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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Information requirement analysis for establishing intelligent natural language query interfaces in BIM-based construction projects by Mengtian Yin, Zhuoqian Wu, Haotian Li, Mun On Wong, Llewellyn Tang, Shu Tang, Junxiang Zhu

“…Emerging artificial intelligence (AI)-based natural language interface (NLI) systems show significant potential for enabling stakeholders to efficiently retrieve complicated building information models (BIM). …”
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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 significance of the obtained results consists in the possibility of solving a complex task of forming a set of reference images, depending on the information content and stochastic conditions of sighting of critical infrastructure objects. …”
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Phenothiazine-Based Nanoaggregates: Dual Role in Bioimaging and Stem Cell-Driven Photodynamic Therapy by Eleonora Calzoni, Alessio Cesaretti, Nicolò Montegiove, Maria Luisa Valicenti, Francesco Morena, Rajneesh Misra, Benedetta Carlotti, Sabata Martino

“…However, a significant obstacle for PDT is the need to selectively deliver photosensitizers to disease sites while minimizing systemic side effects. …”
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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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A Comparative Study of Fractal Models Applied to Artificial and Natural Data by Gil Silva, Fernando Pellon de Miranda, Mateus Michelon, Ana Ovídio, Felipe Venturelli, João Parêdes, João Ferreira, Letícia Moraes, Flávio Barbosa, Alexandre Cury

“…Computational efficiency analysis revealed that methods with linear or logarithmic complexity, such as Persistence and Compass, are most suited for larger datasets, while methods like DFA and Dynamic Fractal Approaches required higher computational resources. …”
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Eco-benign synthesis of multifunctional silver nanoparticles using leptochloa fusca for enhanced biomedical and catalytic applications by Riaz Ahmad Khan, Hidayat Ullah Khan, Shahnaz, Kamran Tahir, Moamen S Refat, Abdel Majid A Adam, Amnah Mohammed Alsuhaibani

“…LF-AgNPs efficiently catalysed the reduction of methylene blue in less than 9 min, using NaBH _4 as a reducing agent. …”
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How to improve your sleep quality? Review of non-pharmacological methods by Urszula Szymczak, Wojciech Wiesław Lachór, Monika Barbara Solarz, Julia Piekarska, Justyna Maria Solarz, Jakub Tomasz Wawrzyńców, Weronika Cyrkler, Jakub Robak, Stanisław Telega, Paweł Bollin

“…They are an effective element of relieving these disorders, but in the case of more complex or severe cases they may not be sufficient. …”
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Research progress on anaerobic digestion and degradation of lignocellulosic waste by rumen microorganisms by MU Lan, XU Fenglian, CHENG Zhanjun, WANG Yifan, SHI Yan, TAO Junyu*, CHEN Guanyi

“…Lignocellulosic biomass waste is an important raw material for anaerobic digestion to produce bioenergy. However, its complex three-dimensional structure leads to a low substrate conversion rate and poor technical economic efficiency during anaerobic digestion. …”
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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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A framework of crop water productivity estimation from UAV observations: A case study of summer maize by Minghan Cheng, Ni Song, Josep Penuelas, Matthew F. McCabe, Xiyun Jiao, Yuping Lv, Chengming Sun, Xiuliang Jin

“…However, current methodologies face limitations in estimation accuracy and operational efficiency due to the multidisciplinary complexity integrating agronomic and hydrological expertise. …”
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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

“…This study constructs a multi-objective ore blending optimization system for complex polymetallic open-pit mines based on the improved matter-element extension model and NSGA-II algorithm. …”
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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

“…However, even skilled observers may diverge in interpreting aerial imagery of complex environments, which may result in downstream instability of models. …”
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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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LWRNPIP: Design of a light weight restrictive non-fungible token based on practically unclonable functions via image signature patterns by Mahesh Kumar Singh, Pushpa Choudhary, Arun Kumar Singh, Pushpendra Singh

“…Designing NFTs requires selecting different blockchain-based consensus models, encryption techniques, and distribution mechanisms. …”
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RACF: A Multimodal Deep Learning Framework for Parkinson’s Disease Diagnosis Using SNP and MRI Data by Jiangbo Cao, Xiaojing Long

“…In contrast to traditional methods, deep learning models are capable of processing large-scale, high-dimensional, and complex datasets to automatically learn latent feature relationships, making them particularly suitable for scenarios involving multimodal data fusion. …”
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