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  1. 1701

    Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

    Published 2024-08-01
    “…The dataset included 768 instances with nine attributes, where the target variable indicated whether a patient tested positive for diabetes. …”
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  2. 1702

    Non-destructive textural quality assessment of peaches and nectarines using near-infrared spectroscopy integration time by Eva Cristina Correa, Paola Baltazar, Pilar Barreiro, Natalia Hernández-Sánchez, Lourdes Lleó, Ángela Melado-Herreros, Belén Diezma

    Published 2025-12-01
    “…A principal component analysis (PCA) was used to analyze textural variability, and discriminant function analysis (DFA) and artificial neural networks (ANNs) were applied to classify fruit firmness levels.PCA effectively defined a new variable, PC1, that captured the variance in fruit texture, correlating positively with juiciness and negatively with firmness. …”
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  3. 1703

    Optimization of medium components for the production of exopolysaccharide by Lycoperdon pyriforme Schaeff.: Pers. using response surface methodology by MA Xiaokui, JIANG Hua, LI Junzhi, CHEN Yong, HE Xiaojing

    Published 2013-09-01
    “….: Pers. is one of medicinal macro-fungi, which has become an attractive topic as a functional food and as a source for the development of drugs and nutraceuticals. …”
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    Article
  4. 1704

    Impact of Low-dose Imaging on PET Quantitative Accuracy and Image Quality by SU Xuesong, GENG Jianhua, ZHENG Rong, WANG Xuejuan

    Published 2025-02-01
    “…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. …”
    Article
  5. 1705

    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

    Published 2025-08-01
    “…By combining selective and variable rate spraying, the smart herbicide sprayer effectively manages herbicide amounts. …”
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  6. 1706

    First-principles investigation on structural, electronic, and optical properties of (Cd1-xZnx)3As2 by Yu Deng, Xun Ge, Rongxiu Feng, Yunye Liang, Xiaohao Zhou

    Published 2025-01-01
    “…Calculations on the optical properties (dielectric function, absorption coefficient) of (Cd1-xZnx)3As2 show that it behaves well in the near infrared and far infrared. …”
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  7. 1707

    Bankruptcy rules and sustainable water management: A MODSIM-NSGAII simulation multi-objective optimization framework for equitable transboundary water allocation by Bentolhoda Asl-Rousta, S. Jamshid Mousavi

    Published 2025-06-01
    “…This study addresses these challenges by introducing a new optimal bankruptcy rule (OpPro rule) through a simulation-optimization model (MODSIM-NSGAII), where MODSIM simulates the spatial and temporal variability of water resources, and the NSGA-II optimization algorithm includes two objective functions of maximizing basin-wide ecological sustainability and maximizing economic efficiency reflecting ''equitable and reasonable utilization'' of water. …”
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  8. 1708

    Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

    Published 2025-07-01
    “…The results revealed a significant negative correlation between SWHC and the smoothed leaf spectral reflectance, with the best correlation coefficient was r = − 0.59. The use of third-order derivatives and logarithmic second-order derivatives further enhanced this correlation, yielding optimal coefficients of r = − 0.78 and r = − 0.72, respectively. …”
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  9. 1709

    Enhancing Thermal–Hydraulic Performance in Nuclear Reactor Subchannels with Al<sub>2</sub>O<sub>3</sub> Nanofluids: A CFD Analysis by Mohammad A. I. Sardar, Mushfiqur Rahman, Philip Rubini

    Published 2024-11-01
    “…This analysis has been carried out using the RNG k-epsilon turbulence model with standard wall function in ANSYS FLUENT 2022R1. The impact of various flow conditions and nanofluid concentrations has been examined. …”
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  10. 1710
  11. 1711

    Correlation between Stressful Life Events and Suicidal Ideation among Patients with Schizophrenia in Remission Stage: A Cross-sectional Study by Ashok Silamban, Kailash Sureshkumar, Aravindh Manogaran, Shabeeba Z Kailash

    Published 2025-07-01
    “…Introduction: Patients with schizophrenia often exhibit impaired executive brain function, which disrupts their daily activities. Relapse in schizophrenia has been linked to stressful life events. …”
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  12. 1712
  13. 1713

    Machine learning-based prediction of pervaporation permeation using physicochemical properties of permeant-membrane and process conditions by Muhammad Mujiburohman, Marwen Elkamel, Farzad Hourfar, Ali Elkamel

    Published 2025-02-01
    “…Two types of inputs were evaluated: regular variables (Type I) and dimensionless groups derived from these regular variables (Type II). …”
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  14. 1714

    Radiotherapy-induced fatigue in Palestinian breast cancer survivors by Hussein ALMasri, Omar Rimawi

    Published 2024-12-01
    “…Our purpose is to assess, compare, and correlate CRF in breast cancer survivors undergoing radiotherapy (RT) with study variables.Methods: CRF in breast cancer survivors was assessed using Functional Assessment of Chronic Illness Therapy – Fatigue Scale (FACIT-F) (version 4). …”
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  15. 1715

    Microbially‐Mediated Soil Carbon‐Nitrogen Dynamics in Response to Future Soil Moisture Change by Wanyu Li, Gangsheng Wang, Zirui Mu, Shanshan Qi, Shuhao Zhou, Daifeng Xiang

    Published 2025-03-01
    “…Furthermore, microbes and enzymes were key drivers of soil C‐N transformations, with soil enzymes displaying the highest correlation with SSI (nonlinear correlation coefficient based on mutual information = 0.81). This study establishes a foundational relationship between soil C‐N variables and soil moisture, accounting for lag effects, to enhance our understanding of the complex responses of these variables under future climate change scenarios.…”
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  16. 1716

    OpenConMap: A Matlab toolbox for mapping the interior of the unit circle to the exterior of simple closed curves by Kai He, Kai Wang

    Published 2024-12-01
    “…The conformal mapping function from the interior of the complex plane's unit circle to the exterior of any simple closed curve on the real plane finds widespread applications, including the use of complex variable methods in elasticity studies. …”
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  17. 1717

    Numerical discussion of phase-lag mixed integral equations with general discontinuous kernels by Abeer M. Al-Bugami, M. A. Abdou

    Published 2025-05-01
    “…This integral equation has coefficients that vary in time and phase-lag time. It was proven that this method linked the time variables to the kernel of the integral equation in terms of the existence of a single solution. …”
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  18. 1718

    Interpretable machine learning for predicting isolated basal septal hypertrophy. by Lei Gao, Boyan Tian, Qiqi Jia, Xingyu He, Guannan Zhao, Yueheng Wang

    Published 2025-01-01
    “…This is a common echocardiographic finding with a prevalence of approximately 7-20%, which may indicate early structural and functional remodeling of the left ventricle in certain pathologies. …”
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  19. 1719

    Three Decades of Land Cover Dynamics in a Boreal Coastal Basin: A Multisensor Spectral Index and Machine Learning Approach Using Landsat Data and GB-SAR Data by Jinsong Zhang, Bochi Zou, Yifei Yuan, Asad Khan, Muhammad Bilawal Junaid, Qaiser Abbas, Rana Muhammad Zulqarnain, Nazih Y. Rebouh, Olga D. Kucher, Hassan Alzahrani

    Published 2025-01-01
    “…Boreal coastal habitats, with their complex hydrological, ecological, and geological functions, play a pivotal role in regulating regional climate, supporting biodiversity, and sustaining local communities. …”
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    Article
  20. 1720

    Applications of mutagenesis methods on affinity maturation of antibodies in vitro by LIU Yuan, LIN Manman, ZHANG Xiao, XU Chongxin, JIAO Linxia, ZHONG Jianfeng, WU Aihua, LIU Xianjin

    Published 2016-01-01
    “…In chain shuffling, a variable heavy or light chain of a specific antibody is recombined with a complementary variable domain library. …”
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