Quantitative assessment of brain metabolism in mice using non-contrast MRI at 11.7T by Xiuli Yang, Yuguo Li, Hanzhang Lu, Zhiliang Wei

“…However, its application in preclinical studies, particularly with rodent animals, is constrained by the need for arterial input function measurements and on-site cyclotron facilities for tracer preparation. …”
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Quantitative analysis of the change in neuronal numerical density of the human nucleus dentatus within development by Gudović Radmila, Marić Dušica L., Krstonošić Bojana, Babović Siniša S., Ristanović Dušan, Milošević Nebojša T.

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A quantitative benchmark of neural network feature selection methods for detecting nonlinear signals by Antoine Passemiers, Pietro Folco, Daniele Raimondi, Giovanni Birolo, Yves Moreau, Piero Fariselli

“…Abstract Classification and regression problems can be challenging when the relevant input features are diluted in noisy datasets, in particular when the sample size is limited. …”
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Design of Eye Models for Quantitative Analysis of Interactions Between Ocular Aberrations and Intraocular Scattering by Feng Rao, Lin Zhang, Xinheng Zhao, Jing Li, Jie Hou, Yan Wang

“…The scattering individual eye model can be used to quantitatively investigate interaction between ocular aberrations and scattering light on retina image quality. …”
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Nonlinear Regression with High-Dimensional Space Mapping for Blood Component Spectral Quantitative Analysis by Xiaoyan Ma, Yanbin Zhang, Hui Cao, Shiliang Zhang, Yan Zhou

“…This paper proposes a nonlinear regression method with high-dimensional space mapping for blood component spectral quantitative analysis. Kernels are introduced to map the input data into high-dimensional space for nonlinear regression. …”
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Noninvasive Quantitative Compression Ultrasound Central Venous Pressure: A Clinical Pilot Study by Alex T. Jaffe, Roger Pallarès-López, Jeffrey K. Raines, Aaron D. Aguirre, Brian W. Anthony

“…Objective: This is an initial study to validate central venous pressure (CVP) measurements derived from quantitative compression ultrasound (QCU). Impact Statement: This study is the first gold standard invasive validation of CVP estimation from QCU. …”
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Quantitative and Qualitative Analysis of Atmospheric Effects on Carbon Steel Corrosion Using an ANN Model by Pasupuleti L. Narayana, Saurabh Tiwari, Anoop K. Maurya, Muhammad Ishtiaq, Nokeun Park, Nagireddy Gari Subba Reddy

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Comparing and Optimizing Four Machine Learning Approaches to Radar-Based Quantitative Precipitation Estimation by Miaomiao Liu, Juncheng Zuo, Jianguo Tan, Dongwei Liu

“…Nine QPE models were constructed using these inputs. The key findings are as follows: (1) For models with a single-variable input, the KAN deep learning model outperformed Random Forest, Gradient Boosting Decision Trees, Support Vector Machines, and the traditional Z-R relationship. (2) When six features were used as inputs, the accuracy of the machine learning models improved significantly, with the KAN deep learning model outperforming other machine learning methods. …”
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Quantitative evaluation of potentially toxic elements and associated risks in Acrisols and Ferralsols of western Ghana by Meryem El Mellouki, Ali Boularbah, Ali Boularbah, Fassil Kebede

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Automated Determination of Arterial Input Function for Dynamic Susceptibility Contrast MRI from Regions around Arteries Using Independent Component Analysis by Sharon Chen, Yu-Chang Tyan, Jui-Jen Lai, Chin-Ching Chang

“…Purpose. Quantitative cerebral blood flow (CBF) measurement using dynamic susceptibility contrast- (DSC-) MRI requires accurate estimation of the arterial input function (AIF). …”
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Quantitative Analysis of Structural Parameters Importance of Helical Temperature Microfiber Sensor by Artificial Neural Network by Juan Liu, Minghui Chen, Hang Yu, Jinjin Han, Hongyi Jia, Zhili Lin, Zhijun Wu, Jixiong Pu, Xining Zhang, Hao Dai

“…Based on the BPNN with precise prediction, the backward stepwise elimination and the holdback input randomization methods are used to quantitatively discuss the influence of the structural parameters on the output intensity of the HMF. …”
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A transient stability assessment method using quantitative analysis of key influencing factors and HGNN by YANG Kaixuan, LU Guoqiang, FU Guobin, ZHANG Wenzhao, LIU Lijun, LI Xing

“…Secondly， with doubly-fed asynchronous wind turbine generators as typical renew energy generation devices and considering their equivalent characteristics， the influence of different renewable energy proportions on the input features of transient stability assessment is quantitatively analyzed. …”
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Nonlinear Quantitative Radiation Sensitivity Prediction Model Based on NCI-60 Cancer Cell Lines by Chunying Zhang, Luc Girard, Amit Das, Sun Chen, Guangqiang Zheng, Kai Song

“…We proposed a nonlinear model to perform a novel quantitative radiation sensitivity prediction. We used the NCI-60 panel, which consists of nine different cancer types, as the platform to train our model. …”
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Quantitative differences in nourishment affect caste-related physiology and development in the paper wasp Polistes metricus. by Timothy M Judd, Peter E A Teal, Edgar Javier Hernandez, Talbia Choudhury, James H Hunt

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Falsifying computational models of endothelial cell network formation through quantitative comparison with in vitro models. by Tessa M Vergroesen, Vincent Vermeulen, Roeland M H Merks

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Reducing demand: a quantitative analysis of energy service demand indicators in sufficiency-oriented scenarios by Frauke Wiese, Carina Zell-Ziegler, Celia Burghardt, Yannick Kloos, Mirko Schäfer

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Quantification of sources and input-output pathways of heavy metals in soils from an abandoned mining watershed using Cd isotope tracing and inventory analysis by Qiumei Wu, Wenyou Hu, Kang Tian, Ya’nan Fan, Khalid Saifullah Khan, Hans Christian Bruun Hansen, Biao Huang

“…Quantitative analysis of regional-scale soil heavy metal (HM) sources presents significant challenges. …”
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Quantitative Estimates of Younger Dryas Freshening From Lipid δ2H Analysis in the Beaufort Sea by Junjie Wu, Ruediger Stein, Julian P. Sachs, Matthew Wolhowe, Kirsten Fahl, Defang You

“…Abstract The leading hypothesis attributes the Younger Dryas (YD) event to a disruption in the Atlantic Meridional Overturning Circulation, driven by meltwater input from North America. Determining the origin, timing, and magnitude of YD freshening are crucial for understanding abrupt climate change. …”
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A Machine Learning Approach to Quantitative Analysis of Enamel Microstructure from Scanning Electron Microscopy Images by Carli Marsico, Cameron Renteria, Jack R. Grimm, Juliana Fernandez‐Arteaga, Donna Guillen, Dwayne Arola

“…Here, a machine learning segmentation method is applied to images of the enamel obtained using scanning electron microscopy to support quantitative analysis of the microstructure. A pretrained convolutional neural network is used to expand the input training image dataset to allow the training of a random forest classifier, which ultimately segments the image with a very small training set (n = 3 images). …”
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Analyzing Activity of Daily Living Data Utilizing Motor Activity Log Toward Quantitative Scoring System by Mohd Azri Bin Abd Mutalib, Norsinnira Zainul Azlan, Nor Mohd Haziq Norsahperi, Ibrahim Hafizu Hassan

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