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Showing 601 - 620 results of 2,280 for search 'variable function ((coefficiency. OR coefficiency.) OR efficiency.)', query time: 0.13s Refine Results
  1. 601

    Functional role of cell classes in monkey prefrontal cortex after learning a working memory task by Amirreza Asadi, Christos Constantinidis, Mohammad Reza Daliri

    Published 2025-05-01
    “…Another broad-spiking subtype showed decreased baseline firing rate and variability, which may optimize neural coding efficiency. …”
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  2. 602
  3. 603

    Coordinated regulation of water use-efficiency-cost in a winter wheat-summer maize rotation system and optimization of water allocation strategies by Li Zhao, Congying Han, Yinong Li, Baozhong Zhang, Yulu Zheng, Jiabing Cai

    Published 2025-09-01
    “…A multi-objective nonlinear programming model was developed, incorporating triangular fuzzy numbers, accuracy functions, and credibility constraints, to balance actual yield (AY), irrigation water productivity (IWP), and total cost (TC). …”
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  4. 604
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    Innovative machine learning-based prediction of early airway hyperresponsiveness using baseline pulmonary function parameters by Hua Yang, Xingru Zhao, Zhuochang Chen, Lihong Yang, Guihua Zhao, Chenxiao Xu, Jinyi Xu

    Published 2025-08-01
    “…This study explores the potential of baseline pulmonary function parameters, particularly small airway indices, in predicting AHR and develops a machine learning-based model to improve screening efficiency and reduce unnecessary BPT referrals.MethodsThis retrospective study analyzed baseline pulmonary function data and BPT results from Henan Provincial People’s Hospital (May to September 2024). …”
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  6. 606

    Correlation between Rainfall and Runoff in Fuchun River Basin Based on Copula Functions and Kernel Density Estimation by YANG Sheng-mei, ZHU De-kang, CHENG Xiang, LI Bo, ZHU Yan-ze, MA Wen-sheng

    Published 2025-05-01
    “…The Gaussian was selected to estimate the marginal distributions of hydrological variables in the Fuchun River Basin, demonstrating higher simulation accuracy without relying on any distribution assumption.(2) By estimating the Kendall and Spearman rank correlation coefficients of the bivariate functions of Gaussian-Copula, t-Copula, Clayton-Copula, Frank-Copula, and Gumbel-Copula, and comparing them with the Kendall and Spearman rank correlation coefficients of the original observed data, it was found that Gaussian-Copula and Gumbel-Copula were closer to the observed data.(3) By calculating the Euclidean distance, the fitting performance of the Copula functions was evaluated. …”
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  9. 609

    Main indicators of the credit organizations of the Russian Federation: vectors of changes by T. V. Grishina

    Published 2017-05-01
    “…In recent years, changes in the structure of the banking system and the profi tability of operations conducted by banks. Analysis of the functioning of the system shows a reduced role of banking indicators in the formation of the Russian GDP. …”
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  10. 610

    Detecting changes in retinal function: Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement (ANSWERS). by Haogang Zhu, Richard A Russell, Luke J Saunders, Stefano Ceccon, David F Garway-Heath, David P Crabb

    Published 2014-01-01
    “…Furthermore, the spatial correlation utilised in ANSWERS was shown to improve the ability to detect deterioration, compared to equivalent models without spatial correlation, especially in short follow-up series. ANSWERS is a new efficient method for detecting changes in retinal function. …”
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  11. 611

    Machine learning predicts improvement of functional outcomes in spinal cord injury patients after inpatient rehabilitation by Mohammad Rasoolinejad, Irene Say, Peter B. Wu, Xinran Liu, Yan Zhou, Yan Zhou, Nathan Zhang, Emily R. Rosario, Daniel C. Lu, Daniel C. Lu, Daniel C. Lu

    Published 2025-08-01
    “…The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.MethodsWe conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes. …”
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  12. 612

    Polymer-Functionalized Magnetic Nanoparticles for Targeted Quercetin Delivery: A Potential Strategy for Colon Cancer Treatment by Júlia Borges de Macedo, Julia Narayana Schoroeder Bueno, Carla Cristine Kanunfre, José Ricardo de Arruda Miranda, Andris Figueiroa Bakuzis, Priscileila Colerato Ferrari

    Published 2025-04-01
    “…<b>Methods</b>: After FA-CS synthesis and 3<sup>2</sup> factorial design, polymer-functionalized MNPs were produced for quercetin loading, characterized, and evaluated by drug dissolution and cytotoxicity assay. …”
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  13. 613

    Cardiorespiratory responses and specificity of effectiveperformance in dance and pairsof dancers by Igor Soronovych, Andrii Diachenko, Georgiy Korobeynikov, Lesia Korobeinikova, Vladimir Raximov

    Published 2025-06-01
    “…The aim of the study: to identify the model characteristics of the functional reserve of elite dancers taking into account cardio-respiratory reactions. …”
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  14. 614
  15. 615

    Vibration characteristics of axially loaded tapered Timoshenko beams made of functionally graded materials by the power series method by M. Soltani

    Published 2017-07-01
    “…According to the power series method, the exact fundamental solutions are found by expressing the variable coefficients presented in motion equations including cross-sectional area, moment of inertia, material properties and the displacement components in a polynomial form. …”
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  16. 616

    Hypercubes to identify geomarkers of rapid cystic fibrosis lung disease progression by Yizi Cheng, Cole Brokamp, Erika Rasnick Manning, Elizabeth L. Kramer, Patrick H. Ryan, Rhonda D. Szczesniak, Emrah Gecili

    Published 2025-08-01
    “…Although geomarkers have been linked to pulmonary outcomes in other respiratory diseases, it is unknown which have the greatest predictive power for rapid lung function decline in CF. Methods We adapted an existing statistical procedure, which arranges candidate variables in a k-dimensional hypercube, where the hypercube forms a set of variables for a multi-stage selection process involving complex longitudinal data. …”
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  17. 617

    SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS by A. V. Panteleev, M. D. Evdokimova

    Published 2017-05-01
    “…The purpose of each task is to minimize the cost and weight of the construction. The object functions in optimization practical problem are nonlinear functions with a lot of variables and a complex layer surface indentations. …”
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  18. 618

    Exploration design for Q-learning-based adaptive linear quadratic optimal regulators under stochastic disturbances by Vina Putri Virgiani, Shiro Masuda

    Published 2025-12-01
    “…Q-learning optimizes the state-action policy by estimating the Q-function iteratively. This study proposes exploration signal design for the bias-free Q-learning algorithm that modifies the recursively defined Q-function by adding a disturbance-influenced term and utilizes an Instrumental Variable (IV) technique to resolve the bias-error issue. …”
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  19. 619

    Optimization algorithms for multivariate sampling reduction using spatial-temporal data by Tamara Cantú Maltauro, Luciana Pagliosa Carvalho Guedes, Miguel Angel Uribe-Opazo

    Published 2025-08-01
    “…ABSTRACT Knowing and defining the spatial and temporal variability of soil chemical properties becomes important for soil management. …”
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  20. 620

    Impact of a Multidisciplinary Functional Recovery Program on Post-Lung Transplant Outcomes: A One-Year Follow-Up by Diana-Lidia Tache-Codreanu, Iuliana David, Dan Corneliu Blendea, Ana-Maria Tache-Codreanu, Maria-Veronica Morcov, Andrei Tache-Codreanu, Corina Sporea

    Published 2025-06-01
    “…Lung transplantation (LT) is a life-saving procedure for patients with end-stage respiratory diseases. Functional recovery post-LT is influenced by multiple factors, including graft integration, physical rehabilitation, and individual variability. …”
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