bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Relationship Between H Index Ranking Evaluation Method and Comprehensive Ranking Based on Big Data Statistics
Authors: Yang Shufen
Published: June 2021

The h index of universities can quantitatively calculate the scale of high-level scientific research personnel in universities, and evaluate the academic influence of universities from a new perspective. It has the advantages of simplicity, intuition, and visibility, but there are also some problems. Based on this research background, the paper uses big data statistical methods to conduct an in-depth theoretical analysis of the problems existing in the h-index of universities. The results show that the h index and other ranking indexes are effective in the academic evaluation of colleges and universities. And the correlation analysis between their comprehensive rankings and various evaluation indicators shows that the correlation between the rankings of various indexes and the comprehensive rankings is higher than that of SCI included rankings.
Semantic keyword search based on information entropy
Authors: Lou Ying , Zhong Feng , Zhang JinXiang , Li Qian
Published: June 2021

Keyword search is still the most effective means for users to obtain information. In the era of massive data, more and more structured and semi-structured data can be directly accessed by users. Different from the web data and text data, structured data and unstructured data contain a lot of semantic information, which can improve the accuracy of search results. Based on the theory of information entropy, we calculates the information entropy of semantic information to determine the semantic relevance of keywords, and then uses the degree of relevance between keywords and semantics, finally constructs a semantical model based on information entropy. Final experiments prove the effectiveness of our model.
Research on a Computer Aid Risk Control System Using Classification Capabilities of Support Vector Machines
Authors: Tian Jia , Hu Naiyue , Li Xin , Zhang Fei
Published: June 2021

The paper proposes the use of support vector machines to establish a financial early warning system and a method for financial risk monitoring, gives a financial evaluation index system and its quantitative methods, and uses the classification capabilities of support vector machines to establish a financial early warning model. At the same time, the paper explores and studies the combination of enterprise group’s financial risk identification, assessment, response and management information system, and proposes an enterprise group’s financial risk control information system. Through experimental comparison, the model based on the support vector machine has good consistency with the experimental data, which is in line with the expected results.
Recurrent Pattern Aware Multiphase Flow Soft Sensor Model
Authors: Wang Luyao
Published: June 2021

Given data captured from multiphase flow industrial process which has non-stationary and dynamic characteristics, it’s difficult to predict the dominant variables precisely via traditional soft sensor models. In this paper, we propose RP-LSTM (Recurrent Pattern Aware Long Short Term Memory) model, a soft sensing method that takes both dynamic of time-sequence and pattern mining of industrial process into account. In this way, we can fully utilize limit model capacity, and enhance model’s knowledge on recurrent data stream patterns. Experiments on real data set demonstrate that RP-LSTM out-performs traditional sequence deep learning models by a significant margin.
Design of Intelligent Logistics Car based on STM32
Authors: Liu Le , Xie Jiawen , Wu Wenxin , Du Gang
Published: June 2021

In the increasingly developing logistics industry, the application of intelligent logistics cars is becoming more and more common. This paper mainly introduces a design scheme of intelligent logistics cars based on the STM32F103ZET6 single-chip microcomputer and OpenMV programmable camera. Its main process is as follows. First, through OpenMV, the car can scan a QR code to read relevant information of the task. Then, OpenMV recognizes the color of the object, and the single-chip microcomputer controls the manipulator arm to grab the object of the corresponding color. Next, the car will carry the object to the designated position along the designated route. Finally, the process is repeated several times until the delivery task is completed. The study of intelligent cars has very important practical value and theoretical significance.
Structure optimization design of transmission system of shearer cutter based on genetic algorithm
Authors: Xu Weipeng
Published: June 2021

As one of the mainstream equipment of fully mechanized mining equipment, shearer is a large complex system with the functions of breaking coal and transporting coal. It is an important milestone for China’s coal industry to move towards modernization and mechanization. In order to adapt to the complex working environment and better meet the needs of social development, the optimization of spatial structure and bearing capacity of coal machine has become the focus of research. Based on genetic algorithm, taking MG500/1170-AWD1 electric haulage shearer as an example, this paper takes the weight function of maximizing the bearing capacity and minimizing the volume as the optimization objective to optimize the structure of the cutting part transmission system, and analyses the rationality of the scheme by comparing the objective function before and after optimization, so as to provide technical support for the R & D department.
Research and Analysis of Electronic Commerce in Network Platforms with Mathematical Model and Cloud Computing
Authors: Han Bing , Gao Renhao , Li Jia , Chen Haonan
Published: June 2021

With the rapid development of science and technology in the world today, the development of the Internet is even more remarkable. Especially under the stimulation of continuous breakthroughs in the computer field, the network economy, as an important part of the knowledge economy, is growing rapidly and has become a new driving force for world economic growth. In order to meet the needs of the development of the network economy, traditional enterprises should implement e-commerce to be able to quickly respond to customer needs, improve business processes with customer relationships, provide personalized services, shorten sales cycles and sales costs, increase revenue, and develop markets, to enhance the competitiveness of enterprises.
The Calculation and Mathematical Modelling of Melbourne Crown Risk by Linear Regression Analysis
Authors: Jing Yihao
Published: June 2021

To improve the performance and meet the rising tourist demand of luxury hotels, Crown Resorts Ltd. proposed to implement a new project, which is supposed to build a 6-star hotel resort with VIP gaming facilities in an iconic building at Barangaroo South (Jones Lang LaSalle 2013). Because the goal of Crown plans to build a luxury hotel with a casino, so the company requires a large amount of capital to launch the new project. The best financial solution to raise capital is to issue the bond. Therefore, according to the current market condition and previous experience of issuing Crown Note I & Crown Note II, here are our recommendations for the most beneficial strategy to issue a new bond--Crown Note III.
Research on Satellite Positioning Based on Total Least Squares Algorithm
Authors: Kong Ting , Wang Xiaolan , Ma Lihua
Published: June 2021

In the technology of satellite positioning, positioning observation equation is constructed by measuring pseudo distance between the satellite and the receiver and the satellite position coordinates from navigation message, then the equation is solved and positioning results are obtained. The algorithm proposed in this paper is to use total least squares method to calculate initial value, and then someone carry out the Taylor series expansion on the basis of it, and then use weighted least squares in the iterative process to get the calculation results. Finally, user positioning is achieved. The algorithm is simulated by using observation series of Fangshan GNSS station in Beijing, and the simulation results are compared with the results obtained by the least squares algorithm. The results show that the satellite positioning algorithm based on total least squares is more accurate and faster in positioning calculation.
Design and Implementation of GNSS Receiver Based on SoC Platform
Authors: Pei Dongbo , Liu Xianyang , Tian Xiaobin , Liu Lei , Yu Qian , Li Fengyi , Gu Jian
Published: June 2021

Benefit from the developed of multi-channel and multi-mode navigation SoC devices, the satellite-borne GNSS receiver scheme with highly integrated SoC platform as the baseband core device has gradually become the mainstream. Based on the NS962 device developed by Space Star Technology CO., LTD, the redundancy design of hardware double backup is proposed. This design is composed of baseband processing module, power management module and interface module. Results show that: the prototype weighs about 3.15kg; size is 198mm × 190mm × 89mm; power consumption is about 17W. It has the capability to process BD B1I/B3I, GPS L1CA/L1P/L2P single and the reliability over 8 years meets the requirement of >0.985. This design provides a new choice for the miniaturized and low-power GNSS receivers.
Studying the Growth Prediction Model of Eucalyptus Research based on Multivariate Statistical Analysis
Authors: Yang Zhe , Wu Weikun , Chen Jingshang , Lu Yongsheng , Yao Jianan
Published: June 2021

Forests have ecological functions such as purifying the atmosphere, fixing carbon and releasing oxygen, conserving water sources, preventing wind and sand invading, and harbouring biodiversity. At the same time, they provide human beings with materials and energy, and thus are important for economic and societal development. However, in our national power grid system, trees might cause interference on power transformation lines. Furthermore, if these circumstances cannot be responded timely, huge economic losses would happen. Therefore, research of forest growth models can more accurately predict the growth and the dynamics of forests, as well as provide a reference for the power warning system. This study conducts a forecast simulation study on the growth of eucalyptus in Guangzhou province, China, proposes a multivariate statistical analysis to predict tree species growth, and then compares its performances with traditional Logistic model results. We found that our multivariate statistical model can effectively consider various environmental influencing factors, thus predict tree height excellently (R2=0.9776), so as provide new foundations for tree height prediction.
Mechanical properties of multilayer coatings TiAlN
Authors: Kolesnikov V I , Suvorova T V , Belyak O A
Published: June 2021

This study aims to examine multilayer TiAlN coatings. The mechanical properties of the coatings were obtained based on micromechanics methods and finite element modeling of a representative volume of a layered medium in ANSYS. Our findings are in line with the data on coating nanoindentation. Besides, we have succeeded in finding the dependence of the mechanical properties of multilayer coatings on various Al/Ti ratios.
Development of apparatus and technology for creation of a superconducting niobium coating on the cryogyroscope rotor
Authors: Okunev M A , Dubrovskiy A R , Makarova O V , Kuznetsov S A
Published: June 2021

The processes of creating a superconducting niobium coating on a cryogyroscope rotor were considered. The conditions for the electrodeposition of superconducting niobium coatings from molten salt on rotors of a cryogenic gyroscope were determined. Niobium coatings obtained from molten salt were electrochemically polished and subsequently protective coating of niobium pentoxide was electroformed. The processes occurring during the electrodeposition, electropolishing and electrooxidation of niobium were considered. The equipment and technology for creating a superconducting niobium coating on the rotor of a cryogenic gyroscope was developed.
Chevrel phase-based solid lubrication coating for wear resistant electrocontact friction pairs in vacuum
Authors: Sergeev V P , Sungatulin A R , Kalashnikov M P , Sergeev O V , Talgat M T , Neufeld V V , Yu Zharkov S
Published: June 2021

The work comparatively studies the wear kinetics of copper friction pairs with Chevrel phase-based coating (Cu-Mo-S) and without it in vacuum of 1.5x10−3 Pa. The coating is deposited on test pads by the ion-plasma method. The tribological investigations scheme were used the “disk – coated pad”. The detected falling of the wear rate of the friction pair with the coating is explained by the change of the adhesive wear mechanism to fatigue one.
Investigation of biological and photocatalytic activity of nanopowders metal oxides with nanosized silver coating
Authors: Sokovnin S Yu , Il’ves V G , Malova O A , Kiseleva M A , Ulitko M V , Sultanova T R
Published: June 2021

Was carried out the assessment of photocatalytic, cytotoxic properties on cells and antibacterial properties against E. coli and Staphylococcus of oxides nanopowders with nanoscale silver coating. Is shown the promising use of such composites as a photocatalytic agent, as well as in medicine.
Application and Implementation of Big Data Visualization Technology in Network Security System
Authors: Tang Chao , Zhang Jie , Wang Sheng , Zhang Linghao , Wang Hai , Liang Huihui
Published: June 2021

In order to improve the safety and reliability of the information system of the State Grid, platforms that apply technologies such as big data and artificial intelligence to realize the safety monitoring and management of information systems have been widely used. At the same time, the application of visualization technology can fully display the current security status and situation of the network, as well as the intrusion and attack process of various attacks and threats. This paper proposes to apply big data visualization technology to realize asset visualization, behavior visualization, and attack visualization, and to show the risk status, intrusion view and process of the entire network.
A Three-stage DEA Study on The Efficiency of Global Intelligent Innovation Based on Big Data
Authors: Guo Xingchen , Ma Xiaoyu , Zhang Linxuan , Li Xiao
Published: June 2021

With the global intelligent technology coming, governments and organizations of various countries are speeding up the strategic layout of intelligent technology and competing to occupy the strategic commanding heights in global intelligent innovation. In this study, 101 countries from 18 regions were selected as samples. Based on the spiral collaborative innovation theory, from the perspectives of politics, industry, research, study and application, the number of Top 600 universities in the world majoring in computer science, R&D investment of hightech enterprises, and e-government investment level were selected as the input variables of intelligent innovation. Intelligence number of published papers linked with intelligent innovation, national high-tech exports, the government maturity level of artificial intelligence as the output variables. We use those input and output data to do the first stage DEA. Then, we choose the set up the number of national science and technology award, the average GDP growth rate nearly three years, intelligent technology industry in compensation levels, ICT development level as 4 environment variables, to figure out SFA analysis as the second stage DEA. Next we use three-stage DEA method to research global intelligent innovation efficiency with and without environment variables, and we find intelligent innovation efficiency presents obvious space characteristic: North America, Oceania and other regions to eliminate environment variables before and after the intelligent innovation efficiency is very high, West Africa, South Asia and other regions in the environment variable influences intelligent innovation efficiency improved significantly, and finally this study to provide path for intelligent innovation low efficiency region to improve their innovative efficiency of intelligent innovation development.
Application of big data in bauxite provenance: A case study of Yanlong area in Western Henan, China
Authors: Sun Fengyu , Cao Gaoshe
Published: June 2021

The application of big data is of great significance to the quantitative study on provenance. In this paper, taking the bauxite in Yanlong area, western Henan, as an example, the detrital zircon U-Pb age big data obtained by Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) are used to study the bauxite provenance. The results show that the Caledonian and Sibao Jinning zircons are from the North Qinling Orogenic Belt (NQOB). In contrast, the Lvliang and Wutai zircons may be derived from karst insoluble of Majiagou Formation limestone.
Discursive Construction of Chinese Literary Classics Based on Big Data Analysis in Global Communication
Authors: Yang Chunye , Xu Defeng
Published: June 2021

Recent studies illustrates that big data analysis now plays a growing importance on business, politics, technology, academic researches, discursive construction of a nation, etc. Big data analysis was applied in broad fields, including translating Chinese literary classics. By using a qualitative method, this article focuses on current studies on big data analysis and Chinese literary classics, impact of big data on discursive construction of Chinese literary classics, and strategies for discursive construction of Chinese literary classics in global communication, so as to better translating Chinese literary classics, transmitting Chinese voices, and constructing discursive power of Chinese literature in the western world. The research finds that big data analysis is a significant method to construct discursive power of Chinese literary classics and there’s still a long way to go before it is finally constructed.
An MEWMA control chart based on multivariate Poisson distribution data
Authors: Xiao Yizhuo , Zi Xuemin
Published: June 2021

Count data appears widely in finance, biomedical science, psychology, actuarial insurance, road safety and many other areas of life, and it is often multivariate. In this paper, we consider using the multivariate exponentially weighted moving average (MEWMA) control chart method to monitor count data under the assumption of multivariate Poisson distribution, which is derived by He [1] from another form of multivariate gamma distribution. We illustrate the proposed scheme by numerical simulation. In this paper, we provide two tables of average run length (ARL) values of the MEWMA control chart with different parameter shifts. The performance of the proposed control chart is evaluated by the ARL, given a parameter shift occurred, which is able to deliver satisfactory control efficiency.
Research status and Frontier hotspots of 5G technolongy based on visualization
Authors: Mao Yuanyuan
Published: June 2021

The 5G era has come, Scholars’ research focuses on 5G technology and applications. Based on the 5G technology-related literature data collected by the WOS, Derwent Innovations Index, this article uses CiteSpace V visualization software to find and explore research hotspots and frontier trends through keyword clustering analysis, mutation detection. Based on the above analysis, it is intended to provide theoretical reference for scholars in this field.
Date Analysis Of Consumers’ Purchase Intention Based On The Safety Of Food Plastic Packaging Materialst
Authors: Kang Jie , Wang Dianhua
Published: June 2021

With the rapid development of food technology and the packaging industry, frequent food contact packaging safety issues. This paper uses questionnaire survey method to obtain related data and uses methods such as multivariate ordered Logistic model to explore the relationship between food packaging material safety and customers’ purchasing intention. It is found that consumers are short of knowledge about food packaging. Education level, food packaging safety knowledge, and perceived risk have a negative impact on consumers’ purchasing intention plastic packaging materials and food. And there is a positive correlation between health status and consumers’ purchasing intention of buying food with plastic packaging materials. We should strengthen the promotion of plastic packaging materials and food, strengthen the risk control of plastic packaging materials and food, and improve the safety management of plastic packaging materials and food.
Peak density algorithm based on KD-tree optimization
Authors: Huang Xueyu , Xiang Chi
Published: June 2021

In view of the high time complexity of the density peak algorithm, it is necessary to manually confirm the clustering center according to the decision graph. A density peaking algorithm KT-DPC based on kd-tree optimization is proposed. The algorithm defines the local density p through K-nearest neighbor and uses kd-tree to accelerate the local density p and distance 8. In addition, in the confirmation stage of clustering center, a clustering center confirmation strategy (C2BD, clustering center confirmation based on difference) is proposed. The difference between adjacent y is calculated by arranging y=p*S in ascending order, and the boundary between clustering center and non-clustering center is found according to the change of difference. This method automatically confirms the clustering center of the algorithm, avoiding the problems of strong subjectivity and insufficient clustering accuracy caused by manually confirming the clustering center. Experiments on multiple UCI public data sets show that the running time and clustering accuracy of the KT-DPC algorithm under low-dimensional data are better than traditional DPC algorithms, KNN-DPC and other improved algorithms.
Research on Path Optimization Problem Based on Satisfaction Degree in Fuzzy Demand Environment
Authors: Jin Chen Xia , Zhang Yan , Li Fa Chao
Published: June 2021

Aiming at the vehicle routing problem with fuzzy demand, this paper takes the fuzzy demand of the customer as the starting point, and first defines the demand satisfaction function; takes the maximum satisfaction and the minimum cost as the goal, constructs the fuzzy demand path optimization multi-objective planning model (MORG-FD), and the characteristics of MORG-FD are analyzed; combined with the actual case of a dairy product distribution for simulation analysis, considering the changes in the distribution plan under different demand parameters, and compared with the commonly used methods, the results show that MORG-FD has good structural characteristics, strong applicability, can provide a way of thinking for solving the problem of fuzzy demand vehicle routing, and can also provide guidance for actual distribution route planning.
Research on Vehicle Classification Method Based on Improved AlexNet
Authors: Zhu Bocheng , Zhang Mengfan , Yusu  , Hu Xinping
Published: June 2021

In the actual traffic intersection environment, vehicles adopted for traffic monitoring miss detection due to various reasons, and because the difference between different types of vehicles is very small, the traditional method cannot effectively distinguish the types of vehicles, and the deep learning image processing method can be used for automatic recognition of vehicle types. We propose an improved AlexNet[1] (ProAlexNet) intersection vehicle classification method by improving and reconstructing the hierarchy and parameters of the AlexNet convolutional neural network structure. In addition, we used a self-made high-quality vehicle category data set, which included 5000 pictures of cars, trucks, buses, motorcycles, and vans. In the experiment, we carried out comparative experiments on three indicators between ProAlexNet network and traditional AlexNet method, and carried out comparative experiments on three traditional recognition algorithms of ProAlexNet. Experimental results show that our improved algorithm has strong competitiveness.
Application of APRIORI correlation algorithm on music education curriculum association rules
Authors: Li Tianjiao
Published: June 2021

Association rules is a research direction of data mining. It can be used in all walks of life by analyzing the correlation of data items in a large amount of data to mine the internal connections between data items. The various professional courses in colleges and universities are independent of each other, and there is a certain sequence of classes, which will also have a certain influence on each other. The learning situation of one course may also affect the learning of other courses. This article uses the APRIORI correlation algorithm to analyze the performance of music education majors, reveals the connections between and within the various course groups, and provides guidance for students’ choice and study of professional courses.
Comparison on the Application of BP Neural Network and Logistic Regression in the Study of Technology Life Cycle
Authors: Xinhui Chai , kun Ding
Published: June 2021

The research on technology life cycle can be used in technology transaction, technology prediction, technology evaluation and so on. It is an important reference basis for enterprise strategy making, government policy making and so on. This study constructed a BP neural network model based on the patent accumulative quantity to judge the TLC, and compares the results with the logistics regression method which is the more mature in academic circles. It is found that it is feasible to use BP neural network to study TLC with a better result on technology prediction and no difference in identifying TLC phase compared to logistics regression.
A Blockchain-based Access Control Scheme
Authors: Jiang Xiong
Published: June 2021

Access control plays an important role in protecting data privacy. However, traditional access control models such as RBAC, ABAC and UCON need to be built based on a central trusted server. Once the central trusted server is controlled by an adversary, it will pose a serious threat to data security. Therefore, this article proposes a blockchain-based access control scheme, which uses the blockchain to replace the central trusted server and uses smart contracts to complete access. The proposed scheme solves the centralization problem of the traditional access control model. Furthermore, it has been tested on representative equipment, and the experimental results show that the proposed scheme is efficient and feasible.
Research on analysis of desert crossing problem based on Dijkstra model
Authors: Feng Jiahui , Mao Yuanyuan
Published: June 2021

This article analyzes the optimal solution of the game desert nuggets in different situations. Taking into account the weather, the amount of resources (water and food), the travel conditions and the number of people in the same group, more funds are reserved for reaching the end. According to the requirements of different backgrounds, various models and solutions are proposed. Based on the Dijkstra model and using methods such as greedy algorithm and game theory, run under Linux terminal to find the optimal strategy.
Using Earned Value Management with exponential smoothing technique to forecast project cost
Authors: Zhao Mengyuan , Zi Xuemin
Published: June 2021

Earned value management (EVM) is developed for cost management and is widely used to evaluate and forecast project cost. Through earned value management, we can calculate the deviation between cost and schedule, as well as performance indicators such as cost performance index (CPI), schedule performance index (SPI) and duration performance index (DPI), and then predict project cost, schedule and duration. However, it is often not comprehensive to rely only on EVM for project prediction, because the project in the next testing period is not necessarily invariable and similar to the previous activities, but dynamic and flexible, and has some correlation with the previous project activities. Therefore, the research method of this paper is to combine the well-known earned Management (EVM) with the mature exponential smoothing technique to simulate the actual data of 32 simulation projects and predict the final cost of the project. After comparing the prediction results with the results of tens of thousands of simulation experiments, the final research results show that the combination of cost performance index (CPI) from earned Management (EVM) and simple exponential smoothing technique have promising performance for the final cost estimation of the project.
The impact of OFDI on employment quality in Hubei Province: An Empirical Analysis Based on VAR model
Authors: Leng Yue
Published: June 2021

With the in-depth development of “going out” strategy, OFDI plays an important role in the development of China’s economy. On the one hand, it promotes the increase of China’s employment, on the other hand, it has a profound impact on the quality of China’s employment. In this paper, Hubei Province as the research object, using the time series data of Hubei Province from 2003 to 2019, using entropy method to measure the comprehensive index of employment quality, on this basis, using VAR model, impulse response test method, empirical analysis of the impact of OFDI on employment quality in Hubei Province. The results show that: the average employment quality index of Hubei Province is less than 6 percent, the quality of employment is not high. For each percentage point of OFDI increase, the employment quality index increases by 0.11%, which can promote the quality of employment, but has no significant effect on the employment quality.
Projective synchronization of a 4D financial hyper-chaotic system with model uncertainty and external disturbance
Authors: Liang Haiming , Guo Rongwei
Published: June 2021

This paper investigates the projective synchronization problem of a 4D financial hyper-chaotic system. Firstly, it is proven that projective synchronization problem of such system exists. Moreover, a non-singular transformation is found and used to divide the 4D financial hyper-chaotic system into two subsystems. Secondly, a UDE-based single input controller is proposed and be used to realize this projective synchronization problem. Finally, the correctness and effectiveness of the proposed results is verified by numerical simulations.
Intrusive Intention Recognition Based on Signaling Game Model
Authors: Zhang Xiaoning , Zhang Hengwei , Sun Pengyu , Wang Jindong
Published: June 2021

In order to accurately assess the network security situation and identify the intrusive intention of attackers, we propose an intrusive intention identification method based on a signaling game model. Based on the attack path graph, an offensive and defensive signalling game model is established, and the payoffs and costs of attack and defence are quantified using CVSS. By calculating the game equilibrium to quantitatively analyse and predict the attack paths that match the attacker’s intent, administrators can be guided to make defensive decisions.
Antibody response to mRNA SARS-CoV-2 vaccines in haemodialysis patients
Authors: Paal Michael , Arend Florian M , Lau Tobias , Hasmann Sandra , Soreth-Rieke Daniela , Sorodoc-Otto Johanna , Beuthien Wilke , Krappe Julia , Toepfer Marcell , Gersdorff Gero von , Thaller Norbert , Rau Simon , Northoff Bernd , Teupser Daniel , Bruegel Mathias , Fischereder Michael , Schönermarck Ulf
Published: June 2021

Background

Some studies have shown an attenuated immune response in haemodialysis patients after vaccination. The present study examines the humoral response after mRNA vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a large population of haemodialysis patients from different outpatient dialysis centres.

Methods

We retrospectively assessed antibodies against SARS-CoV-2 spike protein and nucleocapsid protein (chemiluminescence immunoassays, Roche diagnostics) 3–6 weeks after the second mRNA vaccine dose in 179 maintenance haemodialysis and 70 non-dialysis patients (control cohort). Differences in anti-SARS-CoV-2 spike protein titers were statistically analysed with respect to patient-relevant factors, including age, gender, previous coronavirus disease 2019 (COVID-19) infection, systemic immunosuppressive therapy and time on dialysis.

Results

We found a favourable, but profoundly lower SARS-CoV-2 spike protein antibody response in comparison with a non-dialysis cohort (median 253.5 versus 1756 U/mL, P < 0.001). In multivariate analysis, previous COVID-19 infection (P < 0.001) and female gender were associated with a significantly higher vaccine response (P = 0.006) in haemodialysis patients, while there was a significant inverse correlation with increasing patient age and systemic immunosuppression (P < 0.001). There was no statistically significant correlation between the antibody titer and time on dialysis. Immune response in haemodialysis patients with a previous COVID-19 infection led to substantially higher antibody titers that were equal to those of vaccinated non-dialysis individuals with previous infection.

Conclusion

We strongly argue in favour of regular antibody testing after COVID-19 vaccination in haemodialysis patients. Further studies should elucidate the utility of booster vaccinations to foster a stronger and persistent antibody response.
Lethal and Sublethal Effects of Proteus, Matrine, and Pyridalyl on Frankliniella occidentalis (Thysanoptera: Thripidae)
Authors: Kordestani Mona , Mahdian Kamran , Baniameri Valiollah , Sheikhi Garjan Aziz
Published: June 2021

The western flower thrips (WFT), Frankliniella occidentalis (Pergande) is one of the most harmful pests of crops in greenhouses and fields. Considering the need for studies that introduce new insecticides for control of the WFT, the leaf dip method was carried out to study the acute toxicity of Proteus, matrine, and pyridalyl to adult thrips, and life tables were constructed to assess the impacts of sublethal concentrations (LC25) of these insecticides on the development and reproduction of the F1 generation. Bioassays showed that the toxicity of matrine (LC50: 45.9 µl ml–1) and Proteus (LC50: 54.5 µl ml–1) was higher than pyridalyl (LC50: 176.5 µl ml–1). At LC25 concentration, both Proteus and matrine prolonged the development period and reduced the survival rate of eggs, larval stages, and pupae in the F1 generation. Also, the adults’ longevity, oviposition duration, and the cumulative number of eggs laid per female (fecundity) were decreased significantly. Sublethal concentrations of Proteus and matrine inhibited the population growth rate relative to the control based on the predicted number of offspring. The lowest net reproductive rate (R0), intrinsic rate of increase (r), and finite rate of increase (λ) were estimated for Proteus (7.02 offspring/individual, 0. 0838 d–1, and 1. 08 d–1, respectively). In contrast, the WFT F1 generation that resulted from parent adults treated with pyridalyl was neither affected in their developmental time, nor fecundity, or the intrinsic rate of increase. According to our findings, all tested insecticides, especially Proteus, showed good potential for use in integrated pest management strategies against F. occidentalis.
The association between mean arterial pressure and outcomes in patients with cardiogenic shock: insights from the DOREMI trial
Authors: Parlow Simon , Di Santo Pietro , Mathew Rebecca , Jung Richard G , Simard Trevor , Gillmore Taylor , Mao Brennan , Abdel-Razek Omar , Ramirez F Daniel , Marbach Jeffrey A , Dick Alexander , Glover Christopher , Russo Juan J , Froeschl Michael , Labinaz Marino , Fernando Shannon M , Hibbert Benjamin ,   the CAPITAL DOREMI investigators
Published: June 2021

Aims

Cardiogenic shock (CS) is a state of low cardiac output resulting in end-organ hypoperfusion. Despite high in-hospital mortality rates, little evidence exists regarding the optimal mean arterial pressure (MAP) target in CS. We therefore evaluated the relationship between achieved MAP and clinical outcomes in patients with CS.

Methods and results

We performed a post hoc analysis of the CAPITAL DOREMI trial: a randomized, double-blind trial comparing dobutamine to milrinone in patients with CS. We divided patients into a high MAP group (average MAP ≥ 70 mmHg over the 36 h following randomization), and a low MAP group (average MAP < 70 mmHg). Our primary outcome included in-hospital all-cause mortality, resuscitated cardiac arrest, need for cardiac transplantation or mechanical circulatory support, non-fatal myocardial infarction, transient ischaemic attack or stroke, or initiation of renal replacement therapy. In total, 71 (37.0%) patients achieved an average MAP < 70 mmHg, and 121 (63.0%) achieved an average MAP ≥ 70 mmHg. The primary outcome occurred in 48 (67.6%) patients in the low MAP group and 51 (42.2%) patients in the high MAP group [adjusted relative risk (aRR) 0.70; 95% confidence interval (CI) 0.53–0.92; P = 0.01]. All-cause mortality occurred in 41 (57.8%) and 35 (28.9%) patients in the low and high MAP groups, respectively (aRR 0.56; 95% CI 0.40–0.79; P < 0.01). There were no significant differences in any secondary outcomes between each group.

Conclusions

In patients with CS treated with inotrope therapy, low MAP is associated with worse clinical outcomes. Randomized data evaluating optimal MAP targets in CS is needed to guide medical therapy.
Adjunctive surgery versus medical treatment among patients with cavitary multidrug-resistant tuberculosis
Authors: Vashakidze Sergo A , Gogishvili Shota G , Nikolaishvili Ketino G , Avaliani Zaza R , Chandrakumaran Abivarma , Gogishvili Giorgi Sh , Magee Mathew , Blumberg Henry M , Kempker Russell R
Published: June 2021

OBJECTIVES

Surgical resection is recommended as adjunctive treatment for multidrug-resistant (MDR) tuberculosis (TB) in certain scenarios; however, data are limited. We sought to evaluate the impact of surgery by comparing TB outcomes among patients with cavitary disease who received medical versus combined medical and surgical treatment.

METHODS

A cohort of all patients with cavitary MDR or extensively drug-resistant (XDR) TB treated in Tbilisi, Georgia, between 2008 and 2012. Patients meeting indications for surgery underwent adjunctive resection in addition to medical treatment. We compared TB outcomes (proportions achieving cure/complete) among patients who received adjunctive surgery to those who received medical treatment alone using an adjusted robust Poisson regression.

RESULTS

Among 408 patients, 299 received medical treatment alone and 109 combined medical and surgical treatment. Patients in the non-surgical group were older and had higher rates of tobacco and alcohol use and bilateral disease compared to the surgical group. Patients in the surgical group had higher rates of XDR disease (28% vs 15%). Favourable outcomes were higher among the surgical versus non-surgical group cohort (76% vs 41%). After adjusting for multiple factors, the association between adjunctive resection and favourable outcome remained (adjusted risk ratio 1.6, 95% confidence interval 1.3–2.0); the relationship was also observed in secondary models that excluded patients with bilateral disease (contraindication for surgery) and patients receiving <6 months of treatment. Major postoperative complications occurred among 8 patients (7%) with no postoperative mortality.

CONCLUSIONS

Adjunctive surgery is safe and may improve the effectiveness of treatment among select patients with cavitary MDR- and XDR-TB.
European Heart Journal quality standards
Authors: Alfonso Fernando , Torp-Pedersen Christian , Carter Rickey E. , Crea Filippo
Published: June 2021

The aim of the European Heart Journal (EHJ) is to attract innovative, methodologically sound, and clinically relevant research manuscripts able to change clinical practice and/or substantially advance knowledge on cardiovascular diseases. As the reference journal in cardiovascular medicine, the EHJ is committed to publishing only the best cardiovascular science adhering to the highest ethical principles. EHJ uses highly rigorous peer-review, critical statistical review and the highest quality editorial process, to ensure the novelty, accuracy, quality, and relevance of all accepted manuscripts with the aim of inspiring the clinical practice of EHJ readers and reducing the global burden of cardiovascular diseases. This review article summarizes the quality standards pursued by the EHJ to fulfill its mission.
Precarious work increases depression-based disability among male employees
Authors: Pyöriä Pasi , Ojala Satu , Nätti Jouko
Published: June 2021

Background

Precarious employment is a potent occupational health risk, but little is known about its association with work-related disability and its causes. This study analyzes whether employment precariousness is associated with receiving disability pension (DP) due to depression and whether this differs according to gender.

Methods

Statistics Finland’s Quality of Work Life Surveys (1997, 2003, 2008 and 2013) were merged with register-based DP data obtained from the Finnish Centre for Pensions. The survey material was used to measure employment precariousness using five variables: fear of job loss, poor employability prospects, previous unemployment, low earnings and temporary contracts. We followed 20–60-year-old employees until 2016 and studied Cox proportional hazard ratios (HRs) for receiving DP among women and men, adjusting for sociodemographic covariates, working conditions and health at baseline.

Results

The overall risk of receiving DP tended to increase as precarious job features accumulated. Among men, a higher risk of receiving DP due to depression was associated with previous unemployment [HR 2.2, 95% confidence interval (CI) 1.1–4.2] and poor employability (HR 2.4, 95% CI 1.3–4.7), whereas no corresponding association was found among women.

Conclusions

Employment precariousness may reflect a psychological stress mechanism that predisposes the individual to mental health problems, predicting future disability. Work disability risk shows gendered differences depending on the cause of DP. Promoting employability at workplace and policy levels could offset the health risks associated with precariousness.
Robust estimation via generalized quasi-gradients
Authors: Zhu Banghua , Jiao Jiantao , Steinhardt Jacob
Published: June 2021

We explore why many recently proposed robust estimation problems are efficiently solvable, even though the underlying optimization problems are non-convex. We study the loss landscape of these robust estimation problems, and identify the existence of ’generalized quasi-gradients’. Whenever these quasi-gradients exist, a large family of no-regret algorithms are guaranteed to approximate the global minimum; this includes the commonly used filtering algorithm. For robust mean estimation of distributions under bounded covariance, we show that any first-order stationary point of the associated optimization problem is an approximate global minimum if and only if the corruption level $\epsilon < 1/3$. Consequently, any optimization algorithm that approaches a stationary point yields an efficient robust estimator with breakdown point $1/3$. With carefully designed initialization and step size, we improve this to $1/2$, which is optimal.

For other tasks, including linear regression and joint mean and covariance estimation, the loss landscape is more rugged: there are stationary points arbitrarily far from the global minimum. Nevertheless, we show that generalized quasi-gradients exist and construct efficient algorithms. These algorithms are simpler than previous ones in the literature, and for linear regression we improve the estimation error from $O(\sqrt{\epsilon })$ to the optimal rate of $O(\epsilon )$ for small $\epsilon $ assuming certified hypercontractivity. For mean estimation with near-identity covariance, we show that a simple gradient descent algorithm achieves breakdown point $1/3$ and iteration complexity $\tilde{O}(d/\epsilon ^2)$.
Evaluation of Inappropriate COVID-19 RT–PCR Test Utilization at an Academic Medical Center
Authors: Hardy Naomi L , Luethy Paul M
Published: June 2021

Background

An evolving COVID-19 testing landscape and issues with test supply allocation, especially in the current pandemic, has made it challenging for ordering providers. We audited orders of the Xpert® Xpress SARS-CoV-2 PCR with reverse transcription (RT–PCR) platform—the fastest of several other testing modalities available—to illuminate these challenges utilizing a multidisciplinary laboratory professional team consisting of a pathology resident and microbiology laboratory director.

Methods

Retrospective review of the first 5 hundred Xpert Xpress SARS-CoV-2 RT–PCR test orders from a 2-week period to determine test appropriateness based on the following indications: emergency surgery, emergent obstetric procedures, initial behavioral health admission, and later including discharge to skilled care facilities and pediatric admissions. Our hypothesis was that a significant proportion of orders for this testing platform were inappropriate.

Results

On review, a significant proportion of orders were incorrect, with 69.8% (n = 349, P < 0.0001) not meeting indications for rapid testing. Of all orders, 249 designated as emergency surgery were inappropriate, with 49.0% of those orders never proceeding with any surgical intervention; most of these were trauma related (64.6% were orders associated with a trauma unit).

Conclusions

Significant, pervasive inappropriate ordering practices were identified at this center. A laboratory professional team can be key to identifying problems in testing and play a significant role in combating inappropriate test utilization.
Providing domperidone throughout lactation enhances sow lactation performance
Authors: Farmer Chantal , Palin Marie-France
Published: June 2021

The goal of this project was to determine the effects of domperidone given throughout lactation on hormonal and metabolic status, lactational performance, and gene expression in mammary epithelial cells of sows. Second parity sows were divided in two treatment groups: 1) daily intramuscular injections with canola oil (Control, CTL, n = 24), or 2) daily intramuscular injections with 0.5 mg/kg body weight (BW) of domperidone (DOMP, n = 23). Injections were given at 08h05 starting the day after farrowing until weaning. Over the first 4 d of treatment, DOMP sows also received 0.5 mg/kg BW of domperidone per os twice daily, whereas CTL sows were fed the vehicle. Litter size was standardized to 11 ± 1 within 24 h of birth and piglets were weighed at birth, 24 h postpartum, and on days 7, 22 (weaning on day 23), 35, and 56. Sow feed intake was recorded daily. Representative milk samples were obtained aseptically on day 21 of lactation from 15 sows per treatment for compositional analyses and milk fat globules were used to measure mRNA abundances of various genes. Jugular blood samples were obtained from all sows on days 2, 8, 16, and 23 of lactation to measure concentrations of prolactin, insulin-like growth factor-1 (IGF-1), leptin, adiponectin, insulin, glucose, urea, and free fatty acids (FFA). Concentrations of prolactin (P < 0.001) and FFA (P < 0.01) were increased in DOMP compared with CTL sows, whereas concentrations of insulin were decreased (P < 0.05). Urea concentrations were increased by treatment (P < 0.05) on days 16 and 23 of lactation, and those of IGF-1 were increased (P < 0.01) on day 16. Piglets from DOMP sows were heavier than those from CTL sows on day 22 (P < 0.01). Milk composition was unaffected by treatment. The mRNA abundance in milk fat globules for casein beta and whey acidic protein were lower (P ≤ 0.05) in DOMP than CTL sows. The long form of the prolactin receptor and the signal transducer and activator of transcription 5A mRNA abundances tended to be lower (P < 0.10) in DOMP than CTL sows. In conclusion, hyperprolactinemia induced by domperidone during lactation affected the endocrine and metabolite status of sows and stimulated growth of their suckling piglets.