Design of phase-type soft aperture

2019 ◽  
Author(s):  
Mingliang Yao ◽  
Jianhong Wu ◽  
Kai Wu ◽  
Yanfeng Su
Keyword(s):  
Phase Type

CONTRACEPTION BY AN INJECTABLE LONG-ACTING OESTROGEN-PROGESTOGEN AGENT. III

1972 ◽  
Vol 69 (1) ◽  
pp. 67-76
Author(s):  
Rolf Plesner
Keyword(s):  
Treatment Period ◽  
Treatment Cycle ◽  
Post Treatment ◽  
Mixed Phase ◽  
Discontinuation Of Treatment ◽  
Phase Type ◽  
Secretory Type ◽  
Pre Treatment ◽  
Long Acting ◽  
Fertile Women

ABSTRACT Twenty-two fertile women were treated cyclically in from 4–30 cycles (mean 15.5) with a total of 341 injections of Deladroxate®, an injectable, long-acting oestrogen-progestogen. The injections were administered on the 8th (7th–9th) day of each cycle. Before treatment, the last pre-treatment cycle was controlled by means of daily recordings of the basal body temperature (BBT), urinary excretion of pregnanediol and total pituitary gonadotrophins at certain intervals, and by endometrial biopsies obtained late in the cycle. The effects of Deladroxate® on ovulation, on pituitary gonadotrophic function, and on the endometrium were controlled by the above mentioned parameters during cycles 1, 3, and 6, and all assessments were repeated after discontinuation of treatment. During treatment, there was a statistically significant fall in gonadotrophin excretion values (as compared with the pre-treatment values), and the fall was found to be gradually progressive during treatment. After discontinuation of treatment, there seemed to be a tendency towards an increase in the excretion values. Suppression of ovulation as determined by means of the pregnanediol excretion during treatment, was effective in nearly all of the treatment cycles checked. The fall in pregnanediol excretion was also gradually progressive during treatment, while there was a slight increase in excretion values in the post-treatment period. During treatment, 79 BBT curves were recorded. Nearly 50 % were monophasic, indicating anovulatory cycles, 17 curves were biphasic, but with the rise in temperature occurring at non-characteristic times in the cycles, 18 curves were classified as thermogenic because of a rise in temperature occurring within 24 hours after the injection, and 5 curves were not assessable. During the first month after discontinuation of treatment, 8 out of 10 recorded curves were monophasic. Out of 53 endometrial biopsies obtained around the 23rd day of the cycle, 31 were of the mixed phase type, but showing a predominance of proliferative patterns, 15 were of the secretory type, and 7 were purely proliferative. Out of 15 biopsies obtained in the post-treatment period, only two were of the mixed phase type, 12 were proliferative and one was purely secretory.

scholarly journals Composition equivalents of stainless steels understood via gamma stabilizing efficiency

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shuqi Zhang ◽  
Qing Wang ◽  
Rui Yang ◽  
Chuang Dong
Keyword(s):  
Stainless Steel ◽  
Phase Boundary ◽  
Stainless Steels ◽  
Alloying Elements ◽  
Positive Sign ◽  
Equivalent Scheme ◽  
Α Phase ◽  
Phase Type ◽  
Boundary Lines

AbstractThe phase-type of a stainless steel is generally predicted by equivalent equations in terms of a major austenitic (γ) or ferritic (α) stabilizer Ni or Cr. The present paper attempts to understand the equivalent methods in stainless steels via the slopes of the phase boundary lines separating γ and γ + α phase zones. The prevailing equivalent coefficients are well interpreted using the slope ratios of the alloying elements divided by that of Ni or Cr, after analyzing over one hundred common stainless steels. Different from traditional composition equivalents which evaluate γ stabilizers and α stabilizers separately; the new equivalent scheme provides a unified phase stabilizing parameter for all alloying elements in stainless steels. This parameter is defined as γ stabilizing efficiency. Its negative or positive sign indicates γ stabilizer or α stabilizer, and its value represents the stabilizing efficiency.

scholarly journals Scattering Analysis and Efficiency Optimization of Dielectric Pancharatnam–Berry-Phase Metasurfaces

Nanomaterials ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 586
Author(s):  
Chen-Yi Yu ◽  
Qiu-Chun Zeng ◽  
Chih-Jen Yu ◽  
Chien-Yuan Han ◽  
Chih-Ming Wang
Keyword(s):  
Phase Modulation ◽  
Rotation Angle ◽  
Berry Phase ◽  
Fine Tuning ◽  
Design Rule ◽  
Polarization Conversion ◽  
Swarm Optimization ◽  
Efficiency Optimization ◽  
Phase Type ◽  
Gradient Phase

In this study, the phase modulation ability of a dielectric Pancharatnam–Berry (PB) phase metasurface, consisting of nanofins, is theoretically analyzed. It is generally considered that the optical thickness of the unit cell of a PB-phase metasurface is λ/2, i.e., a half-waveplate for polarization conversion. It is found that the λ/2 is not essential for achieving a full 2π modulation. Nevertheless, a λ/2 thickness is still needed for a high polarization conversion efficiency. Moreover, a gradient phase metasurface is designed. With the help of the particle swarm optimization (PSO) method, the wavefront errors of the gradient phase metasurface are reduced by fine-tuning the rotation angle of the nanofins. The diffraction efficiency of the gradient phase metasurface is thus improved from 73.4% to 87.3%. This design rule can be utilized to optimize the efficiency of phase-type meta-devices, such as meta-deflectors and metalenses.

scholarly journals Computing 3D Phase-Type Holograms Based on Deep Learning Method

Photonics ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 280
Author(s):  
Huadong Zheng ◽  
Jianbin Hu ◽  
Chaojun Zhou ◽  
Xiaoxi Wang
Keyword(s):  
Deep Learning ◽  
Signal To Noise Ratio ◽  
Contrast Ratio ◽  
Angular Spectrum ◽  
Structural Similarity ◽  
Computational Time ◽  
Experimental Investigations ◽  
Training Strategy ◽  
Holographic Display ◽  
Phase Type

Computer holography is a technology that use a mathematical model of optical holography to generate digital holograms. It has wide and promising applications in various areas, especially holographic display. However, traditional computational algorithms for generation of phase-type holograms based on iterative optimization have a built-in tradeoff between the calculating speed and accuracy, which severely limits the performance of computational holograms in advanced applications. Recently, several deep learning based computational methods for generating holograms have gained more and more attention. In this paper, a convolutional neural network for generation of multi-plane holograms and its training strategy is proposed using a multi-plane iterative angular spectrum algorithm (ASM). The well-trained network indicates an excellent ability to generate phase-only holograms for multi-plane input images and to reconstruct correct images in the corresponding depth plane. Numerical simulations and optical reconstructions show that the accuracy of this method is almost the same with traditional iterative methods but the computational time decreases dramatically. The result images show a high quality through analysis of the image performance indicators, e.g., peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and contrast ratio. Finally, the effectiveness of the proposed method is verified through experimental investigations.

Phase Type Distributions with Finite Support

2014 ◽  
Vol 30 (4) ◽  
pp. 576-597 ◽  
Author(s):  
V. Ramaswami ◽  
N. C. Viswanath
Keyword(s):  
Finite Support ◽  
Phase Type ◽  
Phase Type Distributions

Analysis of R-out-of-N repairable systems: the case of phase-type distributions

2004 ◽  
Vol 36 (1) ◽  
pp. 116-138 ◽  
Author(s):  
Yonit Barron ◽  
Esther Frostig ◽  
Benny Levikson
Keyword(s):  
Repairable System ◽  
Repairable Systems ◽  
Regenerative Processes ◽  
Numerical Examples ◽  
Independent Components ◽  
Duality Results ◽  
Phase Type ◽  
Phase Type Distributions ◽  
Two Systems ◽  
Repair Facility

An R-out-of-N repairable system, consisting of N independent components, is operating if at least R components are functioning. The system fails whenever the number of good components decreases from R to R-1. A failed component is sent to a repair facility. After a failed component has been repaired it is as good as new. Formulae for the availability of the system using Markov renewal and semi-regenerative processes are derived. We assume that either the repair times of the components are generally distributed and the components' lifetimes are phase-type distributed or vice versa. Some duality results between the two systems are obtained. Numerical examples are given for several distributions of lifetimes and of repair times.

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