bluuebunny/crossref_metadata_2025 huggingface dataset:
Health assessment for railway switch systems
Authors: Zhang Yao , Xu Tianhua , Xiao Tian , Xing Hao
Published: February 2021

Because of the heavy workload and high failure rate of railway switch system (RSS), the traditional scheduled maintenance can not meet the actual operation needs of the railway. Therefore condition-based maintenance (CBM) and prognostic and health management(PHM), which have been mature in other fields should be introduced into RSS. Health assessment is of a great concern among all the technologies. This paper presents a novel method which can be utilized on the health status evaluation of RSS. First of all, RSS is briefly introduced and the connotation of PHM for RSS is analyzed. Secondly, health indicators (HIs) are extracted by different time domain features, and the best indicators are selected to establish the degradation model. By using clustering algorithm, the change point of state is detected which can be used as an instruction of advance maintenance. Finally, a ZYJ7 RSS is selected to test and verify the proposed method. Result indicates that the algorithm can be effectively applied to health assessment of RSS.
Improved genetic algorithm for 3D printing multi-objective optimization task scheduling
Authors: Zhao Haobin , Yu Hongbin
Published: February 2021

For the 3D printing multi-objective optimization task scheduling problem, the problem model is established from the three aspects of related problem definition, constraint conditions, and objective function, which lays the foundation for subsequent research and solution.
An explicit construction of quantum codes from one-generator generalized quasi-cyclic codes
Authors: Yao Yu , Ma Yuena , Li Husheng , Lv Jingjie
Published: February 2021

In this paper, we take advantage of a class of one-generator generalized quasi-cyclic (GQC) codes of index 2 to construct quantum error-correcting codes. By studying the form of Hermitian dual codes and their algebraic structure, we propose a sufficient condition for self-orthogonality of GQC codes with Hermitian inner product. By comparison, the quantum codes we constructed have better parameters than known codes.
Demodulation algorithm for optical fiber fabry-perot interference sensor
Authors: Wang Wenhua , Wu Weina , Xiong Zhengye , Shi Wenqing , Luo Yuanzheng , Tian Xiuyun , Chen Zhishan
Published: February 2021

In view of resolution of optical fiber Fabry-Perot (FP) interference sensor, this paper analyses and researches high resolution demodulation algorithms including fast Fourier transform demodulation algorithm, cross-correlation calculation demodulation algorithm, vernier demodulation algorithm. Through continuous improvement, the vernier demodulation algorithm has achieved a resolution of 0.084nm. And it has a resolution of 2.3Pa when the vernier demodulation algorithm was applied to osmotic pressure measurement.
Cluster-based routing protocols for wireless sensor networks
Authors: Zhang Huanan
Published: February 2021

Routing technology at the network layer is pivotal in the architecture of wireless sensor networks. As an active branch of routing technology, cluster-based routing protocols excel in network topology management, energy minimization, data aggregation and so on. In this paper, cluster-based routing mechanisms for wireless sensor networks are analyzed. Cluster head selection, cluster formation and data transmission are three key techniques in cluster-based routing protocols. As viewed from the three techniques, recent representative cluster-based routing protocols are presented, and their characteristics and application areas are compared. Finally, the future research issues in this area are pointed out.
Design of signal and system virtual teaching course platform based on LabVIEW
Authors: Yang Haima , Zhang Xianghong , Fang Gang , Li Jun , Zhang Dawei , Liu Jin , Ying Jie
Published: February 2021

"Signals and Systems" is the core professional course of electronic information majors. Aiming at its characteristics of strong theory, abstract content, and high memory requirements, a virtual teaching platform based on LabVIEW is designed to strengthen students' understanding of this course It is of great significance to reduce the difficulty of students' learning, improve students' learning efficiency, and stimulate students' interest in learning. At the same time, with the synchronous teaching of relevant course experiments, it can greatly reduce the difficulty of teachers' teaching and improve the quality of teaching.
A review of recommendation system research based on bipartite graph
Authors: Wu Ziteng , Song Chengyun , Chen Yunqing , Li Lingxuan
Published: February 2021

The interaction history between users and items is usually stored and displayed in the form of bipartite graphs. Neural network recommendation based on the user-item bipartite graph has a significant effect on alleviating the long-standing data sparseness and cold start of the recommendation system. The whole paper is based on the bipartite graph. An review of the recommendation system of graphs summarizes the three characteristics of graph neural network processing bipartite graph data in the recommendation field: interchangeability, Multi-hop transportability, and strong interpretability. The biggest contribution of the full paper is that it summarizes the general framework of graph neural network processing bipartite graph recommendation from the models with the best recommendation effect in the past three years: embedding layer, propagation update layer, and prediction layer. Although there are subtle differences between different models, they are all this framework can be applied, and different models can be regarded as variants of this general model, that is, other models are fine-tuned on the basis of this framework. At the end of the paper, the latest research progress is introduced, and the main challenges and research priorities that will be faced in the future are pointed out.
A social commerce information propagation prediction model based on transformer
Authors: Zhang Huibing , Dai Jingrui , He Junfei , Zhang Huacheng
Published: February 2021

Precise forecasts of the propagation patterns of social commerce information play a crucial part in precision marketing. Traditional forecast relies on machine learning diffusion models, in which the forecast accuracy is dependent on the quality of the designed features. Researchers using these models are required to have experience in this regard, but due to the complexity and variations of real-world social commerce information propagation, design of features for the prediction model turns out difficult and is likely to cause local or universal errors in the model. To address these problems, this study proposed an information propagation prediction model based on Transformer. First, the fully-connected neural network was employed to code the user nodes to low-dimension vectors; then, Transformer was employed to perform information of the user-node vectors; last, the output of the Transformer was uploaded to the output layer to forecast the next user node in information propagation. The model was tested on data sets obtained from Sina Weibo, and the test result shows that the proposed model outperformed baseline models in terms of the indicators of Acc@k and MRR.
Personalized customization system solution using augmented reality technology
Authors: Feng Liying , Ma Liyao , Ng Giapweng
Published: February 2021

This paper presents a personalized clothing customization system using Augmented Reality (AR) technology. The goal of this paper is creating a more interactive and immersive experience for tailor designer by bridging physical personalized clothing customization and digital resources. This system can make the traditional clothing customization process more convenient and efficient and has strong interaction and experience. At the same time, it reduces the time cost, labor cost and material cost of sample making in the traditional clothing customization process. This paper discusses the feasibility of the system, introduces the system development, testing, and application environment, the overall system design scheme and system workflow, and details the specific functions of each module. It also introduces the system detection methods and observation indicators. The system uses technologies such as augmented reality (AR) technology, Azure Kinect somatosensory technology, and OpenGL 3D rendering, combined with the functional advantages of the somatosensory virtual fitting system, focusing on the improvement and role of AR technology in the clothing customization process, effectively improving user satisfaction with clothing customization and saves production time and costs.
The combination of the IoT wireless data acquisition system and edge computation
Authors: Yin Ming , Wang Liwei
Published: February 2021

This paper presents an improvement that cominate the algorithm of edge computation and the Internet of things (IoT) data acuisiton system. Firstly, the environment data acquisition system of the agriculture IoT was analyzed and the distributed data processing approach was proposed to handle the abnormal data. we perform the simply processing of the raw acquisition data via the CC2530 by its spare time computation competence. The results prove our algorithm improve the data acquisition efficiency.
Research on evaluation index system of information system equipment system contribution rate
Authors: Hou Jian , Wang Ruihua , Wang Jiajia , Yang Zhou
Published: February 2021

The construction of index system is the basis of equipment system contribution rate evaluation, and is also one of the main contents of equipment test and appraisal. This paper discusses the concept of systems contribution rate, introduces the evaluation process of system contribution rate of information system equipment, and gives the construction principles and ideas of information system equipment system contribution rate evaluation index system. Then, referring to the theory of operational loop, the evaluation index system of system contribution rate is given from the perspectives of system capability and system effectiveness. The evaluation index of this paper can provide decision support for the development of equipment planning system.
Game-based cache allocation strategy for ICN slicing
Authors: Ge Liping , Zhou Jinhe
Published: February 2021

To reduce the delay of content acquisition, this paper proposes a game-based cache allocation strategy in the Information-Centric Network (ICN) slice. The cache resource allocation of different mobile virtual network operators (MVNOs) is modeled as a non-cooperative game model. The Newton iterative method is used to solve this problem, and the cache space allocated by the base station for each MVNO is obtained. Finally, the Nash equilibrium solution is obtained. Simulation results show that the proposed algorithm can reduce the delay.
Research on driverless vehicle vision algorithm
Authors: Liu Xinchao , Yan Ying , Gan Haiyun
Published: February 2021

Obstacle detection in complex urban traffic environment has become an important part of unmanned vehicle optimization, and its complexity brings great challenges to the reliability of unmanned target detection. YOLOv3 in deep learning algorithm has a good detection effect in target detection, but it has certain defects in detecting targets in complex urban traffic environment. In this paper, the spatial pyramid module is added to YOLOv3 to improve the extraction of data features of the deep model. Then, on the basis of optimized network, the target detection algorithm is streamlined by combining layer pruning and channel pruning. The streamlined algorithm is called YOLOv3-SPP3-Tiny. Comparing the experimental results of YOLOv3-SPP3-tiny and YOLOv3 on Street Scenes dataset, the Precision is improved by 2.77%, the average precision (mAP) is increased by 0.87%, the Total BFLOPS is reduced by 94.49%, and the Inference time is reduced by 80.39%. Experimental results show that the model YOLOv3-SPP3-tiny algorithm is more conducive to unmanned object detection in complex urban road environment.
Forensic face recognition based on KDE and evidence theory
Authors: Xiao Wen
Published: February 2021

Forensic face recognition (FFR) has been studied in recent years in forensic science. Given an automatic face recognition system, output scores of the system are used to describe the similarity of face image pairs, but not suitable for forensics. In this study, a score-mapping model based on kernel density estimation (KDE) and evidence theory is proposed. First, KDE was used to generate probability density function (PDF) for each dimensional feature vector of face image pairs. Then, the PDFs could be utilized to determine separately the basic probability assignment (BPA) of supporting the prosecution hypothesis and the defence hypothesis. Finally, the BPAs of each feature were combined by Dempster’s rule to get the final BPA, which reflects the strength of evidence support. The experimental results demonstrate that compared with the classic KDE-based likelihood ratio method, the proposed method has a better performance in terms of accuracy, sensitivity and specificity.
A method of constructing syllable level Tibetan text classification corpus
Authors: Dao Jizhaxi , Cai Zhijie , Cai Rangzhuoma , San Maocuo , Ban Mabao
Published: February 2021

Corpus serves as an indispensable ingredient for statistical NLP research and real-world applications, therefore corpus construction method has a direct impact on various downstream tasks. This paper proposes a method to construct Tibetan text classification corpus based on a syllable-level processing technique which we refer as TC_TCCNL. Empirical evidence indicates that the algorithm is able to produce a promising performance, which may lay a starting point for research on Tibetan text classification in the future.
Tibetan interrogative sentence recognition and classification based on phrase features
Authors: Ban Mabao , Cai Zhijie , Cai Rangzhuoma , Cai Rangjia
Published: February 2021

The recognition of Tibetan interrogative sentences is a basic work in natural language processing, which has a wide application value in terms of Tibetan syntactic analysis, semantic analysis, intelligent question answering, search engine and other research fields. Employing interrogative pronouns as a entry point to analyze the phrase features before and after interrogative pronouns, the paper proposes a method for Tibetan interrogative sentence recognition and classification based on phrase features by designing a Tibetan interrogative sentence recognition and classification model based on phrase features. Experimental results show that the recognition accuracy, recall rate and F value of this method are 98.21%, 100.00% and 99.10% respectively, and the average classification accuracy, recall rate and F value are 96.98%, 100.00% and 98.39%, respectively.
Local feature extraction of sheepskin based on structure contour shape description
Authors: Hu Lianhua , Xiang Chengyi , Zhang Feng
Published: February 2021

Based on the precise sheepskin contour extracted by computer vision technology in the previous research of the team, this paper proposes the shape description technology based on the structure contour to extract the local features of the sheepskin, such as the head and hooves and the waste edge, which is the basis for the automatic edge removal of the sheepskin in the future. The algorithm uses Angle and position relation to segment the precise contour track of raw sheepskin into graph elements, and then uses geometric parameter shape description operator to describe and extract the edges that need to be removed, so as to obtain the starting point and end point of each local contour that needs to be removed. In this paper, the principle and implementation steps of this method are introduced in detail, and the experimental simulation verification shows that the extraction effect is good, which can meet the requirements of subsequent industrial production of automatic sheepskin cutting.
A spatial and temporal analysis on NDVI in Urad grassland during 2010-2019 over remote sensing
Authors: Zhang Yueying , Liu Tiantian , Wang Yuxi , Zhang Ming , Zheng Yu
Published: February 2021

The temporal-spatial dynamic variation of vegetation coverage from 2010 to 2019 in Urad Grassland, Inner Mongolia has been investigated by analysing on MODIS NDVI remote sensing products. This paper applies pixel dichotomy approach and linear regression trend analysis method to analyze the temporal and spatial evolution trend of vegetation coverage over the past 10 years. The average annual vegetation coverage showed a downward trend in general from 2010 to 2019. The vegetation distribution and change trend analysis provide a thorough and scientific reference for policymaking in environmental protection.
Application of remote sensing to informal garbage dumps recognizing in beijing city
Authors: Cheng Bin , Sun Libo
Published: February 2021

The improvement of urbanization level and the imperfection of waste treatment infrastructure have caused the problem that informal garbage dump become prominent problem in China. With the development of high resolution remote sensing images, the fast monitoring and management of informal garbage dumps become possible. The informal garbage dumps in Beijing are monitored by SPOT-6 image, and the rapid and accurate grasp of the number, position and size of the informal garbage dumps are identified by the establishment of the interpretation key using multivariate data. And then it is classified by the established interpretation key. Irregular garbage sites are uneven in shape and complex in composition, which leads to their atypical features in images. Visual interpretation and classification are more suitable for other methods.
Detection method of space-time conflict for multi route planning
Authors: Li Chong , Huang Yanyan
Published: February 2021

In order to solve the problem of space-time conflict in multi route planning, this paper proposes a space-time conflict detection method based on bounding box. The main research contents include: dividing each route into a limited number of road sections, each road section uses a bounding box to represent the space occupied by the target in the period of time, and then using OBB collision detection method to judge whether there is different bounding box overlap in the same space at the same period of time, so as to judge whether there is a space-time conflict. In addition, calculating the distance among road sections to exclude road sections where conflicts are unlikely to occur before detection. The feasibility of the conflict detection method is verified by experiments on a multi route planning case.
A time domain random flicker band-limited Gaussian noise jamming algorithm for LMS-based GPS
Authors: Wu Tao , Wu Jixiang , Wang Hui , Cui Ligang , Yang Yinsong
Published: February 2021

Global position systems (GPS) receiver based on least mean square (LMS) could resist the interference by null jamming direction. Considering that the existing band-limited Gaussian noise jamming signals were easily suppressed by LMS-based GPS receivers, a time domain random flicker band-limited Gaussian noise jamming algorithm was proposed to improve its performance. By disturbing the convergence of LMS, it could achieve the purpose of suppressing the LMS-based GPS. Simulation result shows that the proposed algorithm has an average performance gain of 2.7dB~4.6dB under different number of interferences compared with band-limited Gaussian noise.
An algorithm acceleration framework for correlation-based feature selection
Authors: Yan Xuefeng , Zhang Yuqing , Khan Arif Ali
Published: February 2021

Repeated calculations lead to a sharp increase in the time of correlation-based feature selection. Incremental iteration has been applied in some algorithms to improve the efficiency. However, the computational efficiency of correlation has generally be ignored. An algorithm acceleration framework for correlation-based feature selection (AFCFS) is proposed. In AFCFS, the criterion of the feature selection will be analyzed and reconstructed based on entropy granularity, and the algorithm structure will also be adjusted accordingly. Specifically, all repeated part of calculation will be saved in mapping tables and can be accessed in next time directly, so as to further reduce the calculation repetition rate and improve the efficiency. The experimental results show that AFCFS can greatly reduce the cost time of these algorithms, and keep the corresponding classification accuracy basically unchanged.
Research on correlation analysis and prediction model of agricultural climate factors based on machine learning
Authors: Deng Yun , Cao Cunliang , Chen Shouxue
Published: February 2021

This article uses machine learning technology to analyze the correlation of climate factors that affect crop yields, and conduct prediction and comprehensive evaluation to guide agricultural production. This paper selects early rice crops in Guangxi as the research object. Based on the climatic data of early rice planting areas in Guangxi from 1990 to 2017, a cart decision tree is constructed to generate a random forest model to analyze the correlation between early rice yield and climatic factors in each growth period, and obtain the various growth periods The ranking of the importance of climatic factors on the yield, thus forming the basis for calculating the weights of the climatic factors in each growth period of early rice; based on the climatic data in Guilin, Guangxi from 2008 to April to July 2017, predicted by the long and short-term memory network Guilin's various climate data from April to July 2018.
An improved data integrity validation model for cloud storage
Authors: Qin Zhijian , Huo Lin , Zhang Shicong
Published: February 2021

Data integrity validation is considered to be an important tool to solve the problem that cloud subscribers cannot accurately know whether there are non-subjective changes in the data they upload to cloud servers. In this paper, a data integrity verification model based on dynamic successor tree index structure, Bloom filter and Merkle tree is proposed. The block labels generated according to the features of the dynamic successor tree index structure can sense whether changes have been made to the user's data, while the Merkle tree can track the cha*nged data blocks, enabling the user to effectively verify the integrity of the data stored in the cloud server and provide more effective protection for data.
Research on authentication encryption mechanism based on intelligent door lock vulnerability risk
Authors: Lu Yili
Published: February 2021

This article introduces the security risks of the commonly used MQTT protocol in the Internet of Things and the security risks caused by smart door lock vulnerabilities, aiming to solve the problem of public MQTT agent leaking smart lock data, causing attackers to use the sensitive data to physically locate and remotely control the connection to the smart door lock supplier Any lock issues in the cloud infrastructure. This paper presents a wireless sensor network authentication encryption method based on SM9 algorithm. By implementing and deploying sensor network authentication encryption in practical applications, it avoids the leakage of sensitive information from public data exposed on the Internet.
Resilient set-membership state estimation for nonlinear complex networks with time-delay and incomplete measurements
Authors: Yang Ning , Chen Dongyan , Hu Jun
Published: February 2021

Taking the incomplete measurements and the weighted try-once-discard (WTOD) protocol into account, this paper develops a novel resilient set-membership state estimation (RSMSE) method for time-varying nonlinear complex networks with time-invariant delay. A classic interval matrix technique is utilized to describe incomplete measurements. The Taylor series expansion is applied to dispose the nonlinearities, where the high-order terms of the linearization errors are described by norm-bounded uncertainties. To mitigate the communication burden, the WTOD protocol is introduced, where only one node can send updated data through a shared communication network at each certain transmission step. Using the recursive linear matrix inequalities (RLMIs), a series of ellipsoidal sets including the state vector can be determined. The desirable estimator gain and a smallest possible estimation ellipsoid can be calculated via solving the convex optimization problem. Lastly, we use an illustrative example to show the feasibility of the introduced RSMSE technique.
Financing and pricing strategies of construction supply chain under capital constraint
Authors: Wen Yuxin , Wu Linyi , Yao Fengmin
Published: February 2021

Affected by factors such as cost, the financial constraints faced by the supply chain are becoming more and more severe. This paper constructs a financing and pricing decision-making model for the construction supply chain under capital constraints, and uses Stackelberg game theory to analyze and obtain the best financing and pricing strategy for the construction supply chain under the internal and external financing modes. The study found that when centralized decision-making is adopted, there is a profit distribution model that makes the profits obtained by construction developers and contractors greater than the profits obtained in decentralized decision-making; the internal financing model of the construction supply chain is better than external financing, and can enable the construction supply chain get higher profits.
Research on transformation mode of scientific and technological achievements with different transaction costs: taking the electric power industry as an example
Authors: Lei Kaiyan , Zhang Meimei
Published: February 2021

Technological innovation and achievement transformation are an important starting point for constructing an industrial innovation ecosystem and coping with hindered external demand. This article starts with the ecological chain of technological achievement transformation, constructs a transaction cost and benefit model of three transformation modes of direct transformation, intermediary participation, and co-construction cooperation, and systematically analyses its transaction costs, benefits, application and the value space of the transaction subject of each mode. With the participation of intermediaries and investors, the "government, industry, university, research, and financial agency" achievement transformation service platform not only reduces transaction costs but also greatly increases returns. Using the advantages of big data and blockchain can obtain more added value than other models, bringing more opportunities for both supply and demand.
The relationship between job satisfaction and work performance of sub-district municipality administrators in the eastern region, Thailand
Authors: Plikamin Sakdipath , Luengalongkot Pongsatean
Published: February 2021

The purpose of this paper is to study the relationship between job satisfaction and work performance of sub- district municipality administrators in the eastern region. The population used in this research is the head and sub-head of sub-district municipality, which have offices in 7 provinces of the eastern region of Thailand, totally 531 people. The sample size consisted of 400 people. Simple random sampling technique was used to collect data. The instruments used for collecting data were questionnaires. In the data analysis, pear son product moment correlation was used to analyse the relationship between job satisfaction and work performance of sub- district municipality administrators in the eastern region by setting statistical significance at the level of 0.01. The results showed that there is a relationship between job satisfaction and work performance of sub- district municipality administrators in the eastern region.
Virtual models of chronic disease management: lessons from the experiences of virtual care during the COVID-19 response
Authors: Smithson Rachael , Roche Elisha , Wicker Christina
Published: February 2021

Objective This study examined Gold Coast staff and patient experiences with the rapid expansion of a virtual model of chronic disease management during the COVID-19 pandemic. Methods The study undertook a survey of enrolled patients (n = 24) and focus groups with clinical and administrative staff (n = 44) delivering chronic disease programs at Gold Coast Health in Queensland. The study also examined routinely collected activity data for the chronic disease programs before COVID (January–February 2020) and for the first 3 months of the COVID-19 response (March–May 2020). Results Chronic disease programs continued to provide similar numbers of appointments over the COVID-19 response period, but there was a marked increase in the proportion of appointments that were delivered virtually, either by telephone or video conference. Most patients were satisfied with their virtual care experiences and felt that their health care needs were met. Conclusions The COVID-19 response provided an opportunity to learn and further develop models of virtual care. Staff and patients were generally supportive of continuing to include virtual appointments in the future. Ongoing concerns were predominantly around the support available to patients and staff to ensure they are trained and equipped to manage the technology and new mode of communicating. What is known about the topic? Emerging evidence suggests that virtual models of health care delivery, such as telephone and video consultations and remote patient monitoring, can be safe and cost-effective alternatives to traditional face-to-face chronic disease management programs. Virtual care is associated with equal or improved clinical outcomes, as well as efficiency improvements, such as reduced failure to attend rates. What does this paper add? The increasing burden of chronic disease across Australia, as well as the need to minimise the risk of vulnerable patient groups attending in-hospital appointments where it is safe and appropriate to do so, means that expanding the delivery of virtual chronic disease management will become increasingly necessary. The results of this study provide an opportunity to learn from a rapid rollout of virtual care for these staff and patient groups and will help inform advances in this area. What are the implications for practitioners? Existing evidence, demographic pressures and the COVID-19 pandemic response all point to virtual care as a viable and safe alternative to traditional models of chronic disease management. The lessons presented here provide more detailed guidance on the support that staff and patients require to ensure virtual care is a seamless and safe alternative or adjunct to traditional chronic disease management programs.
Use of telehealth mental health services during the COVID-19 pandemic
Authors: Jayawardana Danusha , Gannon Brenda
Published: February 2021

During the COVID-19 pandemic, specific mental health telehealth services in Australia have been an important source of help for the increasingly stressed population. This study examined trends in the uptake of telehealth items for mental health during the first 6 months of the COVID-19 pandemic using administrative Medicare data. During the peak of the pandemic there was a 50% reduction in the in-person consultations for mental health but also a substantial increase in uptake largely of the newly introduced temporary Medicare Benefits Schedule telehealth services. Further, the use of telehealth varied across age, gender and state/territory. These findings have important implications for the allocation of resources for telehealth, both now, and into the post-COVID-19 era.
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Authors: Boschma Suzanne P. , Harris Carol A. , Brennan Mark A. , Harden Steven
Published: February 2021

Tropical perennial grasses are an important forage option in the frost prone, summer dominant rainfall zone in eastern Australia. These pastures commonly lack a companion legume and are, at best, irregularly fertilised with nitrogen; therefore, their production potential is not realised. We conducted a study during 2012–16 to evaluate the productivity and persistence of a range of cultivars/lines of eight tropical and two temperate perennial legumes in mixes with digit grass (Digitaria eriantha cv. Premier) at two sites (Bingara and Manilla) in the northern inland region (North-West Slopes) of New South Wales. The sites were subjected to dry conditions during the assessment period, with the Bingara site receiving <25th percentile rainfall for 2 years of the study. Lucerne (Medicago sativa) was the most productive companion legume, with mixes producing 16–18 and 38–46 t dry matter (DM)/ha at the Bingara and Manilla sites respectively. Cultivars of Desmanthus spp. were less productive, with the best performing in mixes producing 13 and 21–23 t DM/ha at Bingara and Manilla respectively. These cultivars were also persistent and readily recruited new seedlings. Their persistence was similar or superior to lucerne, which appeared to be declining, especially at the Manilla site. Mixes of burgundy bean (Macroptilium bracteatum) and digit grass produced 14–17 t DM/ha at the sites but DM tended to decline during the course of the experiment, especially at the Manilla site. Stylosanthes spp. and Chamaecrista rotundifolia had poor persistence, generally failing within 1–2 years of sowing. Therefore, we recommend lucerne and Desmanthus virgatus cvv. Marc and JCU 2 as suitable perennial legumes in mixes with digit grass during drought conditions.
The pictures in our heads of certain diseases
Authors: Yüksel Erkan , Dingin Ali Emre
Published: February 2021

Using the network analysis method, the third level of the agenda-setting proposes that the associations between
the elements on the media agenda are transferred to the public agenda. Focusing on five health issues in Turkey, this paper
proposes a new perspective to third level researches. A media agenda content analysis was conducted on 13 nationwide and five
local newspapers for six months and at the end of it, a public agenda survey on 400 people was conducted in Aydın, a city in
Turkey. Findings show that there is a significant similarity between all the diseases chosen as a sample and taken from the
newspapers and the public agenda network. The high correlation has been ranked in descending areas as: AIDS, cancer, obesity,
diabetes and blood pressure. The concepts of “need for orientation” and “obtrusive and unobtrusive issues” may serve as
explanations for these findings.
Becoming #Instafamous
Authors: Kováčová Dominika
Published: February 2021

Drawing onGoffman’s (1990 [1959])metaphor of stage, this paper considers Instagram a frontstage environment where users are cautious of being watched and attune their performance to how they want to be perceived via strategic self-presentation. This understanding of online performance is particularly pertinent in the discussions of bloggers who turn to Instagram to promote their work to new audiences. Examining the self-presentation practices of three fashion bloggers, this paper argues that to gain popularity on Instagram, bloggers utilize the features of formality and informality in the construction of an authentic and likable self-image. Since in the photographs the bloggers’ professional life is usually depicted as distant from their audience’s reality, the accompanying textual caption serves as a means of providing balance for the overall image the poster seeks to present. Consequently, the caption abounds with features of informality, which connote linguistic immediacy and imitate an intimate conversation with peers.
Persuasive language and features of formality on the r/ChangeMyView subreddit
Authors: Dayter Daria , Messerli Thomas C.
Published: February 2021

The paper investigates formal language in persuasive discourse on ther/ChangeMyViewsubreddit. We collected a corpus of 100 million messages, split into subcorpora based on the user-awarded markerdelta, which rewards changing an original poster’s view. Assuming that formality/informality is potentially an important factor in the persuasiveness of a message, we examine the two subcorpora with respect to formality markers. The results indicate no systematic variation along the formality/informality continuum between persuasive and non-persuasive posts onr/ChangeMyView. The posters use personal pronouns, suasive verbs, emphatics, imperatives, elaborate connectors and WH-questions with similar frequency, and express themselves using vocabulary and syntax of similar complexity. Moreover, keyword lists and n-gram rankings indicate no register difference. A qualitative analysis of concordance lines forpersuadeandchange PRONOUN viewpaints a picture of a community that values factual, evidence-based discourse and openness to logical persuasion, with a linguistic norm of relatively formal, sophisticated register.
Difficulties with telling the truth in non-fictive narratives and the issue of fictionalization
Authors: Filutowska Katarzyna
Published: February 2021

The purpose of this paper is to discuss difficulties with telling the truth in non-fictive narratives (e.g. trauma stories, rape narratives, asylum-seekers’ narratives). In order to do that I analyze, among others, various discourse fictionalization strategies, such as emplotment, narrative substances (Nss), vague predicates, and approximate references. I argue that these strategies are conditioned by the very nature of language, and therefore are present in all types of statements – literary as well as scientific. Referring to the concept of alethic pluralism, I also discuss how it is possible that the use of fictionalization techniques in non-fictive stories does not necessarily transform them into fiction.
Prevalence and clinical association with calcinosis cutis in early systemic sclerosis
Authors: Muktabhant Chawiporn , Thammaroj Punthip , Chowchuen Prathana , Foocharoen Chingching
Published: February 2021

Objectives

Calcinosis cutis is often found with systemic sclerosis (SSc). However the calcinosis cutis and its clinical association among SSc patients is limited. Our aims were to assess the prevalence of calcinosis cutis and its association with clinical features of SSc patients at early onset of the disease.

Methods

A cross-sectional study on clinical characteristics and hand radiographs of 120 newly diagnosed SSc patients with the onset less than four years were evaluated. Calcinosis cutis was described based on the anatomical regions, density (level 1–3) and shapes (net, plate, stone, and amorphous).

Results

Among all SSc patients enrolled, 62.5% were females and 56.1% were diffuse cutaneous SSc. The mean disease duration was 2.0 ± 1.3 years. Calcinosis cutis was detected in 60 patients with the prevalence of 50% (95%confidence interval (CI), 0.41–0.59), of which 53.3% occurred at distal phalanx, 96.7% had stone shape and 48.3% were high density. Univariate analysis revealed that calcinosis cutis was associated with age (p = .02) and high-density calcinosis cutis was associated with Raynaud’s phenomenon (p = .02), ischemic ulcer (p = .04), and telangiectasis (p = .02). Logistic regression analysis revealed that calcinosis cutis at distal phalanx was negatively associated with edema at the onset (odds ratio, 0.09).

Conclusion

Occult calcinosis cutis can be detected by hand radiograph in one half of SSc patients at early onset of the disease. Elderly patient has a risk for calcinosis cutis development and Raynaud’s phenomenon was associated with high density calcinosis cutis. Calcinosis cutis, particularly at distal phalanx was less likely to be detected in an edematous phase of disease.
Phase-dependent fluctuations of resonance fluorescence near the coherent population trapping condition
Authors: de los Santos-Sánchez O , Castro-Beltrán H M
Published: February 2021

We study phase-dependent fluctuations of the resonance fluorescence of a single Λ-type three-level atom in the regime near coherent population trapping, i.e. alongside the two-photon detuning condition. To this end, we employ the method of conditional homodyne detection (CHD) which considers squeezing in the weak driving regime, and extends to non-Gaussian fluctuations for saturating and strong fields. In this framework, and using estimated parameter settings of the resonance fluorescence of a single trapped 138Ba+ ion, the light scattered from the probe transitions is found to manifest a non-classical character and conspicuous asymmetric third-order fluctuations in the amplitude-intensity correlation of CHD.
Fast nuclear spin relaxation rates in tilted cone Weyl semimetals: redshift factors from Korringa relation
Authors: Mohajerani A , Faraei Z , Jafari S A
Published: February 2021

Spin lattice relaxation rate is investigated for 3D tilted cone Weyl semimetals (TCWSMs). The nuclear spin relaxation rate is presented as a function of temperature and tilt parameter. We find that the relaxation rate behaves as

(

1
−

ζ

2

)

−
α

with α ≈ 9 where 0 ⩽ ζ < 1 is the tilt parameter. We demonstrate that such a strong enhancement for ζ ≲ 1 that gives rise to very fast relaxation rates, is contributed by a new hyperfine interactions arising from the tilt itself. This can be attributed to the combination of anisotropy of the Fermi surface and an additional part related to the structure of the spacetime: extracting an effective density of states (DOS)

ρ

̃

from the Korringa relation, we show that it is related to the DOS ρ of the tilted cone dispersion by the ‘redshift factor’ as

ρ

̃

=
ρ
/

1
−

ζ

2

. We interpret this relation as NMR manifestation of an emergent underlying spacetime structure in TCWSMs.
Micro-mesoporous submicron silica particles with pore size tunable in a wide range: synthesis, properties and prospects for LED manufacturing
Authors: Eurov Daniil A , Kurdyukov Dmitry A , Medvedev Alexander V , Kirilenko Demid A , Tomkovich Maria V , Golubev Valery G
Published: February 2021

An approach has been developed that allows the synthesis of submicron spherical silica particles with a controlled micro-mesoporous structure possessing a large specific surface area (up to 1300 m2 g−1). Particle synthesis is carried out by the hydrolysis of a mixture of various organosilanes mostly associated either with CTAB or with each other. A change in the concentration of CTAB in the reaction mixture apparently leads to a change in the formation mechanism of nuclei for the silica particle growth, which allows for varying the diameter of the synthesized particles in the range from 40–450 nm. The effect of the composition of the silica precursor ([3-(methacryloyloxy)propyl]trimethoxysilane, (3-aminopropyl)triethoxysilane and tetraethoxysilane) on the formation process and porosity of the resulting particles is studied. It was shown that by simply varying the ratio of organosilanes in the composition of the precursor, one can control the pore diameter of the particles in a wide range from 0.6–15 nm. The large-pore (up to 15 nm) silica particles are used as a matrix for the spatial distribution of luminescent carbon dots. The incorporation of carbon dots into SiO2 particles prevents their aggregation leading to emission quenching after drying, thus allowing us to obtain highly luminescent composite particles. LEDs based on the obtained composite material show bright visible luminescence with spectral characteristics similar to that of a commercial cold white LED.
Nanonization of a chemically synthesized flavone HMDF (3-hydroxy-3′,4′-methylenedioxyflavone) by entrapping within calcium phosphate nanoparticles and exploring its antioxidant role on neural cells in vitro and zebrafish in vivo
Authors: Patra Mousumi , Banik Milon , Bandopadhyay Pathikrit , Dutta Debanjan , Mukherjee Riya , Das Sreeparna , Begum Naznin Ara , Basu Tarakdas
Published: February 2021

The chemical synthesis of 3-hydroxy-3′,4′-methylenedioxyflavone (HMDF) was reported to generate a modified flavone of potent antioxidant activity with significant neuropharmacological properties. In this study, HMDF was nanonized by entrapping within calcium phosphate nanoparticles (CPNPs). HMDF-CPNPs were of (i) size 25 nm, (ii) zeta potential (−) [22 ± 3] mV and (iii) entrapment efficiency 67%. HMDF-CPNPs, but not HMDF alone, inhibited the in vitro activity of acetylcholinesterase enzymes to break down the major neurotransmitter compound acetylcholine. Moreover, nanonized HMDF had more antioxidant activity than bulk HMDF, as observed from its ability to protect mouse neural (N2A) cells from oxidative damage caused by H2O2 exposure at the levels of cell viability, intracellular reactive oxygen species, mitochondrial membrane potential, cell cycle stages, nuclear integrity and neural connectivity. An in vivo study on zebrafish larvae (Denio rerio) also demonstrated that H2O2-mediated larval death was checked by HMDF-CPNP treatment. These results, therefore, suggest that HMDF-CPNPs may be developed as a potential antioxidant, particularly as a neuroprotectant.
Orientation-dependent mechanical response of graphene/BN hybrid nanostructures
Authors: Patra Lokanath , Mallick Govind , Sachdeva Geeta , Shock Cameron , Pandey Ravindra
Published: February 2021

Graphene-based hybrid van der Waals structures have emerged as a new class of materials for novel multifunctional applications. In such a vertically-stacked heterostructure, it is expected that its mechanical strength can be tailored by the orientation of the constituent monolayers relative to each other. In this paper, we explore this hypothesis by investigating the orientation dependence of the mechanical properties of graphene/h-BN heterostructures together with that of graphene and h-BN bilayers. The calculated results simulating the pull-out experiment show a noticeable dependence of the (out-of-plane) transverse mechanical response, which is primarily governed by the interlayer strength, on the stacking configurations. The degree of the dependence is directly related to the nature of the interlayer interactions, which change from covalent to covalent polar in going from graphene bilayer to graphene/BN to BN bilayer. In contrast, molecular dynamics simulations mimicking nanoindentation experiments predict that the in-plane mechanical response, which mainly depends on the intra-layer interactions, shows little or no dependence on the stacking-order. The BN monolayer is predicted to fracture before graphene regardless of the stacking pattern or configuration in the graphene/BN heterostructure, affirming the mechanical robustness of graphene. Thus, the graphene-based hybrid structures retain both stiffness and toughness required for a wide range of optoelectromechanical applications.
Plant efficiency: a sensitivity analysis of the capacity factor for fusion power plants with high recirculated power
Authors: Mulder R.A. , Melese Y.G. , Lopes Cardozo N.J.
Published: February 2021

The plant efficiency of a nuclear fusion power plant is considered. During nominal operation, the plant efficiency is determined by the thermodynamic efficiency and the recirculated power fraction. However, on average the reactor operates below the nominal power, even when the long shutdown periods for large maintenance are left outside the averaging. Hence, next to the recirculated power fraction the capacity factor must be factored in. An expression for the plant efficiency which incorporates both factors is given. It is shown that the combination of high recirculated power fraction and a low capacity factor, results in poor plant efficiency. This is due to the fact that in a fusion reactor the recirculated power remains high if it runs at reduced output power. It is argued that, at least for a first generation of power plants, this combination is likely to occur. Worked out example calculations are given for the models of the power plant conceptual study. Finally, the impact on the competitiveness of fusion on the energy market is discussed. This analysis stresses the importance of the development of plant designs with low recirculated power fraction.