using Aumann-Shapley values derived from the integrated gradient method. Extensive experiments on ImageNet and VOC datasets demonstrate that SHARPEN-CAM outperforms state-of-the-art methods in terms of explanation quality, localization capability, and computational efficiency. By providing a clearer theoretical basis and practical implementation, SHARPEN-CAM offers a promising solution for interpreting deep neural networks, enhancing their transparency and trustworthiness.

关键词： Bacterial adhesion   Ceramics   Computer-Aided design   Dental polishing   Materials testing  

摘要： ObjectivesBacterial adhesion to dental restorations plays a critical role in the development of biofilms, contributing to periodontal disease and implant failure. This study aimed to evaluate the effects of glazing and polishing on the adhesion of Streptococcus mutans to three types of CAD/CAM ceramics: lithium disilicate, zirconia-reinforced lithium silicate, and monolithic *** and methodsIn this experimental in-vitro study, 81 ceramic specimens (n = 81) from three types-zirconia-reinforced lithium silicate (VITA Suprinity), lithium disilicate (IPS *** CAD), and monolithic zirconia (InCoris ZI)-were prepared by polishing, glazing, and left untreated as controls. The bacterial adhesion of Streptococcus mutans was assessed using the crystal violet biofilm assay. Following a 48-hour incubation, optical density (OD) values were measured to quantify bacterial adhesion. Scanning electron microscopy (SEM) was used for additional biofilm visualization. The data were analyzed using SPSS software with the Kolmogorov-Smirnov test, one-way and two-way ANOVA, and Tukey test with a significance level of *** InCoris ZI demonstrated the lowest bacterial adhesion (0.14). Two-way ANOVA revealed a significant interaction between ceramic type and preparation method (p = 0.003), although neither factor alone showed a significant effect. InCoris ZI exhibited significantly higher bacterial adhesion with glazing compared to polishing (p = 0.005), while no significant differences were observed for Suprinity or IPS *** across preparation methods. Bacterial adhesion to InCoris ZI among glazed samples was significantly higher than Suprinity (p = 0.01) and IPS *** (p = 0.009).ConclusionPreparation methods generally did not significantly influence bacterial adhesion, except for InCoris ZI, where polishing resulted in substantially lower adhesion compared to *** implicationsThe study highlights that polishing, particularly for InCoris ZI ceramic