scholarly journals Exploring Intuitive Approaches to Protein Conformation Clustering Using Regions of High Structural Variance

2021 ◽  
Author(s):  
Yi Yao Tan
Keyword(s):  
Detection Algorithm ◽  
Distance Metrics ◽  
Absolute Position ◽  
Practical Applications ◽  
Angle Data ◽  
Additional Testing ◽  
Single Protein ◽  
Pros And Cons ◽  
Protein Code ◽  
Better Than

This paper presents a method to find structurally high variance segments of the different conformations of a single protein and uses clusters them using different distance metrics and interpretation of coordinate and angle data presented by three different methods: root mean squared derivation RMSD, t-distributed Stochastic Neighbor Embedding (t-SNE) based map, and dihedral-based clustering. The methods were applied on the human cylin-dependent kinase 2 (CDK2) protein, code P24941 uniprot using a series of python scripts and clustering packages. We test our methods on the data of the CDK2 protein as it is a highly researched protein, with practical applications of clustering in cancer research, crucial in the regulation of the cell-cycle, and has a sizeable amount of experimental data collected on the confirmation structures. While using the distance based root mean squared deviation RMSD provides data of structure to structure dissimilarity between different conformations, a simple RMSD matrix lacks to ability to describe the subsequence-wise in shape and absolute position which could be the main identifying elements for a protein's conformation and state. To make up for this loss we explore an intuitive and more flexible method, able to accept multiple high structural variance segments, which takes coordinate based data, through a series of maps and with the help of t-SNE, and maps each segment as a feature in the clustering matrix. This method, however, would require additional testing on other proteins and modifications to verify its consistency and test its robustness. In the end we explore the pros and cons of the three methods applied on the high structural variance regions. Despite the randomness factor by the t-SNE used in mapping the coordinates to lower dimensions, the coordinate-based approach consistently performed better than the RSMD and dihedral based methods in clustering the three groups of the CDK2 protein kinase. We also found that analyzing only the substructures identified by the high variance detection algorithm consistently provided more distinct clusters with higher multi-class F1 scores.

Resolution and measurement in the scanning electron microscope

1987 ◽  
Vol 45 ◽  
pp. 534-537 ◽  
Author(s):  
Michael T. Postek
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Engineering Design ◽  
Resolving Power ◽  
Practical Applications ◽  
Instrument Resolution ◽  
Accurate Definition ◽  
Definition Of ◽  
Scanning Electron ◽  
Better Than

The term ultimate resolution or resolving power is the very best performance that can be obtained from a scanning electron microscope (SEM) given the optimum instrumental conditions and sample. However, as it relates to SEM users, the conventional definitions of this figure are ambiguous. The numbers quoted for the resolution of an instrument are not only theoretically derived, but are also verified through the direct measurement of images on micrographs. However, the samples commonly used for this purpose are specifically optimized for the measurement of instrument resolution and are most often not typical of the sample used in practical applications.SEM RESOLUTION. Some instruments resolve better than others either due to engineering design or other reasons. There is no definitively accurate definition of how to quantify instrument resolution and its measurement in the SEM.

The Analysis on the Tribological Properties of TPU/PVC Blends under Oil Lubrication

2013 ◽  
Vol 774-776 ◽  
pp. 94-98
Author(s):  
Dao Yuan Pan ◽  
Peng Peng Wu ◽  
Zhong Xue Gao ◽  
Yu Zeng Zhang
Keyword(s):  
Working Conditions ◽  
Friction And Wear ◽  
Oil Lubrication ◽  
Wear Properties ◽  
Operation Conditions ◽  
Hydraulic Steering ◽  
Pros And Cons ◽  
Friction And Wear Properties ◽  
Lubrication Conditions ◽  
Better Than

Based on actual working conditions and parameters of the hydraulic steering gear, the purpose is optimizing the rubber seal of steering gear by different rubbers mixing technology. Compare the five kinds of rubber with metal of the friction characteristics in dynamic fit, it can obtain a performance excellent rubber real in the specific operation conditions. And then improve the overall service life of the steering gear. It is first prepared the same hardness TPU and PVC and blends that the ratio is 3:7, 5:5and7:3 in this article. The pros and cons of the five rubbers are analyzed in friction and wear properties of the above experimental. The test curve of coefficient friction and wear with time has been done under different load at constant low speed. It determines TPU/PVC = 3:7 blends through friction and wear and wear mechanism of five rubbers with steel comparatively analyses, and the heat resistance and wear resistance of them are better than the other TPU/PVC blends and PVC under oil lubrication conditions.

A Generic Method to Generate AS-Curve Profile in Commercial Motion Controller

2017 ◽  
Author(s):  
Youdun Bai ◽  
Xin Chen ◽  
Zhijun Yang
Keyword(s):  
Motion Controller ◽  
Residual Vibration ◽  
Practical Applications ◽  
Analytic Polynomial ◽  
Acceleration And Deceleration ◽  
Special Knowledge ◽  
Curve Profile ◽  
S Curve ◽  
Motion Profile ◽  
Better Than

It is well believed that S-curve motion profiles are able to reduce residual vibration, and are widely applied in the motion control fields. Recently, a new asymmetric S-curve (AS-curve) motion profile, which is able to effectively adjust the acceleration and deceleration periods, is proposed to enhance the performance of S-curve motion profile, and proved to be better than the traditional symmetric S-curve in many cases. However, most commercial motion controllers do not support the AS-curve motion profiles inherently. Special knowledge or expensive advanced controlling systems, such as dSPACE system, are required to generate the AS-curve motion command, which limits the applications of the AS-curve motion profile in many practical applications. In this paper, a generic method based on the Position-Velocity-Time (PVT) mode move supported by most commercial motion controllers is proposed to generate exact AS-curve motion command in real machines. The analytic polynomial functions of AS-curve motion profile are also derived to simplify the further application, and the effectiveness of the proposed method is verified by numerical simulation.

Evaluating the Impact of the COSMIC RO Bending Angle Data on Predicting the Heavy Precipitation Episode on 16 June 2008 during SoWMEX-IOP8

2014 ◽  
Vol 142 (11) ◽  
pp. 4139-4163 ◽  
Author(s):  
Shu-Chih Yang ◽  
Shu-Hua Chen ◽  
Shu-Ya Chen ◽  
Ching-Yuang Huang ◽  
Ching-Sen Chen
Keyword(s):  
Lower Troposphere ◽  
Heavy Precipitation ◽  
Southwest Monsoon ◽  
Weather Research And Forecasting ◽  
Heavy Rainfall Event ◽  
Bending Angle ◽  
Angle Data ◽  
Ensemble Transform Kalman Filter ◽  
The Impact ◽  
Better Than

Abstract Global positioning system (GPS) radio occultation (RO) data have been broadly used in global and regional numerical weather predictions. Assimilation with the bending angle often performs better than refractivity, which is inverted from the bending angle under spherical assumption and is sometimes associated with negative biases at the lower troposphere; however, the bending angle operator also requires a higher model top as used in global models. This study furnishes the feasibility of bending-angle assimilation in the prediction of heavy precipitation systems with a regional model. The local RO operators for simulating bending angle and refractivity are implemented in the Weather Research and Forecasting (WRF)–local ensemble transform Kalman filter (LETKF) framework. The impacts of assimilating RO data from the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) using both operators are evaluated on the prediction of a heavy precipitation episode during Southwest Monsoon Experiment intensive observing period 8 (SoWMEX-IOP8) in 2008. Results show that both the refractivity and bending angle provide a favorable condition for generating this heavy rainfall event. In comparison with the refractivity data, the advantage of assimilating the bending angle is identified in the midtroposphere for deepening of the moist layer that leads to a rainfall forecast closer to the observations.

Study of BLAST Signal Detection Algorithm in LTE System

2013 ◽  
Vol 756-759 ◽  
pp. 3183-3188
Author(s):  
Tao Lei ◽  
Deng Ping He ◽  
Fang Tang Chen
Keyword(s):  
Signal Detection ◽  
High Speed ◽  
Data Communication ◽  
Detection Algorithm ◽  
Detection Performance ◽  
Detection Algorithms ◽  
High Speed Data ◽  
Simulation Results ◽  
Better Than

BLAST can achieve high speed data communication. Its signal detection directly affects performance of BLAST receiver. This paper introduced several signal detection algorithmsZF algorithm, MMSE algorithm, ZF-SIC algorithm and MMSE-SIC algorithm. The simulation results show that the traditional ZF algorithm has the worst performance, the traditional MMSE algorithm and the ZF-SIC algorithm is similar, but with the increase of the SNR, the performance of ZF-SIC algorithm is better than MMSE algorithm. MMSE-SIC algorithm has the best detection performance in these detection algorithms.

A New Protocol for Secure Distributed Multiplication of Two Polynomial Shared Values

2014 ◽  
Vol 1042 ◽  
pp. 110-116
Author(s):  
Xiang Ning Hao ◽  
Xue Min Wang ◽  
Li Qiong Deng
Keyword(s):  
Secret Sharing ◽  
Shared Values ◽  
Secret Sharing Scheme ◽  
Threshold Secret Sharing ◽  
Practical Applications ◽  
Classic Problem ◽  
Sharing Scheme ◽  
Better Than

In view of practical applications, it is a high priority to optimize the efficiency of methods for secure multi-party computations. A classic problem is described as following: there are two secrets, α and β, shared among n players using Shamir (t+1,n)-threshold secret sharing scheme, and how to make their product αβshared among n players using the same way. The protocol of Gennaro, Rabin and Rabin (1998) is a well known and efficient protocol for this purpose. It requires one round of communication and O(n2klog2n+nk2) bit-operations per player, where k is the bit size of the computing field and n is the number of players. In a previous paper (2007), the author presented a modification of this protocol, which reduced its complexity toOn2k+nk2. In 2009, Peter Lory reduced its complexity to On2k. A new protocol is presented in our paper, which reduces this complexity further to Onklog2k. It is better than Gennaro protocol unconditionally. And as to Peter Lory protocol, the reduction is profitable in situation where log2k is smaller than n.

scholarly journals Endmember Learning with K-Means through SCD Model in Hyperspectral Scene Reconstructions

2019 ◽  
Vol 5 (11) ◽  
pp. 85 ◽  
Author(s):  
Ayan Chatterjee ◽  
Peter W. T. Yuen
Keyword(s):  
Dictionary Learning ◽  
Sparse Coding ◽  
Clustering Algorithm ◽  
Matching Pursuit ◽  
Orthogonal Matching Pursuit ◽  
Scene Reconstruction ◽  
Data Sets ◽  
Practical Applications ◽  
Input Dataset ◽  
Better Than

This paper proposes a simple yet effective method for improving the efficiency of sparse coding dictionary learning (DL) with an implication of enhancing the ultimate usefulness of compressive sensing (CS) technology for practical applications, such as in hyperspectral imaging (HSI) scene reconstruction. CS is the technique which allows sparse signals to be decomposed into a sparse representation “a” of a dictionary D u . The goodness of the learnt dictionary has direct impacts on the quality of the end results, e.g., in the HSI scene reconstructions. This paper proposes the construction of a concise and comprehensive dictionary by using the cluster centres of the input dataset, and then a greedy approach is adopted to learn all elements within this dictionary. The proposed method consists of an unsupervised clustering algorithm (K-Means), and it is then coupled with an advanced sparse coding dictionary (SCD) method such as the basis pursuit algorithm (orthogonal matching pursuit, OMP) for the dictionary learning. The effectiveness of the proposed K-Means Sparse Coding Dictionary (KMSCD) is illustrated through the reconstructions of several publicly available HSI scenes. The results have shown that the proposed KMSCD achieves ~40% greater accuracy, 5 times faster convergence and is twice as robust as that of the classic Spare Coding Dictionary (C-SCD) method that adopts random sampling of data for the dictionary learning. Over the five data sets that have been employed in this study, it is seen that the proposed KMSCD is capable of reconstructing these scenes with mean accuracies of approximately 20–500% better than all competing algorithms adopted in this work. Furthermore, the reconstruction efficiency of trace materials in the scene has been assessed: it is shown that the KMSCD is capable of recovering ~12% better than that of the C-SCD. These results suggest that the proposed DL using a simple clustering method for the construction of the dictionary has been shown to enhance the scene reconstruction substantially. When the proposed KMSCD is incorporated with the Fast non-negative orthogonal matching pursuit (FNNOMP) to constrain the maximum number of materials to coexist in a pixel to four, experiments have shown that it achieves approximately ten times better than that constrained by using the widely employed TMM algorithm. This may suggest that the proposed DL method using KMSCD and together with the FNNOMP will be more suitable to be the material allocation module of HSI scene simulators like the CameoSim package.

scholarly journals Modal-based vibrothermography using feature extraction with application to composite materials

2019 ◽  
Vol 19 (4) ◽  
pp. 967-986 ◽  
Author(s):  
Xintian Chi ◽  
Dario Di Maio ◽  
Nicholas AJ Lieven
Keyword(s):  
Feature Extraction ◽  
Composite Materials ◽  
Damage Detection ◽  
Infrared Camera ◽  
Experimental Tests ◽  
Detection Algorithm ◽  
Modal Testing ◽  
Theoretical Development ◽  
Operational Environment ◽  
Practical Applications

This research focuses on the development of a damage detection algorithm based on modal testing, vibrothermography, and feature extraction. The theoretical development of mathematical models is presented to illustrate the principles supporting the associated algorithms, through which the importance of the three components contributing to this approach is demonstrated. Experimental tests and analytical simulations have been performed in laboratory conditions to show that the proposed damage detection algorithm is able to detect, locate, and extract the features generated due to the presence of sub-surface damage in aerospace grade composite materials captured by an infrared camera. Through tests and analyses, the reliability and repeatability of this damage detection algorithm are verified. In the concluding observations of this article, suggestions are proposed for this algorithm’s practical applications in an operational environment.

scholarly journals Uncertainty-Aware Action Advising for Deep Reinforcement Learning Agents

2020 ◽  
Vol 34 (04) ◽  
pp. 5792-5799
Author(s):  
Felipe Leno Da Silva ◽  
Pablo Hernandez-Leal ◽  
Bilal Kartal ◽  
Matthew E. Taylor
Keyword(s):  
Reinforcement Learning ◽  
Value Function ◽  
Epistemic Uncertainty ◽  
Policy Advice ◽  
Sequential Decision ◽  
Practical Applications ◽  
Learning Agents ◽  
Standard Value ◽  
Random States ◽  
Better Than

Although Reinforcement Learning (RL) has been one of the most successful approaches for learning in sequential decision making problems, the sample-complexity of RL techniques still represents a major challenge for practical applications. To combat this challenge, whenever a competent policy (e.g., either a legacy system or a human demonstrator) is available, the agent could leverage samples from this policy (advice) to improve sample-efficiency. However, advice is normally limited, hence it should ideally be directed to states where the agent is uncertain on the best action to execute. In this work, we propose Requesting Confidence-Moderated Policy advice (RCMP), an action-advising framework where the agent asks for advice when its epistemic uncertainty is high for a certain state. RCMP takes into account that the advice is limited and might be suboptimal. We also describe a technique to estimate the agent uncertainty by performing minor modifications in standard value-function-based RL methods. Our empirical evaluations show that RCMP performs better than Importance Advising, not receiving advice, and receiving it at random states in Gridworld and Atari Pong scenarios.

The Analysis on the Tribological Properties of CR/EPDM Blends with Chrome-Plated Steel under Dry Sliding

2013 ◽  
Vol 774-776 ◽  
pp. 99-102 ◽  
Author(s):  
Lian Hua Zhao ◽  
Xiao Bo Wei ◽  
Xiao Guang Li
Keyword(s):  
Friction And Wear ◽  
Conveyor Belt ◽  
Operating Conditions ◽  
Dry Sliding ◽  
Wear Properties ◽  
Transportation Equipment ◽  
Pros And Cons ◽  
Friction And Wear Properties ◽  
Technology Comparison ◽  
Better Than

It is based on actual working conditions and parameters of the conveyor belt, to reach the purpose of the optimizing rubber by different rubbers mixing technology. Comparison the five kinds rubber and metal of the friction characteristics in dynamic fit, obtained a performance excellent rubber in the specific operating conditions. Then improve the overall service life of the transportation equipment. It is first prepared the same hardness CR and EPDM and blends that is ratio of 2:8, 5:5and8:2 in this article. The pros and cons of the five rubbers are analyzed by friction and wear properties of the above experimental. The test curve of coefficient friction and wear with time has been done under different load at constant low speed, friction and wear and wear mechanism of five rubbers with chrome-plated steel comparatively analyses to determine CR/EPDM = 8:2 blends has the heat resistance and wear resistance are better than CR and EPDM under dry sliding conditions.

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