Data-driven modeling and regression analysis on ship resistance of in-service performance by Daehyuk Kim, Shin Hyung Rhee

“…The analysis of added resistance due to waves shows significant, but sometimes inconsistent, transfer function coefficients, suggesting simpler model structures could be more effective. …”
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Automatic detection of optic canal fractures and recognition and segmentation of anatomical structures in the orbital apex based on artificial intelligence by Yu-Lin Li, Yu-Hao Li, Mu-Yang Wei, Guang-Yu Li

“…Timely and accurate diagnosis and treatment are crucial for preserving visual function. However, diagnosing OCF can be challenging for inexperienced clinicians due to atypical OCF changes in imaging studies and variability in optic canal anatomy. …”
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RELATIONSHIP BETWEEN PRIVATE DOMESTIC INVESTMENT AND ECONOMIC GROWTH IN NIGERIA (1986-2018): AUTO-REGRESSIVE DISTRIBUTED LAG APPROACH by Isiaka Kareem JIMBA, Rosemary Bukola AJALA

“…The study incorporated other investment measures like foreign direct investment and public investment into the model, while inflation and exchange rate were taken as control variables. Secondary data was sourced from CBN statistical bulletin of various editions and was estimated using autoregressive distributed lag bound test and its coefficients. …”
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Impact of Low-dose Imaging on PET Quantitative Accuracy and Image Quality by SU Xuesong, GENG Jianhua, ZHENG Rong, WANG Xuejuan

“…Subsequently, the recovery coefficient (RC), contrast recovery coefficient (CRC), contrast-to-noise ratio (CNR), percent background variability (PBV), background coefficient of variation (BCV), and residual error (RE) of the lung insert at different image planes were calculated within the phantom. …”

Reverse Active Modification Method of Tooth Profile for RV Reducer Cycloidal Gear by Xiaotao An, Tianxing Li, Chunrong Xing, Guofeng Wang, Meng Tian

“…></graphic></alternatives></inline-formula> of the parabolic modification method are taken as the modification variables of the tooth profile, and the mathematical model of the reverse modification of the tooth profile is established with the minimum transmission error as the objective function. …”
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Words of Mouth on Destination Images and Intentions to Revisit

“…These results highlight the critical function of EWOM in reinforcing positive destination perceptions and encouraging repeat visits. …”
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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

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Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features by Ameya Harmalkar, Roshan Rao, Yuxuan Richard Xie, Jonas Honer, Wibke Deisting, Jonas Anlahr, Anja Hoenig, Julia Czwikla, Eva Sienz-Widmann, Doris Rau, Austin J. Rice, Timothy P. Riley, Danqing Li, Hannah B. Catterall, Christine E. Tinberg, Jeffrey J. Gray, Kathy Y. Wei

“…In this work, we show two machine learning approaches – one with pre-trained language models (PTLM) capturing functional effects of sequence variation, and second, a supervised convolutional neural network (CNN) trained with Rosetta energetic features – to better classify thermostable scFv variants from sequence. …”
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Importance Analysis of Vegetation Change Factors in East Africa Based on Machine Learning by Zhang Xiumei, Ma Bo, Zhang Yijie

“…The independent treatment variables were two climatic factors and five human activity factors affecting vegetation changes in East Africa. …”
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Study on a Quantitative Evaluation Method of Goaf Instability Risk of Phosphate Deposits in Layered Rock Mass by Dongfang CHEN, Mengke WANG, Dingping XU, Haiwang YE, Qizhou WANG, Jian LIU, Bin XIANG

“…The Hermite random polynomial coefficients between the input field of c and <italic>ϕ</italic>_j and the output field of the FAI are solved by the probability collocation method, establishing an explicit function expression between the probability collocation point and the FAI. …”
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Cross-sectional associations between physical activity and sedentary time with cardiovascular health in children from the ALSPAC study using compositional data analysis by K. M. Sansum, B. Bond, R. M. Pulsford, A. McManus, A. O. Agbaje, A. M. Skinner, A. R. Barker

“…Abstract This study adopted a compositional framework to cross-sectionally examine the associations between physical activity (PA) and sedentary time (ST) with vascular structure and function and clustered cardiovascular disease (CVD) risk factors in 4277 children (2,226 girls), aged 10.6±0.2 years. …”
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Strong Amplitude Modulation of Hard-band X-Ray Quasiperiodic Oscillation with Soft-band Flux in RE J1034+396 by Ruisong Xia, Hao Liu, Yongquan Xue

“…They are highly correlated, with an average cross-correlation function (CCF) peak coefficient of 0.61 and a lag of approximately 3 ks. …”
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Long-term evolution of the calibration constant on a mobile water vapour Raman lidar by P. Chazette, J. Totems, F. Laly

“…We note that the use of ground-based measurements does not introduce any more uncertainty in the lidar calibration coefficient than vertical profiles obtained by radiosondes or airborne means. …”
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Climate Change Risk, Performance, and Value Added in Agricultural Sector by Ramin Amani, Zanko Ghorbani, Zana Mozaffari

“…Results and Discussion The results of this research show that both climate change performance index variables and climate change risk have a positive and significant effect on the added value of the agricultural sector in all three functional groups and all deciles. …”
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Developing CGMap: Characterizing Continuous Glucose Monitoring Data in Patients with Type 2 Diabetes by Shuzhen Bai, Chu Lin, Xiaoling Cai, Suiyuan Hu, Jing Wu, Ling Chen, Wenjia Yang, Linong Ji

“…However, glucose variability decreased with increased BMI. Meanwhile, greater glycemic variability was associated with worse islet function, higher baseline glucose level, and higher hemoglobin.…”
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Mild Cognitive Impairment and Cardiometabolic Risk Factors in Bosnian and Herzegovinian Patients with Heart Failure by Jasna Ibrahimović-Pašić, Orhan Lepara, Amela Dervišević, Nermina Babić, Nesina Avdagić, Amina Valjevac, Asija Začiragić

“…Associations between categorical variables and correlation coefficients were assessed by the Chi-square and Spearman test, respectively. …”
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Research on the Inversion of Key Growth Parameters of Rice Based on Multisource Remote Sensing Data and Deep Learning by Jian Li, Jian Lu, Hongkun Fu, Wenlong Zou, Weijian Zhang, Weilin Yu, Yuxuan Feng

“…Dehui City in Jilin Province, China, was selected as the case study area, where multidimensional data including vegetation indices, ecological function parameters, and environmental variables were collected, covering seven key growth stages of rice. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…To overcome these challenges, this study employs the deep learning model TabNet, incorporating Digital Elevation Model (DEM) data and ERA5 meteorological variables, to fuse MERRA-2 AOD with MODIS MAIAC AOD observations. …”
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Effect of Pre-Trip Information in a Traffic Network with Stochastic Travel Conditions: Role of Risk Attitude by Yun Yu, Shiteng Zheng, Yuankai Li, Huaqing Liu, Jianan Cao

“…User equilibrium states of the two regimes have been analyzed, based on the canonical BPR travel time function with power coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi></mrow></semantics></math></inline-formula>. …”
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Three-dimensional ultrasound for carotid vessel wall volume measurement by Ying-An Chen, Pei-Ya Chen, Shinn-Kuang Lin

“…Gray-scale 3D images from the distal common carotid artery (CCA) to internal carotid artery on both sides were acquired using a single-sweep 3D transducer and analyzed offline by using the vascular plaque quantification function of the Philips QLAB software. Then, the 3D IMT(QLAB intima–media thickness [QIMT]), total plaque volume (TPV), and VWV were measured by a neurologist and a technician, and the interobserver variability was assessed. …”
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