Simulation of energy consumption processes at the metallurgical enterprises in the energy-saving projects implementation by Kiyko S. G., Druzhinin E. A., Prokhorov O. V., Haidabrus B. V.

“…The features of improving energy efficiency at a metallurgical enterprise based on portfolio management of energy-saving projects are considered. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…However, satellite-derived AOD datasets frequently suffer from missing values due to factors such as cloud cover, algorithmic limitations, and various atmospheric conditions. …”
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HI4HC and AAAAD: Exploring a hierarchical method and dataset using hybrid intelligence for remote sensing scene captioning by Jiaxin Ren, Wanzeng Liu, Jun Chen, Shunxi Yin

“…Extensive experiments show that AAAAD outperforms traditional single-level caption datasets in terms of the richness of geographical elements, the precision of spatial relations, and overall caption diversity, with improvements observed across 11 out of 13 evaluation metrics. …”
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Application of Image Computing in Non-Destructive Detection of Chinese Cuisine by Xiaowei Huang, Zexiang Li, Zhihua Li, Jiyong Shi, Ning Zhang, Zhou Qin, Liuzi Du, Tingting Shen, Roujia Zhang

“…This study pioneers a hyperspectral imaging framework enhanced with domain-specific deep learning algorithms (spatial–spectral convolutional networks with attention mechanisms) to address these challenges. …”
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Automatic Segmentation of Abdominal Aortic Aneurysm From Computed Tomography Angiography Using a Patch-Based Dilated UNet Model by Merjulah Roby, Juan C. Restrepo, Haehwan Park, Satish C. Muluk, Mark K. Eskandari, Seungik Baek, Ender A. Finol

“…Hence, there is a growing need for automated segmentation algorithms, particularly when these influence treatment planning. …”
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New Advances of the P-SBAS Approach for an Efficient Parallel Processing of Large Volumes of Full-Resolution Multitemporal DInSAR Interferograms by Manuela Bonano, Pasquale Striano, Muhammad Yasir, Sabatino Buonanno, Francesco Casu, Claudio De Luca, Adele Fusco, Yenni Lorena Belen Roa, Ivana Zinno, Maria Virelli, Michele Manunta, Riccardo Lanari

“…The starting point of the developed full-resolution parallel-SBAS (FR P-SBAS) technique involves some algorithmic extensions for improving the quality of the DInSAR time series to effectively analyze extended deformations and localized displacement phenomena, such as those affecting single buildings and infrastructures. …”
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A review of interactions between irrigation and evapotranspiration by Ziyuan Gong, Fei Gao, Xinyu Chang, Tianqi Hu, Yaping Li

“…Improving the high resolution of the model, the uncertainty of the parameters, and the RS data in the lack of data are the development trend of estimating ET and irrigation quantity in the future. …”
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Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review by Anastasios Anastasiadis, Antonios Koudonas, Georgios Langas, Stavros Tsiakaras, Dimitrios Memmos, Ioannis Mykoniatis, Evangelos N. Symeonidis, Dimitrios Tsiptsios, Eliophotos Savvides, Ioannis Vakalopoulos, Georgios Dimitriadis, Jean de la Rosette

“…Methods: A comprehensive literature review was performed using PubMed, Scopus, and Google Scholar databases to identify publications about innovative concepts or supporting applications of AI in the improvement of every medical procedure relating to stone disease. …”
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Automated noise modelling using a triangulated terrain model by Nadine Hobeika, Laurens van Rijssel, Maarit Prusti, Constantijn Dinklo, Denis Giannelli, Balázs Dukai, Arnaud Kok, Rob van Loon, René Nota, Jantien Stoter

“…Since CNOSSOS-EU guidelines were used, the prototype is applicable to the entire European Union and can be the first step in improving the automation of 3D noise modeling using currently available techniques and data.…”
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Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients by Aref Andishgar, Sina Bazmi, Kamran B. Lankarani, Seyed Alireza Taghavi, Mohammad Hadi Imanieh, Gholamreza Sivandzadeh, Samira Saeian, Nazanin Dadashpour, Alireza Shamsaeefar, Mahdi Ravankhah, Hamed Nikoupour Deylami, Reza Tabrizi, Mohammad Hossein Imanieh

“…We identified BC and mortality risk factors, improving decision-making and outcomes.…”
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Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data by Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya, R. Manjunatha, Debasish Shit, M. Nirmala, Ajay Sharma, Sarbeswara Hota, Shirin Shomurotova, Fadhil Faez Sead, Hojjat Abbasi, Mohammad Mahtab Alam

“…Gradient boosting machine (GBM) models were optimized using advanced algorithms like self-adaptive differential evolution (SADE), evolution strategy (ES), Bayesian probability improvement (BPI), and Batch Bayesian optimization (BBO). …”
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Listener Acoustic Personalization Challenge - LAP24: Head-Related Transfer Function Upsampling by Aidan O. T. Hogg, Roberto Barumerli, Rapolas Daugintis, Katarina C. Poole, Fabian Brinkmann, Lorenzo Picinali, Michele Geronazzo

“…Head-related transfer functions (HRTFs) often play a crucial role in spatial hearing, immersive audio applications for virtual reality (VR) and augmented reality (AR), and help in improving hearing assistive devices. The Listener Acoustic Personalisation (LAP) challenge 2024 aimed at advancing research in spatial audio personalisation, with a focus on head-related transfer functions (HRTFs). …”
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Streamlining Thoracic Radiotherapy Quality assurance: One-Class Classification for Automated OAR Contour Assessment by Yihao Zhao BSc, Cuiyun Yuan MSc, Ying Liang PhD, Yang Li MSc, Chunxia Li MSc, Man Zhao MSc, Jun Hu PhD, Ningze Zhong Bsc, Wei Liu PhD, Chenbin Liu PhD

“…Purpose Automating quality assurance (QA) for contours generated by automatic algorithms is critical in radiotherapy treatment planning. …”
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Rethinking the Paradigm of Using Ps for Diagnosing Compartment Syndrome by Yasser Bouklouch, BSc, MPH, July Agel, MA, ATC, William T. Obremskey, MD, MPH, MMHC, Andrew H. Schmidt, MD, Kathy Liu, MB, ChB, Jerald R. Westberg, MPH, Matthew Zakariah, BSc, Eli Bunzel, MD, Greer Henry, MSc, Andres Fidel Diaz, MD, Thierry Bégué, MD, Mitchell Bernstein, MD, Edward J. Harvey, MDCM, MSc

“…Increasing the number of Ps improves the performance up to 4Ps, regardless of the composition of the combination. …”
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Analysis of Regions of Homozygosity: Revisited Through New Bioinformatic Approaches by Susana Valente, Mariana Ribeiro, Jennifer Schnur, Filipe Alves, Nuno Moniz, Dominik Seelow, João Parente Freixo, Paulo Filipe Silva, Jorge Oliveira

“…Whole-exome sequencing (WES) improves HM by detecting ROHs and disease-causing variants. …”
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Dual Control Strategy for Non-Minimum Phase Behavior Mitigation in DC-DC Boost Converters Using Finite Control Set Model Predictive Control and Proportional–Integral Controllers by Alejandra Marmol, Elyas Zamiri, Marziye Purraji, Duberney Murillo, Jairo Tuñón Díaz, Aitor Vazquez, Angel de Castro

“…The proposed method’s effectiveness is validated through a multi-stage simulation test, demonstrating significant improvements in response time and stability compared to traditional control methods. …”
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Machine learning based identification of an amino acid metabolism related signature for predicting prognosis and immune microenvironment in pancreatic cancer by Xiaohong Liu, Xing Wang, Jie Ren, Yuan Fang, Minzhi Gu, Feihan Zhou, Ruiling Xiao, Xiyuan Luo, Jialu Bai, Decheng Jiang, Yuemeng Tang, Bo Ren, Lei You, Yupei Zhao

“…Understanding the interplay between pancreatic cancer and amino acid metabolism offers potential avenues for improving patient clinical outcomes. Methods A comprehensive analysis integrating 10 machine learning algorithms was executed to pinpoint amino acid metabolic signature. …”
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Comprehensive analysis of single-cell and bulk RNA sequencing data reveals an EGFR signature for predicting immunotherapy response and prognosis in pan-cancer by Changchun Ye, Changchun Ye, Xiaoya Chen, Zilu Chen, Shiyuan Liu, Ranran Kong, Wenhao Lin, Minxia Zhu, Xuejun Sun, Zhengshui Xu

“…Furthermore, core genes were identified for future targeting, which will pave the way for improving the effect of immunotherapy in the context of combination immunotherapies.…”
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are prone to various artifacts such as noise amplification and boundary artifact. …”
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Comparing the potential of tree-based and area-based forest height metrics for aboveground biomass estimation in complex forest landscapes by Weiyan Liu, Yuling Chen, Haitao Yang, Guangcai Xu, Shiyu Yan, Lingjun Li, Ling Chen, Qinghua Guo

“…Two modeling approaches—parametric mixed-effects models (MEM) and non-parametric machine learning (ML) algorithms—were applied to evaluate predictive accuracy. …”
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