bluuebunny/crossref_metadata_2025 huggingface dataset:
Short-term power load forecasting based on I-GWO-KELM algorithm
Authors: Chen Xiaoyu , Dong Xiangli , Shi Li
Published: February 2021

In this paper, I-GWO-KELM algorithm is used for short-term power load forecasting. Normalize the power data and meteorological data of the short-term power load, and use GWO to optimize the regularization coefficient of KELM and the RBF kernel parameters. To apply the model to short-term power load forecasting to obtain simulations for the next 24 hours and 168 hours curve. Experiments show that the improved model I3-GWO-KELM proposed in this paper has the best effect. The improvement of GWO in this paper is effective and feasible. In the application of short-term power load forecasting, the IGWO-KELM model is more accurate than the ELM and KELM models.
Power supply for on-line monitoring device of power lines based on double-half ring core
Authors: Xue Kaijin , Liu Jieyu , Kang Naidi , Zhao Yujia , Zhao Yan , Wang Donglai
Published: February 2021

In order to solve the problem of insufficient energy supply of the on-line monitoring device of the transmission line, a sensor energy acquisition scheme directly installed on the transmission line is proposed. In the current power supply, induction power supply is a kind of energy extraction method with better practical applicability. Since the monitoring devices and electronic equipment on the transmission line are often in a strong magnetic field and high voltage environment, designing a stable and reliable power supply is the guarantee for the stable operation of the monitoring devices and electronic equipment. This paper presents a structure of energy-absorbing iron core with two semi-circular magnetic cores, and studies the magnetic saturation problem in the inductive power supply and the design of the DC output circuit.
Multi-face recognition and dynamic tracking based on reinforcement learning algorithm
Authors: Li Yuxin , Xie Yinggang , Lu Xi
Published: February 2021

Aiming at the problem that the current low accuracy rate of face detection and target tracking, a reinforcement learning algorithm is proposed, which integrates face detection technology and target tracking technology organically, adopts the face detection algorithm based on Multi-Task Convolutional Neural Network (MTCNN) and target tracking algorithm based on Kalman filtering, so as to realize face detection, multiplayer face recognition and dynamic tracking of personnel movement. In this paper, the configuration environment is Anaconda, the operating platform is PyCharm, the video-based face detection and dynamic capture and rapid identification system has been designed and developed. The system consists of two modules: face detection module and target tracking module. The optimized face detection and dynamic capture algorithm improved the detection success rate by about 11.5%, the face detection success rate by about 15.2%, the dynamic capture success rate increased by about 12.0%, and the optimized system has a wider practicality.
Application of computer simulation in the study of infectious disease transmission mechanism
Authors: Zhao Chengzhen , Zhao Hui , liang Xun
Published: February 2021

Major infectious diseases have exerted a serious influence on people's lives. Through quantifying the effect of prevention and control, we can deeply understand the transmission mechanism of infectious diseases. This paper estimates the intensity of detection, the degree of isolation and other indicators, and analyzes the influence mechanism of these indicators on the scale of the epidemic, using computer programming to simulate the extended dynamics model of infectious diseases, based on the infectious disease in Hubei. The mortality rate and recovery rate, according to the data of Hubei, in the model are set as time variables, and the threshold is set at the same time. As a result, the improved analysis mechanism of the model will get more realistic simulation prediction results. It is concluded that isolation measures can effectively control the scale of the epidemic, but there is a phenomenon of marginal utility degression with excessively strict isolation measures by analysing and comparing. The increasing detection efforts will reduce the epidemic duration of the later stage, accelerating the arrival of the epidemic peak, although the peak will be slightly larger. All in all, we can comprehensively consider the testing cost and maintain a moderate detection intensity.
Chinese named entity recognition model based on BERT
Authors: Liu Hongshuai , Jun Ge , Zheng Yuanyuan
Published: February 2021

Nowadays, most deep learning models ignore Chinese habits and global information when processing Chinese tasks. To solve this problem, we constructed the BERT-BiLSTM-Attention-CRF model. In the model, we embeded the BERT pre-training language model that adopts the Whole Word Mask strategy, and added a document-level attention. Experimental results show that our method achieves good results in the MSRA corpus, and F1 reaches 95.00%.
The comprehensive quality evaluation of scutellariae radix based on HPLC fingerprint and antibacterial activity
Authors: Gao Yan , Yang Longfei , Ding Xiaoyan , Wang Bianli , Zu Longhui , Yu Yongmei , Li Lu , Zhao Bonian
Published: February 2021

Scutellaria Radix, a traditional Chinese medicine, studies on its main active ingredient are limited. In this study, the purpose was to investigate the quality difference of Scutellariae Radix from different origins based on chemical components and biological activities. The chromatographic fingerprints of Scutellariae Radix from 33 origins were established using HPLC, and the antibacterial activities were studied with the microdilution method. Moreover, orthogonal partial least-square regression, pearson correlational analysis and grey relational analysis methods were performed to explore the relationship between the compositions and bioactivities. In addition, and origin identification model was established to comprehensively evaluate the quality of Scutellariae Radix. The results showed that Scutellariae Radix had in-vitro antibacterial effect on Staphylococcus aureus, and the best were in Gansu, Shandong Province. Multivariate statistical analysis common showed that three components were positively correlated with antibacterial activity, which were respectively wogonin, baicalein and oroxylin. In conclusion, the quality of Scutellariae Radix varies greatly from different origins, and the better was in Gansu and Shandong Province. This work successfully provides a general model that combined the chromatographic fingerprint and bioactivity assay to study the spectrum–effect relationships, which could be used to discover the primary active ingredients in traditional Chinese medicines.
Constant elasticity of substitution function based RANSAC for image stitching
Authors: Zhuang Shengbin , Cao Lin , Guo Yanan
Published: February 2021

Feature matching is very important in image stitching. RANSAC algorithm is a representative algorithm for feature matching. However, RANSAC still has many shortcomings such as a large number of iterations, a large computational complexity and cannot completely eliminate mismatches. To address above problem, in this paper, we propose a novel method termed constant elasticity of substitution function based RANSAC (CES-RANSAC) for image stitching. Specifically, CES-RANSAC improves the RANSAC algorithm by constructing a utility function, optimizing the boundary of the utility function, calculating Cobb-Douglas coefficients. It also introduces Lindahl equilibrium to derive the return value t to help eliminate mismatches. Experiments show that compared with the traditional RANSAC algorithm, CES-RANSAC has improved matching accuracy and increased computational efficiency, which further improves the efficiency of the image matching algorithm.
Underwater image enhancement algorithm based on dark channel prior and underwater imaging model
Authors: Sun Zhengping , Li Fubing , Yang Yuying
Published: February 2021

The main reason for the degradation of the underwater image is the light absorption and scattering. The images are captured in the underwater environment often have some problems such as loss of image information, low contrast, and color distortion. In order to solve the above problems, this paper proposes an image enhancement method for the underwater environment. With the help of the underwater imaging model and dark channel prior theory, a new idea of adding transmission correction and color compensation to G and B color channels is proposed. Experimental results show that, compared with the traditional methods, this method has a better effect on the underwater image with less color deviation.
Study on the application of BP neural network in air quality prediction based on adaptive chaos fruit fly optimization algorithm
Authors: Xia Xin
Published: February 2021

BP neural network is optimized by improved drosophila algorithm, and a prediction model for air quality in Nanchang is established based on the air quality data and meteorological data of Nanchang city in recent three years. The experimental results show that the improved algorithm has improved performance compared with the BP algorithm, and has improved accuracy 4%, with a small difference in time consumption. The performance of the indirect prediction method is slightly better than that of the direct prediction method
Research on path planning of cleaning robot based on an improved ant colony algorithm
Authors: Wang Zhidong , Wu Changhong , Xu Jing , Ling Hongjie
Published: February 2021

The conventional ant colony algorithm is easy to fall into the local optimal in some complex environments, and the blindness in the initial stage of search leads to long searching time and slow convergence. In order to solve these problems, this paper proposes an improved ant colony algorithm and applies it to the path planning of cleaning robot. The algorithm model of the environmental map is established according to the grid method. And it built the obstacle matrix for the expansion and treatment of obstacles, so that the robot can avoid collision with obstacles as much as possible in the process of movement. The directional factor is introduced in the new heuristic function, and we can reduce the value of the inflection point of paths, enhance the algorithm precision, and avoid falling into the local optimal. The volatile factor of pheromones with an adaptive adjustment and the improved updating rule of pheromones can not only solve the problem that the algorithm falls into local optimum, but also accelerate the running efficiency of the algorithm in the later stage. Simulation results show that the algorithm has the better global searching ability, the convergence speed is obviously accelerated, and an optimal path can be planned in the complex environment.
Research on obstacle avoidance technology of fixed wing formation based on improved artificial potential field method with stereo vision
Authors: Liu Yu , Wang Xinhua
Published: February 2021

To solve the problem that distributed fixed wing formation cannot know all the other aircraft states through the ground station and may collide, the improved artificial potential field method based on binocular stereo vision was proposed. This method makes the fixed wing aircraft not need to obtain the position information of other fixed wing aircraft from the ground station, but only need the binocular stereo vision module to obtain the relative position and relative speed information of other fixed wing aircraft. These two parameters are used to improve the traditional artificial potential field method to meet the requirements of distributed fixed wing formation flight. The experimental results show that the improved artificial potential field method improves the safety and reliability of distributed fixed wing formation flying.
An evolutionary band-limited Gaussian noise jamming algorithm for LMS-based GPS
Authors: Wu Tao , Zou Qiubai , Wu Jixiang , Li Wenqiang , Jia Zhenze
Published: February 2021

In this paper, evolutionary algorithm is used to optimize the flicker function of band-limited Gaussian noise interference, which disturbs the convergence of adaptive algorithm based on LMS in GPS receiver, so that the average null depth of GPS receiver under equal power is lower, and better jamming effect is achieved. The simulation results show that the jamming algorithm in this paper has better jamming effect than the band-limited Gaussian noise jamming in different jamming quantity.
A robust watermarking hybrid algorithm for color image
Authors: Song Mengli , Wang Huijun , Wu Jianbin , Yan Xinrong , Yuan Linfeng , Tu Yameng
Published: February 2021

In order to improve the anti-attack performance of the watermark to meet the requirements of copyright protection and content forensics. This paper proposes a digital watermarking hybrid algorithm based on color images. The specific process is to adopt the idea of multi-algorithm layered embedding, choose the algorithm based on discrete cosine transform (DCT) algorithm, discrete wavelet transform_singular value decomposition (DWT_SVD) algorithm, and hologram algorithm, these three algorithms with robust complementary functions, then embed the same watermark image into the color image R, G and B layers to complete the watermark embedding. Compared with the single-algorithm embedded watermark, the hybrid algorithm can achieve blind extraction, at the same time, the algorithm has better robustness and can resist more types and higher intensity attacks. In the process of digital image transmission, the integrity of the watermark information of the carried picture can be guaranteed to achieve copyright protection, content forensics and other purposes.
Improved step tracking algorithm based on gradient method
Authors: Bei Haohan , Liu Yubo , Li Wenhao , Huang Ying
Published: February 2021

The basic principle of the satcom on the move antenna is to detect the error angle between the antenna beam pointing and the satellite direction according to the received satellite signal, and convert it into the corresponding error electrical signal. The controller uses the error electrical signal to control the antenna to make the antenna move in the direction where the error signal decreases. The tracking accuracy of traditional step tracking is not high, and the response speed is very slow, and the signal amplitude fluctuation affects the tracking accuracy. Since the gain graph of the antenna can be regarded as a non-linear stepped objective function, an improved step tracking algorithm based on the gradient method is proposed, which combines the step tracking with the optimization algorithm to achieve precise tracking. The algorithm optimizes the antenna gain pattern as the objective function to find the azimuth and elevation coordinates corresponding to the maximum point of the antenna gain function. The gain function maximization is transformed into the objective function minimization problem, and the minimum value of the objective function is found through the optimization algorithm, which corresponds to the direction of the antenna when the satellite is accurately aligned. The gradient method is selected for optimization, which is stable as a whole and simple iterative process. Theoretical analysis and simulation results show that the algorithm can obtain higher tracking accuracy while maintaining a lower program complexity.
Improved recursive DV-Hop localization algorithm for average hop distance optimization
Authors: Ren Keqiang , Wang Panpan
Published: February 2021

Aiming at the problem of DV-HOP algorithm with error and energy exhaustion, the average hop distance is used for optimization, and an improved recursion method is used to solve it. The algorithm first squares the distance of anchor nodes, proposes a forgetting factor to optimize the average hop distance between anchor nodes, and secondly uses recursive operations to replace anchor nodes with insufficient energy, so that the localization process of unknown nodes can continue. Experimental results show that compared with the DV-Hop algorithm and the algorithms in related literature, the improved algorithm can reduce the localization error to a certain extent and improve the localization accuracy of unknown nodes.
A hybrid Hausdorff distance track correlation algorithm based on time sliding window
Authors: Li Yinlong , Zhang Tianshu
Published: February 2021

In multi-sensor target tracking, track correlation is the key to the unification of global situation. Hausdorff distance has been applied to power fault elimination, point cloud data, medical measurement, image segmentation, vehicle trajectory recognition and other directions. To solve the problem of track correlation, a hybrid Hausdorff distance track correlation algorithm based on time sliding window is proposed. The hybrid Hausdorff distance based on position, speed and azimuth is defined, and the time sliding window is added on this basis. Simulation results show that the proposed algorithm can maintain a high correct correlation rate under the conditions of target maneuver, time asynchronism, and inconsistent radar sampling frequency, the algorithm is superior to traditional track correlation algorithm.
The network architecture optimization based on the server load balancing technology
Authors: Huo Ruicai , Liu Songqiu , He Shiwei
Published: February 2021

The paper takes the authentication gateway system for internal office network as the research object, for the performance bottleneck and single point of failure problem of the single authentication gateway deployed in the existing primary and standby modes, chooses an authentication gateway integration method based on CA certificate. The practical results show that: through implementing the authentication gateway cluster design and introducing load balancing mechanism, this method solves the performance, stability and single point of failure of the authentication gateway, and improves the resource utilization of the authentication gateway device. This method introduced in this paper can be used for reference for the network architecture optimization based on the server load balancing technology.
Research on security situation assessment algorithm under virtual technology of cloud platform
Authors: Liu Jie , Fan Weiping
Published: February 2021

With the increasing attacks and destructions against cloud platforms, the security guarantee mechanism of cloud platforms has also changed from traditional passive protectionto active defense. Situation assessment is a method that can actively analyze and evaluate thecurrent security risk status of the cloud platform, and is a key part of the whole process of situation awareness. This paper aims at a large number of virtual machines deployed in cloud platforms, on the basis of analysis and extraction of virtual layer security situation assessment elements, an improved adaptive genetic simulated annealing algorithm OAGSAA is proposed, and applied to BP neural network, which can effectively analyze and evaluate the security status of the virtual layer. Simulation experiment results show that the method has higher prediction accuracy and convergence speed, and can avoid falling into the local minimum.
Convolutional neural network based evil twin attack detection in WiFi networks
Authors: Tian Yinghua , Wang Sheng , Zhang Long
Published: February 2021

Evil Twin Attack (ETA) refers to attackers use a device to impersonate a legitimate hotspot. To address the problem of ETAs in the WiFi network, a Convolutional Neural Network (CNN) attack detection method is proposed. The method uses the preamble of the WiFi signal as the feature and uses it to train a CNN based classification model. Next, it uses the trained model to detect the potential ETA device by the inconsistent of the identity it claims and the signal feature. Experiments based on the commercial hardware demonstrate that the proposed method can effectively detect the Evil Twin Attack.
Research on tor-based anonymous DDoS attack
Authors: Wang Rui , Yang Zhiye , Li Kun , Chen Chen , Chen Yanru
Published: February 2021

Based on Tor, an anonymous DDoS attack is proposed, and the attacker of this attack is very difficult to trace due to the strong anonymity of Tor. Through conducting experiments in different network environment and making analyzation of security, the experiments results demonstrate the effectiveness of this attack, and the strategy to defense the attack is also discussed.
Polarimetric SAR image classification using 3D generative adversarial network
Authors: Liu Lu , Feng Guobao
Published: February 2021

In this paper, a new architecture of three-dimensional deep convolutional generative adversarial network(3D-DCGAN) is specially defined to solve the unstable training problem of GAN and make full use of the information involved in polarimetric data. Firstly, a data cube with nine components of polarimetric coherency matrix are directly used as the input features of DCGAN. After that, a 3D convolutional model is designed as the components of generator and discriminator to construct the 3D-DCGAN, which considers the effective feature extraction capability of 3D convolutional neural network(CNN). Finally parameters of the network are fine-tuned to realize the polarimetric SAR image classification. The experiments results show the feasibility and efficiency of the proposed method.
Pricing strategy of closed loop supply chain considering different CSR investment modes
Authors: Yan Yingluo , Yao Fengmin
Published: February 2021

More and more companies are beginning to realize that incorporating corporate social responsibility (CSR) and sustainable development into supply chain strategies and operations can bring them more competitive advantages. In the case that the manufacturer or retailer performs CSR through profit donation, the pricing decision-making problem of closed-loop supply chain (CLSC) with dominant retailer under different CSR investment modes is studied. The decision-making models of CLSC under the manufacturer’s and retailer’s CSR investment mode are constructed respectively. The conditions for enterprises to fulfil CSR through profit donation and the influence of different CSR investment modes on the pricing of new products and recycling of waste products are discussed. The research shows that no matter what kind of CSR investment mode, only when the consumers are more sensitive to the CSR investment of enterprises, the manufacturer and retailer will fulfil the CSR through profit donation. The CSR investment mode of the manufacturer is more beneficial to consumers, environment, CLSC members and whole system. No matter whether the dominant retailer carries out CSR investment or not, she always obtains more channel profits than the manufacturer.
The impact of membership on network performance of efficient, innovative and flexible manufacturing enterprises
Authors: Wang Xueyuan , Li Shan , Huang Jiasai
Published: February 2021

Making full use of network member resources to improve performance has become a strategic choice for manufacturing enterprises. Based on the analysis of member relationship dimensions and manufacture enterprise network types, the influences among member relationship dimensions and their influences on network performance are discussed. The weighting indexes and standards are designed, and structural equation method is used to test the hypothesis. The following results can be obtained: member relationship dimension self-accelerating effects commonly exit, and “the communication’s influence on trust” has become the key for member relation optimization. Trust is important for all networks cooperation. The contract, trust and communication individually become the management key or efficiency, innovation and flexibility manufacturing network.
Review of the evaluation of the key nodes in quality system management based on the uncertainty quantification method
Authors: Wang Jun , Ye Qiang , Zhang Chi , Zhang Tong , Li Shicheng
Published: February 2021

To explore the relatively weak link of the quality management system, the evaluation of the key nodes in quality system management is the crucial method for the enterprises and organizations. However, due to inadequate understanding of the goals and principles, the evaluation results are difficult to meet the requirements. Therefore, in this paper we normalize the evaluation of the quality management system and discuss the methods of uncertainty quantification as the supplementary for evaluation which brings the more accurate results for improvement suggestions.
Research on service management of manufacturing enterprises based on quality housing
Authors: Wang Xueyuan , He Meixin , Chen Mingxing
Published: February 2021

Based on house of quality concept, the relation between servitization strategy and strategic elements were confirmed through grey relational analysis method. Accordingly, the specific elements characteristics of manufacturing enterprise management core - talents & team and relationship, knowledge resources and flowing, information infrastructure and treatment methods, and organization structure and management were illustrated in three servitization stages - product servitization enlarging, servitization capability continuously improving and servitization integration and innovation. According to elements characteristics, the strategic targets for different servitization stages were brought forward, and four strategic elements specific managing methods were further offered for different servitization stages. The research can offer decision references for manufacturing enterprise to confirm element character and servitization stage, and give effective support to confirm management key points and methods of servitization in manufacturing enterprises at different stages.
Research on intelligent algorithms for solving portfolio problems
Authors: Wang Hongwei , Huo Lin , Feng Jinhao
Published: February 2021

Investment is a behavior of coexistence of the benefits and risks. In the context of rich asset types, an effective investment portfolio can help investors obtain stable returns and diversify risks. In reality, portfolio problems often contain multiple constraints and objectives that cannot be effectively solved by traditional mathematical optimization methods. This paper proposes a hybrid beetle antennae search sine cosine algorithm based on non-linear inertia weight. Experiments are performed on five portfolio problem datasets in the real stock market. The results show that the proposed algorithm is effective and has some performance advantages in solving portfolio problems.
Comparative study on dynamic mathematical modeling and simulation of coastal sandcastle foundations
Authors: Cao Jiarui , Zhao Wenyue
Published: February 2021

How to make a sandcastle with good stability is an interesting modeling problem, the core of which is how to design the shape of its foundation and select appropriate material so that it can fully resist wave erosion. First, we design the Foundation Shape Optimization (FSO) Model to obtain the geometric shape that last longest. By pre-screening, we preliminarily select the circular truncated cone. Then we analyse the impact force of the sea waves, list the constraint conditions and calculate the optimal parameters for it. Second, the water-to-sand mixture is identified by microcosmic Normalized Extremum Model. Before getting results, the Ideal Sand Particles Plane (ISPP) Model helps us figure out the equivalent relationship among three functions. Finally, we get the objective function through normalization and work out the best proportion (13.14%) with the optimal sub-humid angle through Genetic Algorithm (GA).
Steel logistics park layout based on market basket analysis and accessibility
Authors: Yang Qianqian , Qin Lu
Published: February 2021

In this study, we used market basket analysis and land accessibility for the layout of MG Steel Logistics Park. Due to the unreasonable cargo space layout, the outbound trucks in the MG Steel Logistics Park detour and transfer, which caused congestion. Using market basket analysis, this research took outbound trucks as the research object to measure the degree of correlation between cargo locations. Then, we measured the convenience of cargo locations by the accessibility and matched it with the steel outbound frequency. We established a model and got the layout allocation plan with the maximum degree of relevance and the minimum difference in cargo-location matching as the target. In the solution algorithm, we use roulette method and the elite retention strategy to improve the genetic algorithm. Finally, we compared the results before and after optimization. We found that the number of truck transfers was reduced by 33%, and the truck staying time was reduced by 21%.
Technical methods for accelerating digital transformation of Chinese enterprises
Authors: Qiang Xinjian
Published: February 2021

Chinese enterprises are facing the opportunity of digital transformation, and all enterprises are advancing in exploration. This paper introduces the trend and challenge of digital transformation of Chinese enterprises. This paper expounds the digital transformation strategy of enterprises as the center. This paper discusses the four development processes of enterprise digital transformation, including digital empowerment, process optimization, digital transformation and digital reengineering. This paper puts forward the methods that Chinese enterprises should adopt in the process of transformation. First of all, the digital transformation of enterprises should be scientifically planned. Then select pilot projects in enterprises and try them out first. After that, the trial effect was evaluated. After summarizing and improving, copy and enlarge the scope. Finally, optimize the operation of the enterprise, and constantly adjust.
Analysis and prospect of China's contemporary anti-terrorism intelligence perception
Authors: Zheng Huijie , Chang Zhenxing , Liu Hezi , Zhu Yu
Published: February 2021

New types of weapons of mass destruction are still being developed continuously at a time when traditional violent and terrorist activities such as explosions, hijackings, and hacking are increasingly rampant. In order to prevent major losses caused by terrorist activities and bring chaos to the order of social life, the importance of obtaining terrorist intelligence is increasing. This paper analyzes China’s deficiencies in intelligence perception and monitoring through collation, and summarizes the progress in the corresponding areas, and puts forward some of its own prospects for the future development of intelligence perception in China.
Research on transformation and upgrading of Liuzhou fitness industry under the “Internet +” service platform
Authors: Xie Yi , Xu Shijun , Yang Yanping
Published: February 2021

Under the current situation of prevention and control Corona Virus Disease 2019(COVID-19), the development of fitness industry in Liuzhou is analyzed, and the survival environment, management, coaches' quality and reasons for the closure of the club are analyzed. The results show that Liuzhou fitness market is greatly affected by the economic and social environment, and the seemingly prosperous fitness market has met with bottlenecks, and its operation is in danger. Taking “Internet+” as a new power engine, we should build a service platform of Liuzhou fitness alliance, strengthen the supply side reform such as management and coach quality, increase effective supply of high quality, and guide clubs to play their own advantages to develop differentiated competition, which is an effective way to promote the transformation and upgrading of traditional fitness industry.
Analysis of the impact of construction and operation of pumped-storage power stations on grid companies and the formulation of electricity prices
Authors: Gao Ming , Bian Jiayu , Tian Shoutao , Tan Jing , Chen Lufeng
Published: February 2021

The pumped storage power station is flexible to start, can realize effective storage of electric energy, and has superior peak and frequency modulation effects, which is beneficial to provide comprehensive benefits of the power system. But at present, the construction of pumped-storage power plants has obviously exceeded the speed of policy and market development, resulting in problems in pumped-storage power station operation and cost reduction. Aiming at this problem, this paper further expounds the influence of the construction and operation of pumped storage power station on the electricity price of power grid companies. The revenue of pumped storage power station mainly comes from the auxiliary service market. In China, the peak regulation effect of pumped storage power station is significant and the revenue is considerable. Therefore, this paper studies the formulation of time-of-use price and subsection price of pumped storage power station.
‘Nothing beats the doctor’s face to impart trust in their judgement’: the role of telehealth in cancer care
Authors: Slavova-Azmanova Neli S. , Millar Lesley , Ives Angela , Saunders Christobel M.
Published: February 2021

Despite Western Australia having low COVID-19 case numbers and limited community transmission, cancer service delivery changes were introduced early in the pandemic, including adoption of telehealth. Patients attending telehealth appointments during COVID-19 between 11 May 2020 and 7 August 2020 reported that telehealth lessened their concerns and met their needs to varying degrees. Despite this, 56% of patients still preferred in-person appointments.
Identification and expression characterisation of SbERECTA family genes in Sorghum bicolor
Authors: Zheng Jia Cheng , Yu Jie , Liu Ting , Wang Xin , Zhan Qiu Wen , Li Jie Qin , Xu Zhao Shi , Ma You Zhi
Published: February 2021

ERECTAs are receptor-like kinases that regulate plant biomass and stress resistance. In this study, the wheat (Triticum aestivum) TaERECTA gene was used as a probe to identify the SbERECTA family genes (SbERs) in the sorghum (Sorghum bicolor) genome, analyse their subcellular localisation and characterise their expression. Results showed that the two SbER members, SbER10 with three copies (SbER10_X1, SbER10_X2, and SbER10_X3) and SbER4 with two copies (SbER4_X1 and SbER4_X2), were found on chromosomes 10 and 4 of sorghum, respectively. SbER10 had the highest expression level in the pedicel tissue and showed a remarkable response under treatment with abscisic acid, brassinolide, gibberellin and indole-3-acetic acid. SbER10_X1, functioning on the cell membrane and chloroplast, exhibited abundant transcript in only a few sorghum varieties that are grown in mountainous areas and receive strong light, heat, and water supply. Expression of SbER10_X1 was significantly and positively correlated with plant biomass of 32 sorghum germplasm resources. These results indicate that SbER10 genes have an important regulatory role in sorghum growth, and increasing SbER10 transcription level offers a potential strategic target for breeding or biotechnological approaches to enhance sorghum biomass and environmental adaptability.
Language choice among Chinese-Indonesian children in Palembang City
Authors: Setiawan Budi , Wijana I Dewa Putu , Sajarwa
Published: February 2021

This study examines the language choices among four- to six-year old Chinese-Indonesian children in various social domains to identify patterns of choice and analyze sociocultural factors that significantly affect their language choices. The results show that Chinese-Indonesian children’s language choice is highly patterned based on the type of social domains and interlocutors. Their choices are influenced by three major factors: (1) language attitude including parental attitude and the attitude of the indigenous population; (2) language habit formed at home; (3) social domain and context of communication.
Multimodal strategies for balancing formality and informality
Authors: Kaneyasu Michiko
Published: February 2021

This paper investigates multimodal strategies for balancing formality and informality online. The analysis of 300 comment-reply interactions on a recipe sharing site in Japan demonstrates that writers tend to avoid being overly formal or informal in their messages. For example, most comments and replies are written in polite forms but many incorporate some plain forms and colloquial expressions. Linguistic features, however, are not the only way through which the writers manage an appropriate level of formality and informality. The study examines the role of kaomoji or Japanese-style emoticons for socio-relational work online. Some kaomoji function locally as cues for interpreting the sentences featuring kaomoji. All kaomoji, including those with local functions, work to enhance the social presence of the writers on the screen via pictographic gaze and gestures, which increases the perception of intimate rapport. The findings underscore the importance of a multimodal perspective in examining how people handle social relationships online.
Prescriptively or descriptively speaking?
Authors: Faulkner Tris
Published: February 2021

It is generally put forth that Spanish has the subjunctive as the required mood in the complements of emotive-factives (alegrarse de que‘to be happy that’), desire verbs (querer‘to want’), verbs of uncertainty (dudar‘to doubt’), modals (ser posible que‘to be possible that’), causatives (hacer que‘to make that’), and directives (recomendar que‘to recommend that’) (e.g.,Real Academia Española 2011). However, in spite of these traditional rules, it has been observed that some of these environments allow for the indicative (Blake 1981;Crespo del Río 2014;Deshors and Waltermire 2019;Gallego and Alonso-Marks 2014;García and Terrell 1977;Gregory and Lunn 2012;Kowal 2007;Lipski 1978;Silva-Corvalán 1994; Waltermire 2019). The current study explored one such environment; emotive-factive clauses. Results showed that the presuppositions that speakers hold regarding the knowledge that their addressees possess influence the mood that they select. This, thus, demonstrates the important role that pragmatics plays in the occurrence of mood variation.
Initial data and eccentricity reduction toolkit for binary black hole numerical relativity waveforms
Authors: Habib Sarah , Ramos-Buades Antoni , Huerta E A , Husa Sascha , Haas Roland , Etienne Zachariah
Published: February 2021

The production of numerical relativity waveforms that describe quasi-circular binary black hole mergers requires high-quality initial data, and an algorithm to iteratively reduce residual eccentricity. To date, these tools remain closed source, or in commercial software that prevents their use in high performance computing platforms. To address these limitations, and to ensure that the broader numerical relativity community has access to these tools, herein we provide all the required elements to produce high-quality numerical relativity simulations in supercomputer platforms, namely: open source parameter files to numerically simulate spinning black hole binaries with asymmetric mass-ratios; open source Python tools to produce high-quality initial data for numerical relativity simulations of spinning black hole binaries on quasi-circular orbits; and open source Python tools for eccentricity reduction, both as stand-alone software and also deployed in the Einstein Toolkit’s software infrastructure. This open source toolkit fills in a void in the literature at a time when numerical relativity has an ever increasing role in the study and interpretation of gravitational wave sources. As part of our community building efforts, and to streamline and accelerate the use of these resources, we provide tutorials that describe, step by step, how to obtain and use these open source numerical relativity tools.
Dark–dark soliton breathing patterns in multi-component Bose–Einstein condensates
Authors: Wang Wenlong , Zhao Li-Chen , Charalampidis Efstathios G , Kevrekidis Panayotis G
Published: February 2021

In this work, we explore systematically various SO(2)-rotation-induced multiple dark–dark (DD) soliton breathing patterns obtained from stationary and spectrally stable multiple dark–bright (DB) and DD waveforms in trapped one-dimensional, two-component atomic Bose–Einstein condensates. The stationary states stemming from the associated linear limits (as the eigenfunctions of the quantum harmonic oscillator problem) are parametrically continued to the nonlinear regimes by varying the respective chemical potentials, i.e. from the low-density linear limits to the high-density Thomas–Fermi (TF) regimes. We perform a Bogolyubov–de Gennes spectral stability analysis to identify stable parametric regimes of these states, finding a wide range of stability intervals in the TF regimes for all of the states considered herein. Upon applying an SO(2)-rotation to stable steady states, one-, two-, three-, four-, and many DD soliton breathing patterns are observed in the numerical simulations. Furthermore, analytic solutions up to three DB solitons in the homogeneous setting, and three-component systems are also investigated.
Multiscale modelling of magnetostatic effects on magnetic nanoparticles with application to hyperthermia
Authors: Behbahani Razyeh , Plumer Martin L , Saika-Voivod Ivan
Published: February 2021

We extend a renormalization group-based (RG) coarse-graining method for micromagnetic simulations to include properly scaled magnetostatic interactions. We apply the method in simulations of dynamic hysteresis loops at clinically relevant sweep rates and at 310 K of iron oxide nanoparticles (NPs) of the kind that have been used in preclinical studies of magnetic hyperthermia. The coarse-graining method, along with a time scaling involving sweep rate and Gilbert damping parameter, allow us to span length scales from the unit cell to NPs approximately 50 nm in diameter with reasonable simulation times. For both NPs and the nanorods composing them, we report effective uniaxial anisotropy strengths and saturation magnetizations, which differ from those of the bulk materials magnetite and maghemite of which they are made, on account of the combined non-trivial effects of temperature, inter-rod exchange, magnetostatic interactions and the degree of orientational order within the nanorod composites. The effective parameters allow treating the NPs as single macrospins, and we find for the test case of calculating loops for two aligned NPs that using the dipole approximation is sufficient for distances beyond 1.5 times the NP diameter. We also present a study on relating integration time step to micromagnetic cell size, finding that the optimal time step size scales approximately linearly with cell volume.
Interference effect on the Andreev reflections induced by Majorana bound states
Authors: Gong Tong , Dai Xue-Feng , Zhang Lian-Lian , Jiang Cui , Gong Wei-Jiang
Published: February 2021

We investigate the effect of quantum interference on the Andreev reflections (ARs) induced by Majorana bound states (MBSs), by considering their additional coupling via a quantum-dot molecule. It is found that due to the direct and indirect couplings of MBSs, a quantum ring is constructed in this system. Consequently, the interference effect makes important contribution to the ARs, especially in the presence of the local magnetic flux. All the results are manifested as the tight dependence of the differential conductance and Fano factors on the magnetic flux phase factor, dot-MBS couplings, and the dot level, respectively. Moreover, at the zero-bias limit, the magnitudes of the Fano factors and their relation can be efficiently altered by the interference properties. We believe that quantum interference is important for manipulating the Andreev reflection behaviors of the MBSs.
The 2019–2023 Strategic Plan of the Spanish Society of Radiological Protection (SEPR)
Authors: Carmena Pío , Ginjaume Mercè , Herranz Margarita , Macías María Teresa , Torres Ricardo
Published: February 2021

The Spanish Society for Radiological Protection (SEPR) is a scientific and technical organization that aims to bring together all radioprotection professionals from all the sectors of activity where ionizing and non-ionizing radiation is produced. The development of the SEPR’s Strategic Plan every 5 years is the cornerstone of all the different activities that the Society carries out. This document establishes the SEPR goals and objectives for that period, as well as the activities planned to achieve them. It is a living and open document that draws on past experiences while looking to the future. The Strategic Plan 2019–2023, approved on June 2019, is the Third Strategic Plan of the SEPR. In its preparation, account has been taken of the experience obtained in the application of the two previous Strategic Plans, as well as of the new demands of the general public and of professionals in the area of radiological protection that have become apparent during the previous period. This paper describes the development of the current Strategic Plan, as well as the Plan itself, and briefly analyzes its implementation in the Conclusion.
Highly selective acetone detector based on a separation channel and semiconductor gas sensor
Authors: Du Haiying , Sun Ruizhi , Su Jing , Sun Yanhui , Xia Kaili , Cong Liying , Cui Hemin
Published: February 2021

Acetone is a biomarker of diabetics. The exhaled acetone concentration of diabetics is higher than that of a healthy person. Semiconductor gas sensors provide an accurate non-invasive detection method for low-concentration breath acetone of diabetics, but the their selectivity presents a drawback. In order to detect the concentration of exhaled acetone accurately from exhaled breath, an acetone detector based on a separation channel and semiconductor gas sensors is presented in this paper. Carbon dioxide, acetone, and ethanol were simulated and separated by a gas chromatography (GC) column in the separation channel. The separated time of carbon dioxide, exhaled acetone, and ethanol are 25 s, 236 s, and 574 s at room temperature, respectively. Carbon dioxide, acetone, and ethanol flow into three gas detection channels with the control of a time-sharing conversion switch. Then, carbon dioxide, acetone, and ethanol can be detected accurately by the semiconductor gas sensors. Exhaled acetone can be measured as low as 1 ppm within 5 min without any interference. A highly selective acetone detector based on GC and semiconductor technology has potential in monitoring and detecting diabetes as well as safe driving in a non-invasive way.
OMEGA—open-source emission tomography software
Authors: Wettenhovi V-V , Vauhkonen M , Kolehmainen V
Published: February 2021

In this paper we present OMEGA, an open-source software, for efficient and fast image reconstruction in positron emission tomography (PET). OMEGA uses the scripting language of MATLAB and GNU Octave allowing reconstruction of PET data with a MATLAB or GNU Octave interface. The goal of OMEGA is to allow easy and fast reconstruction of any PET data, and to provide a computationally efficient, easy-access platform for development of new PET algorithms with built-in forward and backward projection operations available to the user as a MATLAB/Octave class. OMEGA also includes direct support for GATE simulated data, facilitating easy evaluation of the new algorithms using Monte Carlo simulated PET data. OMEGA supports parallel computing by utilizing OpenMP for CPU implementations and OpenCL for GPU allowing any hardware to be used. OMEGA includes built-in function for the computation of normalization correction and allows several other corrections to be applied such as attenuation, randoms or scatter. OMEGA includes several different maximum-likelihood and maximum a posteriori (MAP) algorithms with several different priors. The user can also input their own priors to the built-in MAP functions. The image reconstruction in OMEGA can be computed either by using an explicitly computed system matrix or with a matrix-free formalism, where the latter can be accelerated with OpenCL. We provide an overview on the software and present some examples utilizing the different features of the software.