685 research outputs found
Longitudinal Response of Confined Semiflexible Polymers
The longitudinal response of single semiflexible polymers to sudden changes
in externally applied forces is known to be controlled by the propagation and
relaxation of backbone tension. Under many experimental circumstances,
realized, e.g., in nano-fluidic devices or in polymeric networks or solutions,
these polymers are effectively confined in a channel- or tube-like geometry. By
means of heuristic scaling laws and rigorous analytical theory, we analyze the
tension dynamics of confined semiflexible polymers for various generic
experimental setups. It turns out that in contrast to the well-known linear
response, the influence of confinement on the non-linear dynamics can largely
be described as that of an effective prestress. We also study the free
relaxation of an initially confined chain, finding a surprising superlinear
t^(9/8) growth law for the change in end-to-end distance at short times.Comment: 18 pages, 1 figur
Human performance prediction in man-machine systems. Volume 1 - A technical review
Tests and test techniques for human performance prediction in man-machine systems task
Human performance prediction in man-machine systems. Part 2 - The test catalog
Human performance prediction in man machine systems - test catalog table
SCelVis: Powerful explorative single cell data analysis on the desktop and in the cloud
Background: Single cell omics technologies present unique opportunities for biomedical and life sciences from lab to clinic, but the high dimensional nature of such data poses challenges for computational analysis and interpretation. Furthermore, FAIR data management as well as data privacy and security become crucial when working with clinical data, especially in cross-institutional and translational settings. Existing solutions are either bound to the desktop of one researcher or come with dependencies on vendor-specific technology for cloud storage or user authentication. Results: To facilitate analysis and interpretation of single-cell data by users without bioinformatics expertise, we present SCelVis, a flexible, interactive and user-friendly app for web-based visualization of pre-processed single-cell data. Users can survey multiple interactive visualizations of their single cell expression data and cell annotation, and download raw or processed data for further offline analysis. SCelVis can be run both on the desktop and cloud systems, accepts input from local and various remote sources using standard and open protocols, and allows for hosting data in the cloud and locally. Methods: SCelVis is implemented in Python using Dash by Plotly. It is available as a standalone application as a Python package, via Conda/Bioconda and as a Docker image. All components are available as open source under the permissive MIT license and are based on open standards and interfaces, enabling further development and integration with third party pipelines and analysis components. The GitHub repository is https://github.com/bihealth/scelvis
SCelVis: exploratory single cell data analysis on the desktop and in the cloud
BACKGROUND: Single cell omics technologies present unique opportunities for biomedical and life sciences from lab to clinic, but the high dimensional nature of such data poses challenges for computational analysis and interpretation. Furthermore, FAIR data management as well as data privacy and security become crucial when working with clinical data, especially in cross-institutional and translational settings. Existing solutions are either bound to the desktop of one researcher or come with dependencies on vendor-specific technology for cloud storage or user authentication. RESULTS: To facilitate analysis and interpretation of single-cell data by users without bioinformatics expertise, we present SCelVis, a flexible, interactive and user-friendly app for web-based visualization of pre-processed single-cell data. Users can survey multiple interactive visualizations of their single cell expression data and cell annotation, define cell groups by filtering or manual selection and perform differential gene expression, and download raw or processed data for further offline analysis. SCelVis can be run both on the desktop and cloud systems, accepts input from local and various remote sources using standard and open protocols, and allows for hosting data in the cloud and locally. We test and validate our visualization using publicly available scRNA-seq data. METHODS: SCelVis is implemented in Python using Dash by Plotly. It is available as a standalone application as a Python package, via Conda/Bioconda and as a Docker image. All components are available as open source under the permissive MIT license and are based on open standards and interfaces, enabling further development and integration with third party pipelines and analysis components. The GitHub repository is https://github.com/bihealth/scelvis
Pinwheel stabilization by ocular dominance segregation
We present an analytical approach for studying the coupled development of
ocular dominance and orientation preference columns. Using this approach we
demonstrate that ocular dominance segregation can induce the stabilization and
even the production of pinwheels by their crystallization in two types of
periodic lattices. Pinwheel crystallization depends on the overall dominance of
one eye over the other, a condition that is fulfilled during early cortical
development. Increasing the strength of inter-map coupling induces a transition
from pinwheel-free stripe solutions to intermediate and high pinwheel density
states.Comment: 10 pages, 4 figure
Cellular Structures for Computation in the Quantum Regime
We present a new cellular data processing scheme, a hybrid of existing
cellular automata (CA) and gate array architectures, which is optimized for
realization at the quantum scale. For conventional computing, the CA-like
external clocking avoids the time-scale problems associated with ground-state
relaxation schemes. For quantum computing, the architecture constitutes a novel
paradigm whereby the algorithm is embedded in spatial, as opposed to temporal,
structure. The architecture can be exploited to produce highly efficient
algorithms: for example, a list of length N can be searched in time of order
cube root N.Comment: 11 pages (LaTeX), 3 figure
The application of active side arm controllers in helicopters
Eurocopter Deutschland (ECD) started simulation trials to investigate the particular problems of Side Arm Controllers (SAC) applied to helicopters. Two simulation trials have been performed. In the first trial, the handling characteristics of a 'passive' SAC and the basic requirements for the application of an 'active' SAC were evaluated in pilot-in-the-loop simulations, performing the tasks in a realistic scenario representing typical phases of a transport mission. The second simulation trial investigated the general control characteristics of the 'active' in comparison to the 'passive' control principle. A description of the SACs developed by ECD and the principle of the 'passive' and 'active' control concept is given, as well as specific ratings for the investigated dynamic and ergonomic parameters effecting SAC characteristics. The experimental arrangements, as well as the trials procedures of both simulation phases, are described and the results achieved are discussed emphasizing the advantages of the 'active' as opposed to the 'passive' SAC concept. This also includes the presentation of some critical aspects still to be improved and proposals to solve them
Emergence of robust nucleosome patterns from an interplay of positioning mechanisms
Proper positioning of nucleosomes in eukaryotic cells is determined by a complex interplay of factors, including nucleosome-nucleosome interactions, DNA sequence, and active chromatin remodeling. Yet, characteristic features of nucleosome positioning, such as geneaveraged nucleosome patterns, are surprisingly robust across perturbations, conditions, and species. Here, we explore how this robustness arises despite the underlying complexity. We leverage mathematical models to show that a large class of positioning mechanisms merely affects the quantitative characteristics of qualitatively robust positioning patterns. We demonstrate how statistical positioning emerges as an effective description from the complex interplay of different positioning mechanisms, which ultimately only renormalize the model parameter quantifying the effective softness of nucleosomes. This renormalization can be species-specific, rationalizing a puzzling discrepancy between the effective nucleosome softness of S. pombe and S. cerevisiae. More generally, we establish a quantitative framework for dissecting the interplay of different nucleosome positioning determinants
Symmetry considerations and development of pinwheels in visual maps
Neurons in the visual cortex respond best to rod-like stimuli of given
orientation. While the preferred orientation varies continuously across most of
the cortex, there are prominent pinwheel centers around which all orientations
a re present. Oriented segments abound in natural images, and tend to be
collinear}; neurons are also more likely to be connected if their preferred
orientations are aligned to their topographic separation. These are indications
of a reduced symmetry requiring joint rotations of both orientation preference
and the underl ying topography. We verify that this requirement extends to
cortical maps of mo nkey and cat by direct statistical analysis. Furthermore,
analytical arguments and numerical studies indicate that pinwheels are
generically stable in evolving field models which couple orientation and
topography
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