Dataset Information

Accurately predicting electron beam deflections in fringing fields of a solenoid.

ABSTRACT: Computer modelling is widely used in the design of scientific instrumentation for manipulating charged particles, for instance: to evaluate the behaviour of proposed designs, to determine the effects of manufacturing imperfections and to optimise the performance of apparatus. For solenoids, to predict charged particle trajectories, accurate values for the magnetic field through which charged species traverse are required, particularly at the end regions where fringe fields are most prevalent. In this paper, we describe a model that accurately predicts the deflection of an electron beam trajectory in the vicinity of the fringing field of a solenoid. The approach produces accurate beam deflection predictions in the fringe field region as well as in the centre of the solenoid. The model is based on a direct-line-of-action force between charges and is compared against field-based approaches including a commercially available package, with experimental verification (for three distinct cases). The direct-action model is shown to be more accurate than the other models relative to the experimental results obtained.

SUBMITTER: Baumgartel C

PROVIDER: S-EPMC7331722 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Accurately predicting electron beam deflections in fringing fields of a solenoid.

Baumgärtel Christof C Smith Ray T RT Maher Simon S

Scientific reports 20200702 1

Computer modelling is widely used in the design of scientific instrumentation for manipulating charged particles, for instance: to evaluate the behaviour of proposed designs, to determine the effects of manufacturing imperfections and to optimise the performance of apparatus. For solenoids, to predict charged particle trajectories, accurate values for the magnetic field through which charged species traverse are required, particularly at the end regions where fringe fields are most prevalent. In ...[more]

PMID: 32616721

Similar Datasets

Project description:MotivationSolenoid proteins are emerging as a protein class with properties intermediate between structured and intrinsically unstructured proteins. Containing repeating structural units, solenoid proteins are expected to share sequence similarities. However, in many cases, the sequence similarities are weak and non-detectable. Moreover, solenoids can be degenerated and widely vary in the number of units. So that it is difficult to detect them. Recently, several solenoid repeats detection methods have been proposed, such as self-alignment of the sequence, spectral analysis and discrete Fourier transform of sequence. Although these methods have shown good performance on certain data sets, they often fail to detect repeats with weak similarities. In this article, we propose a new approach to recognize solenoid repeats and non-solenoid proteins using stationary wavelet packet transform (SWPT). Our method associates with three advantages: (i) naturally representing five main factors of protein structure and properties by wavelet analysis technique; (ii) extracting novel wavelet features that can capture hidden components from solenoid sequence similarities and distinguish them from global proteins; (iii) obtaining statistics features that capture repeating motifs of solenoid proteins.ResultsOur method analyzes the characteristics of amino acid sequence in both spectral and temporal domains using SWPT. Both global and local information of proteins are captured by SWPT coefficients. We obtain and integrate wavelet-based features and statistics-based features of amino acid sequence to improve the classification task. Our proposed method is evaluated by comparing to state-of-the-art methods such as HHrepID and REPETITA. The experimental results show that our algorithm consistently outperforms them in areas under ROC curve. At the same false positive rate, the sensitivity of our WAVELET method is higher than other methods.Availabilityhttp://www.naaan.org/anvo/Software/Software.htm.

Dataset Information

Accurately predicting electron beam deflections in fringing fields of a solenoid.

Publications

Accurately predicting electron beam deflections in fringing fields of a solenoid.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets