Showing 1,701 - 1,720 results of 2,280 for search '(( variable function efficient. ) OR ( variables function (coefficiency. OR efficiency.) ))', query time: 0.18s Refine Results
  1. 1701

    Minimally Invasive Surgery in Modern Medicine: A Review of Laparoscopic Techniques, Indications, and Postoperative Outcomes by Maksymilian Czarnota, Martyna Adamowicz, Aleksandra Górniak

    Published 2025-07-01
    “…Elderly and frail patients experienced lower pulmonary morbidity and faster functional return, while paediatric and fertility-preserving gynaecologic procedures maintained safety and sustained quality of life. …”
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  2. 1702

    Unveiling the corporate governance dynamics: exploring the nexus of board composition, audit committee attributes, foreign ownership, and firm performance in an emerging market by Mohd Arsh, Mohd Shamim Ansari, Gayas Ahmad, Marghoob Enam, Mosab I. Tabash, Mujeeb Saif Mohsen Al-Absy

    Published 2025-12-01
    “…This study investigates the collective impact of key corporate governance variables namely board composition, audit committee characteristics, and foreign ownership on firm performance in an emerging economy, India. …”
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  3. 1703

    Effect of Solvent and Grain Color on the Biological Activities of Maize Grain by Yolanda Salinas-Moreno, Miguel Ángel Martínez-Ortiz, Eduardo Padilla-Camberos, José Luis Ramírez-Díaz, Alejandro Ledesma-Miramontes, Ivone Alemán de la Torre, Alberto Santillán-Fernández

    Published 2025-03-01
    “…The color of maize grain, ranging from pink to purple, is related to the presence of phenolic compounds whose efficient extraction is affected by the solvent used. …”
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  4. 1704

    Meristic and morphometric comparison of an undescribed sucker of the Río Culiacán (Catostomus sp.) and Yaqui sucker (Catostomus bernardini) (Catostomidae, Teleostei) from the Sierr... by Gorgonio Ruiz-Campos, Sergio Sánchez-Gonzáles, Richard L. Mayden, Alejandro Varela-Romero

    Published 2016-06-01
    “…Likewise, the discrimination was associated with the lowest values for predorsal distance, soft posterior ocular margin to occiput, and number of anal rays. The standardized coefficients for canonical variables 1 and 2 accounted 82.6% of the total variation. …”
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  5. 1705

    A Data-Driven Approach Based on Deep Neural Network Regression for Predicting the Compressive Strength of Steel Fiber Reinforced Concrete by Nhat-Duc Hoang, Van-Duc Tran

    Published 2025-04-01
    “…Experimental results show that the L1 regularization helps achieve the most desired performance, with a coefficient of determination (R2) of roughly 0.96. Notably, an asymmetric loss function is used along with Nadam to decrease the percentage of overestimated cases from 50.83% to 27.08%. …”
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  6. 1706

    A Model-Driven Approach for Estimating the Energy Performance of an Electric Vehicle Used as a Taxi in an Intermediate Andean City by Jairo Castillo-Calderón, Daniel Cordero-Moreno, Emilio Larrodé Pellicer

    Published 2024-12-01
    “…The results demonstrated a Pearson correlation coefficient of 0.93, indicating a strong positive linear dependence between the variables. …”
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  7. 1707

    A Computational Approach to Increasing the Antenna System’s Sensitivity in a Doppler Radar Designed to Detect Human Vital Signs in the UHF-SHF Frequency Ranges by David Vatamanu, Simona Miclaus

    Published 2025-05-01
    “…In the context of Doppler radar, studies have examined the changes in the phase shift of the S<sub>21</sub> transmission coefficient related to minute movements of the human chest as a response to breathing or heartbeat. …”
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  8. 1708

    A simple model of the rheological curve of HPAM solutions at different temperatures by Eduar Pérez, Dario Alviso, Mauricio Carmona, Eduardo Manrique, Guillermo Artana

    Published 2024-12-01
    “…The solvent viscosity and relaxation time-employed as references to define these parameters-are functions of temperature. On the master surface, while the power coefficient of Carreau-Yasuda (n) exhibits only a slight dependency on temperature, the relative viscosity depends monotonically on this variable. …”
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  9. 1709

    Low-frequency rTMS modulates small-world network properties in an AVH-related brain network in schizophrenia by Lin Zhang, Li Guo, Xiaohui Liu, Jing Han, Yuanqiang Zhu, Chaozong Ma, Ye Li, Weiliang Ye

    Published 2025-04-01
    “…Resting-state fMRI data were collected before and after treatment to assess functional connectivity within the predefined 35-region AVH-related network. small-worldness (σ), normalized clustering coefficient (γ), and normalized characteristic path length (λ), as well as functional segregation (clustering coefficient [Cp], local efficiency [El]) and functional integration (global efficiency [Eg], characteristic path length [Lp])—were analyzed before and after rTMS. …”
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  10. 1710

    Feasibility and psychometric quality of smartphone administered cognitive ecological momentary assessments in women with metastatic breast cancer by Ashley M Henneghan, Emily W Paolillo, Kathleen M Van Dyk, Oscar Y Franco-Rocha, Soyeong Bang, Rebecca Tasker, Tara Kaufmann, Darren Haywood, Nicolas H Hart, Raeanne C Moore

    Published 2025-01-01
    “…Test-retest reliability was examined using intraclass correlation coefficients (ICCs) for each EMA, and Pearson's correlation were used to evaluate convergent validity between cognitive EMAs and baseline clinical cognitive and psychosocial variables. …”
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  11. 1711

    Spatially varying parameters improve carbon cycle modeling in the Amazon rainforest with ORCHIDEE r8849 by L. Zhu, L. Zhu, L. Zhu, L. Zhu, P. Ciais, Y. Yao, D. Goll, S. Luyssaert, I. Martínez Cano, A. Fendrich, A. Fendrich, L. Li, H. Yang, S. Saatchi, W. Li, W. Li

    Published 2025-08-01
    “…Current dynamic global vegetation models (DGVMs), which use one or two plant functional types for tropical rainforests, fail to capture observed biomass and mortality gradients in this region, raising concerns about their ability to predict forest responses to global change drivers. …”
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  12. 1712

    Stability analysis of the inner dump with inclined base considering anti-slip pillar by Li MA, Xinyu JIN, Qifeng ZHANG, Kaisheng JIANG, Mengbo LI, Yan HU

    Published 2024-10-01
    “…Taking the angle of inclination of the basement stratum and the discharge height of the soil disposal site as the variables for research, it was obtained that the angle of inclination of the basement stratum α or the height of the soil disposal H and the slope stability coefficient Fs were negatively correlated with the inverse proportionality function, the angle of inclination of the basement stratum had a greater influence on the slope stability, and the height of the discharge height of the soil disposal site had a second greater influence on the stability of the slope. …”
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  13. 1713

    Analysis of factors influencing the increase of extracellular water ratio in tumor patients without edema signs by Heling Zhu, Panpan Gan, Hao Jiang, Liangliang Bao, Chengjiang Liu, Jiawen Yu, Jiawen Yu

    Published 2025-08-01
    “…PA was the most influential factor among all independent variables affecting ECW/TBW (B = −1.006, p &lt; 0.001). …”
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  14. 1714

    Neurocognitive factors of new drone Pilots: Identifying candidates with expert potential by Miguel A. Ramallo-Luna, Sara Gonzalez-Torre, Álvaro Rodríguez-Mora, Gabriel G. de la Torre

    Published 2025-08-01
    “…Identifying the neurocognitive variables that influence the performance of these pilots can optimize selection and training processes. …”
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  15. 1715

    Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

    Published 2025-04-01
    “…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a backpropagation neural network (BPNN) model with a sigmoid activation function exhibited superior predictive accuracy compared to other algorithms. …”
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  16. 1716

    Correlation of the FIB-4 Liver Biomarker Score with the Severity of Heart Failure by Roxana Buzas, Paul Ciubotaru, Alexandra Corina Faur, Marius Preda, Melania Ardelean, Doina Georgescu, Patrick Dumitrescu, Daniel Florin Lighezan, Mihaela-Diana Popa

    Published 2024-11-01
    “…Statistical analysis was based on ANOVA one-way tests for continuous variables and Chi-square tests for categorical variables. …”
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  17. 1717

    Cumulative Distribution-Based Method for Pavement Performance Modeling by Chenhao Tu, Wenya Ye, Rui Zhang, Xudong Qian, Qun Yang

    Published 2024-06-01
    “…Predicting future pavement conditions accurately and efficiently helps determine the optimal maintenance time, select appropriate measures, and allocate rehabilitation funds effectively. …”
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  18. 1718

    Frequency Stability Analysis Based on Full State Model in Autonomous-Synchronization Voltage Source Interfaced Power System by Zhenyao LI, Deqiang GAN, Moude LUAN, Guoqing HE

    Published 2023-05-01
    “…Then, the parameters of the autonomous-synchronization voltage source model are compared with those of the synchronous machine model, and it is proved that the function of the governor is equivalent to increasing the system damping, which can reduce the steady-state error of the system frequency after being disturbed. …”
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  19. 1719

    Examining the Factors Affecting the Use of Crypto Assets as Foreign Payment and Investment Instruments: A Quantitative Study by Güneş Yılmaz, Tayfur Süleyman Koç

    Published 2024-09-01
    “…Along with path coefficients, f² and q² effect sizes were also analyzed to examine the interaction between the variables. …”
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  20. 1720

    Artificial Neural Network (ANN) Modeling of Plasma and Ultrasound-assisted Air Drying of Cumin Seeds by M. Namjoo, M. Moradi, M. A. Nematollahi, H. Golbakhshi

    Published 2025-03-01
    “…Therefore, the wavelet-based neural network (WNN), the multilayer perceptron neural network (MLPNN), and the radial-basis function neural network (RBFNN), as three well-known artificial neural networks models, were used to map the inputs and output data and the results were compared with the Multiple Quadratic Regression (MQR) analysis. …”
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