Quantum-inspired framework for big data analytics: evaluating the impact of movie trailers and its financial returns by Jaiteg Singh, Kamalpreet Singh Bhangu, Farman Ali, Ahmad Ali AlZubi, Babar Shah

“…Unlike sequential problem-solving approach of traditional computing models, Quantum superposition allows exploring multiple options at once. …”
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Advancing Computational Humor: LLaMa-3 Based Generation with DistilBert Evaluation Framework by He Jinliang, Mei Aohan

“…These factors contribute to the variability of human-generated humor, necessitating computational models capable of mastering diverse comedic styles with minimal subjectivity and maximal generalizability. …”
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Modelling of Rough Contact between Linear Viscoelastic Materials by Sergiu Spinu, Delia Cerlinca

“…Moreover, when real surface microtopography is considered, steep slopes inevitably lead to localized plastic deformation at the tip of the asperities that are first brought into contact. A computer model for the rough contact of linear viscoelastic materials, capable of handling deterministic contact geometry, complex viscoelastic models, and arbitrary loading histories, is advanced in this paper. …”
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Contact Dynamic Behaviors of Magnetic Hydrogel Soft Robots by Yunian Shen, Yiming Zou

“…However, their contact dynamic behaviors are complex, considering stick–slip motion at the contact interface, and lack accurate computational models to analyze them. This paper improves the numerical computational method for hydrogel materials with magneto-mechanical coupling effect, analyses the inchworm-like contact motion of the biomimetic bipedal magnetic hydrogel soft robot, and designs and optimizes the robot’s structure. …”
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Molecular simulations reveal intricate coupling between agonist-bound β-adrenergic receptors and G protein by Yanxiao Han, John R.D. Dawson, Kevin R. DeMarco, Kyle C. Rouen, Khoa Ngo, Slava Bekker, Vladimir Yarov-Yarovoy, Colleen E. Clancy, Yang K. Xiang, Surl-Hee Ahn, Igor Vorobyov

“…Summary: G protein-coupled receptors (GPCRs) and G proteins transmit signals from hormones and neurotransmitters across cell membranes, initiating downstream signaling and modulating cellular behavior. Using advanced computer modeling and simulation, we identified atomistic-level structural, dynamic, and energetic mechanisms of norepinephrine (NE) and stimulatory G protein (Gs) interactions with β-adrenergic receptors (βARs), crucial GPCRs for heart function regulation and major drug targets. …”
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2.5D Facial Personality Prediction Based on Deep Learning by Jia Xu, Weijian Tian, Guoyun Lv, Shiya Liu, Yangyu Fan

“…We address the objective of comprehensive understanding of a person’s personality traits by developing a multiperspective 2.5D hybrid personality-computing model to evaluate the potential correlation between static facial contour images and personality characteristics. …”
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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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Time-Efficient Contact Consistent Whole-Body Control Framework via Reduced-Dimension Dynamics Construction by Junewhee Ahn, Jaesug Jung, Hokyun Lee, Jaeheung Park

“…The unconstrained chain is reduced using centroidal dynamics, enabling efficient computational modeling in the operational space. By applying the reduced-dimension dynamics to operational space whole-body control, the computational burden caused by the high degrees of freedom in the whole-body dynamics is reduced, leading to shorter computation times. …”
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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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Agent Based Simulation of Group Emotions Evolution and Strategy Intervention in Extreme Events by Bo Li, Duoyong Sun, Shuquan Guo, Zihan Lin

“…Agent based simulation method has become a prominent approach in computational modeling and analysis of public emergency management in social science research. …”
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Directed Evolution of Microbial Communities in Fermented Foods: Strategies, Mechanisms, and Challenges by Zihan Yao, Ting Xie, Hongjie Deng, Shuzhi Xiao, Tao Yang

“…Looking ahead, the integration of advanced omics technologies and computational modeling is anticipated to significantly enhance the predictability and control of microbial community evolution in food fermentation processes. …”
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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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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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Atomistic Simulation of High-Density Uranium Fuels by Jorge Eduardo Garcés, Guillermo Bozzolo

“…Recent experimental results confirmed early theoretical proposals, along the lines of the results reported in this work, showing that atomistic computational modeling could become a valuable tool to aid the experimental work in the development of nuclear fuels.…”
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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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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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