Development of an integrated microfluidic device for cell lysis and DNA purification by Elahe Jalilvand, Amir Shamloo

“…Finally, PCR and DNA electrophoresis were performed on the purified DNA.The mixing efficiency of the system was evaluated using both computational and experimental methods. …”
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Code-based Masking: From Fields to Bits Bitsliced Higher-Order Masked SKINNY by John Gaspoz, Siemen Dhooghe

“…., elements in F2k ), limiting their applicability to ciphers where the S-box can be efficiently computed via power functions, such as AES. In this paper, we address the aforementioned limitations. …”
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Two novel deep-learning models to predict spontaneous ureteral calculi passage: Model development and validation by Zhiying Xiao, Hui Bai, Yumeng Zhang

“…The aim of this study was to develop and evaluate two deep-learning (DL) models for predicting spontaneous ureteral stone passage (SSP). …”
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Contrast-Enhanced EUS for Differential Diagnosis of Pancreatic Masses: A Meta-Analysis by Sibin Mei, Mengyu Wang, Leimin Sun

“…Though methods for the diagnosis of pancreatic masses are various, such as ultrasonography (US), computed tomography (CT), endoscopic ultrasonography (EUS), and contrast-enhanced computed tomography (CE-CT), their sensitivity, specificity, and accuracy are not quite satisfying. …”
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Influence of boundary conditions and blood rheology on indices of wall shear stress from IVUS-based patient-specific stented coronary artery simulations by R. Patrick McCarthy, Peter J. Mason, David S. Marks, John F. LaDisa

“…Our objective was to evaluate three common assumptions applied with stented coronary artery CFD simulations (inlet velocity profile, outlet boundary conditions, and viscosity) to provide insight for future studies. …”
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Transcriptome Derived Artificial neural networks predict PRRC2A as a potent biomarker for epilepsy by Wayez Naqvi, Prekshi Garg, Prachi Srivastava

“…Artificial neural networks (ANNs) are computer models that attempt to mimic the neurons present in the human brain. …”
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Transfer and deep learning models for daily reference evapotranspiration estimation and forecasting in Spain from local to national scale by Yu Ye, Aurora González-Vidal, Miguel A. Zamora-Izquierdo, Antonio F. Skarmeta

“…However, the most commonly used Penman-Monteith model (FAO56-PM) requires a large amount of input data and it is difficult to compute for general users. Machine Learning (ML) techniques can be used to address this shortcoming. …”
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Global, high-resolution, reduced-complexity air quality modeling for PM2.5 using InMAP (Intervention Model for Air Pollution). by Sumil K Thakrar, Christopher W Tessum, Joshua S Apte, Srinidhi Balasubramanian, Dylan B Millet, Spyros N Pandis, Julian D Marshall, Jason D Hill

“…However, air quality modeling typically has substantial requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. …”
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Deep Learning with Dual-Channel Feature Fusion for Epileptic EEG Signal Classification by Bingbing Yu, Mingliang Zuo, Li Sui

“…The model’s performance was evaluated on the publicly available Bonn EEG dataset. …”
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Perception aspects of a rule system for converting melodies from musical notation into sound by L. FRYDEN, J. SUNDBERG, A. ASKENFELT

“…The starting point of this project is the "mechanical" impression obtained when a computer rather than a good musician converts the musical notation into the corresponding sound sequences. …”
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Leveraging global genetics resources to enhance polygenic prediction across ancestrally diverse populations by Oliver Pain

“…Several methods now aim to leverage multiple GWAS sources, but predictive performance and computational efficiency remain unclear, particularly when individual-level tuning data are unavailable. …”
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Increased Azimuth Resolution by Extrapolating the Antenna Array Aperture Function by Least Squares Linear Prediction Estimation Using Autoregressive Model Coefficients by V. V. Vladimirov

“…The method proposed for increasing the resolution is characterized by a lower computational load, thereby being promising for practical application.…”
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Neural-Driven heuristic for strip packing trained with Black-Box optimization by Mariusz Kaleta, Tomasz Śliwiński

“…Traditional heuristics and metaheuristics struggle with generalization, efficiency, and adaptability, as they rely on predefined rules or require extensive computational effort for each new problem instance. In this paper, we propose a neural-driven constructive heuristic that leverages a lightware neural network trained via black-box optimization to dynamically evaluate item placement decisions. …”
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Validation of Replicable Pipeline 3D Surface Reconstruction for Patient-Specific Abdominal Aortic Lumen Diagnostics by Edoardo Ugolini, Giorgio La Civita, Moad Al Aidroos, Samuele Salti, Giuseppe Lisanti, Emanuele Ghedini, Gianluca Faggioli, Mauro Gargiulo, Giovanni Rossi

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Dataset for legal question answering system in the Indian judiciary contextMendeley Data by Veningston K, Apratim Mishra

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Spectral divergence prioritizes key classes, genes, and pathways shared between substance use disorders and cardiovascular disease by Everest Castaneda, Everest Castaneda, Elissa Chesler, Erich Baker

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A Trust Based Anomaly Detection Scheme Using a Hybrid Deep Learning Model for IoT Routing Attacks Mitigation by Khatereh Ahmadi, Reza Javidan

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Bind: large-scale biological interaction network discovery through knowledge graph-driven machine learning by Naafey Aamer, Muhammad Nabeel Asim, Aamer Iqbal Bhatti, Andreas Dengel

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Sequential or simultaneous-integrated boost in early-stage breast cancer patients: trade-offs between skin toxicity and risk of compromised coverage by Changyou Zhong, Minfeng Huang, Haidong Yu, Jun Yuan, Ruilian Xie, Zhenzhen Lai, Shanzhou Niu, Chunbo Tang

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Validation of oxygen saturations measured in the community by emergency medical services as a marker of clinical deterioration in patients with confirmed COVID-19: a retrospective... by John Black, Helen Pocock, Charles Deakin, Daniel Burns, Matthew Inada-Kim, Michael Boniface, Francis P Chmiel

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