Flash lamp-excited time-resolved fluorescence microscope suppresses autofluorescence in water concentrates to deliver an 11-fold increase in signal-to-noise ratio

2004 ◽  
Vol 9 (4) ◽  
pp. 725 ◽  
Author(s):  
Russell Connally ◽  
Duncan Veal ◽  
James Piper
1988 ◽  
Vol 36 (11) ◽  
pp. 1449-1451 ◽  
Author(s):  
E J Soini ◽  
L J Pelliniemi ◽  
I A Hemmilä ◽  
V M Mukkala ◽  
J J Kankare ◽  
...  

Anti-rabbit IgG labeled with a new fluorescent europium chelate was used to localize rabbit IgG to human smooth muscle myosin in a histological section. The antibody labeled with the europium chelate could be viewed with a conventional fluorescence microscope with a steady-state light source. This result encourages the development of a time-resolved fluorescence microscope, because a significant improvement in the signal-to-noise ratio can be anticipated.


2020 ◽  
Vol 27 (5) ◽  
pp. 1326-1338
Author(s):  
Federica Marone ◽  
Jakob Vogel ◽  
Marco Stampanoni

Modern detectors used at synchrotron tomographic microscopy beamlines typically have sensors with more than 4–5 mega-pixels and are capable of acquiring 100–1000 frames per second at full frame. As a consequence, a data rate of a few TB per day can easily be exceeded, reaching peaks of a few tens of TB per day for time-resolved tomographic experiments. This data needs to be post-processed, analysed, stored and possibly transferred, imposing a significant burden onto the IT infrastructure. Compression of tomographic data, as routinely done for diffraction experiments, is therefore highly desirable. This study considers a set of representative datasets and investigates the effect of lossy compression of the original X-ray projections onto the final tomographic reconstructions. It demonstrates that a compression factor of at least three to four times does not generally impact the reconstruction quality. Potentially, compression with this factor could therefore be used in a transparent way to the user community, for instance, prior to data archiving. Higher factors (six to eight times) can be achieved for tomographic volumes with a high signal-to-noise ratio as it is the case for phase-retrieved datasets. Although a relationship between the dataset signal-to-noise ratio and a safe compression factor exists, this is not simple and, even considering additional dataset characteristics such as image entropy and high-frequency content variation, the automatic optimization of the compression factor for each single dataset, beyond the conservative factor of three to four, is not straightforward.


Author(s):  
Yaxiong He ◽  
Tao Xu ◽  
Yong Zhang ◽  
Chuan Ke ◽  
Yong Zhao ◽  
...  

Abstract Tokamak exhaust is an important part of the deuterium-tritium fuel cycle system in fusion reaction. In this work, we present a laser-induced breakdown spectroscopy (LIBS) based method to monitor the gas compositions from exhaust system in the Tokamak device. Helium (He), a main impurity in the exhaust gas, was mixed with hydrogen (H2) in different ratios through a self-designed gas distribution system, and sealed into a measurement chamber as a standard specimen. A 532 nm wavelength laser pulse with an output power of 100 mJ was used for plasma excitation. The time-resolved LIBS is used to study the time evolution characteristics of the signal strength, signal-to-background-ratio (SBR), signal-to-noise-ratio (SNR) and relative standard deviation (RSD) of the helium and hydrogen characteristic lines. The Boltzmann two-line method was employed to estimate the plasma temperature of laser-induced plasma (LIP). The Stark-broadened profile of He I 587.56 nm was exploited to measure the electron density. From these studies, an appropriate time was determined in which the low RSD% were consistent with the high signal-to-noise ratio. The He I 587.56 nm and Hα emission lines with good signal-to-noise ratio were extracted from the spectrum and used in the external standard method and internal standard method for quantitative analysis. The test results for mixed gas showed that the average relative error of prediction was less than 11.15%, demonstrating the great potential of LIBS in detecting impurities in plasma exhaust gas.


Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3453
Author(s):  
Chen ◽  
Shin

For structures vulnerable to foreign object impact damages, it would be desirable to detect and locate any occurrence of such impacts. This can be achieved by monitoring the stress waves generated by an impact together with certain source localization algorithms. Being small, electromagnetic influence immune and durable, Fiber Bragg grating (FBG) sensors are advantageous for this task. One drawback of FBGs for this purpose is their uneven directional sensitivity, which limits its localization ability to within 50° on either side of the fiber axis. Beyond this range, the signal is too weak and masked by noises and the location errors increase abruptly. Two approaches have been tested on a 0.8 m × 0.8 m × 6 mm plate for possible improvement on the system accuracy: firstly, an interrogation scheme with stronger light source intensity and steeper edge filter is employed to enhance the signal-to-noise ratio and system sensitivity; secondly, rosettes with two orthogonal FBGs are cascaded together to replace single FBGs to alleviate the directional sensitivity problem. It was found that a four-fold increase in signal to noise ratio contributed by stronger light source does improve the location accuracy, but only marginally. For the rosette approach, the relative positions of the Bragg wavelength of the FBGs and the light source spectrum are crucial to accuracy. Three different wavelength configurations have been tested and the reasons for their success or failure are discussed. It was shown that with an optimal wavelength configuration, the rosette array can virtually extend the good location accuracy to all over the plate.


2017 ◽  
Author(s):  
Xiaoqing Gao ◽  
Francesco Gentile ◽  
Bruno Rossion

SummaryFunctional magnetic resonance imaging (fMRI) is a major technique for human brain mapping. We present a Fast Periodic Stimulation (FPS) fMRI approach, demonstrating its high effectiveness in defining category-selective brain regions. Observers see a dynamic stream of widely variable natural object images alternating at a fast rate (6 images/sec). Every 9 seconds, a short burst of variable face images contrasting with objects in pairs induces an objective 0.111 Hz face-selective neural response in the ventral occipito-temporal cortex and beyond. A model-free Fourier analysis achieves a two-fold increase in signal-to-noise ratio compared to a conventional block-design approach with identical stimuli. Periodicity of category contrast and random variability among images minimize low-level visual confounds while preserving naturalness of the stimuli, leading to the highest values (80-90%) of test-retest reliability yet reported in this area of research. FPS-fMRI opens a new avenue for understanding brain function with low temporal resolution methods.HighlightsFPS-fMRI achieves a two-fold increase in peak SNR over conventional approachFPS-fMRI reveals comprehensive extended face-selective areas including ATLFPS-fMRI achieves high specificity by minimizing influence of low-level visual cuesFPS-fMRI achieves very high test-retest reliability (80%-90%) in spatial activation mapeTOC BlurbIn BriefGao et al. present a novel FPS-fMRI approach, which achieves a two-fold increase in peak signal-to-noise ratio in defining the neural basis of visual categorization while preserving ecological validity, minimizing low-level visual confounds and reaching very high (80%-90%) test-retest reliability.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Minna Bührer ◽  
Hong Xu ◽  
Allard A. Hendriksen ◽  
Felix N. Büchi ◽  
Jens Eller ◽  
...  

AbstractTime-resolved X-ray tomographic microscopy is an invaluable technique to investigate dynamic processes in 3D for extended time periods. Because of the limited signal-to-noise ratio caused by the short exposure times and sparse angular sampling frequency, obtaining quantitative information through post-processing remains challenging and requires intensive manual labor. This severely limits the accessible experimental parameter space and so, prevents fully exploiting the capabilities of the dedicated time-resolved X-ray tomographic stations. Though automatic approaches, often exploiting iterative reconstruction methods, are currently being developed, the required computational costs typically remain high. Here, we propose a highly efficient reconstruction and classification pipeline (SIRT-FBP-MS-D-DIFF) that combines an algebraic filter approximation and machine learning to significantly reduce the computational time. The dynamic features are reconstructed by standard filtered back-projection with an algebraic filter to approximate iterative reconstruction quality in a computationally efficient manner. The raw reconstructions are post-processed with a trained convolutional neural network to extract the dynamic features from the low signal-to-noise ratio reconstructions in a fully automatic manner. The capabilities of the proposed pipeline are demonstrated on three different dynamic fuel cell datasets, one exploited for training and two for testing without network retraining. The proposed approach enables automatic processing of several hundreds of datasets in a single day on a single GPU node readily available at most institutions, so extending the possibilities in future dynamic X-ray tomographic investigations.


Author(s):  
V.A. Smalyuk ◽  
S.V. Weber ◽  
D.T. Casey ◽  
D.S. Clark ◽  
J.E. Field ◽  
...  

The first hydrodynamic instability growth measurements with three-dimensional (3D) surface-roughness modulations were performed on CH shell spherical implosions at the National Ignition Facility (NIF) [G. H. Miller, E. I. Moses, and C. R. Wuest, Opt. Eng. 43, 2841 (2004)]. The initial capsule outer-surface amplitudes were increased approximately four times, compared with the standard specifications, to increase the signal-to-noise ratio, helping to qualify a technique for measuring small 3D modulations. The instability growth measurements were performed using x-ray through-foil radiography based on time-resolved pinhole imaging. Averaging over 15 similar images significantly increased the signal-to-noise ratio, making possible a comparison with 3D simulations. At a convergence ratio of ${\sim}2.4$ , the measured modulation levels were ${\sim}3$ times larger than those simulated based on the growth of the known imposed initial surface modulations. Several hypotheses are discussed, including increased instability growth due to modulations of the oxygen content in the bulk of the capsule. Future experiments will be focused on measurements with standard 3D ‘native-roughness’ capsules as well as with deliberately imposed oxygen modulations.


Author(s):  
Franco Stellari ◽  
Peilin Song ◽  
Jim Vickers ◽  
Chris Shaw ◽  
Steven Kasapi ◽  
...  

Abstract In this paper we evaluate the possibility of extending Time Resolved Emission (TRE) technology towards future low voltage SOI technologies. In particular, we investigate and quantify the gain offered by the InGaAs detector improvements devised by Credence Corp., now DCG Systems, the manufacturer of the Emiscope III PICA system used in this analysis. Experiments on a test chip fabricated in the IBM SOI 65 nm technology will demonstrate that the improved tool guarantees the same Signal-to-Noise Ratio (SNR) even at ~90 mV lower supply voltages. In the second part of the paper we also discuss various other acquisition optimizations of the system. Although the analysis presented here refers to a specific tool, the large majority of the results and discussions can easily be generalized and applied to other PICA systems and detectors, as well as low voltage bulk silicon technologies.


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