The use of the joint simultaneous integration methodology to measure the impact of certain macroeconomic variables on the GDP: ARDL model by Farouk Sahnoune, Salim Lagoune

“…Additionally, the study intends to identify the most significant economic variables influencing GDP in Algeria by constructing an econometric model (autoregressive model) based on economic theory and previous studies. …”
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Seasonal differences of Wyrtki Jet intraseasonal variabilities by Guojiao Cao, Tengfei Xu, Tengfei Xu, Zexun Wei, Zexun Wei

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Self-excited Pulsations and the Instability Strip of Long-period Variables: The Transition from Small-amplitude Red Giants to Semi-regular Variables by Michele Trabucchi, Giada Pastorelli

“…This is critical for model-based studies of the PL relations of evolved stars and to exploit their potential as distance and age indicators, in particular given the sensitivity of the onset of pulsation to the envelope composition. …”
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The uncertainty of estimation of doses to the bone marrow from ^89,90Sr due to the variability of the chemical composition and bone density by E. A. Shishkina, P. A. Sharagin, E. A. Tolstykh

“…The objective of this study is to assess the influence of variability of chemical composition and bone density on the results of dosimetric modeling. …”
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Effect of Climate Variables on Monthly Growth in Modeling Biological Yield of Araucaria angustifolia and Pinus taeda in the Juvenile Phase by Naiara Teodoro Zamin, Sebastião do Amaral Machado, Afonso Figueiredo Filho, Henrique Soares Koehler

“…Kuntze and of Pinus taeda L., over a six-year period, as well as verifing the contribution of these variables in the composition of the Chapman-Richards model. …”
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STANCE: a unified statistical model to detect cell-type-specific spatially variable genes in spatial transcriptomics by Haohao Su, Yuesong Wu, Bin Chen, Yuehua Cui

“…We propose STANCE, a unified statistical model for both SVGs and ctSVGs detection under a linear mixed-effect model framework that integrates gene expression, spatial location, and cell type composition information. …”
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Influence of dry-wet cycles on the strength behavior of biopolymer and fiber composite modified loess by Zherui Liang, Changgen Yan, Yihan Cao, Yuling Shi, Han Bao, Huaixin Li

“…This study proposes an innovative reinforcement method using bio-polymer and fiber composite modified loess (BFCL). Through systematic experiments including direct shear tests, quantitative crack characterization via Particle and Crack Analysis System (PCAS), and damage variable modeling, the mechanical response of BFCL under dry-wet cycles was comprehensively evaluated. …”
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An Analytical Solution for Variable Viscosity Flow in Fractured Media: Development and Comparative Analysis With Numerical Simulations by Anis Younes, Mohammad Mahdi Rajabi, Fatemeh Rezaiezadeh Roukerd, Marwan Fahs

“…Our study, recognizing these discrepancies, abandons this uniform viscosity assumption for a more realistic model of variable viscosity flow, focusing on viscous displacement scenarios. …”
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Treatment decisions and surgery variables are predictors of better physical function after total hip and knee arthroplasty: a retrospective cohort study by Janis Nikkhah, Lukas Schöner, Carlos J. Marques, Christoph M. Pros, Reinhard Busse

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Seasonal Variability of PM10 Chemical Composition Including 1,3,5-triphenylbenzene, Marker of Plastic Combustion and Toxicity in Wadowice, South Poland by Przemysław Furman, Katarzyna Styszko, Alicja Skiba, Damian Zięba, Mirosław Zimnoch, Magdalena Kistler, Anne Kasper-Giebl, Stefania Gilardoni

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The Application of Near-Infrared Spectroscopy Combined with Chemometrics in the Determination of the Nutrient Composition in Chinese <i>Cyperus esculentus</i> L. by Xiaobo Jiao, Dongliang Guo, Xinjun Zhang, Yunpeng Su, Rong Ma, Lewen Chen, Kun Tian, Jingyu Su, Tangnuer Sahati, Xiahenazi Aierkenjiang, Jingjing Xia, Liqiong Xie

“…Partial least squares regression (PLSR) was utilized to establish prediction models between NIR and chemical indicators. In addition, to further enhance the prediction performance of the models, various preprocessing and variable selection algorithms were utilized to optimize the prediction models. …”
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Modeling the Energy-dependent Broadband Variability in the Black Hole Transient GX 339–4 Using AstroSat and NICER by Hitesh Tanenia, Akash Garg, Ranjeev Misra, Somasri Sen

“…We present a spectro-timing analysis of the black hole X-ray transient GX 339–4 using simultaneous observations from AstroSat and the Neutron Star Interior Composition Explorer (NICER) during the 2021 outburst period. …”
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Optimization of variables for cadmium and copper removal using magnetic nanocomposite by Chou-Yi Hsu, Mohammed Ahmed Mustafa, Ghadir Kamil Ghadir, Pooja Bansal, Harpreet Kaur, Amjed Qasim Mohammed, Alzahraa S. Abdulwahid, Ahmed Remthan Hussein, Sahira Qasim Namaha, Ahmed Ali Ami, Usama Kadem Radi, Laith H. Alzubaidi, Ali Kazemi

“…Abstract This study aims to investigate cadmium and copper ultrasound-assisted removal efficiency on a laboratory scale using a cobalt ferrite/activated carbon (COF/AC) composite as an adsorbent. For this purpose, the effect of four independent variables (i.e., composite amount, pH, heavy metal concentrations, and ultrasound radiation time) on the performance of the cadmium and copper removal was investigated. …”
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A multidimensional machine learning framework for LST reconstruction and climate variable analysis in forest fire occurrence by Hatef Dastour, Quazi K. Hassan

“…Land Surface Temperature (LST) datasets play a crucial role in understanding the complex interplay between forest fires, climate variables, and vegetation dynamics. This study is divided into two primary parts: the first part investigates the predictive performance of a machine learning framework based on CatBoost and XGBoost models in estimating LST across different land cover classes in Alberta, Canada. …”
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Integrating Hyperspectral, Thermal, and Ground Data with Machine Learning Algorithms Enhances the Prediction of Grapevine Yield and Berry Composition by Shaikh Yassir Yousouf Jewan, Deepak Gautam, Debbie Sparkes, Ajit Singh, Lawal Billa, Alessia Cogato, Erik Murchie, Vinay Pagay

“…These data, together with the canopy state variable data, were then used as inputs for the modelling. …”
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One factor to bind them all: visual foraging organization to predict patch leaving behavior with ROC curves by Marcos Bella-Fernández, Manuel Suero Suñé, Alicia Ferrer-Mendieta, Beatriz Gil-Gómez de Liaño

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Viscosity modelling of chlorinated brines in three-component systems with a continuously variable temperature range between 293-323 K by Andrés Soto-Bubert, Rashmi Bhardwaj, Satheeshkumar Rajendran, Roberto Acevedo

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Variabilidade espacial das propriedades físicas e químicas do solo em áreas intensamente cultivadas Spatial variability of physical and chemical properties of soil in intensively c... by Gláucia de Mello, Célia R. P. Bueno, Gener T. Pereira

“…The chemical and physical variables studied were adjusted to spherical and exponential models and some of them showed semivariogram without defined structure. …”
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Effect of thermocycling on flexural strength of dental CAD/CAM ceramics of variable thicknesses and structures: an in vitro study [version 3; peer review: 1 approved, 2 approved wi... by Shahad T. Alameer, Laila Al Dehailan, Sultan Akhtar, Turki Alshehri, Nourhan M. Aly, Yousif A. Al-Dulaijan, Passent Ellakany

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Effect of thermocycling on flexural strength of dental CAD/CAM ceramics of variable thicknesses and structures: an in vitro study [version 2; peer review: 1 approved, 2 approved wi... by Shahad T. Alameer, Laila Al Dehailan, Sultan Akhtar, Turki Alshehri, Nourhan M. Aly, Yousif A. Al-Dulaijan, Passent Ellakany

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