Theoretical Research on Output Response Characteristics of Vertical Longitudinal Multipole Conductance Sensor by Discrete Phase Distribution

2021 ◽  
Author(s):  
Yingwei Li ◽  
Yuntong Yang ◽  
Jingchao Zhang ◽  
Xingbin Liu ◽  
Ronghua Xie ◽  
...  
Keyword(s):  
Phase Distribution ◽  
Theoretical Research ◽  
Output Response ◽  
Response Characteristics ◽  
Discrete Phase

Asphericity and Discrete Phase Calculation for Optical Freeform Surface Test with Computer Generated Holograms

2013 ◽  
Vol 718-720 ◽  
pp. 1797-1803
Author(s):  
Ya Huang ◽  
Ri Hong Zhu ◽  
Jun Ma ◽  
Hua Shen
Keyword(s):  
Ray Tracing ◽  
Phase Distribution ◽  
Rotational Symmetry ◽  
Optical Design ◽  
Freeform Surface ◽  
Freeform Surfaces ◽  
Maximum Angle ◽  
Phase Calculation ◽  
Discrete Phase ◽  
Computer Generated Holograms

Optical freeform surfaces are complex surfaces with non-rotational symmetry that break through the limitations of conventional optical element, and are widely used in advanced optics application for system configuration simplifying and performance enhancing. Interferometric test with computer generated holograms (CGH) has been widely used in the aspherical surfaces testing for their unique wavefront transformation, as well as the freeform surfaces testing with high precision. As an important parameter, it is different at the definition of asphericity in freeform surfaces manufacture and test. Asphericity for interferometric test which verifies the testing ability of the CGH and determines testing system initial configuration was calculated with minimum maximum angle deviation. Reverse ray tracing could get the optimal solution of CGH local phase at certain location in the CGH design. For the non-rotational symmetry of freeform surfaces, the phase of sample point in CGH surface should be calculated in three-dimensional coordinate system. The calculation method of discrete phase was deduced by ray tracing, as well as the phase distribution on freeform surface were proven by calculating in such way. The results were compared with simulation by optical design software. It shows that the method is right and high accuracy to be used in the CGH design for the freeform surfaces.

scholarly journals A biochemical logarithmic sensor with broad dynamic range

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 200 ◽  
Author(s):  
Steven A. Frank
Keyword(s):  
Dynamic Range ◽  
Mass Action ◽  
Output Response ◽  
Response Characteristics ◽  
Stochastic Fluctuations ◽  
Broad Dynamic Range ◽  
Biochemical Systems ◽  
Parameter Values ◽  
Kinetics Of ◽  
Input Level

Sensory perception often scales logarithmically with the input level. Similarly, the output response of biochemical systems sometimes scales logarithmically with the input signal that drives the system. How biochemical systems achieve logarithmic sensing remains an open puzzle. This article shows how a biochemical logarithmic sensor can be constructed from the most basic principles of chemical reactions. Assuming that reactions follow the classic Michaelis-Menten kinetics of mass action or the more generalized and commonly observed Hill equation response, the summed output of several simple reactions with different sensitivities to the input will often give an aggregate output response that logarithmically transforms the input. The logarithmic response is robust to stochastic fluctuations in parameter values. This model emphasizes the simplicity and robustness by which aggregate chemical circuits composed of sloppy components can achieve precise response characteristics. Both natural and synthetic designs gain from the power of this aggregate approach.

scholarly journals A biochemical logarithmic sensor with broad dynamic range

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 200 ◽  
Author(s):  
Steven A. Frank
Keyword(s):  
Dynamic Range ◽  
Mass Action ◽  
Output Response ◽  
Response Characteristics ◽  
Stochastic Fluctuations ◽  
Broad Dynamic Range ◽  
Biochemical Systems ◽  
Parameter Values ◽  
Kinetics Of ◽  
Input Level

Sensory perception often scales logarithmically with the input level. Similarly, the output response of biochemical systems sometimes scales logarithmically with the input signal that drives the system. How biochemical systems achieve logarithmic sensing remains an open puzzle. This article shows how a biochemical logarithmic sensor can be constructed from the most basic principles of chemical reactions. Assuming that reactions follow the classic Michaelis-Menten kinetics of mass action or the more generalized and commonly observed Hill equation response, the summed output of several simple reactions with different sensitivities to the input will often give an aggregate output response that logarithmically transforms the input. The logarithmic response is robust to stochastic fluctuations in parameter values. This model emphasizes the simplicity and robustness by which aggregate chemical circuits composed of sloppy components can achieve precise response characteristics. Both natural and synthetic designs gain from the power of this aggregate approach.

scholarly journals A biochemical logarithmic sensor with broad dynamic range

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 200 ◽  
Author(s):  
Steven A. Frank
Keyword(s):  
Dynamic Range ◽  
Mass Action ◽  
Output Response ◽  
Response Characteristics ◽  
Stochastic Fluctuations ◽  
Broad Dynamic Range ◽  
Biochemical Systems ◽  
Parameter Values ◽  
Kinetics Of ◽  
Input Level

Sensory perception often scales logarithmically with the input level. Similarly, the output response of biochemical systems sometimes scales logarithmically with the input signal that drives the system. How biochemical systems achieve logarithmic sensing remains an open puzzle. This article shows how a biochemical logarithmic sensor can be constructed from the most basic principles of chemical reactions. Assuming that reactions follow the classic Michaelis-Menton kinetics of mass action or the more generalized and commonly observed Hill equation response, the summed output of several simple reactions with different sensitivities to the input will often give an aggregate output response that logarithmically transforms the input. The logarithmic response is robust to stochastic fluctuations in parameter values. This model emphasizes the simplicity and robustness by which aggregate chemical circuits composed of sloppy components can achieve precise response characteristics. Both natural and synthetic designs gain from the power of this aggregate approach.

Digital phase analysis in interference electron microscopy

1988 ◽  
Vol 46 ◽  
pp. 842-843
Author(s):  
S. Hasegawa ◽  
T. Kawasaki ◽  
J. Endo ◽  
M. Futamoto ◽  
A. Tonomura
Keyword(s):  
Magnetic Field ◽  
Electron Microscopy ◽  
Phase Distribution ◽  
Magnetic Recording Media ◽  
Electron Wave ◽  
Vector Potentials ◽  
Weak Magnetic Fields ◽  
Leakage Magnetic Field ◽  
Optical Reconstruction ◽  
Processing Techniques

Interference electron microscopy enables us to record the phase distribution of an electron wave on a hologram. The distribution is visualized as a fringe pattern in a micrograph by optical reconstruction. The phase is affected by electromagnetic potentials; scalar and vector potentials. Therefore, the electric and magnetic field can be reduced from the recorded phase. This study analyzes a leakage magnetic field from CoCr perpendicular magnetic recording media. Since one contour fringe interval corresponds to a magnetic flux of Φo(=h/e=4x10-15Wb), we can quantitatively measure the field by counting the number of finges. Moreover, by using phase-difference amplification techniques, the sensitivity for magnetic field detection can be improved by a factor of 30, which allows the drawing of a Φo/30 fringe. This sensitivity, however, is insufficient for quantitative analysis of very weak magnetic fields such as high-density magnetic recordings. For this reason we have adopted “fringe scanning interferometry” using digital image processing techniques at the optical reconstruction stage. This method enables us to obtain subfringe information recorded in the interference pattern.

Application of electron holography to material science studies on magnetic domain states of small particles

1993 ◽  
Vol 51 ◽  
pp. 1028-1029
Author(s):  
T. Hirayama ◽  
Q. Ru ◽  
T. Tanji ◽  
A. Tonomura
Keyword(s):  
Magnetic Field ◽  
Material Science ◽  
Science Studies ◽  
Phase Distribution ◽  
Carbon Film ◽  
Objective Lens ◽  
Electron Holography ◽  
Transform Method ◽  
Transmission Electron ◽  
Thin Carbon

The observation of small magnetic materials is one of the most important applications of electron holography to material science, because interferometry by means of electron holography can directly visualize magnetic flux lines in a very small area. To observe magnetic structures by transmission electron microscopy it is important to control the magnetic field applied to the specimen in order to prevent it from changing its magnetic state. The easiest method is tuming off the objective lens current and focusing with the first intermediate lens. The other method is using a low magnetic-field lens, where the specimen is set above the lens gap.Figure 1 shows an interference micrograph of an isolated particle of barium ferrite on a thin carbon film observed from approximately [111]. A hologram of this particle was recorded by the transmission electron microscope, Hitachi HF-2000, equipped with an electron biprism. The phase distribution of the object electron wave was reconstructed digitally by the Fourier transform method and converted to the interference micrograph Fig 1.

Microstructure and microanalysis of sintered Fe-Nd-B permanent magnets

1990 ◽  
Vol 48 (4) ◽  
pp. 990-991
Author(s):  
Mahesh Chandramouli
Keyword(s):  
Electron Microscope ◽  
Liquid Phase ◽  
Permanent Magnets ◽  
Phase Distribution ◽  
Energy Dispersive Spectrometer ◽  
Nucleation And Growth ◽  
Liquid Phase Sintering ◽  
Domain Wall Energy ◽  
Oxide Phases ◽  
Scanning Electron

Magnetization reversal in sintered Fe-Nd-B, a complex, multiphase material, occurs by nucleation and growth of reverse domains making the isolation of the ferromagnetic Fe14Nd2B grains by other nonmagnetic phases crucial. The magnets used in this study were slightly rich in Nd (in comparison to Fe14Nd2B) to promote the formation of Nd-oxides at multigrain junctions and incorporated Dy80Al20 as a liquid phase sintering addition. Dy has been shown to increase the domain wall energy thus making nucleation more difficult while Al is thought to improve the wettability of the Nd-oxide phases.Bulk polished samples were examined in a JEOL 35CF scanning electron microscope (SEM) operated at 30keV equipped with a Be window energy dispersive spectrometer (EDS) detector in order to determine the phase distribution.

Smoothing Facilitates the Detection of Coupled Responses in Psychophysiological Time Series

2000 ◽  
Vol 14 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Joni Kettunen ◽  
Niklas Ravaja ◽  
Liisa Keltikangas-Järvinen
Keyword(s):  
Time Series ◽  
Type I Error ◽  
Electrodermal Activity ◽  
Moving Average ◽  
Type I ◽  
Facial Electromyography ◽  
Response Characteristics ◽  
Smoothing Methods ◽  
Response Systems ◽  
Different Response

Abstract We examined the use of smoothing to enhance the detection of response coupling from the activity of different response systems. Three different types of moving average smoothers were applied to both simulated interbeat interval (IBI) and electrodermal activity (EDA) time series and to empirical IBI, EDA, and facial electromyography time series. The results indicated that progressive smoothing increased the efficiency of the detection of response coupling but did not increase the probability of Type I error. The power of the smoothing methods depended on the response characteristics. The benefits and use of the smoothing methods to extract information from psychophysiological time series are discussed.

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