Design of HP Models of Proteins by Energy Gap Criterion Using Continuous Modeling and Optimization

2004 ◽  
Author(s):  
Sung K. Koh ◽  
G. K. Ananthasuresh
Keyword(s):  
Protein Design ◽  
Compliant Mechanisms ◽  
Energy Gap ◽  
Minimum Energy ◽  
Continuous Optimization ◽  
Combinatorial Problem ◽  
Energy Criterion ◽  
Optimization Method ◽  
Protein Chain ◽  
Folded Structure

The sequence of 20 types of amino acid residues in a heteropolymer chain of a protein is believed to be the basis for the 3-D conformation (folded structure) that a protein assumes to serve its functions. We present a deterministic optimization method to design the sequence of a simplified model of proteins for a desired conformation. A design methodology developed for the topology optimization of compliant mechanisms is adapted here by converting the discrete combinatorial problem of protein sequence design to a continuous optimization problem. It builds upon our recent work which used a minimum energy criterion on a deterministic approach to protein design using continuous models. This paper focuses on the energy gap criterion, which is argued to be one of the most important characteristics determining the stable folding of a protein chain. The concepts, methodology, and illustrative examples are presented using HP models of proteins where only two types (H: hydrophobic and P: polar) of monomers are considered instead of 20. The highlight of the method presented in this paper is the drastic reduction in computational costs.

A Continuous Model for Protein Synthesis Using Artificial Power Law in Topology Optimization

2008 ◽  
Author(s):  
Sung Koh ◽  
Gunagjun Liu ◽  
Wen-Hong Zhu
Keyword(s):  
Protein Synthesis ◽  
Topology Optimization ◽  
Power Law ◽  
Protein Design ◽  
Design Method ◽  
Minimum Energy ◽  
Continuous Optimization ◽  
Continuous Model ◽  
Design Methods ◽  
Structural Topology

A continuous protein synthesis formulation based on the design principles developed for structural topology optimization is proposed in this paper. Unlike conventional continuous protein design methods, the Power Law-based (PL) design formulation proposed in this paper enables using any number of residue types to accomplish the goal of protein synthesis and hence provides a continuous protein design formulation applicable to any general protein design problems. Moreover, a discrete sequence with minimum energy can be synthesized by the PL design method as it inherits the feature of material penalization used for the topology optimization. Since a continuous optimization method is implemented to solve the PL design formulation, the entire design process is more efficient and robust than the conventional design methods employing a stochastic or enumerative search process. The performance of the PL design formulation is demonstrated by designing simple lattice protein models for which an exhaustive search can be carried out to identify the sequence with minimum energy. The comparison with the exchange replica method indicates that the PL design method is millions of times more efficient than the conventional stochastic protein design method.

Adiabatic quantum algorithm for factorization with growing minimum energy gap

2021 ◽  
Author(s):  
Bao Yan ◽  
Haocong Jiang ◽  
Ming Gao ◽  
Qianheng Duan ◽  
Hong Wang ◽  
...  
Keyword(s):  
Energy Gap ◽  
Minimum Energy ◽  
Quantum Algorithm

Nonsmooth Optimization Method for Image Restoration

1995 ◽  
Author(s):  
Kazufumi Ito ◽  
Karl Kunisch
Keyword(s):  
Image Restoration ◽  
Nonsmooth Optimization ◽  
Numerical Optimization ◽  
Augmented Lagrangian ◽  
Energy Criterion ◽  
Optimization Methods ◽  
Optimization Method ◽  
Augmented Lagrangian Methods ◽  
Active Set ◽  
First Order

Abstract In this paper we discuss applications of the numerical optimization methods for nonsmooth optimization, developed in [IK1] for the variational formulation of image restoration problems involving bounded variation type energy criterion. The Uzawa’s algorithm, first order augmented Lagrangian methods and Newton-like update using the active set strategy are described.

scholarly journals A NOVEL FRACTAL GEOMETRY DOPING FOR GRAPHENE NANORIBBON AND THE OPTIMIZATION OF CRYSTAL: A DENSITY FUNCTIONAL THEORY (DFT) STUDY

2020 ◽  
Vol 17 (35) ◽  
pp. 1148-1158
Author(s):  
Mohammed L. JABBAR ◽  
Kadhum J. AL-SHEJAIRY
Keyword(s):  
Density Functional Theory ◽  
Density Functional ◽  
Energy Gap ◽  
Minimum Energy ◽  
Graphene Nanoribbon ◽  
Chemical Doping ◽  
Functional Theory ◽  
Lower Reactivity ◽  
The Density Functional Theory ◽  
Semiconductor Behavior

Chemical doping is a promising route to engineering and controlling the electronic properties of the zigzag graphene nanoribbon (ZGNR). By using the first-principles of the density functional theory (DFT) calculations at the B3LYP/ 6-31G, which implemented in the Gaussian 09 software, various properties, such as the geometrical structure, DOS, HOMO, LUMO infrared spectra, and energy gap of the ZGNR, were investigated with various sites and concentrations of the phosphorus (P). It was observed that the ZGNR could be converted from linear to fractal dimension by using phosphorus (P) impurities. Also, the fractal binary tree of the ZGNR and P-ZGNR structures is a highlight. The results demonstrated that the energy gap has different values, which located at this range from 0.51eV to 1.158 eV for pristine ZGNR and P-ZGNR structures. This range of energy gap is variable according to the use of GNRs in any apparatus. Then, the P-ZGNR has semiconductor behavior. Moreover, there are no imaginary wavenumbers on the evaluated vibrational spectrum confirms that the model corresponds to minimum energy. Then, these results make P-ZGNR can be utilized in various applications due to this structure became more stable and lower reactivity.

Topology Optimization of Compliant Mechanisms Using Hybrid Discretization Model

2010 ◽  
Vol 132 (11) ◽  
Author(s):  
Hong Zhou
Keyword(s):  
Topology Optimization ◽  
Compliant Mechanisms ◽  
Compliant Mechanism ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Diagonal Element ◽  
Initial Guess ◽  
Stress Constraint ◽  
Design Variables ◽  
Hybrid Discretization

The hybrid discretization model for topology optimization of compliant mechanisms is introduced in this paper. The design domain is discretized into quadrilateral design cells. Each design cell is further subdivided into triangular analysis cells. This hybrid discretization model allows any two contiguous design cells to be connected by four triangular analysis cells whether they are in the horizontal, vertical, or diagonal direction. Topological anomalies such as checkerboard patterns, diagonal element chains, and de facto hinges are completely eliminated. In the proposed topology optimization method, design variables are all binary, and every analysis cell is either solid or void to prevent the gray cell problem that is usually caused by intermediate material states. Stress constraint is directly imposed on each analysis cell to make the synthesized compliant mechanism safe. Genetic algorithm is used to search the optimum and to avoid the need to choose the initial guess solution and conduct sensitivity analysis. The obtained topology solutions have no point connection, unsmooth boundary, and zigzag member. No post-processing is needed for topology uncertainty caused by point connection or a gray cell. The introduced hybrid discretization model and the proposed topology optimization procedure are illustrated by two classical synthesis examples of compliant mechanisms.

A survey of unsupervised learning in medical image registration

2022 ◽  
Vol 2 (1) ◽  
pp. 0-0
Keyword(s):  
Deep Learning ◽  
Image Registration ◽  
Unsupervised Learning ◽  
Medical Image ◽  
Continuous Optimization ◽  
Optimization Method ◽  
Clinical Applications ◽  
Future Research ◽  
Medical Image Registration ◽  
Short Time

Medical image registration has important value in actual clinical applications. From the traditional time-consuming iterative similarity optimization method to the short time-consuming supervised deep learning to today's unsupervised learning, the continuous optimization of the registration strategy makes it more feasible in clinical applications. This survey mainly focuses on unsupervised learning methods and introduces the latest solutions for different registration relationships. The registration for inter-modality is a more challenging topic. The application of unsupervised learning in registration for inter-modality is the focus of this article. In addition, this survey also proposes ideas for future research methods to show directions of the future research.

Concerted, Computing-Intense Novel MFL Approach Ensuring Reliability and Reducing the Need for Dig Verification

2020 ◽  
Author(s):  
Johannes Palmer ◽  
Aaron Schartner ◽  
Andrey Danilov ◽  
Vincent Tse
Keyword(s):  
Synthetic Data ◽  
Continuous Optimization ◽  
Optimization Method ◽  
Metal Loss ◽  
Empirical Formulas ◽  
Blind Test ◽  
High Data ◽  
Pure Number ◽  
Accuracy Increase ◽  
Pull Tests

Abstract Magnetic Flux Leakage (MFL) is a robust technology with high data coverage. Decades of continuous sizing improvement allowed for industry-accepted sizing reliability. The continuous optimization of sizing processes ensures accurate results in categorizing metal loss features. However, the identified selection of critical anomalies is not always optimal; sometimes anomalies are dug up too early or unnecessarily, this can be caused by the feature type in the field (true metal loss shape) being incorrectly identified which affects sizing and tolerance. In addition, there is the possibility for incorrectly identifying feature types causing false under-calls. Today, complex empirical formulas together with multifaceted lookup tables fed by pull tests, synthetic data, dig verifications, machine learning, artificial intelligence and last but not least human expertise translate MFL signals into metal loss assessments with high levels of success. Nevertheless, two important principal elements are limiting the possible MFL sizing optimization. One is the empirical character of the signal interpretation. The other is the implicitly induced data and result simplification. The reason to go this principal route for many years is simple: it is methodologically impossible to calculate the metal source geometry directly from the signals. In addition, the pure number of possible relevant geometries is so large that simplification is necessary and inevitable. Moreover, the second methodological reason is the ambiguity of the signal, which defines the target of metal loss sizing as the most probable solution. However, even under the best conditions, the most probable one is not necessarily the correct one. This paper describes a novel, fundamentally different approach as a basic alternative to the common MFL-analysis approach described above. A calculation process is presented, which overcomes the empirical nature of traditional approaches by using a result optimization method that relies on intense computing and avoids any simplification. Additionally, the strategy to overcome MFL ambiguity will be shown. Together with the operator, detailed blind-test examples demonstrate the enormous level of detail, repeatability and accuracy of this groundbreaking technological method with the potential to reduce tool tolerance, increase sizing accuracy, increase growth rate accuracy, and help optimize the dig program to target critical features with greater confidence.

Optimal Viscous Damper Placement Using Level Set Topology Optimization Method

2010 ◽  
Author(s):  
Masoud Ansari ◽  
Amir Khajepour ◽  
Ebrahim Esmailzadeh
Keyword(s):  
Topology Optimization ◽  
Level Set ◽  
Discrete Optimization ◽  
Optimization Problem ◽  
Minimum Energy ◽  
Optimization Method ◽  
Discrete Optimization Problem ◽  
Placement Problem ◽  
New Approach ◽  
Optimal Damping

Vibration control has always been of great interest for many researchers in different fields, especially mechanical and civil engineering. One of the key elements in control of vibration is damper. One way of optimally suppressing unwanted vibrations is to find the best locations of the dampers in the structure, such that the highest dampening effect is achieved. This paper proposes a new approach that turns the conventional discrete optimization problem of optimal damper placement to a continuous topology optimization. In fact, instead of considering a few dampers and run the discrete optimization problem to find their best locations, the whole structure is considered to be connected to infinite numbers of dampers and level set topology optimization will be performed to determine the optimal damping set, while certain number of dampers are used, and the minimum energy for the system is achieved. This method has a few major advantages over the conventional methods, and can handle damper placement problem for complicated structures (systems) more accurately. The results, obtained in this research are very promising and show the capability of this method in finding the best damper location is structures.

On the Extraction of Kinematic Behavior From Optimal Compliant Topologies With Application to Number Synthesis of Linkages

2001 ◽  
Author(s):  
Anupam Saxena ◽  
G. K. Ananthasuresh
Keyword(s):  
Compliant Mechanisms ◽  
Compliant Mechanism ◽  
Optimization Method ◽  
Dimensional Synthesis ◽  
Kinematic Chains ◽  
Design Specifications ◽  
Kinematic Behavior ◽  
Added Benefit ◽  
Number Synthesis ◽  
Elastic Mechanics

Abstract This paper presents a number of systematically designed compliant topologies and discusses how the intrinsic kinematic behavior can be extracted from them. This is then applied to the number synthesis of linkages. Many techniques developed for number synthesis of linkages enumerate numerous possible kinematic chains, but few can select the best configuration among them. A systematic computational approach that can select the best configuration based on kinetostatic design specifications is presented here. This is a serendipitous result that transpired when two well-developed design techniques for compliant mechanisms were combined. A number of examples with non-intuitive design specifications are included to illustrate the new approach to number synthesis. The examples also illustrate that the kinematic behavior is aptly captured in the elastic mechanics-based topology optimization method to compliant mechanism design. Dimensional synthesis is also accomplished in the same procedure, which is an added benefit of this approach.

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