The Alarming State of Hepatitis B Vaccination Among Dentists: Local, National and Global Implications by Muhammad Usman Sultan, Ihsan Ullah, Muhammad Anas

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Fully Digital Phased Array Harmonic Radar for Detecting Concealed Electronic Devices by Wonryeol Lee, Taeyong Jeong, Daju Lee, Kyusik Woo, Kang-Yoon Lee, Chang-Ryul Yun, Chulhun Seo, Juntaek Oh, Keum Cheol Hwang, Sun K. Hong

“…In free-space conditions, the radar achieved accurate target localization with angular errors below 1°. In concealed conditions, nonlinear reflections introduced minor localization errors due to clutter. …”
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AuxDepthNet: Real-Time Monocular 3D Object Detection with Depth-Sensitive Features by Ruochen Zhang, Hyeung-Sik Choi, Dongwook Jung, Phan Huy Nam Anh, Sang-Ki Jeong, Zihao Zhu

“…AuxDepthNet introduces two key components: the Auxiliary Depth Feature (ADF) module, which implicitly learns depth-sensitive features to improve spatial reasoning and computational efficiency, and the Depth Position Mapping (DPM) module, which embeds depth positional information directly into the detection process to enable accurate object localization and 3D bounding box regression. …”
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Multi-scale cross-layer fusion and center position network for pedestrian detection by Qian Liu, Youwei Qi, Cunbao Wang

“…We add a center position branch into the localization regression sub-network in MCF-CP-NET to better detect occluded pedestrians, which predicts the centrality index of the localization box to obtain the center score, and further optimizes the score of non-maximum suppression. …”
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Deep Learning-Driven Multi-Temporal Detection: Leveraging DeeplabV3+/Efficientnet-B08 Semantic Segmentation for Deforestation and Forest Fire Detection by Joe Soundararajan, Andrew Kalukin, Jordan Malof, Dong Xu

“…A qualitative analysis confirms the model’s ability to accurately localize fire hotspots and deforested areas. These results highlight the model’s dual-purpose utility for high-resolution, multi-temporal environmental monitoring. …”
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Depth-Enhanced Tumor Detection Framework for Breast Histopathology Images by Integrating Adaptive Multi-Scale Fusion, Semantic Depth Calibration, and Boundary-Guided Detection by A. Robert Singh, Suganya Athisayamani, Hariharasitaraman S, Faten Khalid Karim, Jose Varela-Aldas, Samih M. Mostafa

“…The proposed loss function optimizes RGB-depth feature alignment, balancing contributions from each modality for robust tumor detection. This approach addresses challenges such as overlapping boundaries, occlusions, and poor contrast in histopathology images, enabling precise localization of tumor regions. …”
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Efficient Deep Learning-Based Device-Free Indoor Localization Using Passive Infrared Sensors by Sira Yongchareon, Jian Yu, Jing Ma

“…Passive infrared (PIR) sensors detecting changes in temperature in an environment are one of the suitable options for human localization due to their lower cost, low energy consumption, electromagnetic tolerance, and enhanced private awareness. …”
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Bitemporal Remote Sensing Change Detection With State-Space Models by Lukun Wang, Qihang Sun, Jiaming Pei, Muhammad Attique Khan, Maryam M. Al Dabel, Yasser D. Al-Otaibi, Ali Kashif Bashir

“…This article investigates the impact of different scanning mechanisms within Mamba, evaluating five mainstream methods to optimize its performance in change detection. We propose local bitemporal change detection mamba (LBCDMamba), a novel architecture based on our proposed local–global selective scan module, which effectively integrates global and local information through a unified scanning strategy. …”
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Randomness-free detection of non-projective measurements: qubits & beyond by Sumit Rout, Some Sankar Bhattacharya, Paweł Horodecki

“…While some of these correlations can be obtained through non-projective measurements on a shared two-qubit state, it is impossible to generate these correlations using projective simulable measurements on bipartite qubit states, or equivalently, by using one bit of shared randomness and local post-processing. For certain target correlations, we show that detecting qubit non-projective measurements is robust under arbitrary depolarizing noise, except in the limiting case. …”
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Hashing to detect identical ordering of species in a shared sublattice by Yoyo Hinuma

“…The digest can tolerate numerical precision errors to some extent, and configurations with the same local environments are identified by simply sorting the digest numbers and detecting crystals with very close digests.…”
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Wavelet-Based Texture Mining and Enhancement for Face Forgery Detection by Xin Li, Hui Zhao, Bingxin Xu, Hongzhe Liu

“…Next, we propose a global–local feature refinement (GLFR) module to enhance the model’s leverage of both global semantic features and local texture features. …”
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(IoT) Network intrusion detection system using optimization algorithms by Luo Shan

“…The complementary design of the two algorithms effectively overcomes the limitations of single-algorithm approaches, such as susceptibility to local optima and slow convergence speed. Compared with traditional models like the Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) and Support Vector Machine (SVM), the proposed framework significantly improves the sensitivity and generalization ability for detecting various types of attacks through dynamic feature selection and parameter optimization. …”
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Plant Disease Detection Using an Innovative Swin-Axial Transformer by Ao Zhang, Wei Liu

“…Plant diseases are a significant threat to global agricultural production, and accurate and efficient disease detection is crucial for ensuring food security. With the rapid development of deep learning technology, Transformer architectures have demonstrated strong global feature extraction capabilities in image classification and detection tasks. …”
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Sysmon event logs for machine learning-based malware detection by Riki Mi’roj Achmad, Dyah Putri Nariswari, Baskoro Adi Pratomo, Hudan Studiawan

“…In this research, we employed various machine learning algorithms, both classification (supervised learning) and outlier detection (unsupervised learning) approaches, such as Naive Bayes, Decision Tree, Random Forest, Support Vector Machine (SVM) for supervised learning, and Isolation Forest, Local Outlier Factor (LOF), and One-Class SVM for unsupervised learning. …”
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Neighbor Similarity Based Agglomerative Method for Community Detection in Networks by Jianjun Cheng, Xing Su, Haijuan Yang, Longjie Li, Jingming Zhang, Shiyan Zhao, Xiaoyun Chen

“…In this paper, we propose a node similarity based community detection method, which is also a local one consisted of two phases. …”
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Ultra-sensitive heterodyne detection at room temperature in the atmospheric windows by Saemian Mohammadreza, Del Balzo Livia, Gacemi Djamal, Todorov Yanko, Rodriguez Etienne, Lopez Olivier, Darquié Benoit, Li Lianhe, Davies Alexander Giles, Linfield Edmund, Vasanelli Angela, Sirtori Carlo

“…We report room temperature heterodyne detection of a quantum cascade laser beaten with a local oscillator on a unipolar quantum photodetector in two different atmospheric windows, at 4.8 µm and 9 µm. …”
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Seminoma Diagnosed by Multicancer Detection Testing: A Case Report by Elizabeth A. Gilman, Aditya K. Ghosh, Sara Seegmiller, Ivana T. Croghan, Ryan T. Hurt

“…A 67-year-old male with positive signals for neuroendocrine and head/neck cancer on a commercially available multicancer detection test underwent an extensive negative diagnostic workup at a local hospital. …”
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Detecting Image Splicing Using Merged Features in Chroma Space by Bo Xu, Guangjie Liu, Yuewei Dai

“…Image splicing is an image editing method to copy a part of an image and paste it onto another image, and it is commonly followed by postprocessing such as local/global blurring, compression, and resizing. …”
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Alzheimer’s Disease Detection Using Deep Learning and Federated Learning by Taha Bin Niaz, Usman Amjad, Humera

“… Appropriate and precise diagnosis of brain diseases is crucial as many forms of Alzheimer’s disease display similar indications in their initial stages. Most automatic detection or classification systems based on deep learning present confidentiality concerns due to their use of integrated computing and local storage data requirements for training. …”
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Rodent malaria parasites detected in the invasive Rattus rattus in Gabon by Clark Mbou-Boutambe, Larson Boundenga, Fanny Degrugillier, Philippe Gauthier, Céline Arnathau, Ana Rivero, Laurent Granjon, Virginie Rougeron, Franck Prugnolle

“…These findings challenge the traditional view that rodent malaria parasites are restricted to native hosts and highlight R. rattus as a potential, albeit likely incidental, host within local Plasmodium transmission networks. Despite a low infection prevalence (0.38 %), this result raises important questions about the capacity of invasive rodents to integrate into local parasite cycles and influence disease dynamics.…”
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