A Software Tool for Simulating Motions and Loading in Planar Tensegrity Structures

Author(s):  
Carl A. Nelson

Tensegrity structures are unique in the sense that they tend to be overconstrained as mechanisms, yet they can be mobile due to the elastic nature of their tensile elements. The ability to easily visualize these motion properties would help designers to create new and useful tensegrity mechanisms. In this paper, a simple and interactive computational tool with a graphical user interface is presented for visualizing loading and displacements in tensegrity structures. This tool can also be extended for use with traditional static structures, including both determinate and indeterminate structures, as well as mechanisms.

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Pavel Novoa-Hernández ◽  
Carlos Cruz Corona ◽  
David A. Pelta

In real world, many optimization problems are dynamic, which means that their model elements vary with time. These problems have received increasing attention over time, especially from the viewpoint of metaheuristics methods. In this context, experimentation is a crucial task because of the stochastic nature of both algorithms and problems. Currently, there are several technologies whose methods, problems, and performance measures can be implemented. However, in most of them, certain features that make the experimentation process easy are not present. Examples of such features are the statistical analysis of the results and a graphical user interface (GUI) that allows an easy management of the experimentation process. Bearing in mind these limitations, in the present work, we present DynOptLab, a software tool for experimental analysis in dynamic environments. DynOptLab has two main components: (1) an object-oriented framework to facilitate the implementation of new proposals and (2) a graphical user interface for the experiment management and the statistical analysis of the results. With the aim of verifying the benefits of DynOptLab’s main features, a typical case study on experimentation in dynamic environments was carried out.


2020 ◽  
Author(s):  
Thomas Blackwell ◽  
W. Tom Stump ◽  
Sarah R. Clippinger ◽  
Michael J. Greenberg

AbstractMolecular motors couple chemical transitions to conformational changes that perform mechanical work in a wide variety of biological processes. Disruption of this coupling can lead to diseases, and therefore there is a need to accurately measure mechanochemical coupling in motors in both health and disease. Optical tweezers, with nanometer spatial and millisecond temporal resolution, have provided valuable insights into these processes. However, fluctuations due to Brownian motion can make it difficult to precisely resolve these conformational changes. One powerful analysis technique that has improved our ability to accurately measure mechanochemical coupling in motor proteins is ensemble averaging of individual trajectories. Here, we present a user-friendly computational tool, Software for Precise Analysis of Single Molecules (SPASM), for generating ensemble averages of single-molecule data. This tool utilizes several conceptual advances, including optimized procedures for identifying single-molecule interactions and the implementation of a change point algorithm, to more precisely resolve molecular transitions. Using both simulated and experimental data, we demonstrate that these advances allow for accurate determination of the mechanics and kinetics of the myosin working stroke with a smaller set of data. Importantly, we provide our open source MATLAB-based program with a graphical user interface that enables others to readily apply these advances to the analysis of their own data.Statement of SignificanceSingle molecule optical trapping experiments have given unprecedented insights into the mechanisms of molecular machines. Analysis of these experiments is often challenging because Brownian motion-induced fluctuations introduce noise that can obscure molecular motions. A powerful technique for analyzing these noisy traces is ensemble averaging of individual binding interactions, which can uncover information about the mechanics and kinetics of molecular motions that are typically obscured by Brownian motion. Here, we provide an open source, easy-to-use computational tool, SPASM, with a graphical user interface for ensemble averaging of single molecule data. This computational tool utilizes several conceptual advances that significantly improve the accuracy and resolution of ensemble averages, enabling the generation of high-resolution averages from a smaller number of binding interactions.


Author(s):  
A. V. Khvostikov ◽  
D. M. Korshunov ◽  
A. S. Krylov ◽  
M. A. Boguslavskiy

Abstract. Automatic identification of minerals in images of polished section is highly demanded in exploratory geology as it can provide a significant reduction in time spent in the study of ores and eliminate the factor of misdiagnosis of minerals. The development of algorithms for automatic analysis of images of polished sections makes it possible to create of a universal tool for comparing ores from different deposits, which is also much in demand. The main contribution of this paper can be summed up in three parts: i) creation of LumenStone dataset (https://imaging.cs.msu.ru/en/research/geology/lumenstone) which unites high-quality geological images of different mineral associations and provides pixel-level semantic segmentation masks, ii) development of CNN-based neural network for automatic identification of minerals in images of polished sections, iii) implementation of software tool with graphical user interface that can be used by expert geologists to perform an automatic analysis of polished sections images.


2018 ◽  
Author(s):  
Christian Trachsel ◽  
Christian Panse ◽  
Tobias Kockmann ◽  
Witold E. Wolski ◽  
Jonas Grossmann ◽  
...  

AbstractOptimizing methods for liquid chromatography coupled to mass spectrometry (LC-MS) is a non-trivial task. Here we present rawDiag, a software tool supporting rational method optimization by providing MS operator-tailored diagnostic plots of scan level metadata. rawDiag is implemented as R package and can be executed on the command line, or through a graphical user interface (GUI) for less experienced users. The code runs platform independent and can process a hundred raw files in less than three minutes on current consumer hardware as we show by our benchmark. In order to demonstrate the functionality of our package, we included a real-world example taken from our daily core facility business.


Heliyon ◽  
2019 ◽  
Vol 5 (6) ◽  
pp. e01766
Author(s):  
Reza Mohammadi ◽  
Javad Zahiri ◽  
Mohammad Javad Niroomand

2005 ◽  
Author(s):  
H. Eletem ◽  
F. Young ◽  
K. Aung

Compressible flow is an important subject in aerospace and mechanical engineering disciplines. This paper describes the development of a web-base interactive compressible flow solver using Java programming language. The main objective of the solver is to provide students with a software tool than can be used in the compressible flow course offered in the Department of Mechanical Engineering at Lamar University. The solver has a graphical user interface (GUI) for ease of use and interactivity. The solver was developed with the intention of free distribution to the educational community and other interested users.


2019 ◽  
Vol 36 (7) ◽  
pp. 2258-2259 ◽  
Author(s):  
Gurjit S Randhawa ◽  
Kathleen A Hill ◽  
Lila Kari

Abstract Summary Machine Learning with Digital Signal Processing and Graphical User Interface (MLDSP-GUI) is an open-source, alignment-free, ultrafast, computationally lightweight, and standalone software tool with an interactive GUI for comparison and analysis of DNA sequences. MLDSP-GUI is a general-purpose tool that can be used for a variety of applications such as taxonomic classification, disease classification, virus subtype classification, evolutionary analyses, among others. Availability and implementation MLDSP-GUI is open-source, cross-platform compatible, and is available under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/). The executable and dataset files are available at https://sourceforge.net/projects/mldsp-gui/. Supplementary information Supplementary data are available at Bioinformatics online.


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