FORECASTING OF PRODUCTION OUTPUT FOR LIGHT INDUSTRY ENTERPRISES WITH PURPOSE TO DETERMINE THEIR POWER RESOURCES REQUIREMENTS. Part 2 by V. N. Romaniuk, D. B. Muslina

“…It is destined for specialists who are engaged in solution of problems pertaining to efficiency of light industry in Belarus which is considered as one of the branches being significantly involved in formation of national economy, its export potential and social climate. …”
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Design and Validation of a Simplified Method to Determine Minimum Bactericidal Concentration in Nontuberculous Mycobacteria by Sara Batista, Mariana Fernández-Pittol, Lorena San Nicolás, Diego Martínez, Sofía Narváez, Mateu Espasa, Elena Garcia Losilla, Marc Rubio, Montserrat Garrigo, Griselda Tudó, Julian González-Martin

“…MBC values provide useful additional information regarding MIC values since the MBC/MIC ratio reveals whether antibiotics have bactericidal or bacteriostatic activity according to the species, which is pivotal for selecting the most adequate antibiotic combination to ensure efficient treatment management.…”
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Machine Learning with Evolutionary Parameter Tuning for Singing Registers Classification by Tales Boratto, Gabriel de Oliveira Costa, Alexsandro Meireles, Anna Klara Sá Teles Rocha Alves, Camila M. Saporetti, Matteo Bodini, Alexandre Cury, Leonardo Goliatt

“…Behind human voice production, a complex biological mechanism generates and modulates sound. …”
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Establishing 3D organoid models from patient-derived conditionally reprogrammed cells to bridge preclinical and clinical insights in pancreatic cancer by Jin Su Kim, Chan Hee Park, Eunyoung Kim, Hee Seung Lee, Jinyoung Lee, Jeehoon Kim, Eun Hee Kam, Sanghee Nam, Moon Jae Chung, Jeong Youp Park, Seung Woo Park, Sangwoo Kim, Galam Leem, Seungmin Bang

“…Notably, the IC50 values for the 3D organoids were generally higher, reflecting the structural complexity and drug penetration barriers observed in vivo. …”
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An Adaptive Variance Adjustment Strategy for a Static Background Error Covariance Matrix—Part I: Verification in the Lorenz-96 Model by Lilan Huang, Hongze Leng, Junqiang Song, Dongzi Wang, Wuxin Wang, Ruisheng Hu, Hang Cao

“…Given its adaptability and efficiency, DRL-AST holds great potential for application in high-dimensional NWP models, where deep learning-based dimensionality reduction and reinforcement learning techniques could further enhance its feasibility and effectiveness in complex assimilation frameworks.…”
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Application of bifidobacterium in tumor therapy by Yinwu Kong, Han Bai, Feifei Deng, Yaomin Zhao, Qianyan Li, Li Chang

“…Nevertheless, their clinical application remains limited by challenges such as complex synthesis, high costs, low delivery efficiency, and poor biodegradability. …”
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Allosteric modulation of Grb2 drives ligand-dependent signal responses by Mariana Di Felice, Lucrezia Romana Rolfi, Julian Toso, Valeria Pennacchietti, Eduarda S. Ventura, Angelo Toto, Antonella Tramutola, Stefano Gianni

“…Abstract Adaptor proteins play a crucial role in signal transduction by facilitating the assembly of protein complexes at specific subcellular domains. These multifunctional molecules contain multiple binding modules that enhance the efficiency and flexibility of cellular signaling pathways, thereby orchestrating complex responses. …”
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SambaMixer: State of Health Prediction of Li-Ion Batteries Using Mamba State Space Models by Jose Ignacio Olalde-Verano, Sascha Kirch, Clara Perez-Molina, Sergio Martin

“…Approaches leveraging deep learning architectures have been proposed to predict the SOH using convolutional networks, recurrent networks, and transformers. Recently, Mamba selective state space models have emerged as a new sequence model that combines fast parallel training with data efficiency and fast sampling. …”
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Generating a Set of Reference Images for Reliable Condition Monitoring of Critical Infrastructure using Mobile Robots by Sotnikov O., Tymochko O., Bondarchuk S., Dzhuma L., Rudenko V., Mandryk Ya., Surkov K., Palonyi A., Olizarenko S.

“…The solution of this task will increase efficiency of critical infrastructure objects state control due to optimization of reference images number used in the monitoring process, increase operability, and provide high control reliability in stochastic sighting conditions. …”
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Study on Connectivity of Fractured-Vuggy Marine Carbonate Reservoirs Based on Dynamic and Static Methods by Yintao Zhang, Chengyan Lin, Lihua Ren, Chong Sun, Jing Li, Zhicheng Wang, Guojin Xu

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Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning by Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama

“…Conversely, high‐frequency features related to charge transfer resistance play a dominant role in the KP detection. To reduce data complexity and improve model efficiency, the input by selecting specific frequency points based on SHAP values is further optimized. …”
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Static pressure prediction method for CO2 flooding oil reservoirs based on time series partitioning Transformer model by LI Chunlei, YANG Heshan, ZHANG Hongxia, CAO Yumin, JIANG Xingxing, JIN Caixia

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Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning by Wajahat Hussain, Muhammad Faheem Mushtaq, Mobeen Shahroz, Urooj Akram, Ehab Seif Ghith, Mehdi Tlija, Tai-hoon Kim, Imran Ashraf

“…In image classification, selecting the appropriate hyperparameters can substantially boost the model’s ability to learn intricate patterns and features from complex image data. …”
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Development of a chemically defined medium for Yarrowia yeasts using a strategy of biological mimicry by Oliver Birrenbach, Peter Czermak

“…Background: The efficiency of recombinant protein production in Yarrowia lipolytica is strongly influenced by the culture medium. …”
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Improved Algorithm to Detect Clandestine Airstrips in Amazon RainForest by Gabriel R. Pardini, Paulo M. Tasinaffo, Elcio H. Shiguemori, Tahisa N. Kuck, Marcos R. O. A. Maximo, William R. Gyotoku

“…By addressing the limitations identified in the initial approach, this refined algorithm aims to improve detection accuracy and operational efficiency in complex rainforest environments. Tests in a selected area of the Amazon showed that the modified algorithm resulted in a recall drop of approximately 1% while reducing false positives by 26.6%. …”
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Prediction of Reservoir Flow Capacity in Sandstone Formations: A Comparative Analysis of Machine Learning Models by Micheal Ayodeji Ogundero, Taiwo Adelakin, Kehinde Orolu, Isaac Femi Johnson, Theophilus Akinfenwa Fashanu, Kingsley Abhulimen

“…The algorithms were selected for their ability to model complex relationships in reservoir characterization, with Random Forest excelling in high-dimensional data handling, ANN in pattern learning, and SVR in regression-based predictions.  …”
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Multi-Objective Ore Blending Optimization for Polymetallic Open-Pit Mines Based on Improved Matter-Element Extension Model and NSGA-II by Jun Xiang, Jianhong Chen, Aishu Zhang, Xing Zhao, Shengyuan Zhuo, Shan Yang

“…With the increasing demand for mineral resources, sustainable mining development faces challenges such as low resource utilization efficiency. Ore blending optimization has emerged as a critical approach to enhance resource utilization. …”
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A framework for assessing reliability of observer annotations of aerial wildlife imagery, with insights for deep learning applications. by Rowan L Converse, Christopher D Lippitt, Steven E Sesnie, Grant M Harris, Matthew J Butler, David R Stewart

“…There is growing interest in using deep learning models to automate wildlife detection in aerial imaging surveys to increase efficiency, but human-generated annotations remain necessary for model training. …”
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Heat Loss Determination of District Heating Pipelines. A Comparison of Numerical and Analytical Methods by Wieland Aaron, Dollhopf Stefan, Weidlich Ingo, Langroudi Pakdad Pourbozorgi

“…Assessing the energy efficiency of district heating systems considers the network heat losses. …”
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Sports data analysis of track and field athletes based on IID-OPK and NonIID-OPK algorithms by Xiaofeng Chen

“…The traditional K-means clustering algorithm randomly selects clustering center points, which can easily lead to unstable clustering results and be affected by outliers, making it unable to handle complex sports data of track and field athletes. …”
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