Capacity Estimation of Lithium-Ion Battery Systems in Fuel Cell Ships Based on Deep Learning Model by Xiangguo Yang, Jia Tang, Qijia Song, Yifan Liu, Lin Liu, Xingwei Zhou, Yuelin Chen, Telu Tang

“…To address the challenge of accurately estimating lithium-ion battery capacity under complex operating conditions, this study extracts universal health factors from battery data under varied charging and discharging scenarios and combines these with a deep learning model to enhance prediction accuracy. First, battery data from three complex conditions are analyzed, extracting partial charge and discharge data. …”
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Discrepancy in Metabolic Dysfunction–Associated Steatotic Liver Disease Prevalence in a Large Northern California Cohort by Luis A. Rodriguez, Lue-Yen S. Tucker, Varun Saxena, Theodore R. Levin

“…Annual MASLD prevalence was identified based on International Classification of Diseases, Ninth or Tenth Revision, Clinical Modification diagnosis codes, the application of natural language processing of all radiology imaging report text that included the liver, and the application of the Dallas Steatosis Index, a MASLD prediction algorithm. Results: Between 2009 and 2018, the estimated MASLD prevalence ranged from 0.37% to 0.95% using diagnosis codes, 0.88%–1.37% using imaging, and 6.14%–11.27% using the Dallas Steatosis Index. …”
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CRITICAL CONTROL POINT IDENTIFICATION THROUGH TROPHOLOGICAL MEAT PRODUCTION CHAINFROM FIELD TO FORK by A. V. Borodin, I. M. Chernukha, M. A. Nikitina

“…The article describes methodological bases for IT-approach to the CCP identification in the trophological meat production chain from field to fork. The algorithmic support and soſtware for the «Decision tree», which allows detecting existing hazards, identifying risks, determining CCPs and describing them, has been developed.…”
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Worst-case energy consumption minimization based on interference analysis and bank mapping in multicore systems by Zhihua Gan, Zhimin Gu, Hai Tan, Mingquan Zhang, Jizan Zhang

“…The bank-to-core mapping provides significant benefits in worst-case energy consumption reduction with 7.23%.…”
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Optimization of connection patterns between mobile phones and base stations using quantum annealing by Taisei Takabayashi, Shoichi Sudo, Toshihiro Aoki, Shun Seo, Masayuki Ohzeki

“…By adopting a variable reduction formulation, we significantly reduce the qubit requirements compared to the naive formulation that is typically used when considering pattern-matching problems. …”
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Perspectives on land use and plant cover in Pucallpa (Perú) between 2000 and 2023 by Indara Venecia Dávila del Valle, Renato Edu Barzola Gomez, Ciza Zarvia Rosario Ramon

“…Finally, a significant land-use transformation was evident, marked by a reduction in vegetation cover and an increase in areas dedicated to crops and pastures. …”
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Dealing with Energy-QoE Trade-Offs in Mobile Video by Fidel Liberal, Ianire Taboada, Jose-Oscar Fajardo

“…Finally, since the optimization solving mechanism is computationally expensive to be implemented in mobile devices, a heuristic algorithm is proposed. This way, significant energy consumption reduction will be achieved while keeping reasonable quality levels.…”
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YOLOv9-GDV: A Power Pylon Detection Model for Remote Sensing Images by Ke Zhang, Ningxuan Zhang, Chaojun Shi, Qiaochu Lu, Xian Zheng, Yujie Cao, Xiaoyun Zhang, Jiyuan Yang

“…On the Satellite Remote Sensing Power Tower Dataset (SRSPTD), the YOLOv9-GDV algorithm achieves an mAP of 80.2%, representing a 4.7% improvement over the baseline algorithm. …”
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Expression Characteristics and Prognostic Value of KLRG2 in Endometrial Cancer: A Comprehensive Analysis Based on Multi-Omics Data by Xiaoyan Huang, Ailian Li, Dianbo Xu

“…High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96) and progression-free interval (HR = 1.98, 95% CI = 1.37–2.87). …”
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The UK Biobank mental health enhancement 2022: Methods and results. by Katrina A S Davis, Jonathan R I Coleman, Mark Adams, Gerome Breen, Na Cai, Helena L Davies, Kelly Davies, Alexandru Dregan, Thalia C Eley, Elaine Fox, Jo Holliday, Christopher Hübel, Ann John, Aliyah S Kassam, Matthew J Kempton, William Lee, Danyang Li, Jared Maina, Rose McCabe, Andrew M McIntosh, Sian Oram, Marcus Richards, Megan Skelton, Fenella Starkey, Abigail R Ter Kuile, Laura M Thornton, Rujia Wang, Zhaoying Yu, Johan Zvrskovec, Matthew Hotopf

“…This paper has just scratched the surface of the results from MHQ2 and how this can be combined with other tranches of UKB data, but we predict it will enable many future discoveries about mental health and health in general.…”
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Study on Lacticaseibacillus casei TCS fermentation kinetic models and high-density culture strategy by Chen Chen, Tianyu Guo, Di Wu, Jingyan Shu, Ningwei Huang, Huaixiang Tian, Haiyan Yu, Chang Ge

“…Fermentation kinetics were modeled using logistic growth and Luedeking–Piret models, which accurately predicted cell growth. Amberlite IRA 67, an anion exchange resin, effectively adsorbed lactic acid and maintained pH levels. …”
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Multi-omics analysis identifies SNP-associated immune-related signatures by integrating Mendelian randomization and machine learning in hepatocellular carcinoma by Qingyan Kou, Zhichao Wu, Wenbin Zhao, Zhenyuan Liu, Shengxian Qiao, Qiang Mu, Xu Zhang

“…High-risk patients exhibited poorer prognosis and higher immune cell infiltration, particularly T cells and neutrophils. The model also predicted drug sensitivity, with high-risk patients showing greater sensitivity to chemotherapy agents like 5-Fluorouracil and Paclitaxel. …”
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Modeling of the Potential Effect of Revaccination against Whooping Cough in Children Aged 6–7 and 14 years within the Framework of the National of preventive vaccinations by N. I. Briko, A. Ya. Mindlina, I. V. Mikheeva, L. D. Popovich, A. V. Lomonosova

“…A simulation dynamic mathematical model is constructed that allows predicting the development of the epidemiological process of whooping cough on the basis of the dynamics of the main indicators of its prevalence in the population that developed in previous years. …”
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The photometry and kinematics studies of NGC 2509 derived from Gaia DR3 by Nasser M. Ahmed, A. L. Tadross

“…We employed the pyUPMASK Python package and HDBSCAN algorithms to identify the cluster member stars. The current analysis introduces a new method that connects the membership probability of stars in the cluster (using the pyUPMASK tool) with the number of stars predicted by the King model at different distances from the center of the cluster. …”
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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

“…The CNN model efficiently extracts workload features from tasks and resources, while the BiLSTM captures complex sequential information, predicting optimal task placement sequences. A real fog-cloud environment is implemented using the COSCO framework for the simulation setup together with four physical nodes from the Azure B2s plan to test the proposed model. …”
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Assessment of Risks of Voltage Quality Decline in Load Nodes of Power Systems by Pylyp Hovorov, Roman Trishch, Romualdas Ginevičius, Vladislavas Petraškevičius, Karel Šuhajda

“…The economic criterion is taken into account through the use of complex and inaccurate models that do not accurately predict the result. The emergence of market relations in the energy sector makes power systems economic entities in terms of production and satisfaction of demand for electricity by various economic entities (industry, households, businesses, etc.). …”
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Radiomic Analysis and Liquid Biopsy in Preoperative CT of NSCLC: An Explorative Experience by Maria Paola Belfiore, Mario Sansone, Giovanni Ciani, Vittorio Patanè, Carlotta Genco, Roberta Grassi, Giovanni Savarese, Marco Montella, Riccardo Monti, Salvatore Cappabianca, Alfonso Reginelli

“…Radiomic features were extracted from CT images, and circulating tumor DNA (ctDNA) was sequenced to identify genetic mutations. Machine learning algorithms were employed to assess the association between radiomic features and gene mutations. …”
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An Integrative Analysis of Transcriptome Combined with Machine Learning and Single-Cell RNA-Seq for the Common Biomarkers in Crohn’s Disease and Kidney Stone Disease by Zhu J, Du Y, Gao L, Wang J, Mei Q

“…Therefore, finding biomarkers that can predict CD with KD become increasingly important.Methods: We obtained three CD and one KSD dataset from GEO database. …”
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On the need of individually optimizing temporal interference stimulation of human brains due to inter-individual variability by Tapasi Brahma, Alexander Guillen, Jeffrey Moreno, Abhishek Datta, Yu Huang

“…Experimental recordings on a head phantom confirms the drop in TI stimulation strength when using unoptimized montages as predicted by our in silico models. Conclusion: This work demonstrates the need of individually optimizing TI to target deep brain areas, and advocates against using a common head model and montage for TI modeling and experimental studies.…”
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Identification of Diagnostic Biomarkers and Therapeutic Targets in Sepsis-Associated ARDS via Combining Bioinformatics with Machine Learning Analysis by Liu T, Gao L, Li X

“…Three machine learning algorithms were applied to refine the intersected genes. …”
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