Rapid global fitting of large fluorescence lifetime imaging microscopy datasets. by Sean C Warren, Anca Margineanu, Dominic Alibhai, Douglas J Kelly, Clifford Talbot, Yuriy Alexandrov, Ian Munro, Matilda Katan, Chris Dunsby, Paul M W French

“…This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. …”
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Strain-specific properties and T cells regulate the susceptibility to papilloma induction by Mus musculus papillomavirus 1. by Alessandra Handisurya, Patricia M Day, Cynthia D Thompson, Michael Bonelli, Douglas R Lowy, John T Schiller

“…Thus, the functional cooperation of CD4+ and CD8+ T cells is required to protect this strain. …”
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Fuzzy rank fusion of deep neural networks for weed identification in groundnut crop by Akshay Dheeraj, Rajnish Kumar Chaturvedi, Sapna Nigam, Md. Ashraful Haque, Sudeep Marwaha

“…By combining selective and variable rate spraying, the smart herbicide sprayer effectively manages herbicide amounts. …”
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Evaluating Sensitivity of the Ranking of Forest Fuel Treatments to Manager’s Risk Attitudes and the Importance of Treatment Objectives, Montana, USA by Tony Prato, Travis Paveglio

“…The conceptual framework involves (1) defining a utility function on an index that is a weighted average of fuel treatment objectives and incorporates a manager’s risk attitude; (2) using the utility function to calculate utility values for FTSs; (3) applying the stochastic efficiency with respect to a function method to utility values to obtain certainty equivalents (CEs); and (4) ranking FTSs based on statistically significant differences in median CEs for pairs of FTSs. …”
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Parameter Estimation for Line Impedance in Distribution Network Based on μPMU Data by Zitong ZHANG, Qun ZHOU, Yulin DIAN, Zichao GUAN, Yue YIN, Minrui LENG, Xueshan LIU

“…Moreover, through designed experiments the weight coefficients of the objective function and the size of the dataset are determined appropriately to reduce the influence of errors on the solution results such that the model can be solved with higher accuracy. …”
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Test–retest reliability and validity in lower limb proprioception tests using image capture technique in healthy adults by Aisuke Takahashi, Hikaru Kawana, Katsuhiro Furukawa

“…In statistical analysis, the test–retest reliability and construct validity were evaluated using intraclass correlation coefficients (ICC) and Spearman’s rank correlation coefficients. …”
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Application of Non-Linear System Model Updating Using Feature Extraction and Parameter Effects Analysis by John F. Schultze, François M. Hemez, Scott W. Doebling, Hoon Sohn

“…This provides indicators of the statistical variation associated with parameters as well as confidence intervals on the coefficients of the resulting meta-model. Also included in this method is the investigation of linear parameter effect screening using a partial factorial variable array for simulation. …”
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Reliability analysis of landing gear operation based on improved support vector machine-based decomposed-coordinated by ZHANG Lei, CHEN Junyu, FENG Jun, FENG Yunwen, LIU Lei

“…The case results show that the proposed ISVM-DC can accurately decompose and coordinate the architecture of landing gear operational failure, and efficiently construct and solve the reliability performance function.…”
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Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition by Marjan Kordani, Mohsen Bagheritabar, Iman Ahmadianfar, Arvin Samadi-Koucheksaraee

“…Statistical metrics confirmed that the proposed OMVMD-GRKR model, concerning the best efficiency in the Ahvaz (R = 0.987, RMSE = 0.761, and U95% = 2.108) and Molasani (R = 0.963, RMSE = 1.379, and U95% = 3.828) stations, outperformed the OMVMD and simple-based methods such as ridge regression (Ridge), least squares support vector machine (LSSVM), deep random vector functional link (DRVFL), and deep extreme learning machine (DELM). …”
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同轴全铰链双输出脉冲发生机构尺度综合与优化 by 杜力, 邹昌平, 冯俊, 向成宣, 黄茂林

“…In order to enhance the efficiency,stability and simplify the structure of the mechanism,the dimension synthesis of the full hinge coaxial two-output function generator is performed by using group-synthesis scheme and regarding the six-bar mechanism as the parallel mechanism of a set of basic four-bar mechanism and a set of equivalent four-bar mechanism.Firstly,a basic four-bar mechanism synthetic model is established and solved based on two position synthesis and equal instantaneous transmission ratio.Then the dimensional parameters of an equivalent four-bar mechanism（a five-bar loop） is solved by using equivalent principle of a variable link-length four-bar mechanism based on the basic four-bar mechanism.By this scheme,the dimensional synthesis of high order of motion parameter can be solved with good results,and the results show that the pulse data of the full hinge coaxial two-output function generator is only six percent.…”
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Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort. by Michelle Taylor, Andrew J Simpkin, Philip C Haycock, Frank Dudbridge, Luisa Zuccolo

“…We tested the association between 89 SNPs (identified from either published GWAS data or from functional literature) and repeated measures of alcohol consumption, separately in mothers (from ages 28-48) and offspring (from ages 15-21) who had ever reported drinking. …”
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Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology by Yurong Zhang, Wenliang Wu, Xianqing Zhou, Jun-Hu Cheng

“…The optimal model was used to visualize the dynamic distribution of these values. (3) Results: the crude fatty acid values exhibited a positive correlation with storage time, functioning as a direct indicator of soybean quality. …”
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Evaluation of Data Mining and Artificial Intelligence Methods to Predict Daily Precipitation by Yaseen Ahmed Hamaamin

“…In ANFIS modelling, for several input variables up to 6 variables, this study recommends using the grid partition method to divide variable ranges into membership functions. …”
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Clinical significance of plasma-free amino acids and tryptophan metabolites in patients with non-small cell lung cancer receiving PD-1 inhibitor: a pilot cohort study for developin... by Akihiko Kawahara, Tetsuro Sasada, Koichi Azuma, Hidenobu Ishii, Norikazu Matsuo, Takaaki Tokito, Tomoaki Hoshino, Yohei Miyagi, Huihui Xiang, Tomoyuki Tagami, Rika Kasajima, Yumiko Kato, Sachise Karakawa, Shinya Kikuchi, Akira Imaizumi, Kenta Murotani

“…Using Cox hazard analysis with these variables, a multivariate model was established to stratify patient overall survival (OS). …”
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Some comments on the assessment of students’ knowledge at the University by Darya I. Yareshchenko

“…The parametric approach consists in choosing the form of the function up to a vector of parameters and the subsequent evaluation of these coefficients by a training sample. …”
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HEART AND VESSEL REMODELING IN DIFFERENT AGE GROUPS OF PATIENTS WITH ARTERIAL HYPERTENSION by V. N. Kandilova

“…The Spearman rank correlation coefficient (r) was used to estimate the relationship between these variables. …”
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An Empirical Analysis of Herding Behavior in the Stock Market: Evidence from Various Economic and Social Conditions in Iran by Majid Aghaei

“…This approach models the response of the dependent variable to the independent variable at various quantiles, denoted as "τ," making it an effective tool for analyzing non-normal distributions. …”
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Research on digital matching methods integrating user intent and patent technology characteristics by Jianwei Yang, Yi Wang, Bonan Zang, Min Peng, George Torrens

“…Abstract The hierarchical analysis of user needs, function mapping, and the intelligent extraction and matching of related product patent technical features are crucial for seeking innovative design solutions and improving design efficiency. …”
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Improved Sliding Mode Active Disturbance Rejection Control for Single-inductance Dual-output Buck Converter by HUANG Jinfeng, ZHOU Jie

“…Based on this insight, the CRESO is formulated to estimate both state variables and total internal/external disturbances. …”
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International Natural Uranium Price Prediction Based on TF-CNN-BiLSTM Model by YANG Jingzhe, XUE Xiaogang

“…The study meticulously constructed and trained the TF-CNN-BiLSTM model using TensorFlow with the Adam optimizer and mean squared error loss function. The training process was optimized with learning rate reduction and early stopping callbacks to prevent overfitting. …”