Unraveling the Length of Hospital Stay for Patients with Urinary Tract Infections: Contributing Factors and Microbial Susceptibility by Deema Rahme, Hania Nakkash Chmaisse, Pascale Salameh

“…Statistical analyses, including descriptive statistics, bivariate tests (<i>t</i>-tests, ANOVA, and Pearson’s correlation), and multiple linear regression (significance: <i>p</i> ≤ 0.05), were performed using IBM SPSS^® 27. …”
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Machine Learning Method for TOC Prediction: Taking Wufeng and Longmaxi Shales in the Sichuan Basin, Southwest China as an Example by Jia Rong, Zongyuan Zheng, Xiaorong Luo, Chao Li, Yuping Li, Xiangfeng Wei, Quanchao Wei, Guangchun Yu, Likuan Zhang, Yuhong Lei

“…Data can be easily updated with machine learning models, which is of primary importance for improving the efficiency of shale gas exploration and development.…”
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Structural Analysis of a Modular High-Concentration PV System Operating at ~1200 Suns by Taher Maatallah, Mussad Alzahrani, William Cameron, Katie Shanks, Souheil El Alimi, Tapas K. Mallick, Sajid Ali

“…The architecture offers a high degree of mechanical flexibility, providing each optical stage with multiple linear and angular adjustment capabilities to support precision alignment. …”
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Development and Verification of the Diagnostic Model of the Sieving Screen by Pavlo Krot, Radoslaw Zimroz, Anna Michalak, Jacek Wodecki, Szymon Ogonowski, Michal Drozda, Marek Jach

“…The considered vibrating screen is investigated on the 6-DOF (degree-of-freedom) dynamical model to reflect all linear and rotational components of spatial motion. …”
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Optimized Application of CGA-SVM in Tight Reservoir Horizontal Well Production Prediction by Chao Wang, Ruogu Wang, Yuhan Lin, Jiafei Zhang, Xiaofei Xie, Zidan Zhao, Yunlin Xu

“…Limited by the number of parameters, the traditional linear fitting method has low computational efficiency and a large error, which brings difficulties to horizontal well production prediction. …”
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Predicting layer thicknesses by numerical simulation for meniscus-guided coating of organic photovoltaics by Fabian Gumpert, Annika Janßen, Christoph J. Brabec, Hans-Joachim Egelhaaf, Jan Lohbreier, Andreas Distler

“…To achieve maximum efficiency in organic photovoltaics (OPV), functional layers with uniform and exactly predefined thickness are required. …”
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Empowering nurse leaders: readiness for AI integration and the perceived benefits of predictive analytics by Mohamed Hashem Kotp, Hossam Ali Ismail, Hassan Ahmed Awad Basyouny, Mohamed Ahmed Aly, Abdelaziz Hendy, Abdulqadir J. Nashwan, Ahmed Hendy, Aliaa Ezz Eldin Abd Elmoaty

“…Confirmatory Factor Analysis (CFA) was subsequently performed to validate the factor structure. Multiple linear regression analysis was conducted to identify significant predictors of AI readiness and perceived benefits. …”
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Key Concepts and Models of Strategic Innovation Management in Ukraine: Modern Approaches by Skrypnyk Svitlana V.

“…The research results demonstrate that traditional linear models of innovation management are losing their efficiency and are being replaced by more flexible approaches such as Agile, Lean Startup, and other iterative methods. …”
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Estimation of nitrogen uptake, biomass, and nitrogen concentration, in cover crop monocultures and mixtures from optical UAV images by Paolo Dal Lago, Nikolaos Vavlas, Lammert Kooistra, Gerlinde B. De Deyn

“…As the CC biomass is incorporated into the soil and decomposes, N is released for the following main crop. The efficiency of CC N uptake and release depends on CC quantity and quality, which can be enhanced in mixtures. …”
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Influence of internal heat source on penetrative convection in a dual-component hybrid nanofluid layer by Y.H. Gangadharaiah, Manjunatha N, M. Girinath Reddy, Maryam Ali Alghafli, Irshad Ayoob, Nabil Mlaiki

“…The system exhibits complex thermosolutal convection, influenced by double-diffusive effects, internal heat generation, and the distribution of nanoparticles. A linear stability analysis is performed using the single-term Galerkin method, which is applied to the governing equations derived under the Boussinesq approximation. …”
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Método estadístico factorial a dos niveles aplicado en los experimentos de explotación de los Simuladores. // Two levels factorial statistical method applied in experiments of Simu... by P. Moreno Quintana, J. Villar Cociña

“…The use of the factorial statistical method at two<br />levels allows the obtaining of a linear model with answer about efficiency or qualification based on the quantitative form of<br />use of diverse means of training and its combinations. …”
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Equation Built by Multiple Adaptive Regression Spline to Estimate Biological Age in Healthy Postmenopausal Women in Taiwan by Chun-Feng Chang, Ta-Wei Chu, Chi-Hao Liu, Sheng-Tang Wu, Chung-Chi Yang

“…MARS was applied, with the results compared to traditional multiple linear regression (MLR). The method with the smaller degree of estimation error was considered to be more accurate. …”
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Development of A Real-Time PCR Assay for Plasmodiophora brassicae and Its Detection in Soil Samples by Jin-ping LI, Yan LI, Yan-xia SHI, Xue-wen XIE, Chai A-li, Bao-ju LI

“…The results demonstrated that standard curve established by recombinant plasmid was shown a fine linear relationship between threshold cycle and template concentration. …”
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Performance of Cassava under Lime, Fertilizer, and Legume Intercropping on Exhausted Land in Northern Zambia by Peter Kaluba, Sydney Mwamba, Dany Pascal Moualeu-Ngangue, Martin Chiona, Kalaluka Munyinda, Etti Winter, Hartmut Stützel, Benson H. Chishala

“…Periodic measurements of leaf area index (LAI), light interception, weather data, and yield components were recorded. A linear mixed model with year as a random factor was performed to assess the treatment effect of lime, fertilizer, and legume species intercropping on cassava growth characteristics, radiation-use efficiency (RUE), and selected yield components. …”
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Multiple Atropo Selectivity by κ2‐N,O‐Oxazoline Urea Ligands in Cobaltaelectro‐Catalyzed C─H Activations: Decoding Selectivity with Data Science Integration by Philipp Boos, Neeraj Kumar Pandit, Suman Dana, Tristan von Münchow, Airu Hashidoko, Laura Haberstock, Regine Herbst‐Irmer, Dietmar Stalke, Lutz Ackermann

“…Particularly, the development of chiral ligands has significantly advanced the efficiency and selectivity of transition metal‐catalyzed enantioselective transformations. …”
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Harnessing dairy wastewater to cultivate Scenedesmus sp. for biofertilizer applications in Phaseolus vulgaris L.: a sustainable agro-biotechnological approach by Xavier Álvarez-Montero, Ingrid Mercado-Reyes, Ingrid Mercado-Reyes, Wiliam Castillo-Chamba, Efrén Santos-Ordóñez, Efrén Santos-Ordóñez

“…Transforming traditional linear production into sustainable circular processes is crucial, and integrating microalgae biomass production with wastewater recycling is a promising approach. …”
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Determination of 60 Food-Borne Stimulant Drug Residues in Animal-Derived Foods by Solid-Phase Extraction Purification and Ultra-High-Performance Liquid Chromatography-Quadrupole/Or... by Liangna He, Qiang Li, Junmei Ma, Meirong Cao, Lixin Fan, Xiaowei Ren, Guohua Shi, Yan Zhang

“…The results showed that the relative deviation of the exact mass of the 60 food-borne stimulants was less than 5.0 × 10−6, which had a good linear relationship in the corresponding concentration, and the correlation coefficient (R2) was greater than 0.9966. …”
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A Novel Transformer-Based Approach for Reliability Evaluation of Composite Systems With Renewables and Plug-in Hybrid Electric Vehicles by Chiranjeevi Yarramsetty, Tukaram Moger, Debashisha Jena, Veeranki Srinivasa Rao

“…To address these issues, this research presents an advanced mixed-integer linear programming (MILP)-based algorithm for optimizing EV charging. …”
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Novel Aggregation Framework for Electric Bus Fleet Scheduling by Maros Janovec, Milan Straka, Michal Kohani, Lubos Buzna

“…We present a mixed-integer linear problem formulation to assign vehicles to service trips and find a suitable charging schedule. …”
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Surface-Related Multiple Suppression Based on Field-Parameter-Guided Semi-Supervised Learning for Marine Data by Jiao Qi, Siyuan Cao, Zhiyong Wang, Yankai Xu, Qiqi Zhang

“…The effectiveness and efficiency of our proposed method are verified through two sets of synthetic data and one marine data example.…”
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