bluuebunny/crossref_metadata_2025_split huggingface dataset:
Key Technologies of Time-Sensitive Networking and Its Application
Authors: Li Qing , Li Dong , Sun Xinbo 
Published: April 2020

Abstract
Network is the core element of many industrial and automation systems. In the future, more attention will be paid to convergent and unified network. Time-critical traffic and non-time-critical traffic need to share communication channels. The goal of the IEEE TSN task group is to extend the existing Ethernet standard to achieve a degree of certainty that meets the hard-real-time requirements of modern control networks in the industrial automation and automotive industries. Time sensitive network (TSN) is characterized by low jitter, low delay and deterministic transmission. It can transmit critical and non-critical traffic in the same network, which is very suitable for time- critical applications with high requirements on transmission delay. This paper briefly summarizes the key components of TSN, studies the key technologies, and carries out a simple traffic scheduling experiment on the switch based on 802.1Qbv function, and finally analyzes the application of TSN in industrial automation and automobile industry.
Stability Analysis of Minimum Broken Top Layer Thickness of Rock Drilling Chamber in a Mining Site Based on Midas/GTS
Authors: Yang Jun , Zhu Zhaoxia , Chen Xiang , Zeng Weiwei 
Published: April 2020

Abstract
The determination of the reasonable thickness of the top layer of the large- diameter deep-hole stope is one of the important process parameters that must be considered in the high-stage mining recovery. The thickness of the top layer can ensure that the large-diameter deep-hole stope is not easy to collapse after the formation of the empty zone. To ensure the stability of the rock drilling chamber. According to the similar mine experience and mechanical model, the scientific and reasonable top-level safety thickness range is calculated. The three-dimensional numerical simulation of MIDAS/GTS is used to verify and optimize the stability of different top layer thicknesses. From the perspective of displacement and stress, comprehensive simulation analysis is carried out. After comprehensive comparison of angles, the optimal thickness of the top layer is determined to be 9 m.
Mineralogy Study on a Fine-Grained Cu-Mo Sulphide Ore in Jiudingshan China
Authors: Nie Qi , Cheng Yong , Liu Cong , Zhang Hanping , Peng Fenlan 
Published: April 2020

Abstract
This study researched mineralogy characteristics of Jiudingshan Cu-Mo sulphide ore by modern testing instruments, such as scanning electron microscope (SEM), reflected light microscope (RLM), X-ray diffractometer (XRD), and mineral liberation analyzer (MLA). The occurrence of Cu, Mo and other valuable minerals were mainly investigated. Results show that: it contain 0.50% Cu, 0.15% Mo and 7.04% Fe. Forty individual minerals are involved in the ore. Main valuable minerals are molybdenite, chalcopyrite, magnetite, pyrite; main gangue minerals are quartz, feldspar, garnet, calcite, dolomite.Molybdenite, chalcopyrite are finely disseminated in the magnetite,quartz, feldspar, garnet; some are inlayed along other minerals such as idocrase, actynolin.
Analysis of Track Bend Limit and Settlement Deformation Affecting the Transition Section of Highway and Bridge of High-speed Railway
Authors: Ling Pingping , Chen Zeshi 
Published: April 2020

Abstract
In recent years, with the rapid development of high-speed railways, the problem of differential settlement of road-bridge transition sections has become increasingly prominent. The uneven settlement of the road-bridge transition has a great impact on the driving safety and comfort of high-speed vehicles, especially for high-speed railway projects under special ground conditions such as soft stop. And with the continuous increase in train speed and axle weight, the differential settlement requirements at the over-bands are becoming more stringent. The problem of “jump at the bridgehead” has become one of the important factors affecting the safety of highspeed trains. In view of the current situation, theoretical analysis and numerical calculation are used as research methods in this paper. The factors of uneven settlement and deformation of the road-bridge transition section are systematically analyzed and corresponding methods for foundation treatment are proposed.
An Accelerated Convergence Algorithm for Sparse-View CT Image Reconstruction
Authors: Wang Zhao , Liu Zhiguo , Zhang Shuang , Pan Kai , Zhou Peng , Wang Xin , Wang Haoran , Sun Tianxi 
Published: April 2020

Abstract
In order to reduce radiation dose during CT scanning, sparse sampling is an effective way. Although the TV-based iterative reconstruction algorithm is a breakthrough to solve the problem of sparse-view CT image reconstruction, its applicability is still limited by huge computational burden. It is necessary to study the acceleration method of TV-based iterative algorithm. This paper show that the FISTA acceleration method is not suitable for POCS-TV algorithm, meanwhile, an improved acceleration method, IFISTA, is proposed to accelerate the convergence rate of POCS-TV. Numerical experiments show that the convergence rate of POCS-TV-IFISTA is about 35% faster than POCS-TV.
A Analysis and Calculation Method for Reasonable Decline of Fluid Production in Affected Wells in Transfer Polymerization Flooding
Authors: Zhang Li , Shu Zheng 
Published: April 2020

Abstract
When the J oilfield is switched from water flooding to polymer flooding, the fluid supply capacity of the effective well will decrease sharply, and it is often judged that the effective well is blocked. In fact, in addition to the blockage that occurs after the polymer flooding, some of the decline in the fluid production is caused by the nature of the polymer flooding. Therefore, it is necessary to analyze the characteristics of water flooding and polymer flooding, and compare the similarities and differences between water flooding and polymer flooding, so as to find the factors that will inevitably lead to the decline of production fluid after water flooding to polymer flooding. The range of decline in fluid production caused by these factors is a reasonable range of decline in the produced fluids of the affected wells, while the decline in fluid production caused by other factors is the blockage.
A mini-review of distribution, growth environment and nutrient composition from Scorias spongiosa (Bamboo Bird’s Nest)
Authors: Zhong Shengnan , Yu Hua , Nong Xiang , Liu Chao 
Published: April 2020

Abstract

Scorias spongiosa is an edible fungus. The fruiting bodies of Scorias spongiosa contain variouss chemical composition such as polysaccharides, steroids which have many pharmacological effects, such as anti-oxidation, antitumor and bacteriostatic. In this review, the distribution, growth environment and nutrient composition of Scorias spongiosa were summarized systematically, and the development prospect of Scorias spongiosa (Bamboo Bird’s Nest) was prospected.
Simulation and Performance Study of Quadrature Amplitude Modulation and Demodulation System
Authors: Zhang Bin , Qu Yuanhang , Chen Min 
Published: April 2020

Abstract
Both traditional frequency modulation and phase modulation digital modulation methods have low spectral utilization, poor multipath fading resistance, slow power spectrum attenuation, and severe out-of-band radiation. Quadrature Amplitude Modulation (QAM) is a digital modulation technique that combines phase and amplitude control. It not only achieves higher spectral efficiency, but also transmits higher rate data in a defined frequency band. In this paper, the basic principle, system structure and performance parameters of QAM modulation and demodulation are studied in depth to realize simulink simulation and performance analysis of QAM modulation and demodulation system. The basic theory and implementation method of analog signal digitization are analyzed in detail to realize simimlink of differential pulse code modulation. Based on the above theory, the analog source QAM transmission system is constructed, and simulink is used for modeling and simulation and performance verification.The simulation results show that the constructed QAM digital transmission system can achieve good transmission of analog signals.
A Quantile K-means Bayes Approach to Classification for Imbalanced Data
Authors: Hu Yanzhu , Zhao Xinghao , Wang Song 
Published: April 2020

Abstract
This paper focuses on the classification of imbalance data. In Machine Learning, a data set is imbalanced when the class proportions are highly skewed. A natural way of handling imbalanced data is to attempt to equalise the class frequencies and train the classifier of choice on balanced data. A new approach called Quantile K-means Bayes was proposed to solve the problem. The first focus is on a modified q-classifier. The second focus is on combine the k-means and Bayes algorithm using the data density. The proposed approach is evaluated by 101 benchmark data sets from KEEL collection. A comparison of the proposed approach and other conventional approaches is presented in terms of the G-mean. It can be seen that the proposed approach is able to acquire good performance among the other conventional approaches do. Therefore, this novel approach is an added value for the classification problem for imbalance data.
Research on New Mining Technology Based on Oilfield Reservoir Water Injection
Authors: Song Penghui 
Published: April 2020

Abstract
During the development of oilfields, we usually study reservoir water injection and water injection well fracturing as two important measures to improve the effect of water flooding. These two technologies play a big role in oilfield development, but there are also some problems in the application process. In this paper, through the analysis of the fracturing mechanism and problems of reservoir water injection and water injection wells, the adjustment method of reservoir water injection and water well fracturing is proposed, which reduces the water injection pressure technology of high pressure water injection well and improves the oilfield development effect.
Study on Land Use Structure of Hexi Corridor Based on Lorenz Curve and Gini Coefficient
Authors: Geng Yonghao , Pan Qiao , Xiao Bingyu 
Published: April 2020

Abstract
The development of the Hexi Corridor area has been attached great importance due to the “Belt and Road” international cooperation initiative. Meanwhile, the optimization of land use structure has played a major role in the development of this area. In order to promote healthier and more efficient development of the Hexi Corridor area, this paper collects and reviews recent multidimensional data on the development of the area. In addition, by applying the Lorentz curve and Gini coefficient method, this paper also concentrates on several aspects in the development of the Hexi Corridor area: (a) quantifying the land use balance based on data from various prefecture-level Hexi cities; (b) revealing developmental experiences and efficiency; (c) exploring overall urban land use status; (d) and proposing targeting urban planning and development strategies.
Research on Hi-C data enhancement technology based on generative adversarial networks
Authors: Bai Qian , Cheng Zhe , Wang Shipu , Zhou Wei 
Published: April 2020

Abstract
Hi-C technology is one of the most popular tools for studying three-dimensional(3D) genome organization. Due to the high cost of sequencing, most Hi-C data have low resolution and cannot be used to connect distal regulatory elements to their target genes. To solve the problem that hi-c data of high resolution are not easy to obtain, this paper proposes a Hi-C enhancement method (HiCGAN) based on generative adversarial networks, Taking the down-sampling interaction matrix which is highly similar to the original matrix as input, only 1/16 of the original sequencing reading can be used to generate the Hi-C interaction matrix of high resolution. In the experiment, Pearson correlation coefficient was used to measure the similarity between the generated high-resolution matrix and the real high-resolution hi-c matrix in numerical distribution. the apparent interaction pairs were analyzed by Fit-Hi-C, and calling ChromHMM annotates state of 12 kinds of chromatin. Experimental results show that HiCGAN models learned in one cell type can predict high-resolution Hi-C matrices for other cell types. This study proposes a computational framework (HiCGAN) for accurately predicting Hi-C data improving the resolution of Hi-C data.
Classification and Recognition of Turtle Images Based on Convolutional Neural Network
Authors: Liu Jiangchuan , Wang Mantao , Bao Lie , Li Xiaofan , Sun Jun , Ming Yue 
Published: April 2020

Abstract
The identification of turtle species mainly depends on the recognition of turtle head and shell, but there is no relevant study on turtle image. In this paper, a turtle image recognition and classification system based on transfer learning is introduced. The system consists of four phases. First, turtle images need to be collected for data enhancement and dataset production. Secondly, the Inception-v3 network model is used to train and save parameters and model structure on the ImageNet dataset. In addition, the network model needs to be modified to change Softmax classifier into 5 categories. Finally, the tortoise dataset was used for training and saving the model, and the classification accuracy of five representative turtles was verified. The experiment proves that the network model of migration learning adopted in this paper is faster and more accurate than the one not adopted.
Nonlinear Correction and Temperature Compensation Method of Turbine Flowmeter Based on Neural Network
Authors: He Wang , Yi Jianjun , Zhou Bo , Chen Bin , He Liang 
Published: April 2020

Abstract
For the nonlinear characteristics of turbine flow sensor and the influence of medium temperature, the traditional compensation method is difficult to apply. This paper uses BP neural network based method to improve measurement accuracy. Firstly, the reason of nonlinearity and the influence of temperature on flow measurement are analyzed theoretically. Then the nonlinear correction and temperature compensation scheme based on neural network is proposed, and different optimization algorithms are used for training. After simulation experiments and analysis, the results show that neural network the maximum reference error of the sensor after compensation is 0.683%. Compared with the traditional least square fitting, the accuracy is greatly improved, which can effectively solve the influence of nonlinearity and temperature change on flow measurement, expand the measurement range of turbine flow meter, and improve the measurement accuracy so as to meet the requirements of industrial use.
The Importance of Tumor Length in Needle Biopsies of the Prostate
Authors: Vollmer Robin T 
Published: April 2020

AbstractObjectivesTo form a composite predictor variable that combines the effects of tumor length, serum prostate-specific antigen (PSA), and International Society of Urologic Pathologists (ISUP) grade on the observation of adverse prostatectomy pathology.MethodsLogistic regression analysis was used to demonstrate how tumor length, serum PSA, and ISUP grade related to adverse prostatectomy results and to derive weighting factors for a composite variable, cx.ResultsThe composite variable, cx, relates closely to adverse prostatectomy results as well as to observed PSA failure.ConclusionsThe composite variable cx uses preoperative information that may allow the sorting of patients into low, intermediate, and high risk for adverse outcomes after prostatectomy.
How to Manage Hypertension in People With Diabetes
Authors: Ali Waleed , Bakris George L 
Published: April 2020

Abstract
Hypertension is a common condition that is often seen in patients with diabetes. Both diseases increase the risk of morbidity and mortality from CV events and kidney disease progression. Factors that influence blood pressure (BP) control in diabetes include the persons’ genetic background for hypertension and kidney disease, level of obesity and insulin resistance, the magnitude of preexisting kidney disease, and lifestyle factors, such as level of sodium and potassium intake, sleep quality and exercise effort all of which can affect levels of sympathetic nerve activity and contribute to increased BP variability. Lifestyle intervention is a key component to the effective management of diabetes and hypertension and can markedly reduce event rates of both heart and kidney outcomes. The approach to pharmacologic treatment of BP in diabetes is crucial since certain classes of agents for both BP and diabetes confer significant benefits to reduce cardiorenal outcomes.
Vargas: heuristic-free alignment for assessing linear and graph read aligners
Authors: Darby Charlotte A , Gaddipati Ravi , Schatz Michael C , Langmead Ben 
Published: April 2020

Abstract

Motivation
Read alignment is central to many aspects of modern genomics. Most aligners use heuristics to accelerate processing, but these heuristics can fail to find the optimal alignments of reads. Alignment accuracy is typically measured through simulated reads; however, the simulated location may not be the (only) location with the optimal alignment score.

Results
Vargas implements a heuristic-free algorithm guaranteed to find the highest-scoring alignment for real sequencing reads to a linear or graph genome. With semiglobal and local alignment modes and affine gap and quality-scaled mismatch penalties, it can implement the scoring functions of commonly used aligners to calculate optimal alignments. While this is computationally intensive, Vargas uses multi-core parallelization and vectorized (SIMD) instructions to make it practical to optimally align large numbers of reads, achieving a maximum speed of 456 billion cell updates per second. We demonstrate how these ‘gold standard’ Vargas alignments can be used to improve heuristic alignment accuracy by optimizing command-line parameters in Bowtie 2, BWA-maximal exact match and vg to align more reads correctly.

Availability and implementation
Source code implemented in C++ and compiled binary releases are available at https://github.com/langmead-lab/vargas under the MIT license.

Supplementary information
Supplementary data are available at Bioinformatics online.
General regression model for the subdistribution of a competing risk under left-truncation and right-censoring
Authors: Bellach A , Kosorok M R , Gilbert P B , Fine J P 
Published: April 2020

Summary
Left-truncation poses extra challenges for the analysis of complex time-to-event data. We propose a general semiparametric regression model for left-truncated and right-censored competing risks data that is based on a novel weighted conditional likelihood function. Targeting the subdistribution hazard, our parameter estimates are directly interpretable with regard to the cumulative incidence function. We compare different weights from recent literature and develop a heuristic interpretation from a cure model perspective that is based on pseudo risk sets. Our approach accommodates external time-dependent covariate effects on the subdistribution hazard. We establish consistency and asymptotic normality of the estimators and propose a sandwich estimator of the variance. In comprehensive simulation studies we demonstrate solid performance of the proposed method. Comparing the sandwich estimator with the inverse Fisher information matrix, we observe a bias for the inverse Fisher information matrix and diminished coverage probabilities in settings with a higher percentage of left-truncation. To illustrate the practical utility of the proposed method, we study its application to a large HIV vaccine efficacy trial dataset.
Testing identification via heteroskedasticity in structural vector autoregressive models
Authors: Lütkepohl Helmut , Meitz Mika , Netšunajev Aleksei , Saikkonen Pentti 
Published: April 2020

Summary
Tests for identification through heteroskedasticity in structural vector autoregressive analysis are developed for models with two volatility states where the time point of volatility change is known. The tests are Wald-type tests for which only the unrestricted model, including the covariance matrices of the two volatility states, has to be estimated. The residuals of the model are assumed to be from the class of elliptical distributions, which includes Gaussian models. The asymptotic null distributions of the test statistics are derived, and simulations are used to explore their small-sample properties. Two empirical examples illustrate the usefulness of the tests in applied work.
A test of oscillation in the human secondary sex ratio
Authors: Catalano Ralph , Casey Joan A , Bruckner Tim A 
Published: April 2020

AbstractBackground and objectivesThe sex ratio of human birth cohorts predicts the health and longevity of their members. Most literature invokes natural selection in support of the argument that heritable tendencies to produce male or female offspring induce oscillation in the sex ratio and its sequelae. Tests of the argument remain exceedingly rare because they require vital statistics describing many generations of a population both unaffected by migration and exposed to an exogenous stressor virulent enough to change the sex ratio at birth. We contribute to the literature by using time-series modeling to detect oscillation in the best data currently available for such a test.MethodologyWe apply rigorous time-series methods to data describing Sweden from 1751 through 1830, a period when the population not only aged in place without migration, but also exhibited the effects of an Icelandic volcanic eruption including a historically low secondary sex ratio. That very low sex ratio should have induced oscillation if heritable mechanisms appear in humans.ResultsWe detected oscillation in the ratio but not that predicted by heritable tendencies to produce males or females. We found peak-to-trough oscillation at 14 rather than the approximately 32 years expected from the heritable tendencies argument.Conclusions and implicationsOur findings suggest that mechanisms other than perturbation of heritable tendencies to produce males or females induce oscillation in the human secondary sex ratio. These other mechanisms may include reproductive suppression and selection in utero.LAY SUMMARYThe male to female ratio in human birth cohorts predicts longevity but its variation over time remains unexplained. We test the long-held theory that the ratio oscillates due to heritable tendencies to produce males or females. We find oscillation, but it appears due to social processes rather than heritable mechanisms.