Multi-objective Bayesian optimization of carbon nanotube yield and diameter control at synthesis by R. Waelder, W. Kim, M. A. Pitt, J. I. Myung, B. Maruyama

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InvarNet: Molecular property prediction via rotation invariant graph neural networks by Danyan Chen, Gaoxiang Duan, Dengbao Miao, Xiaoying Zheng, Yongxin Zhu

“…Predicting molecular properties is crucial in drug synthesis and screening, but traditional molecular dynamics methods are time-consuming and costly. Recently, deep learning methods, particularly Graph Neural Networks (GNNs), have significantly improved efficiency by capturing molecular structures’ invariance under translation, rotation, and permutation. …”
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The OpenLAM Challenges: LAM Crystal Philately competition by Anyang Peng, Xinzijian Liu, Ming-Yu Guo, Linfeng Zhang, Han Wang

“…As part of the OpenLAM Initiative, the OpenLAM Challenges are competitions designed to benchmark atomic modeling methods, encourage community collaboration, and accelerate advances in machine learning-driven scientific discovery. …”
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Starrydata: from published plots to shared materials data by Yukari Katsura, Masaya Kumagai, Tomoya Mato, Yu Takada, Yuki Ando, Erina Fujita, Fumikazu Hosono, Eiji Koyama, Farhan Mudasar, Ton Nu Thanh Phuong, Naoto Saito, Yoshihiro Sakamoto, Atsumi Tanaka, Dewi Yana, Kaoru Kimura, Koji Tsuda, Masahiko Demura

“…It assists users worldwide in extracting and sharing curve data from plot images in published papers, along with relevant sample information such as chemical compositions and fabrication methods. Starrydata2 streamlines the manual data collection process through partial automation. …”
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Towards an intelligent integrated methodology for accurate determination of volume percentages in three-phase flow systems by Abdullah M. Iliyasu, Mohammad Sh. Daoud, Ahmed Sayed Salama, John William Grimaldo Guerrero, Kaoru Hirota

“…The proposed approach demonstrates superior accuracy in determining volume percentages of three-phase fluids compared to traditional methods, thereby making it an effective and integrated technique to analyse fluid composition in a variety of industrial settings and applications.…”
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Algorithmization of the problem of videoscopic evaluation of the steel ropes state by Panfilov A.V., Yusupov A.R., Gavrikov M.M., Sinetsky R.M.

“…The article proposes two approaches to the algorithmizing of the problem of videoscopic control of the state of steel ropes using computer vision technologies, based on software modeling of the logic of visual analysis and machine learning methods, such as deep learning artificial neural networks. …”
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Atmospheric Pollutant Flow and Precipitation: Modeling Effects on the Vegetation Ecosystem by Allag Fateh, Saddek Bouharati, Lamri Tedjar, Mohamed Fenni

“…Different factors are to be considered. The chemical composition of the air, the climatic conditions, and the impacted plant species are complex parameters to be analyzed using conventional mathematical methods. …”
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Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes by Laura Isabel Sinisterra Loaiza, Diego Fernández-Edreira, Jose Liñares-Blanco, Alberto Cepeda, Alejandra Cardelle-Cobas, Carlos Fernandez-Lozano

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About managing the number of simultaneously functioning software robots of different types by A. S. Zuev, D. A. Leonov

“…The study sets out to justify the relevance and investigate approaches for solving the problem of managing the number of simultaneously functioning software robots of various types under conditions of limited computational resources and changes in sets of executable tasks.Methods. A proposed solution is based on models and methods of scenario management, linear programming, inventory management, queuing theory, and machine learning. …”
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Robust coal granularity estimation via deep neural network with an image enhancement layer by Xi Chen, Hua-Yi Feng, Jia-Le Wang

“…Accurate granularity estimation of ore images is vital in automatic geometric parameter detecting and composition analysis of ore dressing progress. Machine learning based methods have been widely used in multi-scenario ore granularity estimation. …”
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Improving Systematic Review Updates With Natural Language Processing Through Abstract Component Classification and Selection: Algorithm Development and Validation by Tatsuki Hasegawa, Hayato Kizaki, Keisho Ikegami, Shungo Imai, Yuki Yanagisawa, Shuntaro Yada, Eiji Aramaki, Satoko Hori

“…The titles and abstracts were classified into 5 categories (Title, Introduction, Methods, Results, and Conclusion). Thirty-one component-composition datasets were created by combining 5 component datasets. …”
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Data-driven design of electrolyte additives supporting high-performance 5 V LiNi0.5Mn1.5O4 positive electrodes by Bingning Wang, Hieu A. Doan, Seoung-Bum Son, Daniel P. Abraham, Stephen E. Trask, Andrew Jansen, Kang Xu, Chen Liao

“…Subsequently, we train machine learning models on this dataset and employ the trained models to suggest 6 binary compositions out of 125, based on predicted final area-specific-impedance, impedance rise, and final specific-capacity. …”
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The Effect of Educational Games on Creativity: A systematic Review by Mohadeseh Ziaee, Mohsen Rostamy-MalKhalifeh, Tofigh Allahviranloo

“…To this end, during the timeframe from 2013 to 2014, a comprehensive search was conducted for all articles pertinent to the effects of educational games on creativity within Persian databases, which include the National Journals Database, the Academic Jihad Scientific Information Center Database, the Noor Specialized Journals Database, and the Iranian Institute of Information Science and Technology Research, in addition to Google Scholar, employing keywords such as educational games, creativity, game-based learning, and educational group games. Following a rigorous screening process based on predefined inclusion and exclusion criteria, 21 relevant articles were chosen for the composition of this manuscript. …”
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Crystal structure generation with autoregressive large language modeling by Luis M. Antunes, Keith T. Butler, Ricardo Grau-Crespo

“…Abstract The generation of plausible crystal structures is often the first step in predicting the structure and properties of a material from its chemical composition. However, most current methods for crystal structure prediction are computationally expensive, slowing the pace of innovation. …”
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Obesity and Systemic Inflammation Disrupt the Compensatory Role of Physical Activity in Chronic Pain Conditions by Taynah Galassi, Kevin Pacheco-Barrios, Anna C. Gianlorenco, Felipe Fregni

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Incremental Support Vector Machine Combined with Ultraviolet-Visible Spectroscopy for Rapid Discriminant Analysis of Red Wine by Jun Liu, Tie-Jun Pan, Zheng-Yong Zhang

“…The novel method based on incremental learning support vector machine (I-SVM) combined with ultraviolet–visible (UV-Vis) spectroscopy was applied to discriminant analysis of the brands of red wine for the first time. …”
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Cell-type annotation with accurate unseen cell-type identification using multiple references. by Yi-Xuan Xiong, Meng-Guo Wang, Luonan Chen, Xiao-Fei Zhang

“…To address this challenge, we propose mtANN (multiple-reference-based scRNA-seq data annotation), a new method to automatically annotate query data while accurately identifying unseen cell types with the aid of multiple references. …”
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Research progress in additive manufacturing for repair technology of single crystal superalloy turbine rotor blades for aero-engine by QIN Renyao, QU Zhiqi, CHEN Bingqing, SUN Bingbing, ZHANG Xuejun, ZHANG Guohui

“…Specific filler material composition design， new process development， and multi-objective collaborative optimization based on deep learning are considered to be important future research directions.…”
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Optimization of non-smooth functions via differentiable surrogates. by Shikun Chen, Zebin Huang, Wenlong Zheng

“…The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”
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Gradus ad Parnassum: International Online Training for Microtonal Singing with 22 Pitches within the Octave by Lock Hans-Gunter

“…According to experiences from the research and teaching/learning process, the article introduces the music theoretical fundamentals of the 22-EDO scale, knowledge of which is an integral part of a potential training method, the creation of teaching materials and musical compositions. …”
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