scholarly journals A partially linearized spin-mapping approach for nonadiabatic dynamics. II. Analysis and comparison with related approaches

2020 ◽  
Vol 153 (19) ◽  
pp. 194110 ◽  
Author(s):  
Jonathan R. Mannouch ◽  
Jeremy O. Richardson
Keyword(s):  
Nonadiabatic Dynamics ◽  
Mapping Approach

scholarly journals Improved population operators for multi-state nonadiabatic dynamics with the mixed quantum-classical mapping approach

2020 ◽  
Vol 221 ◽  
pp. 150-167 ◽  
Author(s):  
Maximilian A. C. Saller ◽  
Aaron Kelly ◽  
Jeremy O. Richardson
Keyword(s):  
Computational Effort ◽  
Frenkel Exciton ◽  
Nonadiabatic Dynamics ◽  
Mapping Approach ◽  
P Application

Application to the 7-state Frenkel-exciton Hamiltonian for the Fenna–Matthews–Olson complex shows that using a different representation of the electronic population operators can drastically improve the accuracy of the quasiclassical mapping approach without increasing the computational effort.

Analysis of the Bath Motion in the MM-SQC Dynamics Using Unsupervised Machine Learning Dimensionality Reduction Approaches: Principal Component Analysis

2020 ◽  
Author(s):  
Jiawei Peng ◽  
Yu Xie ◽  
Deping Hu ◽  
Zhenggang Lan
Keyword(s):  
Machine Learning ◽  
Principal Component Analysis ◽  
Collective Motion ◽  
Principal Component ◽  
Component Analysis ◽  
Nonadiabatic Dynamics ◽  
Trajectory Data ◽  
Unsupervised Machine Learning ◽  
Physical Knowledge ◽  
Vibronic Couplings

The system-plus-bath model is an important tool to understand nonadiabatic dynamics for large molecular systems. The understanding of the collective motion of a huge number of bath modes is essential to reveal their key roles in the overall dynamics. We apply the principal component analysis (PCA) to investigate the bath motion based on the massive data generated from the MM-SQC (symmetrical quasi-classical dynamics method based on the Meyer-Miller mapping Hamiltonian) nonadiabatic dynamics of the excited-state energy transfer dynamics of Frenkel-exciton model. The PCA method clearly clarifies that two types of bath modes, which either display the strong vibronic couplings or have the frequencies close to electronic transition, are very important to the nonadiabatic dynamics. These observations are fully consistent with the physical insights. This conclusion is obtained purely based on the PCA understanding of the trajectory data, without the large involvement of pre-defined physical knowledge. The results show that the PCA approach, one of the simplest unsupervised machine learning methods, is very powerful to analyze the complicated nonadiabatic dynamics in condensed phase involving many degrees of freedom.

Energy Mapping Approach for QoS in MANETs

2017 ◽  
Vol 5 (10) ◽  
pp. 273-275 ◽  
Author(s):  
Bura Vijay Kumar ◽  
◽  
◽  
◽  
Srinivas Aluvala ◽  
...  
Keyword(s):  
Mapping Approach ◽  
Energy Mapping

Developing a novel diabetes distress e-learning program for diabetes educators: an intervention mapping approach

2021 ◽  
Author(s):  
Jennifer A Halliday ◽  
Jane Speight ◽  
Sienna Russell-Green ◽  
Eric O ◽  
Virginia Hagger ◽  
...  
Keyword(s):  
Cognitive Theory ◽  
Tertiary Education ◽  
Emotional Health ◽  
Intervention Mapping ◽  
Diabetes Distress ◽  
Learning Program ◽  
Program Outcomes ◽  
Mapping Approach ◽  
E Learning ◽  
Diabetes Educators

Abstract Diabetes distress is a common negative emotional response to the ongoing burden of living with diabetes. Elevated diabetes distress is associated with impaired diabetes self-management and quality of life yet rarely identified and addressed in clinical practice. Health professionals report numerous barriers to the provision of care for diabetes distress, including lack of skills and confidence, but few diabetes distress training opportunities exist. The purpose of this paper is to describe how we utilized Intervention Mapping to plan the development, implementation, and evaluation of a novel diabetes distress e-learning program for diabetes educators, to meet a well-documented need and significant gap in diabetes care. A multidisciplinary team (combining expertise in research, health and clinical psychology, diabetes education, nursing, tertiary education, and website architecture) developed a diabetes distress e-learning program. We followed a six-step process (logic model of the problem, program outcomes and objectives, program design, program production, program implementation plan, and evaluation plan) known as Intervention Mapping. The program is underpinned by educational and psychological theory, including Bloom’s Taxonomy of Educational Objectives and social cognitive theory. We developed a short (estimated 4 h) e-learning program for diabetes educators, which draws on the content of the Diabetes and Emotional Health handbook and toolkit. It integrates a 7As model, which provides a stepwise approach to identifying and addressing diabetes distress. Our diabetes distress e-learning program has been developed systematically, guided by an Intervention Mapping approach. In the next phase of the project, we will trial the e-learning.

High-Fidelity First Principles Nonadiabaticity: Diabatization, Analytic Representation of Global Diabatic Potential Energy Matrices, and Quantum Dynamics

2021 ◽  
Author(s):  
Yafu Guan ◽  
Changjian Xie ◽  
David R. Yarkony ◽  
Hua Guo
Keyword(s):  
Potential Energy ◽  
Excited States ◽  
First Principles ◽  
Quantum Dynamics ◽  
Chemical Processes ◽  
High Fidelity ◽  
Nonadiabatic Dynamics ◽  
Electronically Excited States ◽  
Electronically Excited ◽  
Oppenheimer Approximation

Nonadiabatic dynamics, which goes beyond the Born-Oppenheimer approximation, has increasingly been shown to play an important role in chemical processes, particularly those involving electronically excited states. Understanding multistate dynamics requires...

scholarly journals Mapping 20 Years of Urban Expansion in 45 Urban Areas of Sub-Saharan Africa

2021 ◽  
Vol 13 (3) ◽  
pp. 525
Author(s):  
Yann Forget ◽  
Michal Shimoni ◽  
Marius Gilbert ◽  
Catherine Linard
Keyword(s):  
Case Studies ◽  
Urban Areas ◽  
Urban Expansion ◽  
Local Population ◽  
Sub Saharan Africa ◽  
Annual Growth Rate ◽  
Urban Dynamics ◽  
Mapping Approach ◽  
Sub Saharan ◽  
The Impact

By 2050, half of the net increase in the world’s population is expected to reside in sub-Saharan Africa (SSA), driving high urbanization rates and drastic land cover changes. However, the data-scarce environment of SSA limits our understanding of the urban dynamics in the region. In this context, Earth Observation (EO) is an opportunity to gather accurate and up-to-date spatial information on urban extents. During the last decade, the adoption of open-access policies by major EO programs (CBERS, Landsat, Sentinel) has allowed the production of several global high resolution (10–30 m) maps of human settlements. However, mapping accuracies in SSA are usually lower, limited by the lack of reference datasets to support the training and the validation of the classification models. Here we propose a mapping approach based on multi-sensor satellite imagery (Landsat, Sentinel-1, Envisat, ERS) and volunteered geographic information (OpenStreetMap) to solve the challenges of urban remote sensing in SSA. The proposed mapping approach is assessed in 17 case studies for an average F1-score of 0.93, and applied in 45 urban areas of SSA to produce a dataset of urban expansion from 1995 to 2015. Across the case studies, built-up areas averaged a compound annual growth rate of 5.5% between 1995 and 2015. The comparison with local population dynamics reveals the heterogeneity of urban dynamics in SSA. Overall, population densities in built-up areas are decreasing. However, the impact of population growth on urban expansion differs depending on the size of the urban area and its income class.

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