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  1. 201

    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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  2. 202

    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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  3. 203

    Refined matrix completion for spectrum estimation of heart rate variability by Lei Lu, Tingting Zhu, Ying Tan, Jiandong Zhou, Jenny Yang, Lei Clifton, Yuan-Ting Zhang, David A. Clifton

    Published 2024-08-01
    “…Heart rate variability (HRV) is an important metric in cardiovascular health monitoring. …”
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  4. 204

    NIRSpredict: a platform for predicting plant traits from near infra-red spectroscopy by Axel Vaillant, Grégory Beurier, Denis Cornet, Lauriane Rouan, Denis Vile, Cyrille Violle, François Vasseur

    Published 2024-11-01
    “…Summary Near-infrared spectroscopy (NIRS) has become a popular tool for investigating phenotypic variability in plants. We developed the Shiny NIRSpredict application to get predictions of 81 Arabidopsis thaliana phenotypic traits, including classical functional traits as well as a large variety of commonly measured chemical compounds, based from near-infrared spectroscopy values based on deep learning. …”
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  5. 205

    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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  6. 206

    An Algorithm for the Conditional Distribution of Independent Binomial Random Variables Given the Sum by Kelly Ayres, Steven E. Rigdon

    Published 2025-06-01
    “…The acceptance probability in the MH algorithm always involves the probability mass function of the proposal distribution. For the random walk MH algorithm, we take this distribution to be uniform across all possible proposals. …”
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  7. 207
  8. 208

    ANALYSIS OF SOME ECONOMIC VARIABLES IN SLOVENIAN FARMS USING FADN DATASET by Nicola GALLUZZO

    Published 2017-01-01
    “…The purpose of this paper was to investigate by a quantitative approach, over the time 2004-2013, in the FADN dataset main correlations among different economic variables, such as financial subsidies allocated by the CAP on Slovenian farms stratified in function of the main typology of farming which is a dummy variable of the productive specialization. …”
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  9. 209
  10. 210

    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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  11. 211

    Effects of Peanut Processing on Masticatory Performance during Variable Appetitive States by Fiona McKiernan, Richard D. Mattes

    Published 2010-01-01
    “…To explore the relationship between peanut form and processing and masticatory function. Subjects/Methods. Thirty nine adults (16 M, 23 F; BMI: 30.4±4.0 kg/m2; age: 27±8 y) with healthy dentition chewed four different forms of peanuts until they would normally swallow and then expectorated the bolus. …”
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  12. 212

    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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  13. 213

    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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  14. 214

    Intelligent trajectory tracking algorithm for autonomous robots under membrane computing by YAO Jiangyun, WU Fangyuan

    Published 2024-08-01
    “…Finally, based on the multi-step parallel membrane structure, a feasible autonomous robot trajectory path was found, and a sliding mode variable structure function was used to design the control rate. …”
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  15. 215

    Factors associated with high glucose variability in patients with type 1 diabetes by V. V. Klimontov, Ju. F. Semenova, A. I. Korbut

    Published 2022-10-01
    “…BACKGROUND: High glucose variability (GV) is recognized as a risk factor for vascular diabetic complications and hypoglycemia. …”
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  16. 216
  17. 217

    Price discovery and market efficiency of cardamom in India by A.N. Vijayakumar

    Published 2022-02-01
    “…Besides, this study did not find the role of cardamom futures contracts intended to serve the economic function of price discovery and price risk management. …”
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  18. 218

    Multivariate Spatial Autoregressive Model with Latent Variables: Application to Economic Growth Modeling by Anik Anekawati, Purhadi, Mohammad Rofik

    Published 2025-10-01
    “…Therefore, this research developed a model that involved multivariate data, latent variables, and spatial data, specifically spatial autoregressive, in the form of a multivariate spatial autoregressive model that involves latent variables (MSAR-VLs). …”
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  19. 219

    Variable Structure Control and Its Ground Experimental Test for the Space Station Robot by Feilong Zhang, Bi Zhang, Bing Han, Danyang Qu, Xingang Zhao

    Published 2022-01-01
    “…To save cost and improve the efficiency of the test, this paper develops a plan in which controllers undergo preliminary testing in a 6-DOF industrial robot. …”
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  20. 220

    Exploring the impact of AI on employee self-competence performance key variables and outcomes by Anas Amayreh, Mohammad A. Ta’Amnha, Ihab K. Magableh, Maher H. Mahrouq, Salsabila Aisyah Alfaiza

    Published 2025-07-01
    “…Abstract In the dynamic business world, organizations must upgrade their functioning and develop human resources skills to achieve optimal performance. …”
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