The Contribution of Thalamocortical Core and Matrix Pathways to Sleep Spindles by Giovanni Piantoni, Eric Halgren, Sydney S. Cash

“…We find evidence for this hypothesis in EEG/MEG studies, intracranial recordings, and computational models that incorporate this difference. This distinction will prove useful in accounting for the multiple functions attributed to spindles, in that spindles of different types might act on local and widespread spatial scales. …”
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A Computational Study on the Use of an Aluminium Metal Matrix Composite and Aramid as Alternative Brake Disc and Brake Pad Material by Nosa Idusuyi, Ijeoma Babajide, Oluwaseun. K. Ajayi, Temilola. T. Olugasa

“…A computational model for the heat generation and dissipation in a disk brake during braking and the following release period has been formulated. …”
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Quantum machine learning with Adaptive Boson Sampling via post-selection by Francesco Hoch, Eugenio Caruccio, Giovanni Rodari, Tommaso Francalanci, Alessia Suprano, Taira Giordani, Gonzalo Carvacho, Nicolò Spagnolo, Seid Koudia, Massimiliano Proietti, Carlo Liorni, Filippo Cerocchi, Riccardo Albiero, Niki Di Giano, Marco Gardina, Francesco Ceccarelli, Giacomo Corrielli, Ulysse Chabaud, Roberto Osellame, Massimiliano Dispenza, Fabio Sciarrino

“…In recent years, an intermediate approach has been pursued to demonstrate quantum computational advantage via non-universal computational models. A relevant example for photonic platforms has been provided by the Boson Sampling paradigm and its variants, which are known to be computationally hard while requiring at the same time only the manipulation of the generated photonic resources via linear optics and detection. …”
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Eyes Open on Sleep and Wake: In Vivo to In Silico Neural Networks by Amaury Vanvinckenroye, Gilles Vandewalle, Christophe Phillips, Sarah L. Chellappa

“…A key limitation of human neuroscience is the difficulty in isolating neuronal excitation/inhibition drive in vivo. Therefore, computational models are noninvasive approaches of choice to indirectly access hidden neuronal states. …”
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Cyber ranges: survey and perspective by ZOU Xing, HU Ning, GU Zhaoquan, JIA Yan

“…With the continuous evolution of basic support technologies and computational models, cyber ranges face new problems and challenges. …”
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Predicting amyloid proteins using attention-based long short-term memory by Zhuowen Li

“…In this study, we develop a computational model for in silico identification of amyloid proteins using bidirectional long short-term memory in combination with an attention mechanism. …”
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Meso-mechanics simulation analysis of microwave-assisted mineral liberation by Qin Like, Dai Jun, Yuan Liqun

“…This paper takes rock grains with galena and calcite as the research object to establish a two-dimensional computational model through the finite difference software FLAC2D. …”
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Learning predictive signatures of HLA type from T-cell repertoires. by María Ruiz Ortega, Mikhail V Pogorelyy, Anastasia A Minervina, Paul G Thomas, Thierry Mora, Aleksandra M Walczak

“…Using our TCR-HLA associations, we trained a computational model to predict the HLA type of individuals from their TCR repertoire alone. …”
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A human single-neuron dataset for object recognition by Runnan Cao, Peter Brunner, Nicholas J. Brandmeir, Jon T. Willie, Shuo Wang

“…Together, our extensive dataset, offering the highest spatial and temporal resolution currently available in humans, will not only facilitate a comprehensive analysis of the neural correlates of object recognition but also provide valuable opportunities for training and validating computational models.…”
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Ensuring Safety and Reliability: An Overview of Lithium-Ion Battery Service Assessment by Cezar Comanescu

“…Current reliability assessment techniques include experimental methods, computational models, and data-driven approaches. Emerging trends, such as advanced characterization techniques and standardized testing protocols, advocate for improved practices to enhance the reliability and safety of LIBs across all applications.…”
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The Resilience of Public Policies in Economic Development by Gonzalo Castañeda, Omar A. Guerrero

“…In order to estimate the allocation of resources across policies, we employ a computational model that accounts for diverse social mechanisms, for example, coevolutionary learning and network interdependencies. …”
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Research on Monitoring method of Urban Road Waterlogging Depth Based on Deep Learning and Ellipse Detection by LIAO Yuhong, HUANG Guoru

“…In order to solve the problem that the traditional urban waterlogging monitoring methods consume a lot of manpower and material resources and also have a high cost,which cannot meet the needs of comprehensive and rapid monitoring of urban flood,a method of monitoring the depth of urban road waterlogging using deep learning and ellipse detection algorithm is applied,which constructs a computation model of the urban road waterlogging depth by detecting and segmenting the wheels of different types of vehicles on the images through a deep learning model and using ellipse detection algorithm to extract the geometric characteristic parameters of submerged wheels.Verified by typical video monitoring sites in Dongying City,The results show that the average positioning precision and segmentation precision of the model on the dataset can reach over 94%;the model has a good monitoring effect on waterlogging depth for vehicles on both the directly lateral side and the oblique lateral side in actual waterlogging monitoring;furthermore,the results at the near point are better than that at the far point,and the results for vehicles on the directly lateral side are better than the oblique lateral side.The results can lay the foundation for further research,and provide technical support for urban waterlogging monitoring and flood emergency management.…”
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Structured Dynamics in the Algorithmic Agent by Giulio Ruffini, Francesca Castaldo, Jakub Vohryzek

“…Our findings bridge perspectives from algorithmic information theory (Kolmogorov complexity, compressive modeling), symmetry (group theory), and dynamics (conservation laws, reduced manifolds), offering insights into the neural correlates of agenthood and structured experience in natural systems, as well as the design of artificial intelligence and computational models of the brain.…”
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Atrioventricular nodal reentrant tachycardia onset, sustainability, and spontaneous termination in rabbit atrioventricular node model with autonomic nervous system control by Maxim Ryzhii, Elena Ryzhii

“…For the first time, a computer model reveals the potential to identify hidden processes within the AV node, thereby bringing us closer to understanding the role of ANS control in AVNRT. …”
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ENHANCING OPERATIONAL EFFICIENCY IN COAL ENTERPRISES THROUGH CAPACITY LAYOUT OPTIMISATION: A COST-EFFECTIVENESS ANALYSIS by D. A. Pervukhin, Lisha Tang

“… In particular, this work explores the effectiveness of capacity layout optimisation on workflows and organizational performance for coal enterprises through reliance on advanced technologies such as GIS, Lean Six Sigma, Artificial Intelligence (AI), and Big Data, filling in those gaps in prior studies by using software from AnyLogic to develop computational models and conduct simulations. It analyses the critical parameters of processing time, throughput rates, resource utilization, queue lengths, and idle times to determine operational efficiency and employee satisfaction. …”
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Modeling the endocrine control of vitellogenin production in female rainbow trout by Kaitlin Sundling, Gheorghe Craciun, Irvin Schultz, Sharon Hook, James Nagler, Tim Cavileer, Joseph Verducci, Yushi Liu, Jonghan Kim, William Hayton

“…We anticipate that these mathematical and computational models will play an important role in future regulatory toxicity assessments and in the prediction of ecological risk.…”
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m5C‐TNKmer: Identification of 5‐Methylated Base Cytosine of Ribonucleic Acid Using Supervised Machine Learning Techniques by Shahid Qazi, Dilawar Shah, Mohammad Asmat Ullah Khan, Shujaat Ali, Mohammad Abrar, Asfandyar Khan, Muhammad Tahir

“…This study introduces a novel computational model m5C‐TNKmer, which utilizes k‐mer feature extraction to enhance the identification of m5C sites in RNA sequences. …”
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Modeling Forced Flow Chemical Vapor Infiltration Fabrication of SiC-SiC Composites for Advanced Nuclear Reactors by Christian P. Deck, H. E. Khalifa, B. Sammuli, C. A. Back

“…To help optimize this process, a computer model was developed. This model simulates the transport of the SiC precursors, the deposition of SiC matrix on the fiber surfaces, and the effects of byproducts on the process. …”
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Image Reconstruction for High-Performance Electrical Capacitance Tomography System Using Deep Learning by Yanpeng Zhang, Deyun Chen

“…An optimization model for imaging is generated as a powerful optimizer for building a computational model to ameliorate the reconstruction accuracy. …”
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Assessing ECG Interpretation Expertise in Medical Practitioners Through Eye Movement Data and Neuromorphic Models by Syed Mohsin Bokhari, Muhammad Shafi, Fazal Noor, Sarmad Sohaib, Saad Alqahtany, Mark Donnelly

“…We examine eye movement patterns from five separate groups of cardiology practitioners utilizing a combination of neuromorphic computing models, including Spiking Neural Networks (SNN), Spiking Convolutional Neural Networks (SCNN), Recurrent Spiking Neural Networks (RSNN), and Spiking Convolutional Long Short-Term Memory (SCLSTM). …”
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