Qualitative and Quantitative Computed Tomography Analyses of Lung Adenocarcinoma for Predicting Spread Through Air Spaces by Fumi Kameda, Yoshie Kunihiro, Masahiro Tanabe, Masatoshi Nakashima, Taiga Kobayashi, Toshiki Tanaka, Yoshinobu Hoshii, Katsuyoshi Ito

“…This study aimed to evaluate the preoperative computed tomography (CT) findings of primary lung adenocarcinoma in surgically resected T1 cases and to compare CT findings with and without STAS. …”
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<i>Zingiber officinale</i> Uncovered: Integrating Experimental and Computational Approaches to Antibacterial and Phytochemical Profiling by Abdel Moneim Elhadi Sulieman, Safa Mustafa Ibrahim, Mamdouh Alshammari, Fahad Abdulaziz, Hajo Idriss, Naimah Asid H. Alanazi, Emad M. Abdallah, Arif Jamal Siddiqui, Sohair A. M. Shommo, Arshad Jamal, Riadh Badraoui

“…The inhibition zones ranged from 12.87 ± 0.11 mm to 14.5 ± 0.12 mm at 30 µg/disc. The minimum inhibitory concentration ranged from 6.25 to 25 µg/mL, while the MBC ranged from 25 to 50 µg/mL. …”
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Enhancing extractive multi-documents summarization with a novel dominating set model for semantic relationship detection by Said Yunus, Cengiz Hark, Fatih Okumuş

“…In this paper, the Dominant Set-Based Extractive Text summarizing (DSETS) framework is proposed, which gives a new approach to automatic text summarizing. Utilizing the Minimum Dominant Set technique, the proposed framework creates summaries based on a word-level graphical representation that minimizes information loss while maintaining significant semantics. …”
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Two-Stage Systematic Forecasting of Earthquakes by Valery Gitis, Alexander Derendyaev

“…This study introduces an enhanced iteration of the method of the minimum area of alarm (MMAA), refined to advance earthquake forecasting technology closer to its practical application. …”
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Ground truth clustering is not the optimum clustering by Lucia Absalom Bautista, Timotej Hrga, Janez Povh, Shudian Zhao

“…Despite being NP-hard, solvers exist that can compute optimal solutions for small to medium-sized datasets. …”
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Optimizing energy and latency in edge computing through a Boltzmann driven Bayesian framework for adaptive resource scheduling by Dinesh Sahu, Nidhi, Rajnish Chaturvedi, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Idrees Alsolbi

“…Abstract This paper presents a new approach based on Boltzmann Distribution and Bayesian Optimization to solve the energy-efficient resource allocation in edge computing. It employs Bayesian Optimization to optimize the parameters iteratively for the minimum energy consumption and latency. …”
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Assessment of Anatomical Dentin Thickness in Mandibular First Molar: An In Vivo Cone-Beam Computed Tomographic Study by Sahil Choudhari, Kavalipurapu Venkata Teja, Sindhu Ramesh, Jerry Jose, Mariangela Cernera, Parisa Soltani, Emmanuel João Nogueira Leal da Silva, Gianrico Spagnuolo

“…Aim. To determine the minimum dentin thickness in the mesial and distal walls of the mesiobuccal (MB) and mesiolingual (ML) canals of the mandibular first molars using cone-beam computed tomography (CBCT). …”
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Distributed networked localization using neighboring distances only through a computational topology control approach by Xiaochu Wang, Ting Sun, Changhao Sun, Junqi Wang

“…Theoretical analyses reveal that with the proposed algorithm, any local minimum of the localization will be unstable, and the global optimum would finally be achieved with probability 1 after enough time of iterations. …”
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Effect of Ionic and Nonionic Compounds Structure on the Fluidity of Model Lipid Membranes: Computer Simulation and EPR Experiment by Dariusz Man, Barbara Pytel

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Experimental and computational optimization of sheet metal forming parameters for cylindrical cups of Al1100 and SS202 by Amit Kaimkuriya, S. Balaguru

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Hybrid System: Parallel Neural -Genetic Algorithm Algorithm for Compacting Fractal Images Using Multiple Computers by Shahla Abdel-Qader, Suzan Ibrahim, Omia Abdel-Jabbar

“…The optimum weights obtained will classify the correct search domains with the least deviation ,which, in turn ,helps decompress the images using the fractal method with the minimum time and with high resolution through multiple computers. …”
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One-pot synthesis of quercetin-functionalized silver and copper nanoparticles for enhanced optical, antimicrobial, and computational properties by Dara Muhammed Aziz, Alla Ahmed Muhammed Amin, Sangar Ali Hassan, Habibe Özmen, Gökhan Kursad INCILI, Yakup Say

“…Antibacterial assays against Escherichia coli and Staphylococcus aureus demonstrated minimum inhibitory concentrations of 2.11 ± 1.22 µg/mL and 4.69 ± 2.68 µg/mL for Qn@AgNPs, and 7.50 ± 0.00 µg/mL and 6.25 ± 0.17 µg/mL for Qn@CuNPs, significantly outperforming free quercetin (188 and 375 µg/mL). …”
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Exploring water, sanitation, and hygiene coverage targets for reaching and sustaining trachoma elimination: G-computation analysis. by Kristin M Sullivan, Emma M Harding-Esch, Alexander P Keil, Matthew C Freeman, Wilfrid E Batcho, Amadou A Bio Issifou, Victor Bucumi, Assumpta L Bella, Emilienne Epee, Segni Bobo Barkesa, Fikre Seife Gebretsadik, Salimato Sanha, Khumbo M Kalua, Michael P Masika, Abdallahi O Minnih, Mariamo Abdala, Marília E Massangaie, Abdou Amza, Boubacar Kadri, Beido Nassirou, Caleb D Mpyet, Nicholas Olobio, Mouctar D Badiane, Balgesa E Elshafie, Gilbert Baayenda, George E Kabona, Oscar Kaitaba, Alistidia Simon, Tawfik Q Al-Khateeb, Consity Mwale, Ana Bakhtiari, Daniel Westreich, Anthony W Solomon, Emily W Gower

“…<h4>Methods/findings</h4>We used g-computation to estimate the impact on the prevalence of trachomatous inflammation-follicular among children aged 1-9 years (TF1-9) when hypothetical WaSH interventions raised the minimum coverages from 5% to 100% for "nearby" face-washing water (<30 minutes roundtrip collection time) and adult latrine use in an evaluation unit (EU). …”
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The value of diagnosing coronary slow flow based on epicardial adipose tissue radiomics in chest computed tomography by Jing Tong, Libo Zhang, Guiguang Bei, Wenyuan Liu, Mingyu Zou, Yuze Li, Xiaogang Li, Yu Sun, Xinrui Wang, Jingya Zhu, Zhenguo Wang, Benqiang Yang

“…Features selected using the maximum relevance minimum redundancy and the least absolute shrinkage and selection operator were adopted to construct an EAT radiomics model. …”
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Prognostic value of computed tomography-derived fractional flow reserve in patients with diabetes mellitus and unstable angina by Qi Zhao, Li Liu, Huimin Xian, Xing Luo, Donghui Zhang, Shenglong Hou, Chao Qu, Ruoxi Zhang, Xiufen Qu

“…Abstract Background Coronary artery calcification is commonly found in patients with type 2 diabetes mellitus (T2DM), which may compromise the diagnostic accuracy of coronary computed tomography angiography (CTA). Computed tomography-derived fractional flow reserve (CT-FFR), which integrates coronary anatomy with functional assessment, holds the potential to become a powerful diagnostic tool for evaluating calcified lesions. …”
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Prediction of the Characteristics of Concrete Containing Crushed Brick Aggregate by Marijana Hadzima-Nyarko, Miljan Kovačević, Ivanka Netinger Grubeša, Silva Lozančić

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Knowledge Graph Completion With Pattern-Based Methods by Maryam Sabet, Mohammadreza Pajoohan, Mohammad Reza Moosavi

“…We use global internal information, namely patterns, by adapting the minimum-cost circulation problem to the flow network. …”
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Dynamic, symmetry-preserving, and hardware-adaptable circuits for quantum computing many-body states and correlators of the Anderson impurity model by Eric B. Jones, Cody James Winkleblack, Colin Campbell, Caleb Rotello, Edward D. Dahl, Matthew Reynolds, Peter Graf, Wesley Jones

“…The many-body ground state of the AIM is determined as the minimum over all minima of O(N_{q}^{2}) distinct charge-spin sectors. …”
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A recursive filter for a class of two-dimensional nonlinear stochastic systems by Shulan Kong, Chengbin Wang, Yawen Sun

“…A recursive filtering problem on minimum variance is investigated for a type of two-dimensional systems incorporating noise and a random parameter matrix in the measurement equation, along with random nonlinearity. …”
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Fast sparse representative tree splitting via local density for large-scale clustering by Renmin Wang, Jie Li

“…This paper proposes a novel large-scale clustering framework with three key innovations: (1) Parameter-free cluster discovery: unlike conventional methods requiring predefined cluster numbers, our algorithm autonomously identifies natural cluster structures through dynamic density-based splitting decisions. (2) Hybrid sampling-partitioning strategy: by integrating randomized sampling with K-means-based partitioning, we extract high-quality representative points that preserve data integrity with linear computational complexity. (3) Local density-driven MST segmentation: A minimum spanning tree (MST) constructed from representatives is adaptively partitioned using a local density criterion, which dynamically disconnects weakly associated edges by comparing density peaks between adjacent representative points. …”
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