Marangoni Convection of Self-Rewetting Fluid Layers with a Deformable Interface in a Square Enclosure and Driven by Imposed Nonuniform Heat Energy Fluxes by Bashir Elbousefi, William Schupbach, Kannan N. Premnath

“…To achieve this, we have enhanced a central-moment-based lattice Boltzmann method (LBM) utilizing three distribution functions for tracking interfaces, computing two-fluid motions with temperature-dependent surface tension and energy transport, respectively. …”
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Deep learning approach with ConvNeXt-SE-attn model for in vitro oral squamous cell carcinoma and chemotherapy analysis by Abhay Nath, Om Roy, Priyanka Silveri, Sanskruti Patel

“…Our method applies residual connections with Squeeze-and-Excitation blocks along with hybrid attention systems and enhanced activation functions and optimization algorithms to boost gradient movement throughout feature extraction. …”
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Machine learning model and hemoglobin to red cell distribution width ratio evaluates all-cause mortality in pulmonary embolism by Dan Du, Lei Zhang, Xue Wen, Xian-Ming Zhang, Ya-dong Yuan

“…Abstract The ratio of hemoglobin (Hb) to red blood cell distribution width (RDW), known as HRR, functions as an innovative indicator related to prognosis. …”
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Fabrication effect on SLM and cast Inconel 718 properties for energy conversion by Hafiz Muzammil Irshad, Ameeq Farooq, Muhammad Ammar, Abbas Saeed Hakeem, Bilal Anjum Ahmed, Samaneh Shahgaldi, Muhammad Ali Ehsan, Khalid Askar

“…This attribute is due to ultra-fast cooling rate and high-temperature gradient during sintering of 3D-printed samples in a layer-by-layer fashion. …”
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Anticancer evaluation of Myo-inositol through carbonic anhydrase IV inhibition activity: A spectroscopic, quantum computational, topological, drug-likeness and in-silico molecular... by K. Rajkumar, V. Gokulakrishnan, S. Anand, R. Durga, G. Senthilkumar, S. Sri Karthick, R. Kayalvizhi Kothai

“…Understanding the charge distribution, localized electrons and weak interaction sites was achieved through molecular electrostatic potential surface, electron localization function, local orbital locator and reduced density gradient analyses. …”
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Disturbance intensity drives structural, compositional and diversity attributes in tropical dry forests of Central India by Satendra Kumar Rathaude, Shairq Irtiqa, P.P. Abdul Rahim, Zishan Ahmad Wani, Subashree Kothandaraman, Javid Ahmad Dar

“…Disturbance intensity plays an important role in influencing the structural and functional dynamics of ecosystems. The present study was undertaken in the tropical dry deciduous forests of Central India under varying disturbance intensities to understand their influence on structure, diversity and compositional attributes. …”
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HGCS-Det: A Deep Learning-Based Solution for Localizing and Recognizing Household Garbage in Complex Scenarios by Houkui Zhou, Chang Chen, Zhongyi Xia, Qifeng Ding, Qinqin Liao, Qun Wang, Huimin Yu, Haoji Hu, Guangqun Zhang, Junguo Hu, Tao He

“…Subsequently, an Instance Boundary Reinforcement module is established to capture the fine-grained features of garbage by combining strong gradient information with semantic information. Finally, the Slide Loss function is applied to dynamically weight hard samples arising from the complex detection environments to improve the recognition accuracy of hard samples. …”
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Regression-based leaf nitrogen concentration estimation of young Cephalotaxus hainanensis in small and imbalanced samples by Mengmeng Shi, Tian Wang, Ling Lin, Qingxue Li, Zhulin Chen, Xingjing Chen, Peng Wang, Xuefeng Wang

“…The research employed an image processing workflow to extract color and texture features, combined with data preprocessing techniques such as natural logarithmic transformation, feature selection based on Least Absolute Shrinkage and Selection Operator (LASSO), and resampling methods, especially the application of the Synthetic Minority Over-Sampling Technique for Regression with Gaussian Noise (SMOGN) and Adaptive Synthetic combined with a relevance function for regression (ADASYNR) to address critical challenges associated with small and imbalanced samples in regression. …”
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Identification of Priority Areas for Ecological Restoration at a Small Watershed Scale: A Case Study in Dali Prefecture of Yunnan Province in China by Qiyuan Zhou, Qiuping Zhu, Yu Feng, Jinman Wang

“…Integrating ecological quality and risk levels, the study area was classified into four functional zones: Zone I (high quality, high risk), Zone II (low quality, high risk), Zone III (low quality, low risk), and Zone IV (high quality, low risk). …”
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Evaluation of internal fixation stability of distal humerus C-type fractures based on musculoskeletal dynamics: finite element analysis under dynamic loading by Zhengfeng Jia, Cheng Xu, Weilu Gao, Changsen Yang, Peifu Tang, Jiantao Li

“…Results In this study, we systematically evaluated the biomechanical pattern of internal fixation of distal humerus fracture as well as the postoperative safe activity window and elucidated the enhancement path of functional recovery of distal humerus fracture utilizing AnyBody musculoskeletal dynamics analysis. …”
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Canopy‐Mediated Dynamics of Moss Communities in Primary Succession: Coupling of N2‐Fixation and Biomass Accumulation in Subalpine Forests Following Glacial Retreat by Jie Deng, Genxu Wang, Shouqin Sun, Wentian Xie, Feng Long, Zhaoyong Hu, Juying Sun, Xiangyang Sun, Thomas H. DeLuca

“…The effects of canopy cover and composition on moss productivity, photosynthesis, and N2‐fixation rates represent a dynamic set of canopy‐bottom layer interactions that may shape the structure and function of developing subalpine forest.…”
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Clinical characteristics, outcomes, and predictive modeling of patients diagnosed with immune checkpoint inhibitor therapy-related pneumonitis by Antonious Hazim, Irene Riestra Guiance, Jacob Shreve, Gordon Ruan, Damian McGlothlin, Allison LeMahieu, Robert Haemmerle, Keith Mcconn, Richard C. Godby, Lisa Kottschade, Anna Schwecke, Casey Fazer-Posorske, Tobias Peikert, Eric Edell, Konstantinos Leventakos, Ashley Egan

“…Predictive modeling was performed using gradient boosting machine learning technology, XGBoost (Chen in 1(4):1, 2015), to conduct binary classification and model reverse engineering using Shapley statistics (Lundberg and Lee in Adv Neural Inf Process Syst 30, 2017). …”
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Tale of three services: early UK experience with mavacamten treatment for hypertrophic cardiomyopathy with left ventricular outflow tract obstruction by Jane Draper, Antonio De Marvao, Robert M Cooper, Gerry Carr-White, Nabeel Sheikh, Rachel Bastiaenen, Yande Kasolo, Jason N Dungu, Edward Burford

“…Eligibility criteria included New York Heart Association (NYHA) class II–III symptoms and LVOT gradients >30 mm Hg with normal left ventricular ejection function (LVEF >55%), as per National Institute for Health and Care Excellence guidelines and product literature. …”
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Cerebral microbleeds: prevalence and relationship to clinical features in cognitive impairment with lewy body disease by Zhihong Ren, Jinghuan Gan, Zhichao Chen, Zhihong Shi, Shuai Liu, Hao Lu, Guili Zhang, Yong Ji

“…CMBs were classified as “present” or “absent” in the Gradient Recalled-Echo or Susceptibility Weighted Imaging. …”
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A machine learning-based approach for constructing a 3D apparent geological model using multi-resistivity data by Jordi Mahardika Puntu, Ping-Yu Chang, Haiyina Hasbia Amania, Ding-Jiun Lin, M. Syahdan Akbar Suryantara, Jui-Pin Tsai, Hwa-Lung Yu, Liang-Cheng Chang, Jun-Ru Zeng, Lingerew Nebere Kassie

“…Furthermore, python-based modeling and radial basis function interpolation were employed to construct the 3D resistivity model for greater flexibility and effectiveness than conventional software. …”
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Characterization and Significance of Monocytes in Acute Stanford Type B Aortic Dissection by Li Lu, Yuanhao Tong, Wenwen Wang, Yayi Hou, Huan Dou, Zhao Liu

“…Then, blood mononuclear cell (PBMC) samples were collected by Ficoll density gradient centrifugation, followed with CD14+ magnetic bead sorting. …”
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Probing Equatorial Ionospheric TEC at Sub-GHz Frequencies with Wide-Band (B4) uGMRT Interferometric Data by Dipanjan Banerjee, Abhik Ghosh, Sushanta K. Mondal, Parimal Ghosh

“…The measured <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>δ</mi><mi>TEC</mi></mrow></semantics></math></inline-formula> values are used to estimate the TEC gradient across GMRT arm antennas. We measure the ionospheric phase structure function and find a power-law slope of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>β</mi><mo>=</mo><mn>1.72</mn><mo>±</mo><mn>0.07</mn></mrow></semantics></math></inline-formula>, indicating deviations from pure Kolmogorov turbulence. …”
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Machine Learning Framework for Early Detection of Chronic Kidney Disease Stages Using Optimized Estimated Glomerular Filtration Rate by Samit Kumar Ghosh, Namareq Widatalla, Ahsan H. Khandoker

“…Conventional CKD diagnosis relies on estimated Glomerular Filtration Rate (eGFR), a measure of kidney function derived from serum biomarkers such as serum creatinine (SCr) and cystatin C (SCysC). …”
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A Novel LSTM Architecture for Automatic Modulation Recognition: Comparative Analysis With Conventional Machine Learning and RNN-Based Approaches by Sam Ansari, Soliman Mahmoud, Sohaib Majzoub, Eqab Almajali, Anwar Jarndal, Talal Bonny

“…The proposed framework is engineered to capture intricate temporal dependencies within modulated signals, leveraging a gated architecture that effectively mitigates the vanishing gradient problem. This innovation markedly improves recognition accuracy, particularly in low-SNR conditions where traditional methods are often limited. …”
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Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach by Zhengyuan Su, Huadong Jiang, Ying Yang, Xiangqing Hou, Yanli Su, Li Yang

“…Basic acoustic features (eg, Mel Frequency Cepstral Coefficients, formant frequencies, jitter, shimmer) and high-level statistical function (HSF) features (using OpenSMILE [Open-Source Speech and Music Interpretation by Large-Space Extraction] with the ComParE 2016 configuration) were extracted. …”
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