Modelling the rheology of living cell cytoplasm: poroviscoelasticity and fluid-to-solid transition by Thekkethil, Namshad, Köry, Jakub, Guo, Ming, Stewart, Peter S., Hill, Nicholas A., Luo, Xiaoyu

“…To gain insights into this complex rheological behaviour, we construct a computational model for the cell cytoplasm as a poroviscoelastic material formulated on the principles of nonlinear continuum mechanics, where we model the cytoplasm as a porous viscoelastic scaffold with an embedded viscous fluid flowing between the pores to model the cytosol. …”
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Identification of potential critical virulent sites based on hemagglutinin of influenza A virus in past pandemic strains by Yin, Rui, Fransiskus, Xaverius Ivan, Zheng, Jie, Zhou, Xinrui, Chow, Vincent T. K., Kwoh, Chee Keong

“…With increasingly huge biological data, computational modeling is a good technique for analyzing data, providing novel insight into significant patterns and rules. …”
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PCA based feature extraction for cell image retrieval by Ananthagunan Muthukumaran

“…In this Dissertation work a Software programme has been developed which implement Principal Component Analysis for Cell Image retrieval:Principal component analysis, based on information theory concepts, seek a computational model that best describes a cell image, by extracting the most relevant information contained In that image. …”
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A deep learning approach to image quality assessment by Feng, Yeli

“…We explore the computational modeling of image quality assessment (IQA), investigate the vulnerability of DCNNs, and utilize IQA principle to mitigate it. …”
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Modeling osmotic membrane processes without pressure and porosity simplifications by Chong, Y. K., Liang, Y. Y.

“…This work introduces a comprehensive semi-empirical and computational model that eludes these typical simplifications for evaluating forward osmosis (FO), pressure assisted osmosis (PAO), pressure retarded osmosis (PRO) and osmotically assisted reverse osmosis (OARO). …”
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The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware by Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Mohd Zamri, Osman, Alanda, Alde, Erianda, Aldo, Shahreen, Kasim, Mohd Faizal, Ab Razak

“…Deep learning is a machine learning technology that allows computational models to learn via experience, mimicking human cognitive processes. …”
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HIV decision support : from molecule to man by Sloot, Peter M. A., Coveney, P. V., Muller, V., Boucher, Charles A. B., Ertaylan, Gokhan, Bubak, Marian

“…ViroLab contains computational models that cover various spatial and temporal scales from atomic-level interactions in nanoseconds up to sociological interactions on the epidemiological level, spanning years of disease progression. …”
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Information gathering: dissociable effects of autistic and alexithymic traits in youths aged 6–25 years by Lee, KS, Long, EL, Catmur, C, Hauser, TU, Bird, G

“…Dimensional autistic traits were associated with more information gathering regardless of costs and information type. Computational modeling suggested this may be because of the delayed emergence of subjective costs of information gathering in high autistic trait individuals, resulting in later guesses. …”

A review of high-speed rotating HP turbine heat transfer and cooling studies over the last decade in the Oxford Turbine Research Facility by Falsetti, C, Beard, PF, Cardwell, DN, Chana, KS

“…Over the last years, advanced experiments under engine-representative conditions have been performed in the Oxford Turbine Research Facility (OTRF) to obtain high-quality aerothermal data that are essential for developing novel cooling designs and for validating computational models. Thanks to its unique experimental capabilities, the OTRF plays a crucial role in the advancement of HP turbines, which are life limiting components of modern gas turbines due to the harsh high temperature environment. …”

Left Atrial Appendage Occlusion: Current Stroke Prevention Strategies and a Shift Toward Data-Driven, Patient-Specific Approaches by Mendez, Keegan, Kennedy, Darragh G., Wang, Dee Dee, O’Neill, Brian, Roche, Ellen T.

“…We highlighted recent advances in computed tomography imaging, preprocedural planning, computational modeling, and novel additive manufacturing techniques, which represent the tools needed for a paradigm shift toward patient-centric LAA occlusion. …”
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Weighted-persistent-homology-based machine learning for RNA flexibility analysis by Pun, Chi Seng, Yong, Brandon Yung Sin, Xia, Kelin

“…Theoretically, elastic network models, Gaussian network model, flexibility-rigidity model, and other computational models have been proposed for flexibility analysis by shedding light on the biomolecular inner topological structures. …”
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Pre-failure strain localization in siliclastic rocks: a comparative study of laboratory and numerical approaches by Bianchi, Patrick, Selvadurai, Paul Antony, Zilio, Dal Luca, Vásquez, Antonio Salazar, Madonna, Claudio, Gerya, Taras, Wiemer, Stefan

“…A physics-based computational model was subsequently employed to understand the underlying physics of these observations and to establish a spatio-temporal correlation between the laboratory and modeling results. …”
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Modelling the dynamics of microbubble undergoing stable and inertial cavitation: delineating the effects of ultrasound and microbubble parameters on sonothrombolysis by Tan, Zhi Qi, Ooi, Ean Hin, Chiew, Yeong Shiong, Foo, Ji Jinn, Ng, Yin Kwee, Ooi, Ean Tat

“…To address this, a computational model was developed to investigate the bubble behaviour during sonothrombolysis. …”
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Implementation of frequency analysis modules for audio coding on GPU by Meher, Subrat.

“…GPGPU leverages on the enormous computing resources of GPU for data-parallel scientific and engineering applications. Under the GPU computing model, the sequential component of a given application is executed by the CPU, while the computation-intensive data-parallel component is executed concurrently by the multiple cores in GPU. …”
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The search for inhibitors of the quorum sensing receptor of pseudomonas aeruginosa. by Chua, Jenna.

“…An automated docking system was used to run a collection of 10,000 diverse compounds against a computationally modeled PqsR structure, using cavity- and template- based docking methods. …”
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Predicting the antigenicity and reassortment probability of influenza viruses by Ong, Wenqi

“…With data and knowledge on the influenza virus becoming more abundant and accessible in the field of bioinformatics, there is accordingly an increase in the development of computational models for analysis and prediction based on various characteristics of the influenza virus, such as influenza antigenicity. …”
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Revolutionizing treatment for disorders of consciousness: a multidisciplinary review of advancements in deep brain stimulation by Yang, Y, Cao, T, He, S, Wang, L, He, Q, Fan, L, Huang, Y, Zhang, H, Wang, Y, Dang, Y, Wang, N, Chai, X, Wang, D, Jiang, Q, Li, X, Liu, C, Wang, S

“…During the evolution of DOC therapy, the segmentation of central nuclei, the recording of single-neurons, and the analysis of local field potentials have emerged as favorable technical factors that enhance the efficacy of DBS treatment. Advances in computational models have also facilitated a deeper exploration of the neural dynamics associated with DOC, linking neuron-level dynamics with macroscopic behavioral changes. …”

Development of a semi-empirical physical model for transient NOx emissions prediction from a high-speed diesel engine by Bajwa, A, Zou, G, Zhong, F, Fang, X, Leach, F, Davy, M

“…Progress in experimental engine development and computational modelling has led to the generation of a large amount of high-fidelity emissions and in-cylinder data, making it attractive to use data-driven emissions prediction and control models. …”

Heat diffusion during thin-film composite membrane formation by Deshmukh, Akshay, Lienhard, John H., Elimelech, Menachem

“…Using a combination of analytic solutions and computational models, we demonstrate that the thermal effusivities of fluid and material layers can have a significant effect on the temporal evolution of interfacial temperature during IP. …”
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Two complementary features of humoral immune memory confer protection against the same or variant antigens by Van Beek, Matthew, Nussenzweig, Michel C, Chakraborty, Arup K

“…We developed a computational model to study how humoral memory is recalled upon reinfection or booster vaccination. …”
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