The Experts below are selected from a list of 763398 Experts worldwide ranked by ideXlab platform
Peter T Cummings - One of the best experts on this subject based on the ideXlab platform.
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investigation of bone resorption within a cortical basic multicellular unit using a lattice based Computational Model
Bone, 2012Co-Authors: Pascal R Buenzli, Junhwan Jeon, Peter Pivonka, David C Smith, Peter T CummingsAbstract:In this paper we develop a lattice-based Computational Model focused on bone resorption by osteoclasts in a single cortical basic multicellular unit (BMU). Our Model takes into account the interaction of osteoclasts with the bone matrix, the interaction of osteoclasts with each other, the generation of osteoclasts from a growing blood vessel, and the renewal of osteoclast nuclei by cell fusion. All these features are shown to strongly influence the geometrical properties of the developing resorption cavity including its size, shape and progression rate, and are also shown to influence the distribution, resorption pattern and trajectories of individual osteoclasts within the BMU. We demonstrate that for certain parameter combinations, resorption cavity shapes can be recovered from the Computational Model that closely resemble resorption cavity shapes observed from microCT imaging of human cortical bone.
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investigation of bone resorption within a cortical basic multicellular unit using a lattice based Computational Model
Institute of Health and Biomedical Innovation; Science & Engineering Faculty, 2012Co-Authors: Pascal R Buenzli, Junhwan Jeon, Peter Pivonka, David C Smith, Peter T CummingsAbstract:In this paper we develop a lattice-based Computational Model focused on bone resorption by osteoclasts in a single cortical basic multicellular unit (BMU). Our Model takes into account the interaction of osteoclasts with the bone matrix, the interaction of osteoclasts with each other, the generation of osteoclasts from a growing blood vessel, and the renewal of osteoclast nuclei by cell fusion. All these features are shown to strongly influence the geometrical properties of the developing resorption cavity including its size, shape and progression rate, and are also shown to influence the distribution, resorption pattern and trajectories of individual osteoclasts within the BMU. We demonstrate that for certain parameter combinations, resorption cavity shapes can be recovered from the Computational Model that closely resemble resorption cavity shapes observed from microCT imaging of human cortical bone. (C) 2011 Elsevier Inc. All rights reserved.
Parthajit Roy - One of the best experts on this subject based on the ideXlab platform.
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A homomorphic Computational Model for Chinese remainder theorem-based secret sharing
Innovations in Systems and Software Engineering, 2019Co-Authors: Parthajit RoyAbstract:This paper proposes a fully homomorphic Computational Model for secret sharing. The backbone of the proposed Model is Chinese remainder theorem. The proposed Model achieves non-threshold secret sharing. The homomorphism has been achieved using ElGamal and Paillier systems. Cryptographic hash function has been used for the identification of the true shareholders. The Model identifies the legitimate shareholders without revealing their secret information. Thus, the Model is a zero-knowledge proof of the identification Model also. Further, the Model regenerates the secret in the homomorphic domain. The efficiency and security of the Model have also been analyzed.
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A homomorphic Computational Model for Chinese remainder theorem-based secret sharing
Innovations in Systems and Software Engineering, 2019Co-Authors: Parthajit RoyAbstract:This paper proposes a fully homomorphic Computational Model for secret sharing. The backbone of the proposed Model is Chinese remainder theorem. The proposed Model achieves non-threshold secret sharing. The homomorphism has been achieved using ElGamal and Paillier systems. Cryptographic hash function has been used for the identification of the true shareholders. The Model identifies the legitimate shareholders without revealing their secret information. Thus, the Model is a zero-knowledge proof of the identification Model also. Further, the Model regenerates the secret in the homomorphic domain. The efficiency and security of the Model have also been analyzed.
Pascal R Buenzli - One of the best experts on this subject based on the ideXlab platform.
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investigation of bone resorption within a cortical basic multicellular unit using a lattice based Computational Model
Bone, 2012Co-Authors: Pascal R Buenzli, Junhwan Jeon, Peter Pivonka, David C Smith, Peter T CummingsAbstract:In this paper we develop a lattice-based Computational Model focused on bone resorption by osteoclasts in a single cortical basic multicellular unit (BMU). Our Model takes into account the interaction of osteoclasts with the bone matrix, the interaction of osteoclasts with each other, the generation of osteoclasts from a growing blood vessel, and the renewal of osteoclast nuclei by cell fusion. All these features are shown to strongly influence the geometrical properties of the developing resorption cavity including its size, shape and progression rate, and are also shown to influence the distribution, resorption pattern and trajectories of individual osteoclasts within the BMU. We demonstrate that for certain parameter combinations, resorption cavity shapes can be recovered from the Computational Model that closely resemble resorption cavity shapes observed from microCT imaging of human cortical bone.
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investigation of bone resorption within a cortical basic multicellular unit using a lattice based Computational Model
Institute of Health and Biomedical Innovation; Science & Engineering Faculty, 2012Co-Authors: Pascal R Buenzli, Junhwan Jeon, Peter Pivonka, David C Smith, Peter T CummingsAbstract:In this paper we develop a lattice-based Computational Model focused on bone resorption by osteoclasts in a single cortical basic multicellular unit (BMU). Our Model takes into account the interaction of osteoclasts with the bone matrix, the interaction of osteoclasts with each other, the generation of osteoclasts from a growing blood vessel, and the renewal of osteoclast nuclei by cell fusion. All these features are shown to strongly influence the geometrical properties of the developing resorption cavity including its size, shape and progression rate, and are also shown to influence the distribution, resorption pattern and trajectories of individual osteoclasts within the BMU. We demonstrate that for certain parameter combinations, resorption cavity shapes can be recovered from the Computational Model that closely resemble resorption cavity shapes observed from microCT imaging of human cortical bone. (C) 2011 Elsevier Inc. All rights reserved.
Nicolas P. Rougier - One of the best experts on this subject based on the ideXlab platform.
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A distributed Computational Model of spatial memory anticipation during a visual search task
2007Co-Authors: Jérémy Fix, Julien Vitay, Nicolas P. RougierAbstract:Some visual search tasks require the memorization of the location of stimuli that have been previously focused. Considerations about the eye movements raise the question of how we are able to maintain a coherent memory, despite the frequent drastic changes in the perception. In this article, we present a Computational Model that is able to anticipate the consequences of eye movements on visual perception in order to update a spatial working memory.
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A Computational Model of Spatial Memory Anticipation during Visual Search
2006Co-Authors: Jérémy Fix, Julien Vitay, Nicolas P. RougierAbstract:Some visual search tasks require to memorize the location of stimuli that have been previously scanned. Considerations about the eye movements raise the question of how we are able to maintain a coherent memory, despite the frequent drastically changes in the perception. In this article, we present a Computational Model that is able to anticipate the consequences of the eye movements on the visual perception in order to update a spatial memory
Wolfgang Kelsch - One of the best experts on this subject based on the ideXlab platform.
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a Computational Model of oxytocin modulation of olfactory recognition memory
eNeuro, 2019Co-Authors: Christiane Linster, Wolfgang KelschAbstract:Abstract Social recognition in mammals depends on complex interactions between sensory and other brain areas as well as modulatory inputs by specific neuropeptides such as oxytocin (OXT). Social recognition memory specifically has been shown to depend among others on olfactory processing, and can be probed using methods similar to those used when probing non-social odor memory. We here use a Computational Model of two interconnected olfactory networks in the mouse, the olfactory bulb and anterior olfactory nucleus, to propose a mechanism for olfactory short term recognition memory and its modulation in social situations. Based on previous experiments, we propose one early locus for memory to be the olfactory bulb. During social encounters in mice, pyramidal cells in the AON, themselves driven by olfactory input, are rendered more excitable by OXT release, resulting in stronger feedback to olfactory bulb local interneurons. This additional input to the OB creates stronger dynamics and improves signal to noise ratio of odor responses in the OB proper. As a consequence, mouse social olfactory memories are more strongly encoded and their duration is modulated. Significance statement Oxytocin has long been associated with modulating neural networks during social encounters. We here use a Computational Model to show how neural plasticity, modulation and memory for social odors interact when animals encounter conspecific odors. To date the exact neural processes of oxytocin modulation of social odor memory are not elucidated; our Modeling approach allows us to draw from a number of experimental data from different levels of analyses to create a coherent framework for how oxytocin modulates odor processing to match behavioral demands.
