Estimating fine age structure and time trends in human contact patterns from coarse contact data: The Bayesian rate consistency model. by Shozen Dan, Yu Chen, Yining Chen, Melodie Monod, Veronika K Jaeger, Samir Bhatt, André Karch, Oliver Ratmann, Machine Learning & Global Health network

“…Here, we present a model-based Bayesian approach that can reconstruct contact patterns at 1-year resolution even when the age of the contacts is reported coarsely by 5 or 10-year age bands. …”
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Balancing central control and sensory feedback produces adaptable and robust locomotor patterns in a spiking, neuromechanical model of the salamander spinal cord. by Alessandro Pazzaglia, Andrej Bicanski, Andrea Ferrario, Jonathan Arreguit, Dimitri Ryczko, Auke Ijspeert

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A Novel Case Base Reasoning and Frequent Pattern Based Decision Support System for Mitigating Software Risk Factors by Muhammad Asif, Jamil Ahmed

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Healthcare Costs and Treatment Patterns of Triplet Therapies in Relapsed/Refractory Multiple Myeloma: Real World Evidence from Italy by Perrone V, Leogrande M, Giacomini E, Cappuccilli M, Degli Esposti L

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A New Approach for the Betterment of Wireless Network Performance Using Bandwidth Degradation and Ad-hoc Relaying by Maryam Monemian, Pejman Khadivi

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Flower Automata Pattern-Based Discrimination of Fibromyalgia From Control Subjects Using Fusion of Sleep EEG and ECG Signals by Prabal Datta Barua, Makiko Kobayashi, Sengul Dogan, Mehmet Baygin, Turker Tuncer, Jose Kunnel Paul, Thomas Iype, U. R. Acharya

“…The novelty of the model is the use of dynamic and interpretable feature engineering framework comprising of two innovations: 1) Flower Automata Pattern (FAP) for self-organized pattern-based feature extraction, and 2) Attention-Driven Wavelet Transform and Absolute Maximum Pooling (ADWTAMP) method for signal decomposition and compression. …”
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Internet of Things Enabled Machine Learning-Based Smart Systems: A Bird’s Eye View by Ashish Kumar Rastogi, Swapnesh Taterh, Billakurthi Suresh Kumar

“…Machine learning (ML) helps the Internet of Things (IoT) become widely used by automatically identifying data patterns and extracting important insights from the vast pool of observed data. …”
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Decoding the digital: a corpus-based study of simplifications and other translation universals in translated texts by Muhammad Afzaal, Muhammad Afzaal, Baorong Huang, Baorong Huang, Dina Abdel Salam El-Dakhs

“…This exploration discerns overarching patterns, termed translation universals, along with nuances distinctive to the computing sector. …”
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Long-Term Performance Analysis of Direct Photovoltaic Thermal-Assisted Heat Pump Water Heater Using Computational Model by Demiss Alemu Amibe, Alemayehu Tenaw Eneyaw

“…Besides, the effect of hot water consumption patterns (variability effect in three dissimilar cases constant, restaurant, and motel) on the system performance was examined. …”
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Synergistic grasp analysis: A cross-sectional exploration using a multi-sensory data glove by Subhash Pratap, Kazuaki Ito, Shyamanta M. Hazarika

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Manhattan Distance-based K-Medoids Clustering Improvement for Diagnosing Diabetic Disease by Solikhun, Muhammad Rahmansyah Siregar, Lise Pujiastuti, Mochamad Wahyudi

“…Compared to classical computers, quantum computing has the potential for an exponential speedup in problem-solving. …”
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PV<i>k</i>NN: A Publicly Verifiable and Privacy-Preserving Exact <i>k</i>NN Query Scheme for Cloud-Based Location Services by Jingyi Li, Yuqi Song, Chengliang Tian, Weizhong Tian

“…Additionally, our scheme enhances computational efficiency through optimized data-packing techniques and simplified Voronoi diagram-based ciphertext index construction, leading to substantial savings in computational and communication overheads. …”
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Numerical Investigation on the Cavitating Flow and the Cavitation-induced Noise in the Pump-jet Propeller by P. Zhang, J. Yuan, Y. Fu, X. Hou, J. Hao

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Evaluating User Interactions and Adoption Patterns of Generative AI in Health Care Occupations Using Claude: Cross-Sectional Study by Gabriel Alain, James Crick, Ella Snead, Catherine C Quatman-Yates, Carmen E Quatman

“…Understanding these organic usage patterns is key for assessing GenAI’s impact on health care delivery and patient-provider dynamics. …”
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Amplitude of Intracranial Induced Electric Fields Does Not Linearly Decrease with Age: A Computational Study of Anatomical Effects in Adults by Jianxu Zhang, Zilong Yan, Anshun Kang, Jian Ouyang, Lihua Ma, Xinyue Wang, Jinglong Wu, Dingjie Suo, Shintaro Funahashi, Wei Meng, Li Wang, Jian Zhang

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New approaches to quantifying early disorders and perfusion inhomogeneity of the myocardium according to the data of single-photon emission computed tomography by A. A. Ansheles, L. A. Martirosyan, I. V. Sergienko, V. B. Sergienko

“…None of patients had current cardiac symptoms, positive stress-test results and/or single-photon emission computed tomography (SPECT) signs of stress-induced ischemia, so only rest images were analyzed. …”
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Anomaly Detection and Root Cause Analysis in Cloud-Native Environments Using Large Language Models and Bayesian Networks by Diego Frazatto Pedroso, Luis Almeida, Lucas Eduardo Gulka Pulcinelli, William Akihiro Alves Aisawa, Ines Dutra, Sarita Mazzini Bruschi

“…Cloud computing technologies offer significant advantages in scalability and performance, enabling rapid deployment of applications. …”
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Attention Lempel-Ziv complexity: an improved Lempel-Ziv complexity with high computational efficiency for bearing early fault detection by Jiancheng Yin, Wentao Sui, Xuye Zhuang, Yunlong Sheng

“…Lempel-Ziv complexity assesses time series anomalies by quantifying the amount of novel patterns within the time series. It has been effectively utilized in assessing bearing fault severity and classification. …”
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Computational Thinking and Academic Performance Across Different Instructional Modalities in Pre‐University Courses: A Data‐Driven Study by Jorge Parraga‐Alava, Jorge Rodas‐Silva

“…ABSTRACT In preuniversity education, educators and decision‐makers need to understand how teaching methods affect student learning in computational thinking (CT). This helps identify factors influencing student outcomes and inform the development of personalized learning programs. …”
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Computational inference of co-regulatory modules from transcription factors, MicroRNAs, and their targets using CanMod2 by Ziynet Nesibe Kesimoglu, Jubair Ibn Malik Rifat, Serdar Bozdag

“…Here, we propose a computational pipeline, CanMod2, which infers modules of TFs, miRNAs, and their co-regulatory targets that are involved in a common biological process. …”
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