Bayesian surrogate assisted neural network model to predict the hydrogen storage in 9-ethylcarbazole by Ahsan Ali, Mohammad Usman, Hafiz Muhammad Ali, Uzair Sajjad, Md. Abdul Aziz, M. Nasiruzzaman Shaikh

“…Correlational analysis using Pearson, Spearman, and Kendal correlations identified time (r = 0.83) as the most influential factor impacting the hydrogen storage positively, whereas catalyst dosage (r =- 0.75) exhibited a strong negative correlation. …”
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Effects of soil water on fungal community composition along elevational gradients on the northern slope of the Central Kunlun Mountains by Yongguang Zhang, Yongguang Zhang, Chaonan Li, Zhihao Zhang, Chenhong Li, Bo Zhang, Hongchen Jiang, Waqar Islam, Xiangzhen Li, Fanjiang Zeng

“…Soil fungi are essential to ecosystem processes, yet their elevational distribution patterns and the ecological mechanisms shaping their communities remain poorly understood and actively debated, particularly in arid regions. …”
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Gaseous hydrocarbons absorption by ILs: insights from artificial intelligence strategy by Reyhaneh Alborz, Mohammad Mahmoudnezhad, Alireza Baghban

“…Abstract Accurate prediction of hydrocarbon solubility in ionic liquids (ILs) is essential for optimizing solvent selection and designing efficient chemical processes in industries such as energy production and environmental remediation. …”
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Effect of Particle Size of Zinc Powder on the Efficiency of Ni-Cd Cementation in Cold Purification Reactor by P. Abbasi, K. Shayesteh, V. Vahidfard, M.J. Khani

“…These parameters are influential on cost reduction as well as the manufacturing rate of zinc ingot. …”
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Optimization of cultivation conditions of Candida catenulata in synthesizing acidic sophorolipid by F. Amiri, A. R. Habibi, M. M. Nourouzpour

“…The inoculum size was another influential factor in the fermentation process. The optimization of these factors was evaluated by the one-factor-at-a-time and the response surface methodology (RSM). …”
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Assessment of spatial cyclone surge susceptibility through GIS-based AHP multi-criteria analysis and frequency ratio: a case study from the Bangladesh coast by M. M. Abdullah Al Mamun, Li Zhang, Bowei Chen, Zahid Ur Rahman, Tarana Mahzabin, Jian Zuo, Qinglan Zhang, Syed Ahmed Reza

“…A Geographic Information Systems-based analytical hierarchy process (AHP) multi-criteria analysis and bivariate frequency ratio (FR) techniques were conducted to understand the surge susceptibility level of a cyclone-prone area on the Bangladesh coast. …”
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Multi-Criteria Analysis of a Potential Expansion of Protected Agriculture in Imbabura, Ecuador by Luis Marcelo Albuja-Illescas, Oscar Hernando Eraso Terán, Paúl Arias-Muñoz, Telmo-Fernando Basantes-Vizcaíno, Rafael Jiménez-Lao, María Teresa Lao

“…Two widely used methods were compared: the Analytical Hierarchy Process (AHP) integrated with Geographic Information Systems (GIS) and the Maximum Entropy (MaxEnt) model. …”
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Analysis of the Causal Model of the Effective Criteria on the Development of Creative Tourism in Iran by Ahmad hajarian

“…They were identified as the most effective sub-criteria, and therefore, by increasing and improving the educational classes, the field of tourism can be improved, which in turn will improve the criteria of the creative tourism process. The results of the examination of the sub-criteria related to the criterion of industries and creative products indicated that the sub-criteria of performing and visual arts with the highest value of D-R is the most influential sub-criteria of industries and creative products and creative services as the most influential sub-criteria and is placed in the disabled group. …”
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Interpretable Machine Learning for High-Accuracy Reservoir Temperature Prediction in Geothermal Energy Systems by Mohammadali Ahmadi

“…Feature importance analysis reveals that SiO₂ concentration as the most influential predictor, aligning with domain knowledge. …”
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Leveraging machine learning to evaluate the effect of raw materials on the compressive strength of ultra-high-performance concrete by Mohamed Abdellatief, G. Murali, Saurav Dixit

“…The impact of 12 influential features on CS was evaluated to optimize the performance of the proposed models. …”
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Assessment of geotechnical behavior of gypseous soil under leaching effect using machine learning by Saif M. Hassan Al-Riahi, Nur Irfah Mohd Pauzi, Mohammed Y. Fattah, Hasan Ali Abbas

“…Three machine learning models—Random Forest (RF), Support Vector Machine (SVM), and Gaussian Process Regression (GPR)—were trained to predict leaching strain, a critical indicator of collapse potential. …”
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FORMATION OF TOILET HABITS IN CHILDREN IN MOSCOW. RETROSPECTIVE STUDY RESULTS. PART II by G. A. Karkashadze, L. S. Namazova-Baranova, O. I. Maslova, A. K. Gevorkyan, S. B. Lazurenko, S. N. Zorkin, E. V. Komarova, A. K. Gevorkyan, O. I. Denisova, S. D. Polyakov, T. A. Konstantinidi

“…The selected training strategy and tactics, style of communication with a child also affect the training process. The most influential family-social factors in terms of toilet habits training processes are: two- or one-parent family, mother’s education and twins in the family.…”
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The Short Stint of a Coordinator: National Security Adviser H. R. McMaster in the Trump Administration by Mikael Blomdahl

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Optimizing Vendor Selection in Laser Cutting Services: an Evaluation Framework Using VPI and F-ANP by Hendro Prassetiyo, Said Muhammad Baisa, Arif Imran, Sri Suci Yuniar, Rangga Try Anugrah

“…This study focuses on optimizing vendor selection in laser cutting services through a comprehensive evaluation framework integrating the Vendor Performance Indicator (VPI) and the Fuzzy Analytical Network Process (F-ANP). The methodology quantifies vendor performance across five key criteria: quality, cost, delivery, flexibility, and responsiveness. …”
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User-generated content vs. firm-generated content: do consumers trust fellow consumers more than firms? Evidence from the Saudi telecommunication sector by Ghaith Al-Abdallah, Len Tiu Wright

“…This contributes to the broader discourse on content marketing and consumer trust by refining the conditions under which UGC or FGC is more influential, this research highlights that industry-specific factors play a critical role in shaping content credibility perceptions. …”
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The Identification and Prioritization of the Factors Affecting Corporate Social Responsibility Implementation in the Construction Industry—The Perspective of Developing Countries by Yunxia Ran, Azlan Shah Ali, Liyin Shen, Hafez Bin Salleh, Mingli Zhu, Kaiyi Li, Rui Wang, Yu Cao

“…The Analytic Hierarchy Process (AHP) is then applied to prioritize the identified factors. …”
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Analyzing the Development of Scientific Research in the Field of Digital Transformations by Bondarenko Dmytro V., Khaustov Mykyta M., Kalashnikova Kateryna Yu.

“…In accordance with the aim of the article, the study considers the features of bibliometric analysis as a research method that allows conducting a thorough comprehensive review of all the most influential publications in a particular subject area. …”
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Advanced machine learning models for the prediction of ceramic tiles’ properties during the firing stage by V. Vasic, Milica, Awoyera, Paul O., Fadugba, Oladlu George, Barisic, Ivana, Nettinger Grubeša, Ivanka

“…These results demonstrate the value of explainable artificial intelligence (AI) in enabling real-time process optimization, enhancing product consistency, and supporting energy-efficient ceramic manufacturing. …”
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How to Evaluate and Improve E-Commerce Implementation and Administration Success State? a New Approach for Managing Success-Relevant Activities by Sadra Ahmadi, Babak Amiri

“…In this research, a Fuzzy Cognitive Maps- analytical hierarchy process (FCM-AHP) approach is used to address this issue by (1) determining interrelationships between influential activities, (2) determining how much these activities influence each other and the overall success, and (3) prioritizing activities to develop a sound improvement plan. …”
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The innovation capability equation: A systematic review of global determinants of SME’s success by Mariza Tsakalerou, Akmaral Abil, Vincent Ribiere, Yevgeniy Lukhmanov, Narkes Tynybayeva

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