Showing 361 - 380 results of 2,280 for search '(( variables function coefficiency. ) OR ( variable function (efficient. OR efficiency.) ))*', query time: 0.18s Refine Results
  1. 361

    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. 362

    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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  3. 363

    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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  4. 364

    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. 365

    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. 366
  7. 367

    In-depth characterization of accessory gene regulator loci and associated virulence factors in tcdA+B+ Clostridioides difficile isolates by Mansoor Kodori, Zohreh Ghalavand, Abbas Yadegar, Gita Eslami, Masoumeh Azimirad, Mohammad Reza Zali

    Published 2025-01-01
    “…The study uncovered significant variability in sporulation efficiency among isolates, with high efficiency correlating with tcdC-A genotype. …”
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  8. 368

    Association mapping for root system architecture under varying levels of phosphorus application in Brassica juncea L. Czern & Coss by Priyanka Upadhyay, Mehak Gupta, Simarjeet Kaur Sra, Gurdeep Cheema, Virender K. Sardana, Rakesh Sharda, Nitika Sandhu, Javed Akhatar, Gurpreet Kaur

    Published 2025-08-01
    “…Root system architecture (RSAr) plays a crucial role in Pi uptake from soil and thereby improving phosphorus use efficiency (PUE) of plants. Studying the genetic variability of RSAr traits across various Pi levels offers insights for enhancing crop resilience to Pi deficiency. …”
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  9. 369
  10. 370

    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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  11. 371

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

    Published 2010-01-01
    “…While no significant differences were noted in response to appetitive state, peanut form and processing had a significant influence on masticatory efficiency, as measured by proportional particle size distributions. …”
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  12. 372

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

    Published 2025-06-01
    “…While in general, random walk MH algorithms tend to outperform independence samplers, we find that in this case the independence sampler is more efficient.…”
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  13. 373

    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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  14. 374

    Jump around: Selecting Markov Chain Monte Carlo parameters and diagnostics for improved food web model quality and ecosystem representation by Gemma Gerber, Ursula M. Scharler

    Published 2024-12-01
    “…However, little information exists on how each LIM-MCMC algorithm parameter affects the degree of empirical data variability introduced into the ensemble. Further, post hoc algorithm quality diagnostics with commonly used trace plots and the coefficient of variation (CoV) rarely address critical aspects of algorithm quality, such as (1) if the returned ensemble successfully targeted the solution space distribution (stationarity), (2) correlation between ensemble solutions (mixing), and (3) if the ensemble contains enough solutions to adequately capture input data variability (sampling efficiency). …”
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  15. 375

    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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  16. 376

    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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  17. 377

    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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  18. 378

    Incorporating Neutrosophic Uncertainty in Data Envelopment Analysis by A.Almutairi, Hamiden Abd El- Wahed Khalifa, Basma E. El- Demerdash

    Published 2025-02-01
    “…In the realm of Data Envelopment Analysis (DEA), the assessment of relative efficiency has historically relied on deterministic variables. …”
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  19. 379

    Variable Structure Depth Controller for Energy Savings in an Underwater Device: Proof of Stability by João Bravo Pinto, João Falcão Carneiro, Fernando Gomes de Almeida, Nuno A. Cruz

    Published 2025-07-01
    “…Various control strategies have been proposed to enhance energy efficiency, including robust and optimal controllers, energy-optimal model predictive control, and disturbance-aware strategies. …”
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  20. 380

    A metaheuristic optimization framework inspired by virus mutations and its ability to optimize the structural design of 2D and 3D steel frames compared to other methods by Mehdi Ghasri, Hamid Reza Karimi, Abdolhamid Salarnia

    Published 2025-06-01
    “…MVPO integrates population-based exploration, simulating viral spread through intra-community interactions (guided by wavelet functions to model transmission variability) and inter-community propagation, with a two-phase mutation strategy: the first phase enhances global exploration via elongated search steps during accelerated spread, while the second phase introduces structural perturbations to escape local optima. …”
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