scholarly journals Erratum: “A unified framework for quantum activated rate processes. II. The nonadiabatic limit” [J. Chem. Phys. 106, 1769 (1997)]

1998 ◽  
Vol 109 (5) ◽  
pp. 2043-2043 ◽  
Author(s):  
Jianshu Cao ◽  
Gregory A. Voth
Keyword(s):  
Chem Phys ◽  
Unified Framework ◽  
Rate Processes

A unified framework for quantum activated rate processes. I. General theory

1996 ◽  
Vol 105 (16) ◽  
pp. 6856-6870 ◽  
Author(s):  
Jianshu Cao ◽  
Gregory A. Voth
Keyword(s):  
General Theory ◽  
Unified Framework ◽  
Rate Processes

A unified framework for automated person re-indentification

2020 ◽  
Vol 71 (7) ◽  
pp. 868-880
Author(s):  
Nguyen Hong-Quan ◽  
Nguyen Thuy-Binh ◽  
Tran Duc-Long ◽  
Le Thi-Lan
Keyword(s):  
Deep Learning ◽  
Video Analysis ◽  
Camera Network ◽  
Unified Framework ◽  
Person Detection ◽  
Practical Applications ◽  
Detection And Tracking ◽  
Analysis System ◽  
Bounding Boxes

Along with the strong development of camera networks, a video analysis system has been become more and more popular and has been applied in various practical applications. In this paper, we focus on person re-identification (person ReID) task that is a crucial step of video analysis systems. The purpose of person ReID is to associate multiple images of a given person when moving in a non-overlapping camera network. Many efforts have been made to person ReID. However, most of studies on person ReID only deal with well-alignment bounding boxes which are detected manually and considered as the perfect inputs for person ReID. In fact, when building a fully automated person ReID system the quality of the two previous steps that are person detection and tracking may have a strong effect on the person ReID performance. The contribution of this paper are two-folds. First, a unified framework for person ReID based on deep learning models is proposed. In this framework, the coupling of a deep neural network for person detection and a deep-learning-based tracking method is used. Besides, features extracted from an improved ResNet architecture are proposed for person representation to achieve a higher ReID accuracy. Second, our self-built dataset is introduced and employed for evaluation of all three steps in the fully automated person ReID framework.

Computational Investigation of the Asymmetry in Photosynthetic Reaction Center Models from First Principles

2020 ◽  
Author(s):  
Denis Artiukhin ◽  
Patrick Eschenbach ◽  
Johannes Neugebauer
Keyword(s):  
Spin Density ◽  
Reaction Center ◽  
Density Functional ◽  
Photosynthetic Reaction Center ◽  
Chem Phys ◽  
Molecular Structures ◽  
Error Characteristic ◽  
Molecular Systems ◽  
Density Distributions ◽  
The Asymmetry

We present a computational analysis of the asymmetry in reaction center models of photosystem I, photosystem II, and bacteria from <i>Synechococcus elongatus</i>, <i>Thermococcus vulcanus</i>, and <i>Rhodobacter sphaeroides</i>, respectively. The recently developed FDE-diab methodology [J. Chem. Phys., 148 (2018), 214104] allowed us to effectively avoid the spin-density overdelocalization error characteristic for standard Kohn–Sham Density Functional Theory and to reliably calculate spin-density distributions and electronic couplings for a number of molecular systems ranging from dimeric models in vacuum to large protein including up to about 2000 atoms. The calculated spin densities showed a good agreement with available experimental results and were used to validate reaction center models reported in the literature. We demonstrated that the applied theoretical approach is very sensitive to changes in molecular structures and relative orientation of molecules. This makes FDE-diab a valuable tool for electronic structure calculations of large photosynthetic models effectively complementing the existing experimental techniques.

`Diet GMKTN55' Offers Accelerated Benchmarking Through a Representative Subset Approach

2018 ◽  
Author(s):  
Tim Gould
Keyword(s):  
Density Functional ◽  
Chem Phys ◽  
Comprehensive Analysis ◽  
Genetic Approach ◽  
Representative Subset ◽  
Phys Chem Chem Phys

The GMTKN55 benchmarking protocol introduced by [Goerigk et al., Phys. Chem. Chem. Phys., 2017, 19, 32184] allows comprehensive analysis and ranking of density functional approximations with diverse chemical behaviours. But this comprehensiveness comes at a cost: GMTKN55's 1500 benchmarking values require energies for around 2500 systems to be calculated, making it a costly exercise. This manuscript introduces three subsets of GMTKN55, consisting of 30, 100 and 150 systems, as `diet' substitutes for the full database. The subsets are chosen via a stochastic genetic approach, and consequently can reproduce key results of the full GMTKN55 database, including ranking of approximations.

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