Place and Route Optimization for High Coverage Multi-corner Multi-mode Timing Fix

2019 ◽  
pp. 195-201
Author(s):  
J. S. K. Lee ◽  
M. F. Packeer Mohamed ◽  
M. A. Md. Zawawi ◽  
N. Z. I. Hashim
Keyword(s):  
Route Optimization ◽  
High Coverage ◽  
Place And Route ◽  
Multi Mode

Multi-mode light microscopy of microtubule assembly dynamics and chromosome movement in vivo and In vitro

1996 ◽  
Vol 54 ◽  
pp. 730-731
Author(s):  
E. D. Salmon ◽  
J. C. Waters ◽  
C. Waterman-Storer
Keyword(s):  
Imaging System ◽  
Ccd Camera ◽  
Transmitted Light ◽  
Microtubule Assembly ◽  
Live Cells ◽  
Optical Efficiency ◽  
Multiple Band ◽  
Multi Mode

We have developed a multi-mode digital imaging system which acquires images with a cooled CCD camera (Figure 1). A multiple band pass dichromatic mirror and robotically controlled filter wheels provide wavelength selection for epi-fluorescence. Shutters select illumination either by epi-fluorescence or by transmitted light for phase contrast or DIC. Many of our experiments involve investigations of spindle assembly dynamics and chromosome movements in live cells or unfixed reconstituted preparations in vitro in which photodamage and phototoxicity are major concerns. As a consequence, a major factor in the design was optical efficiency: achieving the highest image quality with the least number of illumination photons. This principle applies to both epi-fluorescence and transmitted light imaging modes. In living cells and extracts, microtubules are visualized using X-rhodamine labeled tubulin. Photoactivation of C2CF-fluorescein labeled tubulin is used to locally mark microtubules in studies of microtubule dynamics and translocation. Chromosomes are labeled with DAPI or Hoechst DNA intercalating dyes.

Route Optimization of Construction Machine by Deep Reinforcement Learning

2019 ◽  
Vol 139 (4) ◽  
pp. 401-408
Author(s):  
Shunya Tanabe ◽  
Zeyuan Sun ◽  
Masayuki Nakatani ◽  
Yutaka Uchimura
Keyword(s):  
Reinforcement Learning ◽  
Route Optimization ◽  
Construction Machine

Time-Frequency Channel Parameterization with Application to Multi-Mode Receivers

2009 ◽  
Vol E92-B (12) ◽  
pp. 3717-3725
Author(s):  
Thomas HUNZIKER ◽  
Ziyang JU ◽  
Dirk DAHLHAUS
Keyword(s):  
Frequency Channel ◽  
Time Frequency ◽  
Multi Mode

Power Supply Voltage Dependence of Within-Die Delay Variation of Regular Manual Layout and Irregular Place-and-Route Layout

2011 ◽  
Vol E94-C (6) ◽  
pp. 1072-1075
Author(s):  
Tadashi YASUFUKU ◽  
Yasumi NAKAMURA ◽  
Zhe PIAO ◽  
Makoto TAKAMIYA ◽  
Takayasu SAKURAI
Keyword(s):  
Power Supply ◽  
Voltage Dependence ◽  
Supply Voltage ◽  
Power Supply Voltage ◽  
Place And Route ◽  
Delay Variation

Split pump region in 1.55 ^|^mu;m InGaAsP/InGaAsP asymmetric active multi-mode interferometer laser diode for improved modulation bandwidth

2014 ◽  
Vol E97.C (7) ◽  
pp. 781-786 ◽  
Author(s):  
Mohammad NASIR UDDIN ◽  
Takaaki KIZU ◽  
Yasuhiro HINOKUMA ◽  
Kazuhiro TANABE ◽  
Akio TAJIMA ◽  
...  
Keyword(s):  
Laser Diode ◽  
Modulation Bandwidth ◽  
Multi Mode

Scalable Approach to High Coverages on Oxides via Iterative Training of a Machine-Learning Algorithm

2019 ◽  
Author(s):  
Andrew Medford ◽  
Shengchun Yang ◽  
Fuzhu Liu
Keyword(s):  
Machine Learning ◽  
Chemical Potential ◽  
Learning Algorithm ◽  
Absolute Error ◽  
Low Energy ◽  
Training Data ◽  
High Coverage ◽  
Metal Compounds ◽  
Adsorption Energies ◽  
The Stability

Understanding the interaction of multiple types of adsorbate molecules on solid surfaces is crucial to establishing the stability of catalysts under various chemical environments. Computational studies on the high coverage and mixed coverages of reaction intermediates are still challenging, especially for transition-metal compounds. In this work, we present a framework to predict differential adsorption energies and identify low-energy structures under high- and mixed-adsorbate coverages on oxide materials. The approach uses Gaussian process machine-learning models with quantified uncertainty in conjunction with an iterative training algorithm to actively identify the training set. The framework is demonstrated for the mixed adsorption of CH<sub>x</sub>, NH<sub>x</sub> and OH<sub>x</sub> species on the oxygen vacancy and pristine rutile TiO<sub>2</sub>(110) surface sites. The results indicate that the proposed algorithm is highly efficient at identifying the most valuable training data, and is able to predict differential adsorption energies with a mean absolute error of ~0.3 eV based on <25% of the total DFT data. The algorithm is also used to identify 76% of the low-energy structures based on <30% of the total DFT data, enabling construction of surface phase diagrams that account for high and mixed coverage as a function of the chemical potential of C, H, O, and N. Furthermore, the computational scaling indicates the algorithm scales nearly linearly (N<sup>1.12</sup>) as the number of adsorbates increases. This framework can be directly extended to metals, metal oxides, and other materials, providing a practical route toward the investigation of the behavior of catalysts under high-coverage conditions.

SP3-FAIMS Chemoproteomics for High Coverage Profiling of the Human Cysteinome

2020 ◽  
Author(s):  
Tianyang Yan ◽  
Heta Desai ◽  
Lisa Boatner ◽  
Stephanie Yen ◽  
Jian Cao ◽  
...  
Keyword(s):  
High Throughput ◽  
High Coverage ◽  
Method Integration ◽  
Coverage Analysis

<p>We report a new cysteine chemoproteomic method, termed SP3-FAIMS chemoproteomics, which enables rapid and high coverage analysis of the human cysteinome. By combining enhanced cysteine biotinylation with SP3 sample decontamination and FAIMS online fraction, we identified in aggregate 34,225 unique cysteines found on 7,243 proteins. Showcasing the versatility of our method, integration with the isoTOP-ABPP workflow enabled the high throughput discovery of cysteines labelled by electrophilic compounds. </p>

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