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