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关键词： Digital twins   Geometric coherence   Spatial mapping   Anchor   Augmented reality  

摘要： This paper presents an augmented reality framework designed for real-time positioning and orientation synchronization of CAD models within physical environments, with a specific focus on maintaining digital twin coherence. A key advantage of this framework is its autonomy in two aspects: (1) it does not require the physical environment to be equipped with tags or other devices, relying only on identifying stable reference items within the real space;and (2) it operates independently of web connectivity, allowing offline functionality and making it particularly suitable for workshop environments, where data synchronization can occur at a later stage. The framework addresses the challenges of achieving accurate indoor positioning and orientation, particularly in the absence of GPS signals, by integrating advanced technologies such as SLAM (Simultaneous Localization and Mapping), visual-based methods, and AR-based anchoring systems. We detail the experimental setup used to evaluate the framework's efficiency, comparing its performance with existing solutions like Azure Spatial Anchors and QR image targets under various conditions. Our findings highlight the framework's robustness and precision in maintaining geometric coherence, demonstrating its practical applicability in diverse industrial and operational contexts. The proposed solution offers significant improvements in spatial mapping, error correction, and system adaptability, thereby enhancing the overall reliability and functionality of digital twins in real-world applications.

关键词： Genomics   Bioinformatics   Throughput   Heuristic algorithms   Accuracy   Redundancy   Hamming distances   DNA sequencing   Microprocessors   Transistors   Approximate search   content-addressable memory (CAM)   genome analysis   memristors   shifted Hamming distance (SHD)  

摘要： Genome analysis has been critical in various applications, such as infectious disease control. High throughput is an essential requirement for genome analysis in data-intensive scenarios, which requires acceleration by content-addressable memory (CAM) with parallel comparison capability. However, existing genome analysis CAMs still face inadequate throughput issues due to large cell area, excessive array storage redundancy, and inefficient comparison algorithms. To address these issues, we propose a high-throughput dynamic shifted Hamming distance (SHD) resistive random access memory (RRAM)-based CAM (DSHD-CAM) that leverages the characteristics of genome analysis. First, we propose a compact RRAM-based CAM cell utilizing one-hot encoding and time-domain computation to minimize cell area. Second, we propose a dense CAM array utilizing an efficient storage scheme to reduce array storage redundancy. Third, we propose a dynamic SHD search algorithm filtering out low-match-potential cases to reduce search latency. Compared to the state-of-the-art (SOTA), DSHD-CAM achieves an average of 7.58 & times;higher throughput under the same area constraints while maintaining competitive sensitivity and precision.

关键词： Calmodulin   Calmodulin-like protein   Chickpea   EF-hand   Gene expression   Promoter  

摘要： Calcium (Ca2+) is a ubiquitous secondary messenger that conveys a variety of internal and external signals. Sensor proteins most likely detect these Ca2+signals and can bind Ca2+using the EF-hand motif, a helix-loop-helix structure. Calmodulins (CaMs) and calmodulin-like proteins (CMLs) are one of the major classes of calcium (Ca2+) sensors in plants. However, knowledge about the CaM and CML families in chickpea is still missing. To fill this knowledge gap, a comprehensive analysis ofCaMandCMLwas performed in this study, and sixCaMand twenty-threeCMLgenes in chickpea were identified. The gene structure analysis showed that twenty-one out of twenty-threeCaCMLs were intron-less, whereas all theCaCaMs were rich in introns. Their chromosomal locations showed that twenty-six out of twenty-nine genes could be mapped on seven chromosomes, and three genes i.e.,CaCaM3,CaCML18, andCaCML20are placed on the scaffold region. Ka/Ks analysis of orthologous and paralogous gene pairs indicated that all theCaCaMandCaCMLgene pairs evolved through purifying selection. According to phylogenetic analysis, CaCaM and CaCML proteins were clustered into five orthologous groups. Group V contains the highest number of CaM and CML protein members of chickpea. Numerous cis-acting regulatory elements associated with abiotic stress, hormone signalling, and plant growth and development were identified through promoter analysis. Box 4 cis-acting regulatory element is present in all theCaCaMandCaCMLpromoter sequences. By analyzing the available transcriptome data, we generated a detailed expression profile ofCaCaMs andCaCMLs across different tissues, such as root, shoot, mature leaf, flower bud, and young pod, various developmental stages of flowers, and different abiotic stress conditions. The identification and description ofCaCaMs andCaCMLs in chickpea provide a framework for further functional characterization of these genes. These results suggest that theCaMandCMLgene family may play an importan

关键词： chest pain   contrast agent   echocardiography   electrocardiogram   CAD   coronary artery disease   CARPA   complement activation-related pseudoallergy   CPR   cardiopulmonary resuscitation   IgE   immunoglobulin E   PEA   pulseless electrical activity   PEG   polyethylene glycol   TTE   transthoracic echocardiography   UEA   ultrasound-enhancing agent  

摘要： Ultrasound-enhancing agents (UEAs) are generally considered safe, with severe reactions exceptionally rare. Cross-reactivity between agents remains poorly understood.

关键词： CAD/CAM technology   curriculum development   dental education   dental students   digital dentistry   knowledge and attitudes  

摘要： Introduction: CAD/CAM (Computer-Aided Design/Computer-Aided Manufacturing) technology has become integral to modern dental practice, requiring structured integration into dental education. However, little is known about how well dental students in Croatia understand and engage with these technologies. This study aimed to quantitatively assess the level of knowledge, attitudes and practical experience with CAD/CAM among dental students in Osijek, and to explore the influence of academic year, gender and family background in dentistry on these dimensions. Materials and Methods: A cross-sectional survey was conducted at the Faculty of Dental Medicine and Health in Osijek, including 102 students from the 3rd to 6th year., with 44 (44.88%) in preclinical and 58 (55.12%) in clinical training. A 21-item questionnaire assessed theoretical knowledge, practical exposure and attitudes. Data were analysed using descriptive statistics, ANOVA, t-tests and chi-square tests (p < 0.05). Results: While 88.24% of students had heard of CAD/CAM, only 45.10% had practical experience and just 11.76% had attended extracurricular CAD/CAM training. Nonetheless, 90.20% believed CAD/CAM should be more thoroughly taught, and 85.29% expressed interest in further education. Clinical-year students and those with family in dentistry showed significantly higher knowledge and more positive attitudes (p < 0.001), whereas no significant gender differences were observed (p = 0.222). Conclusion: The findings indicate a gap between theoretical familiarity and practical competence among Croatian dental students regarding CAD/CAM technology. To address this, we recommend the development of a structured undergraduate CAD/CAM module that includes theoretical instruction, digital simulation and supervised clinical training across all study years. Such curriculum development is essential to prepare future dentists for the demands of digital clinical practice.

关键词： lung cancer   classification   densenet121   efficientnetb0   spatial attention module  

摘要： Background/Objectives: Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, making early and accurate diagnosis crucial for improving patient outcomes. Although chest computed tomography (CT) enables detailed assessment of lung abnormalities, manual interpretation is time-consuming, requires expert expertise, and is prone to diagnostic variability. To address these challenges, this study proposes DE-SAMNet, a hybrid deep learning framework for automated multi-class LC classification from CT scans. Methods: The model integrates two pre-trained convolutional neural networks-DenseNet121 and EfficientNetB0-operating in parallel to extract complementary multi-scale features. A Spatial Attention Module (SAM) is applied to each feature stream to emphasize clinically important regions. Final classification is performed through a compact fusion mechanism involving global average pooling, batch normalization, and a fully connected layer. DE-SAMNet was evaluated on two datasets: a public dataset (IQ-OTH/NCCD) with benign, malignant, and normal cases, and a private clinical dataset including benign, malignant, cystic, and healthy cases. Results: On the public dataset, the model achieved a 99.00% F1-score, 98.41% recall, 99.64% precision, and 99.54% accuracy. On the private dataset, it obtained 95.96% accuracy, 95.99% precision, 96.04% F1-score, and 96.21% recall, outperforming existing approaches. To enhance reliability, explainable AI (XAI) techniques such as Grad-CAM were used to visualize the model's decision rationale. The resulting heatmaps effectively highlight lesion-specific regions, offering transparency and supporting clinical interpretability. Conclusions: This explainability strengthens trust in automated predictions and demonstrates the clinical potential of the proposed system. Overall, DE-SAMNet delivers a highly accurate and interpretable solution for early LC detection.

关键词： Metrology   telecentric vision   YOLO   imaging-to-CAD reconstruction  

摘要： vision and deep learning for high-accuracy digital reconstruction of printed circuit boards (PCBs). The framework integrates a telecentric camera with a Cartesian scanning platform to capture distortion-free, high-resolution PCB images, which are stitched into a single orthographic composite. A YOLO-based detection model, trained on a dataset of 270 PCB images across 23 component classes with data augmentation, identifies and localizes electronic components with a mean average precision of 0.932. Detected components are automatically matched to corresponding 3D CAD models from a part library and assembled within a Fusion 360 environment, producing a 3D digital replica. Experimental results show a similarity score of 0.894 and dimensional deviations below 2%, outperforming both SensoPart image measurement and manual vernier methods. The proposed approach bridges optical metrology and CAD automation, providing a scalable solution for AI-assisted reverse engineering, digital archiving, and intelligent manufacturing.

关键词： AQLQ   Asthma Quality of Life Questionnaire   ASHMI   Anti-asthma Herbal Medicine Intervention   ACT   Asthma Control Test   AHR   Airway hyper responsiveness   ANOVA   Analysis of Variance   BALF   Bronchoalveolar lavage fluid   BID   Bis in Die   COX-1   Cyclooxygenase‑1   CAM   Complementary and alternative medicine   COPD   Chronic Obstructive Pulmonary Disease   CS   Cough severity   ES   Effect Size   GINA   Global Initiative for Asthma   12-HETE   12-hydroxyeicosatetraenoic acid   IL-1β   Interleukin-1 beta   IL-4   Interleukin‑4   IgE   Immunoglobulin E   ICS   Inhaled Corticosteroid   ICC   Intraclass correlation coefficients   INOS   Inducible Nitric Oxide Synthase   IL   Interleukin   12-LOX   12-Lipoxygenase   NF-κB   Nuclear Factor kappa-light-chain-enhancer of activated B cells   NO   Nitric Oxide   OB   Ocimum basilicum   PB   placebo group   PGE2   Prostaglandin E2   SMS   Short Message Service   SD   standard deviation   TAMC   Total aerobic microbial count   TYMC   total yeast and mold count   TNF-α   Tumor Necrosis Factor-alpha   Th   T helper   USP   United States Pharmacopeia   UDP   Up-and-Down Procedure   VAS   Visual analog scale   Asthma   Inflammatory cytokines   Complementary and alternative medicine   Cytokine   Herbs  

摘要： Complementary and alternative medicine (CAM) plays a significant role in asthma management.

摘要： La réalisation d’acquisitions scintigraphiques corps entier, après injection de 117Lu-PSMA, permet d’évaluer la réponse au traitement. Ces enregistrements, qui étaient jusqu’à présent réalisés sur caméra 360 °CZT en 18 minutes sur le pic à 113 keV (SP-18), peuvent être optimisés en combinant les informations provenant des deux pics en énergie 113/208 keV. Nous avons évalué une réduction du temps d’acquisition à 9 minutes, rendue possible grâce au gain d’un facteur 2 en sensibilité des pics en énergie 113/208 keV (DP-9).

关键词： HET-CAM test   Moisturizing creams   Ocular irritation   Sunscreen creams  

摘要： Cosmetic products applied around the eyes, such as moisturizing and sunscreen creams, can come into contact with the conjunctiva, potentially causing irritation due to the thinness of the ocular epithelium. These products, widely used by the general population, remain in contact with the skin for extended periods. In this study, 41 cosmetic creams marketed in Algeria (moisturizers and sunscreens) were evaluated using the Hen's Egg Test on the Chorioallantoic Membrane (HET-CAM), an alternative to the Draize test. The results showed that 36.6 % of the tested creams induced irritation, with varying degrees of severity. Moisturizing creams were more frequently associated with irritation (44.0 %) compared to sunscreens (25.0 %). Among products intended for children, 44.4 % elicited an irritation response, and 60 % of irritating products carried the precautionary statement “avoid contact with eyes.” These findings provide the first data on the ocular irritation potential of cosmetic creams available in the Algerian market and contribute to regional safety assessment by identifying specific product categories with irritant potential.