Recent advances in live imaging and genetics of mammalian development which integrate observations of biochemical activity, cell-cell signaling and mechanical interactions between cells pave the way for predictive mathematical multi-scale modeling. In early mammalian embryo development, two of the most critical events which lead to tissue patterning involve changes in gene expression as well as...

As semiconductor devices scale to new dimensions, the materials and designs become more dependent on atomic details. NEMO5 is a nanoelectronics modeling package designed for comprehending the critical multi-scale, multi-physics phenomena through efficient computational approaches and quantitatively modeling new generations of nanoelectronic devices as well as predicting novel device architectur...

this paper presents theoretical and numerical state-of-the-art information in the field of hygro-thermo-mechanical deformation simulation in structural concrete. the aspects discussed include coupled hygro-thermo-mechanical performance of porous materials including concrete, multi-scale simulation of concrete properties especially the volumetric and structural deformation performance, and the m...

This paper presents an integrated knowledge-based approach to multi-scale modeling of aquatic systems, with a view to enhancing predictive power and aiding environmental management and policy-making. The basic phases of this approach have been exemplified in the case of a bay in Saronicos Gulf (Attiki, Greece). The results showed a significant problem with rising phytoplankton blooms linked to ...

Dust evolution simulation provides an important way to analyze the impact of dust on the environment. Since wind speed plays a key role in dust evolution, multi-scale simulation is applied to simulate the wind speed in order to improve the accuracy of wind speed simulation and reduce the amount of calculation. Through k-means clustering, the virtual campus can be divided by grids with different...

With the evolution of distributed systems in size and complexity, software deployment remains a challenging task. Despite the existence of several approaches, most of them use informal models that lack a solid mathematic foundation. In this paper, we propose a bigraphical based approach for modeling and formalizing the deployment of distributed applications. This approach relies on multi-scale ...

Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have b...

This study proposes two straightforward yet effective approaches to reduce the required computational time of training process for time-series modeling through a recurrent neural network (RNN) using multi-time-scale data as input. One approach provides coarse and fine temporal resolutions input RNN in parallel. The other concatenates over before considering them RNN. In both approaches, first, ...

We introduce HPS a new topological data structure that e ciently represents hierarchies of planar subdivisions thus providing direct and e cient support for GIS concepts such as abstract generalizations and multi scale partitions Unlike previous ad hoc solutions HPS provides e cient access to adjacency information for each level and across levels while storing the complete hierarchy in a single...