Integrative computational approaches identify haptoglobin inhibitors to modulate erythrocyte sedimentation rate in trauma-linked inflammatory and haematological malignancies by Abdulaziz H. Al Khzem, Shaban Ahmad

“…The study also included Density Functional Theory computations and pharmacokinetic profiling to assess these compounds’ suitability further, revealing promising results. …”
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Long-Term Effects of COVID-19: Analysis of Imaging Findings in Patients Evaluated by Computed Tomography from 2020 to 2024 by Zeynep Keskin, Mihrican Yeşildağ, Ömer Özberk, Kemal Ödev, Fatih Ateş, Bengü Özkan Bakdık, Şehriban Çağlak Kardaş

“…<b>Background:</b> This study aims to systematically evaluate the findings from computed tomography (CT) examinations conducted at least three months post-diagnosis of COVID-19 in patients diagnosed between 2020 and 2024. …”
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Automated dairy cow identification and feeding behaviour analysis using a computer vision model based on YOLOv8 by Claudia Giannone, Mohsen Sahraeibelverdy, Martina Lamanna, Damiano Cavallini, Andrea Formigoni, Patrizia Tassinari, Daniele Torreggiani, Marco Bovo

“…Sick cows often exhibit altered feeding patterns, such as reduced feeding time and frequency, making early detection crucial for effective farm management. …”
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Usefulness of 18F-fluorodeoxyglucose-positron emission tomography/computed tomography in primary cystadenocarcinoma of the mesentery: a case report by Yuto Hozaka, Yuko Mataki, Hiroshi Kurahara, Kiyonori Tanoue, Tetsuya Idichi, Yota Kawasaki, Satoshi Iino, Pramod Nepal, Takaaki Arigami, Kosei Maemura, Hirotsugu Noguchi, Hiroyuki Shinchi, Akihide Tanimoto, Shoji Natsugoe, Takao Ohtsuka

“…Pathological examination of the specimens revealed various histologic patterns of adenocarcinoma, including mucin production in the mural nodules. …”
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Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images by Jamal Alsamri, Hamed Alqahtani, Ali M. Al-Sharafi, Abdulbasit A. Darem, Khalid Nazim, Abdul Sattar, Menwa Alshammeri, Ahmad A. Alzahrani, Marwa Obayya

“…Machine learning (ML) and deep learning (DL) have aided the classification and collection of patterns in data, foremost in the growth of AI methods employed in numerous haematology fields. …”
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Robust zero-watermarking for color images using hybrid deep learning models and encryption by Hager A. Gharib, Noha M. M. Abdelnapi, Khalid M. Hosny

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Energy Efficiency in Measurement and Image Reconstruction Processes in Electrical Impedance Tomography by Barbara Stefaniak, Tomasz Rymarczyk, Dariusz Wójcik, Marta Cholewa-Wiktor, Tomasz Cieplak, Zbigniew Orzeł, Janusz Gudowski, Ewa Golec, Michał Oleszek, Marcin Kowalski

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Comparison of the Performance of the C.45 Algorithm with Naive Bayes in Analyzing Book Borrowing at the Library Pringsewu Muhammadiyah University by Dani Wilian, Sriyanto Sriyanto

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Effect of Cathode Cooling in Three-Dimensional Simulations of an Atmospheric Pressure Glow Discharge by Valentin Boutrouche, Juan Pablo Trelles

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Contactless Detection of Abnormal Breathing Using Orthogonal Frequency Division Multiplexing Signals and Deep Learning in Multi-Person Scenarios by Muneeb Ullah, Xiaodong Yang, Zhiya Zhang, Tong Wu, Nan Zhao, Lei Guan, Malik Muhammad Arslan, Akram Alomainy, Hafiza Maryum Ishfaq, Qammer H. Abbasi

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A High-Efficient Method for Synthesizing Multiple Antenna Array Radiation Patterns Simultaneously Based on Convolutional Neural Network by Shiyuan Zhang, Chuan Shi, Ming Bai

“…The results demonstrate that this method offers the advantage of computational efficiency for simultaneous synthesis of multiple incoherent radiation patterns.…”
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Application of a Sparsity Pattern and Region Clustering for Near Field Sparse Approximate Inverse Preconditioners in Method of Moments Simulations by Carlos Delgado, Javier Moreno, Felipe Cátedra

“…A distance parameter is used to determine the sparsity pattern of the preconditioner. The rows of the preconditioner are computed in groups at a time, according to the number of unknowns contained in each region of the geometry. …”
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Exploring spatial–temporal evolution patterns of urban heat islands in summer and winter: evidence from a megacity of China by Nuocheng Yang, Chunyan Lu, Ling Ouyang, Riqing Chen, Weidong Man, Zili Wang, Jingwen Lin, Qianru Yu, Ziqi Li

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A Multi-Kernel Mode Using a Local Binary Pattern and Random Patch Convolution for Hyperspectral Image Classification by Wei Huang, Yao Huang, Zebin Wu, Junru Yin, Qiqiang Chen

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Exploring trans-regional harvesting operation patterns based on multi-scale spatiotemporal partition using GNSS trajectory data by Daoye Zhu, Boyong Xiao, Haoling Xie, Dong Li, Haitong He, Weixin Zhai

“…Current research focuses solely on administrative divisions, overlooking the links between machinery movement, natural spatial patterns, and spatiotemporal dependencies. The direct clustering of GNSS points is inefficient and incurs substantial computational costs. …”
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Early-life snack and drink consumption patterns among children: findings from a U.S. birth cohort study by Samantha Manning, Ahmed Alkadi, Ying Meng, Hongzhe Xu, Tong Tong Wu, Jin Xiao

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Investigation of combustion patterns in furnace type chemical reactor with non-stoichiometric combustion of fuel in the Ansys CFX software package by P. A. Batrakov, D. G. Mumladze

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Core Concepts Behind Quadripartitioned Neutrosophic Soft Block Matrices by S. Ramesh Kumar, A. Stanis Arul Mary

“…The model proves especially valuable for complex decision-making in artificial intelligence, pattern recognition, and fuzzy logic, handling multiple uncertainty layers. …”
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Illumination Invariant Face Recognition using SQI and Weighted LBP Histogram by Mohsen Biglari, Faezeh Mirzaei, Hossein Ebrahimpour-Komleh

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Evaluating the Impact of Replay-Based Continual Learning on Long-Term sEMG Pattern Recognition in Instance-Incremental Learning by Yuto Okawa, Suguru Kanoga, Takayuki Hoshino, Shin-Nosuke Ishikawa

“…The field of surface electromyogram (sEMG)-based human-computer interfaces is rapidly evolving through the integration of wearable sensors and deep learning models. …”
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