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  1. 101

    A joint learning approach for automated diagnosis of keratinocyte carcinoma using optical attenuation coefficients by Lei Zhang, Xiaoran Li, Wen Chen, Yuanjie Gu, Hao Wu, Zhong Lu, Biqin Dong

    Published 2025-04-01
    “…By incorporating probability distribution function (PDF) information alongside OAC images, the model achieved an accuracy of over 80% and approaching 100% by utilizing 3D OAC data to enhance robustness. …”
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  2. 102

    Experimental Study: Stress Path Coefficient in Unconsolidated Sands: Effects of Re-Pressurization and Depletion Hysteresis by Sabyasachi Prakash, Michael Myers, George Wong, Lori Hathon, Duane Mikulencak

    Published 2024-12-01
    “…It investigates the variability of horizontal stress path coefficient as a function of changing pore pressure (depressurization and re-pressurization) in unconsolidated sandstone reservoirs. …”
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  3. 103

    Carotid Intima-Media Thickness and Visit-to-Visit HbA1c Variability Predict Progression of Chronic Kidney Disease in Type 2 Diabetic Patients with Preserved Kidney Function by Akiko Takenouchi, Ayaka Tsuboi, Miki Kurata, Keisuke Fukuo, Tsutomu Kazumi

    Published 2016-01-01
    “…Subclinical atherosclerosis and long-term glycemic variability predict deterioration of chronic kidney disease (as defined by incident or worsening CKD) in type 2 diabetic patients with preserved kidney function.…”
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  4. 104

    Evaluation of remote sensing soil moisture data products with a new approach to analyse footprint mismatch with in-situ measurements by Qiuxia Xie, Li Jia, Massimo Menenti, Qiting Chen, Jingxue Bi, Yonghui Chen, Chunmei Wang, Xinju Yu

    Published 2024-12-01
    “…SMAP L3.0, ASCAT V3.0, ESA/CCI V7.1 and GLDAS V2.2) are vital for applications in hydrology, climate variability, and agriculture. This study uses a new SSM evaluation approach by combining temporal evolution, Coefficient of Variation (CV), Cumulative Distribution Function (CDF), evaluation metrics, and Triple Collocation Analysis (TCA) to assess SSM accuracy and spatial–temporal variability, particularly the impact of footprint mismatch when comparing retrieved SSM with in-situ measurements. …”
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  5. 105

    Resolving structural variability in network models and the brain. by Florian Klimm, Danielle S Bassett, Jean M Carlson, Peter J Mucha

    Published 2014-03-01
    “…Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. …”
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  6. 106
  7. 107

    Multiyear Measurements of the Aerosol Absorption Coefficient Near the Surface in a Small-Sized Urban Area in Portugal by Sérgio Nepomuceno Pereira, Frank Wagner, Ana Maria Silva

    Published 2014-01-01
    “…Also, a strong negative correlation between the aerosol absorption coefficient and the wind speed was verified, and an exponential decay function was found to fit very well to the data. …”
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  8. 108

    Effects of Mental Fatigue on Gait Performance and Variability by Ali Zardosht, Jessie Daw, Lee T Atkins, C Roger James, Hyung Suk Yang

    Published 2025-01-01
    “…OBJECTIVES Mental fatigue has been shown to negatively impact physical performance, including motor skills and neuromuscular function. This study aimed to investigate the effects of mental fatigue on gait performance and variability in healthy young male adults. …”
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  9. 109
  10. 110

    Bio-optical variability of particulate matter in the Southern Ocean by Juan Li, Juan Li, David Antoine, David Antoine, Yannick Huot

    Published 2024-10-01
    “…Here, we combined field measurements from hydrographic casts from two research voyages and from autonomous profiling floats (BGC-Argo) to examine particulate bio-optical properties and relationships among several ecologically and optically important variables, namely the phytoplankton chlorophyll a concentration (Chl), the particulate absorption coefficient (ap), the particulate backscattering coefficient (bbp), and the particulate organic carbon (POC) concentration. …”
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  11. 111

    Spatial variability of the snow depth on mountain slope in Svalbard by P. A. Chernous, N. I. Osokin, R. A. Chernov

    Published 2018-09-01
    “…The study was carried out to estimate the spatial variability of snow cover depths in avalanche centers of the mountain slopes of Svalbard. …”
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  12. 112

    The Zhegalkin Polynomial of Multiseat Sole Sufficient Operator by Leonid Y. Bystrov, Egor V. Kuzmin

    Published 2023-06-01
    “…The value of it allows one to determine the self-duality of a Boolean function. It is proved that the preserving 0 and 1 or preserving neither 0 nor 1 Boolean function is self-dual if and only if the dual remainder of its corresponding Zhegalkin polynomial is equal to 0 for any sets of function variable values. …”
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  13. 113

    Exploring the Differential Geometry of Reliability Function: Insights from Lifetime Weibull Distributions Under Neutrosophic Environment by Nada Mohammed Abbas, Ghazi Abdullah, Ahmed Hadi Hussain

    Published 2025-06-01
    “…Also, we discuss the same results in a neutrosophic environment, with neutrosophic variables and coefficients from the neutrosophic real ring R(I), where we get similar results of the original approach. …”
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  14. 114

    Related factors and prognostic significance of predialysis blood pressure variability by LV Yu-feng, DONG Hai-xia

    Published 2018-01-01
    “…Objective To study the clinical variables that may plausibly influence predialysis systolic blood pressure variability(SBPV),and to investigate the correlations of predialysis SBPV with all-cause mortality in patients receiving prevalent maintenance hemodialysis(MHD).Methods A total of 50 patients were enrolled in the study.All the blood pressure values before each dialysis were recorded between March and May in 2011.The mean systolic pressure(SBP)was calculated,and SBPV was estimated with the coefficient of variability.During the three months,clinical data and related biochemical parameters were collected,and echocardiography was carried out to detect cardiac structure and function.Death events were recorded during the next five years.Results The predialysis SBPV was 8.5% ±2.1%.SBPV showed a positive correlation with the age,body mass index(BMI)and left atrial diameter(LAD)(P<0.05 for all).Meantime,SBPV showed a negative correlation with the serum creatinine(SCr),average DBP,parathyroid hormone(PTH),doses of calcium carbonate and activated vitamin D(P<0.05).Patients with diabetes mellitus(DM),coronary artery disease(CAD)or taking alfablocker had higher SBPV(P<0.05).SBPV was used as a variate for conducting the multiple linear regression analysis,after adjustment,the seven variables of age,DM,CAD,BMI,LAD,SCr and taking alfa-blocker maintained their associations with predialysis SBPV(P<0.05).The equation of R~2=0.630.During 5 years of follow-up,12 patients died(24.0%).The Kaplan-meier survival analysis showed that the predialysis SBPV elevation was associated with the mortality rate(P<0.01).Conclusions Advanced age,the history of DM and/or CAD,lower SCr,higher BMI and LAD,and taking alpha-blocker were the independent risk factors of increased predialysis SBPV.The predialysis SBPV increase is associated with all-cause mortality in patients given prevalent MHD.…”
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  15. 115

    Inter-phantom variability in digital mammography: implications for quality control by Gisella Gennaro, Gilberto Contento, Andrea Ballaminut, Francesca Caumo

    Published 2025-04-01
    “…Variability was assessed by calculating intra- and inter-phantom variances and coefficients of variation (COVs). …”
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  16. 116

    Modeling the Impact of Fabrication Variabilities on the Performance of Silicon Avalanche Photodetectors by David Liu, Luca F. Errico, Matteo G. C. Alasio, Mike Zhu, Enrico Bellotti

    Published 2024-01-01
    “…This work presents a systematic study of the sensitivities of silicon avalanche photodiode (APD) performance metrics, including gain, excess noise, and bandwidth, to potential variabilities in the fabrication process. The APDs simulations are performed using a state-of-the-art Full-Band Monte Carlo (FBMC) device simulator with the integrated band structure and scattering rates calculated <inline-formula><tex-math notation="LaTeX">$\mathit{ab{-}initio}$</tex-math></inline-formula> with density-functional theory (DFT). …”
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  17. 117

    A novel extraction model optimization with effective separation coefficient for rare earth extraction process using improve differential evolution by Fangping Xu, Hui Yang, Jianyong Zhu, Wenjia Chang

    Published 2025-04-01
    “…This model also facilitates the construction of an optimized objective function for determining the effective separation coefficient. …”
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  18. 118

    Methods of evaluating maturity level of the organization based on fuzzy modeling by Lyudmila Viktorovna Borisova, Lyubov Azatovna Dimitrova, Inna Nikolaevna Nurutdinova

    Published 2017-03-01
    “…Membership functions of all the linguistic variables are developed according to the estimates of four experts for which purpose the typical trapezoidal functions are used. …”
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  19. 119

    A study on the effect of spatially variation rainfall on urban flooding by Jinping Zhang, Ruyu Wang, Xuechun Li, Zhiwei Li, Yao Wang, Xi Zhang

    Published 2025-12-01
    “…A three-dimensional probabilistic model, incorporating the variation coefficient, total rainfall, and flooding risk, was constructed using the Copula function. …”
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  20. 120

    Heart Rate Variability Time-Domain Analysis Across Glaucoma Subtypes by Yuto Yoshida, Hinako Takei, Misaki Ukisu, Keigo Takagi, Masaki Tanito

    Published 2025-04-01
    “…This study aimed to investigate the association between different glaucoma subtypes and the following time-domain heart rate variability (HRV) parameters: the standard deviation of normal-to-normal intervals (SDNN), the square root of the mean of the sum of the squared differences between adjacent normal-to-normal intervals (RMSSD), and the coefficient of variation of R-R intervals (CVRR). …”
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