bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tungsten divertor plasma simulation with bundled charge state model by SOLPS-ITER on EAST
Authors: Gao Shanlu , Liu Xiaoju , Deng Guozhong , Ming Tingfeng , Li Guoqiang , Zhang Xuexi , Tao Yuqiang , Gao Xiang 
Published: February 2021

Research was originally carried out to evaluate plasma performance with a tungsten (W) divertor on EAST using the bundled charge state model by the coupled multi-fluid plasma and kinetic neutral code SOLPS-ITER. This work focuses on the comparisons of several bundled charge state models of W and the all W ion model in low and high recycling divertor operational regimes. It is found that bundled charge state models have a pronounced effect on the reduction of computational time and computer memory and provide an improved marked code speed by a factor of more than five. In the low recycling regime, compared to the full W charge state model, the differences in the plasma parameters at both divertor targets are within 15% for different bundling schemes. In the high recycling regime, no significant difference between bundled charge state models and the all charge state model is observed due to the very low W concentration (∼10−6). It, therefore, indicates that bundled charge state models of W can describe divertor parameters well to a considerable degree. Besides, the errors of tungsten concentration (CW) and the effective ion charge number (Zeff) at the outer mid-plane for bundled models are within 40% inside the separatrix. At the same time, highly resolved bundled models with more than 20 W fluids can describe the radiation power loss consistently within 50% as compared with the all charge state model, while it varies greatly from one aggressively bundled model to the other, especially for core radiation, which is strongly related to the bundling schemes for relatively high charge states.
Widespread polycistronic gene expression in green algae
Authors: Gallaher Sean D. , Craig Rory J. , Ganesan Iniyan , Purvine Samuel O. , McCorkle Sean R. , Grimwood Jane , Strenkert Daniela , Davidi Lital , Roth Melissa S. , Jeffers Tim L. , Lipton Mary S. , Niyogi Krishna K. , Schmutz Jeremy , Theg Steven M. , Blaby-Haas Crysten E. , Merchant Sabeeha S. 
Published: February 2021

Significance
Historically, it has been understood that for gene expression in eukaryotes, each messenger RNA encodes a single protein. With the recent development of technologies to sequence full-length transcripts en masse, we have discovered hundreds of examples in two species of green algae where two, three, or more proteins are translated from a single transcript. These “polycistronic” transcripts are found in diverse species throughout the green algal lineage, which highlights their biological importance. We have leveraged these findings to coexpress pairs of genes on polycistronic transcripts in vitro, which should facilitate efforts to engineer algae for research and industrial applications.
Semi-infinite travelling waves arising in a general reaction–diffusion Stefan model
Authors: Fadai Nabil T 
Published: February 2021

Abstract
We examine travelling wave solutions of the reaction–diffusion equation,

∂

t

u
=
R

(

u

)

+

∂

x

D

(

u

)

∂

x

u

, with a Stefan-like condition at the edge of the moving front. With only a few assumptions on R(u) and D(u), a variety of new semi-infinite travelling waves arise in this reaction–diffusion Stefan model. While other reaction–diffusion models can admit semi-infinite travelling waves for a unique wavespeed, we show that semi-infinite travelling waves in the reaction–diffusion Stefan model exist over a range of wavespeeds. Furthermore, we determine the necessary conditions on R(u) and D(u) for which semi-infinite travelling waves exist for all wavespeeds. Using asymptotic analysis in various distinguished limits of the wavespeed, we obtain approximate solutions of these travelling waves, agreeing with numerical simulations with high accuracy.
Project ThaiPASS: international outreach blending astronomy and Python
Authors: Keegans James D , Stancliffe Richard J , Bilton Lawrence E , Cashmore Claire R , Gibson Brad K , Kristensen Mikkel Theiss , Lawson Thomas V , Pignatari Marco , Vaezzadeh Iraj , Côté Benoit , Chongchitnan Siri 
Published: February 2021

Abstract
We present our outreach program, the Thailand–UK Python+Astronomy Summer School (ThaiPASS), a collaborative project comprising UK and Thai institutions and assess its impact and possible application to schools in the United Kingdom. Since its inception in 2018, the annual ThaiPASS has trained around 60 Thai high-school students in basic data handling skills using Python in the context of various astronomy topics, using current research from the teaching team. Our impact assessment of the 5 day summer schools shows an overwhelmingly positive response from students in both years, with over 80% of students scoring the activities above average in all activities but one. We use this data to suggest possible future improvements. We also discuss how ThaiPASS may inspire further outreach and engagement activities within the UK and beyond.
Designing an argumentation-based educational digital game to teach the subject of force
Authors: Bağ Hasan , Çalık Muammer 
Published: February 2021

Abstract
The aim of this study is to design an argumentation-based educational digital game to teach the subject of force. Through a design-based research method, each game section includes the argumentation questions that foster students to think about the ‘force’ subject. We pilot studied the game with 12 grade 4 students in a state primary school. After successive three pilot studies, we revised and fixed technical and pedagogical problems. We believe that the argumentation-based digital game has the potential to improve grade 4 students’ argumentation qualities and stimulate their learning interest/motivations.
Bounds of the sum of edge lengths in linear arrangements of trees
Authors: Ferrer-i-Cancho Ramon , Gómez-Rodríguez Carlos , Luis Esteban Juan 
Published: February 2021

Abstract
A fundamental problem in network science is the normalization of the topological or physical distance between vertices, which requires understanding the range of variation of the unnormalized distances. Here we investigate the limits of the variation of the physical distance in linear arrangements of the vertices of trees. In particular, we investigate various problems of the sum of edge lengths in trees of a fixed size: the minimum and the maximum value of the sum for specific trees, the minimum and the maximum in classes of trees (bistar trees and caterpillar trees) and finally the minimum and the maximum for any tree. We establish some foundations for research on optimality scores for spatial networks in one dimension.
Virtual-Vector-Based FCS Model Predictive Current Control with Duty Cycle Optimization for Dual Three-Phase Motors
Authors: He Shuai , Li Yaoheng , Shuai Zhibin , Zhang Ying , Gai Jiangtao , Zhou Guangming 
Published: February 2021

Abstract
This paper presents an improved finite control set model predictive current control (FCS-MPCC) based on virtual vectors with duty cycle control for dual three-phase permanent magnet synchronous motor (DTP PMSM) drives. Virtual vectors synthesized by two basic voltage vectors of the inverter are introduced to suppress the harmonic current by the vector space decomposition (VSD) model. And the virtual vectors with the optimal duty cycle can be obtained by duty cycle control using zero vectors to generate a fixed switching frequency. Moreover, a simple scheme of centrosymmetric switching patterns is presented for the realtime implementation. In this way, the performance of current tracking is improved while the computational burden is reduced. Finally, results of simulation analysis and DSP test for the three different strategies are given to verify the validity of the proposed strategy.
A dynamic sliding mode control method for multi-agent formation
Authors: Liu Jinyu , Li Yonggang , Yang Zhaofeng 
Published: February 2021

AbstractIn this article, we study the formation control problem of multiple agents. In the past studies on sliding mode control, when the state trajectory reaches the sliding mode surface, it is difficult to strictly slide along the sliding mode surface to the equilibrium point, but it travels back and forth on both sides to approach the equilibrium point, resulting in chattering. This is also the main obstacle in the practical application of sliding mode control, and in actual scenarios, the agent has a limited communication distance and perception distance. In order to solve this problem, we propose a dynamic sliding mode control method. First, we establish an agent motion model to determine the leader and follower. The trajectory of the formation is deter-mined by the leader, and the follower agent maintains an ideal position in the leader coordinate system. Then, multiple agents conduct formation movement under the guidance of the leader. In this paper, two examples are used for simulation, and the simulation results show the effectiveness of the pro-posed formation control method.
Design of the extruder drive motor and its HNTSM speed control with disturbance observer
Authors: Zhang Jiacheng , Fan Yuanxun , Lu Pengcheng , Cao Dawei , Liu Zhikang 
Published: February 2021

Abstract
In order to meet the requirements of 25kW rated power and 1500r/min rated speed required by the extrusion process of polyester fiber composite materials, a PMSM suitable for this working condition was designed to complete the driving task of the extruder. The geometric model of the motor was established using RMxprt, and the load operation state of the motor was simulated by Maxwell. The motor speed was controlled by a HNTSM control scheme with a disturbance observer, and based on Twin builder and simulink coupled simulation. The simulation results show that the motor can reach the required rated power and rated speed. HNTSM control with disturbance observer is more robust than HNTSM and PID control, and can suppress the jitter caused by sliding mode control. However, compared with PID control, there is still some jitter.
Research on Fault Diagnosis of Steam Turbine Based on Bayesian Network
Authors: Zhang Dongliang , Wang Liufeng , Hong Qinqin , Zhang Kaiwen 
Published: February 2021

Abstract
In the fault diagnosis of steam turbine, multiple faults contain number of uncertainties due to the complexity of fault diagnosis knowledge and the strong correlation and coupling between different faults and massive prior knowledge is needed. In this paper, a fault diagnosis method of steam turbine based on Bayesian network is proposed. Various faults and symptoms are parameterized using Bayesian network nodes. Then rough set theory is used to simplify the complex causal relationship between faults and symptoms, and Noisy-Or model is used to simplify the conditional probability parameters. A diagnostic model of the steam turbine was developed using a simplified Bayesian network. The experiment results are shown to validate the practicality and effectiveness of the proposed designs.
Bearing roller smearing testing machine and its simulation analysis
Authors: Hu Junming , Wang Wen , Hao Xiaopeng 
Published: February 2021

Abstract
Rolling bearings are the most common rotating mechanical parts in actual work, with the rapid development of industrial technology, the performance requirements of rolling bearings in actual work are getting widely used, but under the actual working conditions, some large bearings with low speed and heavy load are easy to be smeared and lead to the extension of bearing life. In order to study the effect of early surface smearing on the fatigue life of rolling bearings, a self-designed bearing roller early smearing tester was designed, the test machine can simulate the movement process of roller in the bearing and make different degree of smearing on the surface of roller. According to the function, the smearing testing machine is divided into four parts: driving system, loading system, signal acquisition system and test system. The smearing testing machine can set the test conditions according to relevant theories to fabricate different degree of early smearing on the bearing roller surface, the transient dynamics simulation can simulate the smearing test of the testing machine, by comparing the results of the simulation analysis with the actual experimental circumstances, the stability and reliability of the testing machine can be proved, and it can also be testified that the test results of the testing machine are researchable.
Linear Superposition Compensation Strategy to Optimize Transient Response for Critical Conduction Mode Boost Converter
Authors: Lyu Dian , li Qidong , Zhang Desheng , Li Linkai , Min Run , Tong Qiaoling 
Published: February 2021

Abstract
For boost converter operating in the Critical Conduction Mode (CRM), linear compensation strategy is widely used to improve the control performance. However, conventional linear compensation is designed for limited input, since transfer functions for different input are often incompatible. In this paper, transient responses with respect to input/reference voltage and load variations are optimized simultaneously by a linear superposition compensation strategy. The objective closed-loop transfer functions for each kind of variations are investigated, which contribute to the overall compensation loop design. According to linear superposition principle, the compensation results are summed as reference current, based on which the switching on/off time is modulated. Although the summed results are convergence, separate compensation loop that includes integral terms can lead to divergence in calculation process. To eliminate the potential divergence, the overall compensation loop is re-designed so as to suit digital implementation. Experimental results show that the linear superposition compensation strategy achieves great transient performance to different kind of variations.
Development and application of substation intelligent inspection robot supporting deep learning accelerating
Authors: Su Lei , Yang Xingang , Cao Boyuan , Wang Yun , Li Xinjia , Lu Wenlian 
Published: February 2021

Abstract
Substation inspection robots usually have low computation capability to run deep learning models. In this paper, a substation intelligent inspection robot that can support real time deep learning models is developed. The Nvidia Jetson TX2 module is the accelerating hardware module of the robot, and TensorRT is the software framework for deep learning model inference accelerating. The robot can satisfy the computational requirement of deep learning based applications, and operate in very low energy consumption. Test results on a fault diagnostic task based on object detection and instance segmentation show that with deep learning accelerating, not only high detection accuracy is achieved, but also inference time is short enough for real time fault diagnostic application.
Low-error star pattern recognition based on point cloud matching algorithm*
Authors: Liang Luo Jing , Bo Yu Cheng , Min Luo 
Published: February 2021

Abstract
Aiming at the problem that the matching rate of traditional star map recognition methods is not high enough, this paper proposes a star map recognition method based on the ICP point cloud matching algorithm based on feature point extraction. Feature points are selected through the change of the local normal vector of the point cloud, and then used Common (ICP) algorithm to realize more accurate registration of point clouds. In order to further reduce the error rate of star map matching, an improved ICP algorithm based on feature points is used to accurately register the point cloud. Finally, the matching conditions of several star maps are obtained through MATLAB tool simulation and the matching rate error rate is calculated. Common ICP algorithm The minimum matching error of is 14.224, and the minimum matching error of the improved ICP algorithm based on feature points is 14.0715. Obviously, the star map matching error rate of the ICP algorithm based on feature points is lower, which also verifies the superiority of the improved ICP algorithm.
Research on the Deviation Analysis of Utilization Hours in Wind Power Plants Based on Regulatory Data Fusion and Feature Extraction & Processing Technologies
Authors: Xiao CHENG , Ping LI , Li-shi SUN , Bing WANG , Lin CONG , Yang YU 
Published: February 2021

Abstract
The continuous elevation of wind power consumption pressure has proposed higher requirements for the technical means, which comprehensively support the wind power consumption. The power generation level of a wind power plant is measured through the utilization hours at present, but the factors influencing the utilization hours are scarcely analyzed and quantified. In order to accurately figure out the reasons for the different utilization hours of wind power plants located in the same area, the total power prediction, power plant data, standalone data, resources, etc. were summarized, and the contribution degrees of five dimensions—resources, equipment availability, AGC command balance degree, AGC command following performance, and power generation capacity—to the utilization hours were analyzed and quantified through the data fusion and feature extraction, in an effort to find the main factors influencing the utilization hours in different power plants. The customized measures were proposed according to the conclusions in order to increase the utilization hours for the power plants. The derived computing method was applied to the wind power plant data acquired by a company in a province, followed by the difference analysis of the utilization hours. It was found that in Mulan sectional area, the reason for partially low utilization hours in Jifeng and Xunfeng Wind Power Plants was resource factor, that for Daheishan and Songshan Wind Power Plants lied in equipment availability, and that for Jufeng Wind Power Plant was possibly equipment following performance or equipment power generation capacity. In addition, the AGC command balance degrees in all target power plants were at low levels.
Optimal Number of Cluster Heads for Selection Cooperation in Clustering Wireless Sensor Networks
Authors: Li Min , Gu Huiping , Li Qing 
Published: February 2021

Abstract
In clustering wireless sensor networks, the number of cluster heads has great impact on energy consumption and transmission reliability of the system. With the increase of the number of transmission rounds, the area where the survival nodes are located gradually shrinks. In order to reduce the energy consumption of sensor nodes and improve the network lifetime, this paper proposes a dynamic cluster head (CH) number optimization scheme for selection cooperation. In order to reflect the area where the survival node is located, the network area as a variable is introduced into the energy consumption model. According to the behavioural characteristics of various nodes in the two-stage selection cooperation, the energy consumption model for each round is established. By solving the energy consumption model, the optimal number of cluster head in each round can be obtained. In this way, each round of transmission is carried out according to the minimum energy consumption. The simulation results show that the proposed scheme can reduce the energy consumption of the network, avoid energy waste caused by improper selection of cluster heads and extend the network lifetime.
Two approaches to car sequencing in the paint shop
Authors: Bysko Sara , Krystek Jolanta , Bysko Szymon 
Published: February 2021

Abstract
The problem of car sequencing has been considered in the literature many times, but very often with the assumption of many simplifications, which meant that the discussed issue was far from the problems occurring in reality. The article presents an attempt to capture the real problem of sequencing, in particular in paint shop, because from the point of view of economic indicators, painting process is today a complex, multistage, extremely energy consuming and cost intensive operation. The main goal is therefore to minimize the number of costly changeovers of painting guns, resulting from color changes and synchronize those with periodic cleanings, forced by technological requirements. For this purpose, a buffer located in the paint shop is applied. In the paper a game-theoretic framework is presented to analyze the considered problem. Two games: Buffer Slot Assignment Game and Buffer-OutShuttle are compared with algorithms based on priority rules. Based on the performed simulations the effectivity of presented algorithms is verified using several datasets.
Real-time motion detection in H.264 compressed domain for surveillance application
Authors: Kim Young Keun , Jeon Yeong Gyoo , Shin Seung Ho 
Published: February 2021

Abstract
Camera motion detection is a useful functionality in video surveillance and many other areas, but with its widespread application in many areas, the compaction power has increased and needs to be addressed how to reduce it. So far, there has been a lot of research on pixel domain, but it is hard to operate with real-time and consumes very much computing power. However, since the compressed domain of block-based codec contains useful information for video analysis, this allows accurate video analysis at a low cost. The proposed method shows how to perform a motion detection accurately while significantly reducing the amount of computation compared to the pixel domain by using the DCT coefficients, motion vectors and other features in the compressed domain of the H.264 video. The proposed algorithm is designed for motion detection in video surveillance servers in the form of a cloud. The results of the experiment were shown to support validity.
Divergent responses of permafrost peatlands to recent climate change
Authors: Sim Thomas G , Swindles Graeme T , Morris Paul J , Baird Andy J , Cooper Claire L , Gallego-Sala Angela V , Charman Dan J , Roland Thomas P , Borken Werner , Mullan Donal J , Aquino-López Marco A , Gałka Mariusz 
Published: February 2021

Abstract
Permafrost peatlands are found in high-latitude regions and store globally-important amounts of soil organic carbon. These regions are warming at over twice the global average rate, causing permafrost thaw, and exposing previously inert carbon to decomposition and emission to the atmosphere as greenhouse gases. However, it is unclear how peatland hydrological behaviour, vegetation structure and carbon balance, and the linkages between them, will respond to permafrost thaw in a warming climate. Here we show that permafrost peatlands follow divergent ecohydrological trajectories in response to recent climate change within the same rapidly warming region (northern Sweden). Whether a site becomes wetter or drier depends on local factors and the autogenic response of individual peatlands. We find that bryophyte-dominated vegetation demonstrates resistance, and in some cases resilience, to climatic and hydrological shifts. Drying at four sites is clearly associated with reduced carbon sequestration, while no clear relationship at wetting sites is observed. We highlight the complex dynamics of permafrost peatlands and warn against an overly-simple approach when considering their ecohydrological trajectories and role as C sinks under a warming climate.