Fiscal Sustainability in Iran A Markov-Switching Fiscal Regime Change and Time-Varying Parameter Models Approach by Hossein Aghilifar, Khosrow Piraei, Hashem Zare, Mehrzad Ebrahimi

“…Then the Markov-switching fiscal regime change model and the time-varying parameter fiscal reaction function are estimated. Among the constant parameter linear and non-linear models, only the linear model including control variables has a significant debt-to-GDP ratio coefficient, which its sign is negative. …”
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Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…After the chemometrics related to hyperspectral imaging had been examined, the least square-support vector regression models based on the feature bands, which were selected by the shuffled frog leaping algorithm, showed the best performance, and the determination coefficients of prediction (R2P) for cherry sugar content and acidity reached 0.976 and 0.906, respectively. …”
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Approximation by interpolation spectral subspaces of operators with discrete spectrum by M.I. Dmytryshyn

“…Applications to spectral approximations of the regular elliptic operators with variable smooth coefficients in the space $L_q(\Omega)$ over an open bounded set $\Omega\subset\mathbb{R}^n$ and some self-adjoint ordinary elliptic differential operators in a bounded interval $\Omega=(a,b)$ are shown.…”
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Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals. by Antonio Rivero-Juárez, David Guijo-Rubio, Francisco Tellez, Rosario Palacios, Dolores Merino, Juan Macías, Juan Carlos Fernández, Pedro Antonio Gutiérrez, Antonio Rivero, César Hervás-Martínez

“…This study was based on the Spanish HERACLES cohort (NCT02511496) (April-September 2015, 2940 patients) and involved application of different neural network models with different basis functions (product-unit, sigmoid unit and radial basis function neural networks) for automatic classification of patients for treatment. …”
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Arterial hypertension and myocardial electric heterogeneity in patients with coronary heart disease by L. A. Leshchinsky, B. L. Multanovsky, A. G. Petrov, S. B. Ponomarev

“…Myocardial electric heterogeneity, especially in PS, correlated with left ventricular (LV) hypertrophy, LV diastolic function, and the overall functional status of cardiovascular system. …”
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Determinants of growth differentiation factor 15 plasma levels in outpatients with peripheral arterial disease by Emma Skau, Philippe Wagner, Jerzy Leppert, Johan Ärnlöv, Pär Hedberg

“…Results: The multivariable analysis identified independent relations of GDF-15 with several of the included variables (adjusted R2 = 0.48). Diabetes (beta coefficient [β] of 0.37, 95% confidence interval [95% CI] 0.25 to 0.50), low-density lipoprotein (LDL) cholesterol (β = −0.22, 95% confidence interval [CI]: −0.34 to −0.09), and physical activity (β = −0.16, 95% CI: −0.25 to −0.06) had the strongest associations. …”
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A New Four‐Component L*‐Dependent Model for Radial Diffusion Based on Solar Wind and Magnetospheric Drivers of ULF Waves by Kyle R. Murphy, Jasmine Sandhu, I. Jonathan Rae, Thomas Daggitt, Sarah Glauert, Richard B. Horne, Clare E. J. Watt, Sarah Bentley, Adam Kellerman, Louis Ozeke, Alexa J. Halford, Sheng Tian, Aaron Breneman, Leonid Olifer, Ian R. Mann, Vassilis Angelopoulos, John Wygant

“…The new models use L∗ as it accounts for adiabatic changes due to the dynamic magnetic field coupled with an optimized set of four components of solar wind and geomagnetic activity, Bz, V, Pdyn, and Sym−H, as independent variables (inputs). These independent variables are known drivers of ULF waves and offer the ability to calculate diffusion coefficients at a higher cadence then existing models based on Kp. …”
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Generalized Type-2 Fuzzy Approach for Parameter Adaptation in the Whale Optimization Algorithm by Leticia Amador-Angulo, Oscar Castillo, Patricia Melin, Zong Woo Geem

“…The efficiency of a fuzzy WOA with a GT2FLS (FWOA-GT2FLS) is highlighted by presenting the excellent results of the case study of the benchmark function optimization. …”
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Possibilities of Using Artificial Intelligence in Security Analysis by Maciej Norbert Ciesielski

“…In total, out of twelve features/variables that make up analytical imagination, artificial intelligence already functions efficiently (or will function efficiently soon) in practically all of them.…”
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Native learning ability and not age determines the effects of brain stimulation by Pablo Maceira-Elvira, Traian Popa, Anne-Christine Schmid, Andéol Cadic-Melchior, Henning Müller, Roger Schaer, Leonardo G. Cohen, Friedhelm C. Hummel

“…Brain stimulation shows potential to enhance these functions, but studies show variable effects. Previous studies have tried to identify responders and non-responders through correlations between behavioral change and baseline parameters, but results lack generalization to independent cohorts. …”
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Exercise, Training & Health by Mentz L, Winkert K, Schlegel S, Rohlmann F, Steinacker JM, Treff G

“…To this end, we evaluated it during rowing ergometer testing in elite rowers.Methods: Twenty-three elite rowers of the German National squad (10 female; age: 24.53.5 years) performed an incremental step test on a C2 rowing-ergometer modified with an external reference system (REF) allowing evaluation of stroke-to-stroke variability during rowing ergometer testing.Results: The coefficient of variation (CV) for PREF was 4.7% (95% CI [4.3, 5.3]). …”
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A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1 by E. Black, E. Black, J. Ellis, R. I. Maidment, R. I. Maidment, R. I. Maidment

“…The model presented here, General TAMSAT-ALERT, represents a significant scientific and functional advance on previous implementations. Notably, General TAMSAT-ALERT is applicable to any variable for which time series data are available. …”
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Enhanced image hash using cellular automata with sponge construction and elliptic curve cryptography for secure image transaction by M. Mohammed Ibrahim, R. Venkatesan, Nasir Ali, Muhammad Imran Qureshi, Hafiz Muhammad Afzal Siddiqui, Fikadu Tesgera Tolasa, Suhad Ali Osman Abdallah

“…The novelty of this work is that it creates synergy between the CA’s chaotic behaviour, the flexibility of sponge functions, and the lightweight but powerful security of ECC, resulting in a hash algorithm that is both secure and efficient. …”
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Seasonal and diurnal freeze–thaw dynamics of a rock glacier and their impacts on mixing and solute transport by C. Louis, L. J. S. Halloran, C. Roques

“…<p>Rock glaciers play a vital role in the hydrological functioning of many alpine catchments. Here, we investigate seasonal and daily freeze–thaw cycles of the previously undocumented Canfinal rock glacier (RG) located in the Val d'Ursé catchment (Bernina Range, Switzerland) and the RG's influence on the dynamics of the hydrogeological system. …”
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Enhancing Urban Heat Island Analysis Through Multisensor Data Fusion and GRU-Based Deep Learning Approaches for Climate Modeling by Ning Tang, Muhammad Farhan, Pir Mohammad, M. Abdullah-Al-Wadud, Saddam Hussain, Umair Hamza, Rana Muhammad Zulqarnain, Nazih Yacer Rebouh

“…The GRU-based model achieved a coefficient of determination (R²) of 0.90 with an RMSE value of 0.09, indicating robust predictive performance. …”
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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

“…Based on the above conclusions, a method for estimating the virtual inertia and droop coefficient of renewable energy with the autonomous-synchronization voltage source that meets the preset frequency dynamic safety requirements is proposed. …”
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Development and Validation of Quantile Regression Forests for Prediction of Reference Quantiles in Handgrip and Chair‐Stand Test by Giulia Giordano, Luca Mastrantoni, Francesco Landi, The Lookup 8+ Study Group

“…The predictive outputs of these models may serve as surrogate biomarkers of the aging process, capturing functional decline.…”
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Study on the Photosynthetic Physiological Responses of Greenhouse Young Chinese Cabbage (<i>Brassica rapa</i> L. <i>Chinensis Group</i>) Affected by Particulate Matter Based on Hyp... by Lijuan Kong, Siyao Gao, Jianlei Qiao, Lina Zhou, Shuang Liu, Yue Yu, Haiye Yu

“…Particulate matter affects both the light environment and air quality in greenhouses, obstructing normal gas exchange and hindering efficient physiological activities such as photosynthesis. …”
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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

“…According to the results, the WNN model with an average correlation coefficient of R2 > 0.92 for the train data set, and R2 > 0.83 for the test data set provided the most beneficial tool for evaluating the drying process of cumin seeds.…”
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Research on optimization strategies of university ideological and political parenting models under the empowerment of digital intelligence by Fan Lv

“…It constructs the no-incentive, cost-sharing, and collaborative cooperation models, respectively, and obtains the optimal trajectories for the degree of effort, the subsidy coefficient, the optimal benefit function, and the digital and intelligent technology stock. …”
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