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  1. 121

    Quantitative Prediction of Protein Content in Corn Kernel Based on Near-Infrared Spectroscopy by Chenlong Fan, Ying Liu, Tao Cui, Mengmeng Qiao, Yang Yu, Weijun Xie, Yuping Huang

    Published 2024-12-01
    “…Near-infrared spectral data from different varieties of maize grain powder were collected, and quantitative analysis of protein content was conducted using Partial Least Squares Regression (PLSR), Support Vector Machine (SVM), and Extreme Learning Machine (ELM) models. …”
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  2. 122

    Runoff Variations and Quantitative Analysis in the Qinghai Lake Basin Under Changing Environments by Li Mo, Xinxiao Yu, Yonghan Feng, Tao Jiang

    Published 2025-04-01
    “…The elasticity coefficient of runoff with respect to precipitation is significantly higher than that for other climate variables. …”
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  3. 123
  4. 124

    HPLC Quantitative Analysis of Main Stilbenes and Flavones in Different Parts of Matteuccia struthiopteris by Shubei Li, Dong Zhang, Lan Yang, Yujie Li, Xiaoxin Zhu, Eva Kmoníčková, Zdeněk Zídek

    Published 2013-01-01
    “…A simple and accurate HPLC-UV method was developed for the simultaneous quantitative analysis of main stilbenes and flavones in different parts (fronds, rhizomes, and frond bases) of M. struthiopteris. …”
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  5. 125

    Risk Factors for Stable and Intimate Interpersonal Relationships: A Qualitative-quantitative Methodology by Behrooz Faridmarandi, Saeid Komasi

    Published 2025-01-01
    “…., detachment manifestations) using a quantitative methodology. Materials and Methods: Thematic and content analysis methods were used to identify the experiences and perspectives of seven nonclinical and four clinical adults through semi-structured interviews (study I). …”
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  6. 126

    Research on quantitative identification of mine water inflow based on multivariate statistical analysis by Huai WANG, Xinyi WANG, Hongwei MENG, Tong XI, Peng LIU, Zihan WANG

    Published 2025-05-01
    “…Therefore, integrating multivariate statistical analysis techniques can achieve quantitative identification of water gushing sources.…”
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  7. 127
  8. 128

    Determination of Spearman Correlation Coefficient (r) to Evaluate the Linear Association of Dermal Collagen and Elastic Fibers in the Perspectives of Skin Injury by Naveen Kumar, Pramod Kumar, Satheesha Nayak Badagabettu, Melissa Glenda Lewis, Murali Adiga, Ashwini Aithal Padur

    Published 2018-01-01
    “…Spearman correlation coefficients (r) of collagen and elastic fibers in horizontal (H) and in vertical (V) directions (variables CV, CH, EV, and EH) were measured from the respective quantitative fraction data in 320 skin samples from 32 human cadavers collected at five selected sites over extremities. …”
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  9. 129
  10. 130

    Deep learning approaches for quantitative and qualitative assessment of cervical vertebral maturation staging systems. by Abbas Ahmed Abdulqader, Fulin Jiang, Bushra Sufyan Almaqrami, Fangyuan Cheng, Jinghong Yu, Yong Qiu, Juan Li

    Published 2025-01-01
    “…Statistical analyses evaluated the methods' performance, including the Pearson correlation coefficient, mean square error (MSE), success detection rate (SDR), precision-recall metrics, and the F1 score. …”
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  11. 131

    Performance evaluation of the high-throughput quantitative Alinity m Epstein-Barr virus assay by D. Yitzchak Goldstein, Mark M. Sasaki, Momka Narlieva, Nhi Nhan, Tianxi Liu, April Kegl, Tanjina Akter, Tanisha Dickerson, Eriel Thornton, Patricia Jim, Stephen Young, Danijela Lucic, Julie W. Hirschhorn

    Published 2025-01-01
    “…We evaluated the analytical and clinical performance of the quantitative Alinity m EBV assay for plasma sample testing on the fully automated Alinity m platform. …”
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  12. 132

    Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

    Published 2025-07-01
    “…The optimization targeted the perforation friction coefficient <italic>k</italic><sub>perf</sub> as the primary unknown variable. …”
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  13. 133

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

    Published 2024-12-01
    “…To improve radar-based quantitative precipitation estimation (QPE) methods, this study investigated the relationship between radar reflectivity (Z) and hourly rainfall intensity (R) using data from 289 precipitation events in Shanghai between September 2020 and March 2024. …”
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  14. 134
  15. 135

    Quantitative study of the impact of land use change on groundwater level in the Songnen Plain, China by Zhong Lu, Jinliang Zhang, Dengming Yan, Chaoqun Li, Guoping Lei, Zhiqiang Dong, Quanlai Ma

    Published 2025-06-01
    “…New hydrological insights for the region: The study showcased the great simulation accuracy of the MIKE SHE/MIKE 11 model in simulating the groundwater level on the Songnen Plain. The correlation coefficient (R) between different stations exceeds 0.8, and the Nash efficiency coefficient (NSE) surpasses 0.75. …”
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  16. 136

    Quantitative Determination of Ivermectin in Raw Milk Using Positive ESI LC-MS/MS by Meenakshi Dahiya, Shanta Sen, Kiran Lamba, Manjeet Aggarwal, R. K. Khandal

    Published 2010-01-01
    “…The limit of detection of the method was found to be 0.1 μg/kg and the limit of quantitation was calculated as 0.2 μg/kg. The method was found to be linear in the range of 1.0 ng/mL to 100.0 ng/mL with correlation coefficient of 0.9992 for pure calibration curve and 0.9990 for the matrix- matched calibration curve. …”
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    Liquid Chromatography/Tandem Mass Spectrometry Method for Quantitation of Cremophor EL and Its Applications by V. Vijaya Bhaskar, Anil Middha

    Published 2013-01-01
    “…The lower limit of quantitation for CrEL was 1.00 μg/mL using 50 μL plasma. …”
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  19. 139

    Quantitative Estimation of Organic Pollution in Inland Water Using Sentinel-2 Multispectral Imager by Jiayi Li, Ruru Deng, Yu Guo, Cong Lei, Zhenqun Hua, Junying Yang

    Published 2025-04-01
    “…Accuracy assessment results demonstrate good performance in the quantitative assessment of organic pollution, with a coefficient of determination (R<sup>2</sup>) of 0.79, a mean absolute percentage error (MAPE) of 13.03%, and a root mean square error (RMSE) of 0.39 mg/L. …”
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  20. 140