bluuebunny/crossref_metadata_2025 huggingface dataset:
Intelligent Multi-Drive Inspection Technology for Water Environment of Cable Pipe Gallery Based on Random Forest Algorithm
Authors: Wang Lei , Cheng Yuan , Li XiaoJun , Qin Bo
Published: October 2020

Image technology is widely used in intelligent applications. Based on the intelligent multi-drive patrol inspection of the water environment of cable duct corridors, the original technical methods and corresponding algorithms cannot be effectively solved. This paper mainly studies the intelligent multi-drive patrol inspection technology for the water environment of cable duct corridor based on random forest algorithm. In this paper, a feature that is insensitive to changes in illumination is designed and used for image change detection. At the same time, the Haar-like feature is improved according to this feature. The improved Haar-like feature and random forest calculation are used to detect the change area of the image. The experiment in this paper found that the cable fire of underground comprehensive pipe corridor burned more violently during 200 s-600 s. This stage only accounted for 22.3% of the burning time, but contributed 73.4% of the mass loss. The experimental results in this paper show that the intelligent multi-drive patrol inspection technology for the water environment of cable duct corridors based on the random forest algorithm is in line with the actual application standards and has important significance in practical applications.
Research on Cost Control of Exhibition Advertising Based on Scheduling Plan
Authors: Zhang Yan
Published: October 2020

With the development and innovation of my country’s market economy, advertising is playing an increasingly important role in the market, and the effective combination of advertising and exhibition marketing can greatly increase product sales and promote economic development. The purpose of this article is to study the control of exhibition advertising costs in the scheduling plan. In order to evaluate whether the scheduling is efficient and reasonable, this paper proposes an evaluation model of the exhibition advertisement scheduling plan with the best overall cost. This article focuses on the development of conference and exhibition advertising cost control based on the scheduling plan, and a stable dynamic advertising cost model established by the economic market to fully display advertising information to enterprises in related fields of the technology market, and at the same time release their needs, to obtain the optimal solution. The experimental results show that through short-term scheduling and scheduling, the cost of advertising in exhibitions can be dynamically controlled in real time and maximized in the pursuit of benefits, so as to achieve mutual benefit and win-win results for advertisers and enterprises.
RETRACTED: Research on College English Online Learning Platform Model Based on Big Data Technology
Authors: Zhang Yang
Published: October 2020

In this era of rapid development, the level of human science and technology is constantly improving. With the continuous development of the times and the continuous progress of society, big data technology has been widely used in our daily production and life. The research of College English online learning platform model is a hot topic in the teaching of many college English majors. In order to better study the model of College English online learning platform, many colleges and universities put forward the method of using big data technology to analyze the research of College English network learning platform model, through the big data technology to college English Based on the prediction of the development of e-learning platform model, combined with the new requirements for the research of College English online learning platform model in this era of rapid development, this paper provides guidance for the research of College English online learning platform model in China. Through the analysis, it is found that the method of using big data technology to analyze the model of College English online learning platform has a profound guiding role in the research of College English online learning platform model.
Application of Unbalanced Data Classification Algorithm in Quantitative Financial Risk Management
Authors: Zhu JinPeng , Wang HanChen
Published: October 2020

The global financial crisis that has erupted many times in recent years has not only harmed the financial systems of various countries, but even severely hit the economies of various countries. Therefore, the importance of financial risk early warning has become more prominent and the challenges facing it have become more severe. In view of this, it is very important to explore an extreme risk early warning model that suits the reality of the Chinese financial market, and to accurately predict and prevent extreme financial risks. This article first constructs the model’s early-warning indicator system, and determines the state indicators by synthesizing the two state indicator definition methods based on the crisis period and EVT, in order to determine whether extreme financial risks occur in the financial market at a certain time. The prediction performance of the improved SVM under different unbalanced sample data sets is compared. It is highly feasible to use it for early warning of extreme risks in China’s financial market. This paper presents a BADASYN algorithm based on boundary sample adaptive synthesis at the data level. The algorithm first finds a small number of samples in the class boundary region, then adaptively synthesizes some samples according to their distribution, and adds the newly synthesized samples to the training set. In the data set sampled by BADASYN, the support vector of the trained SVM model is mainly composed of newly synthesized samples, and finally the separation hyperplane is close to multiple types of samples. Experimental research shows that after testing SVMs constructed with four kernel functions, the prediction accuracy of each model is very high, reaching more than 93%, reflecting the stability of SVM prediction performance.
Preschool Teacher Education System Based on Remote Network System
Authors: Xu Meng
Published: October 2020

How to achieve effective communication between school parents on online platforms, online office work on campus, and storage and sharing of massive learning resources will surely become important issues facing early childhood education. The purpose of this article is to design a kindergarten teacher education system based on the remote network system. This paper uses the increasingly perfect non-relational database technology to help store massive big data resources, and uses its characteristics to improve the access and operation speed of big data resources, which will effectively solve campus information management and improve the processing efficiency of resource storage and access. Develop a comprehensive platform for online office, communication, learning, and resource sharing for early childhood education. Research In order to realize the storage of massive data and the rapid operation of the system, the system database chose a complementary method of combining MySQL database and MongoDB database, using MySQL to store data involving operations such as relational lookup, and using MongoDB to store various file and photo resources. The system is developed using the SSH framework. First, the functional and non-functional requirements of the system are analyzed. The functional requirements use UML to establish the overall use case diagram of the foreground and background modules respectively. Through the complementary technology of MySQL and MongoDB, the storage and access efficiency of big data and the operating speed of the system’s functional modules are greatly improved.
Research and Hardware Design of Image Processing Algorithm Based on FPGA
Authors: Wei Yanping , Xiao Hailiu
Published: October 2020

With the continuous development of computer technology and microelectronics technology, image processing technology is constantly being improved, especially real-time image processing technology has been studied by a large number of scholars. This article aims to achieve the purpose of FPGA-based fast image processing through the research of FPGA’s fast image processing algorithm. Based on the advantages of FPGA high-speed hardware computing and parallel computing, this paper proposes a design based on FPGA parallel dual template strategy, and designs a comparative experiment to verify. Obtain objective evaluation indexes of image processing results through experiments, and analyze the data results. The experimental results show that: the implementation of the mean filter algorithm based on FPGA parallel dual templates, the time required is about half that of the mean filter algorithm based on FPGA single templates. Relative to the reference Matlab software programming method to achieve 678 times performance improvement. It shows that the realization method of the mean filter algorithm based on FPGA parallel dual template is feasible. Give full play to the advantages of FPGA parallel processing data, improve the processing speed of the image algorithm module.
VR Open Computer Network Virtual Laboratory Based on Big Data Technology
Authors: Xiao Shoubai
Published: October 2020

The rapid development of computer technology and network bandwidth has produced unprecedented influence on the way of human learning. Along with the humanized development of computer software technology and high-level program language, experimental teaching is gradually becoming virtualized. Not only a variety of multimedia teaching courseware emerges one after another, but also a large number of virtual laboratories appear on the network. Virtual laboratory is essentially the simulation of real experiment scene, in which students should have similar experience and the same learning effect as real laboratory. Therefore, the virtual laboratory should be able to satisfy the students to carry out autonomous exploratory operation. The purpose of this paper is to study the open computer network virtual laboratory based on big data technology. This paper first introduces the meaning of big data technology, then studies the content of video decoding technology, and then introduces the definition scope and characteristics of virtual reality technology. This paper designs and implements VR open computer network virtual laboratory based on big data technology. The test results show that the system designed in this paper has good performance. The CPU consumption rate of the system server designed in this paper only accounts for 4.5%.
Economic evaluation model of greenhouse soil information collection technology based on fuzzy comprehensive evaluation
Authors: Lu Shuisheng , Sun Xiaoying
Published: October 2020

The purpose of soil information collection is to grasp the real-time status of soil, which is of great significance to improve the yield and quality of crops and improve the ecological environment. The purpose of this paper is to build a comprehensive benefit evaluation model of soil information collection technology based on the fuzzy comprehensive evaluation of the economy of greenhouse soil information collection technology. The experimental results show that in terms of economic and environmental benefits, the scores of wired communication technology and wireless acquisition technology are average and good respectively. In terms of social benefits, the scores of wired communication technology and wireless acquisition technology are good and excellent respectively, the scores of social benefits, the scores of wired communication technology and wireless acquisition technology are good and excellent respectively, the scores of comprehensive benefits of wired communication technology and wireless acquisition technology are general and good respectively, and the membership degrees of corresponding grades are 0.4144 and 0.5898 respectively.
RETRACTED: Network Information Security Risk Assessment Based on Artificial Intelligence
Authors: Wang Yaosheng
Published: October 2020

With the development of society and the progress of human civilization, science and technology are more and more widely used in people’s daily production and life, and artificial intelligence technology is also more and more widely used in this era. With the advent of the information age, the development of the network is faster and faster, and the popularization rate is higher and higher. The network information security problem has gradually become a hot issue of social concern question. With the increasingly open network environment, network attack tools become easier to obtain, more automated, more intelligent, which poses a huge challenge to information security protection. Therefore, in order to deal with the network information security problems in this information age, this paper studies the method of network information security risk assessment and analysis based on artificial intelligence, through in-depth study of network information security, simulate attacks on network information, so as to find the weakness of the current network information security system. In the research, a large number of network information security vulnerabilities are found by simulating the attack of network information, so as to repair the vulnerabilities one by one. Through the analysis, this paper studies the Content Filtering Gateway filtering system to filter out 94.8% of the virus and garbage, improve the network information security rate.
Application of Task Driven Method in the Computer Application Basic Course
Authors: Zhang Yan , Sun Shujie
Published: October 2020

In view of the existing that occupation college students’ learning interest is not high, docking and enterprise skills learned cannot work well in the computer application basic course, we use the task driven teaching method instead of the traditional, summarized the eight major tasks of the enterprise and its sub tasks based on the real work, and puts forward some problems should pay attention to in the process of operation.
Mooc Method of Military Theory Course Based on Network Technology
Authors: Zhao Jing-Yuan
Published: October 2020

With the development of information technology and the increasingly mature of network teaching, it has become an indispensable part of teaching reform to introduce moocs into the public curriculum system of colleges and universities. Combined with the characteristics of the Internet and big data, moocs and teaching have greatly improved the teaching effect and brought many advantages to the traditional teaching methods. Under the background of information technology era, military theory courses in colleges and universities have ushered in new development opportunities. Faced with the new teaching form of moocs, many colleges and universities have successively introduced military theory moocs, but the effect is not satisfactory. Therefore, it is very important to accelerate the combination of theory and online and optimize the teaching methods of military theory. The purpose of this paper is to explore the research on the application of military theory courses under the theoretical basis of network technology, so as to update the existing teaching Internet model by combining the application technology of Internet of things. This paper will adopt the research method of concrete analysis of specific problems and make data comparison to draw conclusions. The research results of this paper show that the advantages and disadvantages of moocs reflect the teaching reform path of military theory course based on moocs, which requires the establishment of professional moocs team and the provision of abundant course resources.
A Newton Type Iterative Method with Seventh-Order Convergence
Authors: Tao Yuxi , Wan Xiaofeng
Published: October 2020

We based on King Method, a seventh-order convergent Newton type iterative scheme is proposed in order to solving the root of nonlinear equation, the efficiency index of proposed method is 1.627. Numerical experiment show that the new iterative scheme has some advantages over other iterative schemes.
Molecular modelling as a downstream effort in the discovery of novel anionic sulphate surfactants
Authors: Iswanto P , Delsy E V Y
Published: October 2020

Sulphate anionic surfactant is a type of surfactant that is widely used as a cleaning agent. The discovery and development of anionic sulphate surfactant molecule is necessary because it has a huge impact, both in science and economics. Molecular modelling to produce new anionic sulphate surfactant molecules has been carried out. The mathematical equation of the Quantitative Structure-Property Relationship (QSPR) based on Ab Initio has been obtained. Molecules that were candidates for structural modelling and modification were those that have the smallest critical micelle concentration (CMC). The smallest experimental data was C16H33SO4Na with a CMC value = 0.000579 M. The result of this study was CnH3sSO4Na molecules with a theoretical CMC value of 0.000515 M.
Glucose-water interactions at increasing concentrations and temperatures as revealed by Near-Infrared Spectroscopy
Authors: Rondonuwu F S , Setiawan A , Muninggar J , Karwur F F
Published: October 2020

Water is an essential molecule and one of the most intensive research subjects, yet it is a peculiar molecule. The non-invasive measurement of blood glucose levels by near-infrared spectroscopy requires detailed information about the glucose-water interactions. The glucose in water induces strong hydrogen bonds and may influence the tetrahedral structure of water molecules. This knowledge is essential in constructing a non-invasive calibration of the blood glucose prediction model. How they are related to the absorption spectra of water and glucose is particularly valuable to comprehend. The evaluations were carried out using near-infrared spectroscopy, tracing changes in absorption intensity and shifts in corresponding peaks with glucose varying at an increasing concentration from a 0-0.9 molar fraction. The near-infrared spectra analysed were around 6900 cm-1 and 4716 cm-1 corresponding to the overtone and the combination band of water and glucose absorptions, respectively. The analysis suggests that glucose prefers to enter a water cluster, rather than bind to free molecules, and induce bond breaking at low glucose concentrations at which the molecular fraction is less than 0.05.
Ab initio computational study: Adsorption of CO molecule on various base metal oxide surfaces
Authors: Kurnia I , Siahaan P , Suseno A
Published: October 2020

The use of some base metal oxide already widely studied for having beneficial properties in CO oxidation catalytic system. The properties of these base metals such as lower working temperature, high CO affinity, and economically cheaper would be beneficial for this solid system catalyst. The study of various base metal oxides shown these kinds of characteristics, but there still a few analyses of comparison among the various base oxide metals used as the support system for the oxidation reaction catalytic system. This study would give a comparison in the difference of the adsorption energy of various base oxide metals. This adsorption energy is one factor that promoting the activity of the catalytic system due to its affinity to the reactant on their surfaces. The DFT ab initio calculation for this comparison shows that NiO is the base metal oxide that having the highest CO adsorption energy. This oxide could be a potential support system combined with potential solid oxidative catalytic system.
The effectiveness of online learning by EdPuzzle in polymer materials on students’ problem-solving skills
Authors: Giyanto  , Heliawaty L , Rubini B
Published: October 2020

This study aims to produce EdPuzzle content in polymer materials and examine its effectiveness on students’ problem-solving skills. The method used in this research is experimental research, employing a pre-test post-test one-group design through online learning. The subject of this study is 70 tenth grade students. Data were collected using students’ problem-solving skills tests and analysis of the learning process to determine the effectiveness of online learning. The data obtained were then analyzed using quantitative descriptive. The results showed that learning using EdPuzzle is statistically very significant in improving students’ problem-solving skills and is quite effective in online learning. The study concludes that EdPuzzle is quite effective to improve students’ problem-solving skills which are characterized by an increase in the score of pre-test to post-test, with an N-gain of 63%. The implementation of online learning EdPuzzle is quite effective with an effectiveness score reaching 91%.
Study of final temperature and heating rate variation to pyrolysis of Acacia (Acacia mangium W.) wood waste
Authors: Pranoto  , Nugrahaningtyas K D , Putri R N O
Published: October 2020

The research pyrolysis of acacia wood waste has been carried out. This research was conducted to determine the optimal conditions that can be used for the pyrolysis process of acacia sawdust and the effect of the pyrolysis products. The pyrolysis process was carried out on the principle of slow pyrolysis using a batch type reactor. Pyrolysis was carried out by varying the final temperature of pyrolysis 375°C, 475°C, and 575°C and variations of heating rates 5°C/min, 10°C/min, and 15°C/min with a holding time of 20 minutes. The content of cellulose, hemicellulose and lignin at raw material was determined with the van soest method and the values are 32.75%, 35.16%, and 16.81%, respectively. The result of the pyrolysis process in the form of char at the final temperature of 575°C with a heating rate of 5°C/min produces a calorific value of 6.816 cal/gram. In the tar (oil) tested using GCMS, the acacia tar contains quite high phenol, acetic acid, 2 propanone. The results of pyrolysis can be seen that the highest activation energy value is found in the pyrolysis process with a variation of the heating rate of 15°C/min and the final temperature of the pyrolysis 575°C which is 49.56 kJ/mol.
Carbon and zinc oxide synthesized by gelatin template as potential material for fight viruses covid-19: Future potential material
Authors: Ulfa M , Prasetoko D , Fajar M
Published: October 2020

The COVID-19 pandemic that attacks the respiratory tract is spreading rapidly to all regions in Indonesia. In this pandemic situation, daily products such as sprays, tissue paper and masks need to be developed using nanomaterials. In this paper, graphite carbon and zinc oxide were synthesized using gelatin as a pore guide. The morphology and character of graphite carbon and zinc oxide were characterized by SEM, EDX and XRD to address appropriate active centers to counteract the protein spike interaction in covid-19 with ACE in the human body. Several illustrations are presented in this paper to understand the opportunity of carbon and zinc oxide materials as the basis for making antiviral devices to store viral molecules so that human-to-human transmission can be prevented.
Silver nanoparticles (AgNPs) as photocatalyst in the photodegradation of rhemazol brilliant blue
Authors: Suprihatin I E , Lestari G A D , Mardhani R , Edoway V
Published: October 2020

The phytosynthesis of silver nano particles (AgNPs) and its use as a photocatalyst to photodegrade rhemazol brilliant blue are discussed. The AgNPs was prepared by reducing Ag+ from 0.01 M AgNO3 using frangipani (Plumeria rubra) water extract. The photodegradation was conducted by irradiating the suspension of the coloring agent and the AgNPs with UV rays at 259 nm. The optimum p H, AgNPs volume, and irradiation time were determined by measuring the degradation percentages at various pH, AgNPs volumes, and irradiation times. The study found that the optimum photodegradation occurred at pH 4, using 10 mL AgNPs, and irradiated for 60 minutes. Under the optimum conditions, AgNPs is capable of effectively photodegrading (97.84 ± 1.09) % of 600 ppm rhemazol brilliant blue
Synthesis of Carbon Nanotubes (CNT) by Chemical Vapor Deposition (CVD) using a biogas-based carbon precursor: A review
Authors: Saputri D D , Jan’ah A M , Saraswati T E
Published: October 2020

Carbon is the fourth most abundant element in the universe. Among all carbon allotropes, carbon nanotube (CNT) with a cylindrical tube structure becomes an attractive carbon nanomaterial due to its unique physical and chemical properties. The typical gas sources that are usually used in CNT synthesis are mostly hydrocarbons, e.g., alcohol, methanol, methane (CH4), ethylene (C2H4), acetylene (C2H2), propane (C3H8), and cyclohexane (C6H12). Unfortunately, those carbon precursors are not environmentally friendly due to their origin from fossil fuels. Considering its continuity production, utilizing “green” alternatives and inexpensive materials will be more promising for industrial-scale production. Biogas is one of the alternative ideas as a carbon precursor in the process of CNT synthesis. Biogas consists of 40–60% methane (CH4), 40–60% carbon dioxide (CO2), and traces of nitrogen (N2), oxygen (O2), hydrogen sulfide (H2S), hydrogen (H2), and ammonia (NH3). The most commonly used to produce CNT is CH4through chemical vapor deposition (CVD). CVD is the most expectant and scalable method for future power and electronic devices with its economical and straightforward friendly design.
The Effect of Mandatory Insurer Reporting on Settlement Delay
Authors: Heaton Paul
Published: October 2020

To improve their fiscal position, Medicare and some state Medicaid programs have recently taken steps to mandate reporting of personal injury awards and thus facilitate subrogation against such awards. Participants in the tort system have argued these additional reporting requirements might delay settlement of claims, harming both plaintiffs and defendants. This article examines this problem empirically, using a rich, national data set of closed automobile bodily injury claims. Using a differences-in-differences research design that exploits the introduction of a new Medicare reporting requirement in 2011, it demonstrates that mandated reporting increased time to settlement by 19%, or an average of 58 days. Robustness checks using data from closed malpractice claims reveal a similar delay. Conservative calculations suggest such delays could generate hundreds of millions of dollars in waiting costs each year. Policymakers should be aware of and seek to avoid such costs as they assess whether and how to expand reporting of personal injury awards.
Medium-term results of arthroscopic treatment for femoroacetabular impingement
Authors: Migliorini Filippo , Liu Yu , Catalano Giovanni , Trivellas Andromahi , Eschweiler Jörg , Tingart Markus , Maffulli Nicola
Published: October 2020

Introduction

Femoroacetabular impingement (FAI) is a dynamic pathomechanical process of the femoral head–neck junction. Arthroscopic surgery for FAI has increased exponentially in the last decade, and this trend is expected to increase.

Source of data

Recent published literatures.

Areas of agreement

FAI promotes quick rehabilitation and low complication rates in the short-term follow-up.

Areas of controversy

Despite the growing interest on arthroscopic surgery for FAI, current evidence regarding the medium- and long-term role of arthroscopy are unsatisfactory.

Growing points

Systematically summarize current evidences, analyse the quantitative available data and investigate the medium- and long-term outcomes of arthroscopic surgery for FAI.

Areas timely for developing research

Arthroscopic surgery achieves very satisfactory outcomes for patients with FAI at a mean follow-up of 4 years.
The minimum-mortality estimated glomerular filtration rate percentile shifts upward in the aged population: a nationwide population-based study
Authors: Kim Yaerim , Lee Soojin , Lee Yeonhee , Park Sehoon , Park Sanghyun , Paek Jin Hyuk , Park Woo Yeong , Jin Kyubok , Han Seungyeup , Kim Yong Chul , Han Seung Seok , Lee Hajeong , Lee Jung Pyo , Joo Kwon Wook , Lim Chun Soo , Kim Yon Su , Han Kyungdo , Kim Dong Ki
Published: October 2020

Background

The estimated glomerular filtration rate (eGFR) is a biomarker not only for kidney function, but also for major clinical outcomes. We aimed to evaluate the patterns of mortality across the entire eGFR percentile spectrum using a population-based dataset.

Methods

We retrospectively reviewed the National Health Insurance Service (NHIS) database for people who received nationwide health check-ups from 2009 to 2012. Subjects who were ≥45 years old and had one or more serum creatinine values available were included in the study. The primary outcome was all-cause mortality as a function of eGFR percentile.

Results

The middle-aged group (45–64 years) showed a U-shaped pattern of association between eGFR percentile and all-cause mortality. The minimum-mortality eGFR percentile was shifted upward in the elderly group (≥65 years). Specifically, the minimum-mortality eGFR percentiles were the 28th percentile (83.8 mL/min/1.73 m2) for middle-aged males, the 63rd percentile (86.2 mL/min/1.73 m2) for elderly males, the 42nd percentile (102.8 mL/min/1.73 m2) for middle-aged females and the 75th percentile (90.1 mL/min/1.73 m2) for elderly females. Diabetes and hypertension shifted the minimum-mortality eGFR percentile upward in the middle-aged group. This pattern was attenuated in the elderly group.

Conclusions

The eGFR percentile showing minimum mortality moves upward in the aged population as well as patients with diabetes and hypertension, which might reduce the clinical significance of hyperfiltration. Risk stratification for mortality should be approached differently according to the specific conditions of the patient group.
Units of measurement and the inverse hyperbolic sine transformation
Authors: Aihounton Ghislain B D , Henningsen Arne
Published: October 2020

The inverse hyperbolic sine (IHS) transformation is frequently applied in econometric studies to transform right-skewed variables that include zero or negative values. We show that regression results can heavily depend on the units of measurement of IHS-transformed variables. Hence, arbitrary choices regarding the units of measurement for these variables can have a considerable effect on recommendations for policies or business decisions. In order to address this problem, we suggest a procedure for choosing units of measurement for IHS-transformed variables. A Monte Carlo simulation assesses this procedure under various scenarios, and an empirical illustration shows the relevance and applicability of our suggested procedure.
A new calcium score to predict paravalvular leak in transcatheter aortic valve implantation
Authors: Kofler Markus , Meyer Alexander , Schwartz Julian , Sündermann Simon , Penkalla Adam , Solowjowa Natalia , Klein Christoph , Unbehaun Axel , Falk Volkmar , Kempfert Jörg
Published: October 2020

OBJECTIVES

The present study sought to develop a reliable calcium score (Ca-score) to predict paravalvular leak (PVL) in patients undergoing transcatheter aortic valve (AV) implantation.

METHODS

A total of 965 patients were prospectively included from 2012 to 2019. Preprocedural contrast-media-enhanced computed tomography scans were analysed regarding the amount of AV cusp calcification and the presence of upper and lower left ventricular outflow tract calcification. The calcium volume threshold of each AV cusp [non-coronary cusp (NCC); left coronary cusp (LCC); right coronary cusp (RCC)] with optimal PVL prediction was defined using the Youden index value derived from receiver operating characteristic analysis. The final score was developed based on the multivariable regression analysis, while individual variables were weighted based on their corresponding odds ratio.

RESULTS

The AV calcium volume threshold with optimal PVL prediction was 733.6, 296.0 and 131.2 mm3 for the NCC, RCC and LCC respectively. Overall, calcification of the upper left ventricular outflow tract was present in 233 (23%), 111 (12%) and 304 (32%) of patients below the NCC, RCC and LCC respectively, while 260 (27%), 44 (5%) and 217 (23%) patients suffered from calcification under the NCC, RCC and LCC, respectively. A total Ca-score of ≥4 was present in 356 (37%) of patients and was independently associated with ≥ mild PVL [odds ratio 3.662; 95% confidence interval (2.740–4.911); P < 0.001]. The area under the curve of the Ca-score was 0.713 [95% confidence interval (0.678–0.748); P < 0.001].

CONCLUSION

The provided Ca-score independently correlates with the development of PVL and improves risk stratification in patients undergoing transcatheter AV implantation.
Farmer preferences for adopting precision farming technologies: a case study from Italy
Authors: Blasch J , van der Kroon B , van Beukering P , Munster R , Fabiani S , Nino P , Vanino S
Published: October 2020

Precision farming (PF) technologies can help to mitigate the environmental impact of agriculture by reducing fertiliser use and irrigation while saving cost for the farmer. However, these technologies are not widely adopted in Europe. We study farmers’ willingness to adopt PF technologies based on a choice experiment. Among other determinants, we explore the role of social influence for the valuation of PF technology features. The data are analysed using mixed and latent class logit models. Our results show that knowledge of fellow farmers who adopted the technology positively influences the valuation of PF technology features, stressing the importance of networks.
The Dynamic Proteome of Oligodendrocyte Lineage Differentiation Features Planar Cell Polarity and Macroautophagy Pathways
Authors: Pooyan Paria , Karamzadeh Razieh , Mirzaei Mehdi , Meyfour Anna , Amirkhan Ardeshir , Wu Yunqi , Gupta Vivek , Baharvand Hossein , Javan Mohammad , Salekdeh Ghasem Hosseini
Published: October 2020

Background

Generation of oligodendrocytes is a sophisticated multistep process, the mechanistic underpinnings of which are not fully understood and demand further investigation. To systematically profile proteome dynamics during human embryonic stem cell differentiation into oligodendrocytes, we applied in-depth quantitative proteomics at different developmental stages and monitored changes in protein abundance using a multiplexed tandem mass tag-based proteomics approach.

Findings

Our proteome data provided a comprehensive protein expression profile that highlighted specific expression clusters based on the protein abundances over the course of human oligodendrocyte lineage differentiation. We identified the eminence of the planar cell polarity signalling and autophagy (particularly macroautophagy) in the progression of oligodendrocyte lineage differentiation—the cooperation of which is assisted by 106 and 77 proteins, respectively, that showed significant expression changes in this differentiation process. Furthermore, differentially expressed protein analysis of the proteome profile of oligodendrocyte lineage cells revealed 378 proteins that were specifically upregulated only in 1 differentiation stage. In addition, comparative pairwise analysis of differentiation stages demonstrated that abundances of 352 proteins differentially changed between consecutive differentiation time points.

Conclusions

Our study provides a comprehensive systematic proteomics profile of oligodendrocyte lineage cells that can serve as a resource for identifying novel biomarkers from these cells and for indicating numerous proteins that may contribute to regulating the development of myelinating oligodendrocytes and other cells of oligodendrocyte lineage. We showed the importance of planar cell polarity signalling in oligodendrocyte lineage differentiation and revealed the autophagy-related proteins that participate in oligodendrocyte lineage differentiation.
Two Dualities: Markov and Schur–Weyl
Authors: Kuan Jeffrey
Published: November 2020

We show that quantum Schur–Weyl duality leads to Markov duality for a variety of asymmetric interacting particle systems. In particular, we consider the following three cases:

(1) Using a Schur–Weyl duality between a two-parameter quantum group and a two-parameter Hecke algebra from [6], we recover the Markov self-duality of multi-species ASEP previously discovered in [23] and [3].

(2) From a Schur–Weyl duality between a co-ideal subalgebra of a quantum group and a Hecke algebra of type B [2], we find a Markov duality for a multi-species open ASEP on the semi-infinite line. The duality functional has not previously appeared in the literature.

(3) A “fused” Hecke algebra from [15] leads to a new process, which we call braided ASEP. In braided ASEP, up to $m$ particles may occupy a site and up to $m$ particles may jump at a time. The Schur–Weyl duality between this Hecke algebra and a quantum group lead to a Markov duality. The duality function had previously appeared as the duality function of the multi-species ASEP$(q,m/2)$ [23] and the stochastic multi-species higher spin vertex model [24].
Computing Higher Symplectic Capacities I
Authors: Siegel Kyler
Published: November 2020

We present recursive formulas that compute the recently defined “higher symplectic capacities” for all convex toric domains. In the special case of four-dimensional ellipsoids, we apply homological perturbation theory to the associated filtered $\mathcal{L}_\infty $ algebras and prove that the resulting structure coefficients count punctured pseudoholomorphic curves in cobordisms between ellipsoids. As sample applications, we produce new previously inaccessible obstructions for stabilized embeddings of ellipsoids and polydisks and we give new counts of curves with tangency constraints.
Use of electronic health records to support a public health response to the COVID-19 pandemic in the United States: a perspective from 15 academic medical centers
Authors: Madhavan Subha , Bastarache Lisa , Brown Jeffrey S , Butte Atul J , Dorr David A , Embi Peter J , Friedman Charles P , Johnson Kevin B , Moore Jason H , Kohane Isaac S , Payne Philip R O , Tenenbaum Jessica D , Weiner Mark G , Wilcox Adam B , Ohno-Machado Lucila
Published: October 2020

Our goal is to summarize the collective experience of 15 organizations in dealing with uncoordinated efforts that result in unnecessary delays in understanding, predicting, preparing for, containing, and mitigating the COVID-19 pandemic in the US. Response efforts involve the collection and analysis of data corresponding to healthcare organizations, public health departments, socioeconomic indicators, as well as additional signals collected directly from individuals and communities. We focused on electronic health record (EHR) data, since EHRs can be leveraged and scaled to improve clinical care, research, and to inform public health decision-making. We outline the current challenges in the data ecosystem and the technology infrastructure that are relevant to COVID-19, as witnessed in our 15 institutions. The infrastructure includes registries and clinical data networks to support population-level analyses. We propose a specific set of strategic next steps to increase interoperability, overall organization, and efficiencies
Predictive Factors for Returning to Work in Burn Adult Patients That Were Working Before Their Injury
Authors: Tolentino-Bazán Karina , Chavez-Heres Tatiana , Morales-García Mariana , Macías-Hernández Salvador Israel , Ramírez-Ramírez Alma Citlallic , Velázquez-Bustamante Ana Esthela , Rhoades-Torres Gerald Martin , Velez-Palafox Mario
Published: October 2020

The goal of this study was to identify predictive factors that influence return to work in burn patients treated at the National Center for Burn Care and Research at the National Institute of Rehabilitation (CENIAQ) in México City. This is a retrospective case–control study that included all burn patients of working age (16–91 years old), treated between January 2011 and December 2013. Patients were divided into two groups: unemployed (no work group) and those who returned to work (RTW). The statistical analysis was performed by a logistic regression univariate and multivariate analysis. A total of 210 subjects were included in the study. The mean age was 38 ± 15 years and 66.7% of them were male. One hundred sixty-five patients (79.6%) were able to return to work after treatment. Through univariate analysis it was found that the predictive factors for not returning to work after injury were: education lower than elementary school (OR: 3.59; CI 95%: 1.79–7.32); history of epilepsy prior to burn injury (OR: 10.18; CI 95%: 1.9–54.43); total burned surface area (TBSA) ≥20% (OR: 2.87; CI 95%: 1.46–5.64); third-degree burns (OR: 2.64; CI 95%: 1.32–5.29); hospital stay ≥20 days (OR: 2.8; CI 95%: 1.47–5.68); length of stay in the burn intensive care unit (OR: 2.5; CI 95%: 1.25–4.97); secondary infection (OR: 2.24; CI 95%: 1.15–4.38); amputations (one or more regardless of amputation level; OR: 8; CI 95%: 2.52–25.30); burn of the upper extremity (shoulder; OR: 2.21; CI 95%: 0.97–5.03); thigh (OR: 2.41; CI 95%: 1.32–5.14); and knee (OR: 2.81; CI 95%: 1.21–6.55). Some of these factors have never been reported by other authors.
A Cautionary Tale of Etanercept Use in Patients With Toxic Epidermal Necrolysis
Authors: Faris Janie , Wilson Jordan , Dolman Heather S , Isaacson Andrew , Baylor Alfred E , Tyburski James G , White Michael T
Published: October 2020

Toxic epidermal necrolysis (TEN) is a severe cutaneous reaction that can be life-threatening. In the United States, there are no established guidelines for the treatment of TEN. Supportive care including fluids and supportive therapies are the current recommendations. Research surrounding TEN involves mostly case studies or small, uncontrolled studies. Recent literature describes the use of tumor necrosis factor blockers in the treatment of TEN with positive results. These case reports describe decreased time to reepithelization, hospital length of stay, and minimal side effects. Conversely, we present three fatalities after the administration of etanercept.
Social Norms and Fertility
Authors: Myong Sunha , Park JungJae , Yi Junjian
Published: October 2020

We document three stylized facts on marriage and fertility patterns in East Asian societies: (i) their marriage rates are among the highest in the world, but their total fertility is the lowest; (ii) although they have the lowest total fertility, almost all married women have at least one child; and (iii) almost no single women have any children. As these societies have been influenced by Confucianism over millennia, marriage and fertility decisions are potentially shaped by two social norms: the unequal gender division of childcare and the stigma attached to out-of-wedlock births. We present a model incorporating the two social norms, and structurally estimate it using data from South Korea. We find that the social norm of unequal gender division of childcare plays a significant role in the low fertility rates, especially for highly educated women. However, the social stigma attached to out-of-wedlock births has modest effects on the childlessness rate for single women. Our results show that the tension between the persistent gender ideology and the rapid socioeconomic development is the main driving force behind the unique marriage and fertility patterns in East Asian societies.
NEVBD Pesticide Resistance Monitoring Network: Establishing a Centralized Network to Increase Regional Capacity for Pesticide Resistance Detection and Monitoring
Authors: Burtis James C , Poggi Joseph D , McMillan Joseph R , Crans Scott C , Campbell Scott R , Isenberg Amy , Pulver Janice , Casey Patti , White Kerry , Zondag Craig , Badger John R , Berger Russell , Betz John , Giordano Stacey , Kawalkowski Malgorzata , Petersen John L , Williams Gregory , Andreadis Theodore G , Armstrong Philip M , Harrington Laura C
Published: October 2020

Pesticide resistance in arthropod vectors of disease agents is a growing issue globally. Despite the importance of resistance monitoring to inform mosquito control programs, no regional monitoring programs exist in the United States. The Northeastern Regional Center for Excellence in Vector-Borne Diseases (NEVBD) is a consortium of researchers and public health practitioners with a primary goal of supporting regional vector control activities. NEVBD initiated a pesticide resistance monitoring program to detect resistant mosquito populations throughout the northeastern United States. A regionwide survey was distributed to vector control agencies to determine needs and refine program development and in response, a specimen submission system was established, allowing agencies to submit Culex pipiens (L.) (Diptera:Culicidae) and Aedes albopictus (Skuse) (Diptera: Culicidae) for pesticide resistance testing. NEVBD also established larvicide resistance diagnostics for Bacillus thuringiensis israelensis (Bti) and methoprene. Additional diagnostics were developed for Cx. pipiens resistance to Lysinibacillus sphaericus. We received 58 survey responses, representing at least one agency from each of the 13 northeastern U.S. states. Results indicated that larvicides were deployed more frequently than adulticides, but rarely paired with resistance monitoring. Over 18,000 mosquitoes were tested from six states. Widespread low-level (1 × LC-99) methoprene resistance was detected in Cx. pipiens, but not in Ae. albopictus. No resistance to Bti or L. sphaericus was detected. Resistance to pyrethroids was detected in many locations for both species. Our results highlight the need for increased pesticide resistance testing in the United States and we provide guidance for building a centralized pesticide resistance testing program.
Iron in plant–pathogen interactions
Authors: Liu Yi , Kong Danyu , Wu Hui-Lan , Ling Hong-Qing
Published: October 2020

Iron is an essential element for most organisms. As an indispensable co-factor of many enzymes, iron is involved in various crucial metabolic processes that are required for the survival of plants and pathogens. Conversely, excessive iron produces highly active reactive oxygen species, which are toxic to the cells of plants and pathogens. Therefore, plants and pathogens have evolved sophisticated mechanisms to modulate iron status at a moderate level for maintaining their fitness. Over the past decades, many efforts have been made to reveal these mechanisms, and some progress has been made. In this review, we describe recent advances in understanding the roles of iron in plant–pathogen interactions and propose prospects for future studies.
Prevalence of coccidioidomycosis in cystic fibrosis patients residing in Southern Arizona
Authors: Estrada Lauren , August Jessica , Ojo Tammy , Campion Janet
Published: November 2020

Sparse data exists about patients with cystic fibrosis (CF) and their risk of contracting coccidioidiomycosis or Valley Fever, which is highly endemic in southern Arizona. A retrospective review of medical records of 79 adult CF patients residing in Arizona was performed. Two cases only of coccidioidomycosis were documented between in the 790 patient years. However, false-positive serologies were found in 15 patients. This 10-year retrospective review of 79 adult CF patients found that there was a lower prevalence of coccidioidomycosis in CF patients compared to that of the general population of the area.

Lay Summary

Patients with cystic fibrosis (CF) suffer from chronic lung infection. Little is known about CF and fungal infection. Coccidioidomycosis is a fungal infection common in Arizona and this study shows a lower infection rate from Coccidioidomycosis in CF patients compared to the general population.