scholarly journals Non-uniform sampling in pulse dipolar spectroscopy by EPR: the redistribution of noise and the optimization of data acquisition

2021 ◽  
Author(s):  
Anna G. Matveeva ◽  
Victoria N. Syryamina ◽  
Vyacheslav M. Nekrasov ◽  
Michael K. Bowman
Keyword(s):  
Data Acquisition ◽  
Spectroscopy Data ◽  
Distance Spectrum ◽  
Uniform Sampling ◽  
Increased Sensitivity ◽  
Non Uniform Sampling

Non-uniform schemes for collection of pulse dipole spectroscopy data can decrease and redistribute noise in the distance spectrum for increased sensitivity and throughput.

scholarly journals Evaluation of Non-Uniform Sampling 2D 1H–13C HSQC Spectra for Semi-Quantitative Metabolomics

Metabolites ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 203
Author(s):  
Bo Zhang ◽  
Robert Powers ◽  
Elizabeth M. O’Day
Keyword(s):  
Quantum Coherence ◽  
Limit Of Detection ◽  
Biochemical Processes ◽  
Uniform Sampling ◽  
Quantitative Metabolomics ◽  
Disease States ◽  
Equivalent Time ◽  
Increased Sensitivity ◽  
Non Uniform Sampling ◽  
Significant Chemical

Metabolomics is the comprehensive study of metabolism, the biochemical processes that sustain life. By comparing metabolites between healthy and disease states, new insights into disease mechanisms can be uncovered. NMR is a powerful analytical method to detect and quantify metabolites. Standard one-dimensional (1D) 1H-NMR metabolite profiling is informative but challenged by significant chemical shift overlap. Multi-dimensional NMR can increase resolution, but the required long acquisition times lead to limited throughput. Non-uniform sampling (NUS) is a well-accepted mode of acquiring multi-dimensional NMR data, enabling either reduced acquisition times or increased sensitivity in equivalent time. Despite these advantages, the technique is not widely applied to metabolomics. In this study, we evaluated the utility of NUS 1H–13C heteronuclear single quantum coherence (HSQC) for semi-quantitative metabolomics. We demonstrated that NUS improved sensitivity compared to uniform sampling (US). We verified that the NUS measurement maintains linearity, making it possible to detect metabolite changes across samples and studies. Furthermore, we calculated the lower limit of detection and quantification (LOD/LOQ) of common metabolites. Finally, we demonstrate that the measurements are repeatable on the same system and across different systems. In conclusion, our results detail the analytical capability of NUS and, in doing so, empower the future use of NUS 1H–13C HSQC in metabolomic studies.

Non-uniform sampling in EPR – optimizing data acquisition for HYSCORE spectroscopy

2014 ◽  
Vol 16 (31) ◽  
pp. 16378-16382 ◽  
Author(s):  
K. K. Nakka ◽  
Y. A. Tesiram ◽  
I. M. Brereton ◽  
M. Mobli ◽  
J. R. Harmer
Keyword(s):  
Data Acquisition ◽  
Maximum Entropy ◽  
Uniform Sampling ◽  
Maximum Entropy Reconstruction ◽  
Order Of Magnitude ◽  
Non Uniform Sampling

Non-uniformly sampled HYSCORE data combined with maximum entropy reconstruction can shorten experimental times by approximately an order of magnitude.

scholarly journals An Optimized Triggering Algorithm for Event-Triggered Control of Networked Control Systems

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1262
Author(s):  
Sunil Kumar Mishra ◽  
Amitkumar V. Jha ◽  
Vijay Kumar Verma ◽  
Bhargav Appasani ◽  
Almoataz Y. Abdelaziz ◽  
...  
Keyword(s):  
Control Systems ◽  
Networked Control Systems ◽  
Networked Control ◽  
Pendulum System ◽  
Uniform Sampling ◽  
Inverted Pendulum System ◽  
Event Triggering ◽  
Non Uniform Sampling ◽  
System States ◽  
Event Triggered

This paper presents an optimized algorithm for event-triggered control (ETC) of networked control systems (NCS). Initially, the traditional backstepping controller is designed for a generalized nonlinear plant in strict-feedback form that is subsequently extended to the ETC. In the NCS, the controller and the plant communicate with each other using a communication network. In order to minimize the bandwidth required, the number of samples to be sent over the communication channel should be reduced. This can be achieved using the non-uniform sampling of data. However, the implementation of non-uniform sampling without a proper event triggering rule might lead the closed-loop system towards instability. Therefore, an optimized event triggering algorithm has been designed such that the system states are always forced to remain in stable trajectory. Additionally, the effect of ETC on the stability of backstepping control has been analyzed using the Lyapunov stability theory. Two case studies on an inverted pendulum system and single-link robot system have been carried out to demonstrate the effectiveness of the proposed ETC in terms of system states, control effort and inter-event execution time.

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