scholarly journals Multi-scale imaging and analysis identify pan-embryo cell dynamics of germlayer formation in zebrafish

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Gopi Shah ◽  
Konstantin Thierbach ◽  
Benjamin Schmid ◽  
Johannes Waschke ◽  
Anna Reade ◽  
...  
Keyword(s):  
Cell Movement ◽  
Automated Analysis ◽  
Embryo Cell ◽  
Tissue Formation ◽  
Cell Dynamics ◽  
Multi Scale ◽  
Movement Characteristics ◽  
Global Movement ◽  
Spatio Temporal ◽  
Distinct Distribution

AbstractThe coordination of cell movements across spatio-temporal scales ensures precise positioning of organs during vertebrate gastrulation. Mechanisms governing such morphogenetic movements have been studied only within a local region, a single germlayer or in whole embryos without cell identity. Scale-bridging imaging and automated analysis of cell dynamics are needed for a deeper understanding of tissue formation during gastrulation. Here, we report pan-embryo analyses of formation and dynamics of all three germlayers simultaneously within a developing zebrafish embryo. We show that a distinct distribution of cells in each germlayer is established during early gastrulation via cell movement characteristics that are predominantly determined by their position in the embryo. The differences in initial germlayer distributions are subsequently amplified by a global movement, which organizes the organ precursors along the embryonic body axis, giving rise to the blueprint of organ formation. The tools and data are available as a resource for the community.

scholarly journals Pan-embryo cell dynamics of germlayer formation in zebrafish

2017 ◽  
Author(s):  
Gopi Shah ◽  
Konstantin Thierbach ◽  
Benjamin Schmid ◽  
Anna Reade ◽  
Ingo Roeder ◽  
...  
Keyword(s):  
Cell Movement ◽  
Initial Distribution ◽  
Embryo Cell ◽  
Local Region ◽  
Cell Dynamics ◽  
Fate Specification ◽  
Movement Characteristics ◽  
Global Movement ◽  
Spatio Temporal ◽  
Distinct Distribution

AbstractCell movements are coordinated across spatio-temporal scales to achieve precise positioning of organs during vertebrate gastrulation. In zebrafish, mechanisms governing such morphogenetic movements have so far only been studied within a local region or a single germlayer. Here, we present pan-embryo analyses of fate specification and dynamics of all three germlayers simultaneously within a gastrulating embryo, showing that cell movement characteristics are predominantly determined by its position within the embryo, independent of its germlayer identity. The spatially confined fate specification establishes a distinct distribution of cells in each germlayer during early gastrulation. The differences in the initial distribution are subsequently amplified by a unique global movement, which organizes the organ precursors along the embryonic body axis, giving rise to the blueprint of organ formation.

scholarly journals A Spatio-Temporal Local Association Query Algorithm for Multi-Source Remote Sensing Big Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2333
Author(s):  
Lilu Zhu ◽  
Xiaolu Su ◽  
Yanfeng Hu ◽  
Xianqing Tai ◽  
Kun Fu
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Temporal Correlation ◽  
Local Association ◽  
Sensing Data ◽  
Multi Scale ◽  
Correlation Networks ◽  
Efficient Integration ◽  
Spatio Temporal ◽  
Query Algorithm

It is extremely important to extract valuable information and achieve efficient integration of remote sensing data. The multi-source and heterogeneous nature of remote sensing data leads to the increasing complexity of these relationships, and means that the processing mode based on data ontology cannot meet requirements any more. On the other hand, the multi-dimensional features of remote sensing data bring more difficulties in data query and analysis, especially for datasets with a lot of noise. Therefore, data quality has become the bottleneck of data value discovery, and a single batch query is not enough to support the optimal combination of global data resources. In this paper, we propose a spatio-temporal local association query algorithm for remote sensing data (STLAQ). Firstly, we design a spatio-temporal data model and a bottom-up spatio-temporal correlation network. Then, we use the method of partition-based clustering and the method of spectral clustering to measure the correlation between spatio-temporal correlation networks. Finally, we construct a spatio-temporal index to provide joint query capabilities. We carry out local association query efficiency experiments to verify the feasibility of STLAQ on multi-scale datasets. The results show that the STLAQ weakens the barriers between remote sensing data, and improves their application value effectively.

scholarly journals Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

Sensors ◽  
2018 ◽  
Vol 18 (2) ◽  
pp. 498 ◽  
Author(s):  
Hong Zhu ◽  
Xinming Tang ◽  
Junfeng Xie ◽  
Weidong Song ◽  
Fan Mo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Super Resolution ◽  
Remote Sensing Images ◽  
Multi Scale ◽  
Spatio Temporal ◽  
Detail Enhancement

ON THE REPRESENTATION, LEARNING AND TRANSFER OF SPATIO-TEMPORAL MOVEMENT CHARACTERISTICS

2004 ◽  
Vol 01 (04) ◽  
pp. 613-636 ◽  
Author(s):  
WINFRIED ILG ◽  
GÖKHAN H. BAKIR ◽  
JOHANNES MEZGER ◽  
MARTIN A. GIESE
Keyword(s):  
Representation Learning ◽  
Movement Sequences ◽  
Movement Trajectories ◽  
Movement Characteristics ◽  
Human Movements ◽  
Complex Sequences ◽  
Movement Representation ◽  
Spatio Temporal ◽  
Morphable Models ◽  
Complex Movement

In this paper we present a learning-based approach for the modeling of complex movement sequences. Based on the method of Spatio-Temporal Morphable Models (STMMs) we derive a hierarchical algorithm that, in a first step, identifies automatically movement elements in movement sequences based on a coarse spatio-temporal description, and in a second step models these movement primitives by approximation through linear combinations of learned example movement trajectories. We describe the different steps of the algorithm and show how it can be applied for modeling and synthesis of complex sequences of human movements that contain movement elements with a variable style. The proposed method is demonstrated on different applications of movement representation relevant for imitation learning of movement styles in humanoid robotics.

scholarly journals Re-Arranging Space, Time and Scales in GIS: Alternative Models for Multi-Scale Spatio-Temporal Modeling and Analyses

2019 ◽  
Vol 8 (2) ◽  
pp. 72 ◽  
Author(s):  
Yi Qiang ◽  
Nico Van de Weghe
Keyword(s):  
Spatial Data ◽  
Spatial Scales ◽  
Space Time ◽  
Unified Framework ◽  
Temporal Modeling ◽  
Multi Scale ◽  
Space And Time ◽  
Pyramid Model ◽  
Temporal And Spatial ◽  
Spatio Temporal

The representations of space and time are fundamental issues in GIScience. In prevalent GIS and analytical systems, time is modeled as a linear stream of real numbers and space is represented as flat layers with timestamps. Despite their dominance in GIS and information visualization, these representations are inefficient for visualizing data with complex temporal and spatial extents and the variation of data at multiple temporal and spatial scales. This article presents alternative representations that incorporate the scale dimension into time and space. The article first reviews a series of work about the triangular model (TM), which is a multi-scale temporal model. Then, it introduces the pyramid model (PM), which is the extension of the TM for spatial data, and demonstrates the utility of the PM in visualizing multi-scale spatial patterns of land cover data. Finally, it discusses the potential of integrating the TM and the PM into a unified framework for multi-scale spatio-temporal modeling. This article systematically documents the models with alternative arrangements of space and time and their applications in analyzing different types of data. Additionally, this article aims to inspire the re-thinking of organizations of space, time, and scales in the future development of GIS and analytical tools to handle the increasing quantity and complexity of spatio-temporal data.

scholarly journals Editorial

2019 ◽  
Vol 30 (5) ◽  
pp. 829-829
Author(s):  
R. Kuske ◽  
D. Yurchenko
Keyword(s):  
Stochastic Models ◽  
Stochastic Dynamics ◽  
Single Issue ◽  
Stochastic Effects ◽  
Multi Scale ◽  
Multiscale Dynamics ◽  
New Methodologies ◽  
Spatio Temporal ◽  
Multi Mode ◽  
Different Sources

The origin of this special issue took place at the 9th European Nonlinear Dynamics Conference (ENOC 2017) in Budapest, Hungary. Specifically, the mini-symposium on Random Dynamical Systems – Recent Advances and New Directions brought together novel perspectives on analyzing stochastic dynamics with applications including biology, structural dynamics, control, energy and mechanics. The expanded use of stochasticity in more realistic models exposes questions related to bifurcations, meta-stability, tipping and early warning signals, multiscale dynamics, and connections between chaos and stochastic dynamics. The observed phenomena in applications drive new methodologies and analyses, needed to understand the interplay between different sources of stochastic effects and nonlinearities, network structure, multi-mode and multi-scale behavior, non-smooth dynamics, energy transfer, and spatio-temporal phenomena. Of course, a single issue cannot hope to cover all of the new topics in stochastic analysis for applications. Nevertheless, we hope that the collection of applications and stochastic models presented in this issue illustrates some of the exciting advances and perspectives relevant for broad classes of stochastic models and demonstrates the need in advancing the theory of stochastic processes.

scholarly journals A multi-scale eco-evolutionary model of cooperation reveals how microbial adaptation influences soil decomposition

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Elsa Abs ◽  
Hélène Leman ◽  
Régis Ferrière
Keyword(s):  
Temporal Dynamics ◽  
Global Environmental Change ◽  
Evolutionary Model ◽  
Terrestrial Ecosystems ◽  
Microbial Decomposition ◽  
Multi Scale ◽  
Spatio Temporal ◽  
The Stability ◽  
Micro Organisms ◽  
Som Decomposition

AbstractThe decomposition of soil organic matter (SOM) is a critical process in global terrestrial ecosystems. SOM decomposition is driven by micro-organisms that cooperate by secreting costly extracellular (exo-)enzymes. This raises a fundamental puzzle: the stability of microbial decomposition in spite of its evolutionary vulnerability to “cheaters”—mutant strains that reap the benefits of cooperation while paying a lower cost. Resolving this puzzle requires a multi-scale eco-evolutionary model that captures the spatio-temporal dynamics of molecule-molecule, molecule-cell, and cell-cell interactions. The analysis of such a model reveals local extinctions, microbial dispersal, and limited soil diffusivity as key factors of the evolutionary stability of microbial decomposition. At the scale of whole-ecosystem function, soil diffusivity influences the evolution of exo-enzyme production, which feeds back to the average SOM decomposition rate and stock. Microbial adaptive evolution may thus be an important factor in the response of soil carbon fluxes to global environmental change.

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