scholarly journals Towards NeuroML: Model Description Methods for Collaborative Modelling in Neuroscience

2001 ◽  
Vol 356 (1412) ◽  
pp. 1209-1228 ◽  
Author(s):  
Nigel H. Goddard ◽  
Michael Hucka ◽  
Fred Howell ◽  
Hugo Cornelis ◽  
Kavita Shankar ◽  
...  
Keyword(s):  
High Performance ◽  
Computational Models ◽  
Object Oriented ◽  
Model Description ◽  
Specific Component ◽  
Nervous Systems ◽  
Efficient Simulation ◽  
Performance Framework ◽  
Structural Levels ◽  
Modelling Process

Biological nervous systems and the mechanisms underlying their operation exhibit astonishing complexity. Computational models of these systems have been correspondingly complex. As these models become ever more sophisticated, they become increasingly difficult to define, comprehend, manage and communicate. Consequently, for scientific understanding of biological nervous systems to progress, it is crucial for modellers to have software tools that support discussion, development and exchange of computational models. We describe methodologies that focus on these tasks, improving the ability of neuroscientists to engage in the modelling process. We report our findings on the requirements for these tools and discuss the use of declarative forms of model description—equivalent to object–oriented classes and database schema—which we call templates. We introduce NeuroML, a mark–up language for the neurosciences which is defined syntactically using templates, and its specific component intended as a common format for communication between modelling–related tools. Finally, we propose a template hierarchy for this modelling component of NeuroML, sufficient for describing models ranging in structural levels from neuron cell membranes to neural networks. These templates support both a framework for user–level interaction with models, and a high–performance framework for efficient simulation of the models.

scholarly journals Cells in Silico – introducing a high-performance framework for large-scale tissue modeling

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Marco Berghoff ◽  
Jakob Rosenbauer ◽  
Felix Hoffmann ◽  
Alexander Schug
Keyword(s):  
In Silico ◽  
High Performance ◽  
Large Scale ◽  
Computational Models ◽  
Modular Design ◽  
Model Simulation ◽  
Three Dimensional ◽  
Cellular Potts Model ◽  
Performance Framework ◽  
Wide Range

Abstract Background Discoveries in cellular dynamics and tissue development constantly reshape our understanding of fundamental biological processes such as embryogenesis, wound-healing, and tumorigenesis. High-quality microscopy data and ever-improving understanding of single-cell effects rapidly accelerate new discoveries. Still, many computational models either describe few cells highly detailed or larger cell ensembles and tissues more coarsely. Here, we connect these two scales in a joint theoretical model. Results We developed a highly parallel version of the cellular Potts model that can be flexibly applied and provides an agent-based model driving cellular events. The model can be modular extended to a multi-model simulation on both scales. Based on the NAStJA framework, a scaling implementation running efficiently on high-performance computing systems was realized. We demonstrate independence of bias in our approach as well as excellent scaling behavior. Conclusions Our model scales approximately linear beyond 10,000 cores and thus enables the simulation of large-scale three-dimensional tissues only confined by available computational resources. The strict modular design allows arbitrary models to be configured flexibly and enables applications in a wide range of research questions. Cells in Silico (CiS) can be easily molded to different model assumptions and help push computational scientists to expand their simulations to a new area in tissue simulations. As an example we highlight a 10003 voxel-sized cancerous tissue simulation at sub-cellular resolution.

scholarly journals Supervised Domain Adaptation for Automated Semantic Segmentation of the Atrial Cavity

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 898
Author(s):  
Marta Saiz-Vivó ◽  
Adrián Colomer ◽  
Carles Fonfría ◽  
Luis Martí-Bonmatí ◽  
Valery Naranjo
Keyword(s):  
High Performance ◽  
Computational Models ◽  
Domain Adaptation ◽  
Semantic Segmentation ◽  
Patient Specific ◽  
Mr Images ◽  
Training Samples ◽  
Volumetric Images ◽  
Acquisition Costs ◽  
Left And Right

Atrial fibrillation (AF) is the most common cardiac arrhythmia. At present, cardiac ablation is the main treatment procedure for AF. To guide and plan this procedure, it is essential for clinicians to obtain patient-specific 3D geometrical models of the atria. For this, there is an interest in automatic image segmentation algorithms, such as deep learning (DL) methods, as opposed to manual segmentation, an error-prone and time-consuming method. However, to optimize DL algorithms, many annotated examples are required, increasing acquisition costs. The aim of this work is to develop automatic and high-performance computational models for left and right atrium (LA and RA) segmentation from a few labelled MRI volumetric images with a 3D Dual U-Net algorithm. For this, a supervised domain adaptation (SDA) method is introduced to infer knowledge from late gadolinium enhanced (LGE) MRI volumetric training samples (80 LA annotated samples) to a network trained with balanced steady-state free precession (bSSFP) MR images of limited number of annotations (19 RA and LA annotated samples). The resulting knowledge-transferred model SDA outperformed the same network trained from scratch in both RA (Dice equals 0.9160) and LA (Dice equals 0.8813) segmentation tasks.

scholarly journals A Chip for a Routing Table Based on a Novel Modified Trie Algorithm

VLSI Design ◽  
2000 ◽  
Vol 11 (4) ◽  
pp. 405-415
Author(s):  
D. Torres ◽  
A. Larios ◽  
M. Guzmán
Keyword(s):  
Data Structure ◽  
High Performance ◽  
Object Oriented ◽  
Pci Bus ◽  
Memory Space ◽  
General Behavior ◽  
Routing Table ◽  
Starting Point ◽  
Associated Data

The design for a routing table circuit for Ethernet-, IP- and ATM-applications is presented. Starting point for the design was an object-oriented general behavior of the routing table. The selected data structure for the routing table is based on a modification of the structure denominated trie, saving one search level and memory space. The architecture for searching and sorting of data, implemented in hardware, is explained. This modified trie stores 64 K addresses and the associated data, achieving a high performance too. The circuit, which can support a flow of 500000 frames/s, is connected to the PCI Bus. For the implementation a FLEX10K100 from Altera Company was used.

scholarly journals Multi-Scale Digital Image Correlation Analysis of In Situ Deformation of Open-Cell UHMWPE Foam

2020 ◽  
Author(s):  
Eugene S. Statnik ◽  
Codrutza Dragu ◽  
Cyril Besnard ◽  
Alexander J.G. Lunt ◽  
Alexey I. Salimon ◽  
...  
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
High Performance ◽  
Structural Evolution ◽  
Image Correlation ◽  
Deformation Bands ◽  
Open Cell ◽  
Polyether Ether Ketone ◽  
Structural Levels

Porous ultra-high molecular weight polyethylene (UHMWPE) is a high performance bioinert polymer used in cranio-facial reconstructive surgery in procedures where relatively low mechanical stresses arise. As an alternative to much stiffer and costly polyether-ether-ketone (PEEK) polymer, UHMWPE finds further wide application in hierarchically structured hybrids for advanced implants mimicking cartilage, cortical and trabecular bone tissues within a single component. The mechanical behaviour of open-cell UHMWPE sponges obtained through sacrificial desalination of hot compression-moulded UHMWPE-NaCl powder mixtures shows a complex dependence on the fabrication parameters and microstructural features. In particular, similarly to other porous media it displays significant inhomogeneity of strain that readily localises within deformation bands that govern the overall response. In this article, we report advances in the development of accurate experimental techniques for operando studies of the structure-performance relationship applied to the porous UHMWPE medium with pore sizes of about 250 µm that are most well-suited for live cell proliferation and fast vascularization of implants. Samples of UHMWPE sponges were subjected to in situ compression using a micromechanical testing device within Scanning Electron Microscope (SEM) chamber, allowing the acquisition of high-resolution image sequences for Digital Image Correlation (DIC) analysis. Special masking and image processing algorithms were developed and applied to reveal the evolution of pore size and aspect ratio. Key structural evolution and deformation localisation phenomena were identified at both macro- and micro-structural levels in the elastic and plastic regimes. The motion of pore walls was quantitatively described, and the presence and influence of strain localisation zones were revealed and analysed using DIC technique.

scholarly journals Two-Chains: High Performance Framework for Function Injection and Execution

2021 ◽  
Author(s):  
Megan Grodowitz ◽  
Luis E. Pena ◽  
Curtis Dunham ◽  
Dong Zhong ◽  
Pavel Shamis ◽  
...  
Keyword(s):  
High Performance ◽  
Performance Framework
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