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Computation, Volume 11, Issue 2

February 2023 - 28 articles

Cover Story: Coarse-grained (CG) modeling is an established approach of simulating simplified systems to reach greater space and time scales than expensive all-atomic (AA) molecular dynamics (MD) simulations. The development of CG models requires deriving CG interactions that match AA or experimental properties. We proposed a physics-informed machine learning (PIML) framework for CG modeling, applied it to model the SARS-CoV-2 spike glycoprotein, and determined the force-field parameters using a force-matching scheme. With our framework, CGMD validation simulations reach microsecond time scales and are 40,000 times faster than conventional AAMD. The framework achieves improved accuracy compared to traditional iterative approaches, opening avenues in illuminating protein mechanisms and complex interactions. View this paper
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Articles (28)

  • Article
  • Open Access
7 Citations
5,132 Views
15 Pages

Multilabel data share important features, including label imbalance, which has a significant influence on the performance of classifiers. Because of this problem, a widely used multilabel classification algorithm, the multilabel k-nearest neighbor (M...

  • Article
  • Open Access
5 Citations
2,962 Views
20 Pages

The paper is written to demonstrate the applicability of the notion of triangulation typically used in social sciences research to computationally enhance the mathematics education of future K-12 teachers. The paper starts with the so-called Brain Te...

  • Article
  • Open Access
3 Citations
3,138 Views
20 Pages

Pricing and Hedging Index Options under Mean-Variance Criteria in Incomplete Markets

  • Pornnapat Yamphram,
  • Phiraphat Sutthimat and
  • Udomsak Rakwongwan

This paper studies the portfolio selection problem where tradable assets are a bank account, and standard put and call options are written on the S&P 500 index in incomplete markets in which there exist bid–ask spreads and finite liquidity....

  • Article
  • Open Access
4 Citations
4,299 Views
17 Pages

Measuring the Recovery Performance of a Portfolio of NPLs

  • Alessandra Carleo,
  • Roberto Rocci and
  • Maria Sole Staffa

The objective of the present paper is to propose a new method to measure the recovery performance of a portfolio of non-performing loans (NPLs) in terms of recovery rate and time to liquidate. The fundamental idea is to draw a curve representing the...

  • Article
  • Open Access
5 Citations
3,274 Views
13 Pages

Nonparametric Estimation of Range Value at Risk

  • Suparna Biswas and
  • Rituparna Sen

Range value at risk (RVaR) is a quantile-based risk measure with two parameters. As special examples, the value at risk (VaR) and the expected shortfall (ES), two well-known but competing regulatory risk measures, are both members of the RVaR family....

  • Article
  • Open Access
11 Citations
3,700 Views
23 Pages

Operation of Gate-Controlled Irrigation System Using HEC-RAS 2D for Spring Flood Hazard Reduction

  • Farida Akiyanova,
  • Nurlan Ongdas,
  • Nurlybek Zinabdin,
  • Yergali Karakulov,
  • Adlet Nazhbiyev,
  • Zhanbota Mussagaliyeva and
  • Aksholpan Atalikhova

Flooding events have been negatively affecting the Republic of Kazakhstan, with higher occurrence in flat parts of the country during spring snowmelt in snow-fed rivers. The current project aims to assess the flood hazard reduction capacity of Alva i...

  • Article
  • Open Access
10 Citations
3,142 Views
26 Pages

A New Extension of the Kumaraswamy Generated Family of Distributions with Applications to Real Data

  • Salma Abbas,
  • Mustapha Muhammad,
  • Farrukh Jamal,
  • Christophe Chesneau,
  • Isyaku Muhammad and
  • Mouna Bouchane

In this paper, we develop the new extended Kumaraswamy generated (NEKwG) family of distributions. It aims to improve the modeling capability of the standard Kumaraswamy family by using a one-parameter exponential-logarithmic transformation. Mathemati...

  • Article
  • Open Access
11 Citations
5,501 Views
8 Pages

Several studies estimate the volatility spillover effects between gold and silver returns, but none of them used the implied volatility to evaluate the long-term relationship between these two metal markets. Our paper aims to fill this gap in the exi...

  • Article
  • Open Access
3 Citations
3,536 Views
18 Pages

Coarse-Grained Modeling of the SARS-CoV-2 Spike Glycoprotein by Physics-Informed Machine Learning

  • David Liang,
  • Ziji Zhang,
  • Miriam Rafailovich,
  • Marcia Simon,
  • Yuefan Deng and
  • Peng Zhang

Coarse-grained (CG) modeling has defined a well-established approach to accessing greater space and time scales inaccessible to the computationally expensive all-atomic (AA) molecular dynamics (MD) simulations. Popular methods of CG follow a bottom-u...

  • Article
  • Open Access
13 Citations
2,849 Views
13 Pages

A Novel Computational Model for Traction Performance Characterization of Footwear Outsoles with Horizontal Tread Channels

  • Shubham Gupta,
  • Subhodip Chatterjee,
  • Ayush Malviya,
  • Gurpreet Singh and
  • Arnab Chanda

Slips and falls are among the most serious public safety hazards. Adequate friction at the shoe–floor contact is necessary to reduce these risks. In the presence of slippery fluids such as water or oil, the footwear outsole is crucial for ensur...

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Computation - ISSN 2079-3197Creative Common CC BY license