bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on the Reactive Power Control in Hybrid DC Asynchronous Interconnection System
Authors: Han Yan , Jia Yang , Keshan Che , Hui Chen , Wenli Yang , Ke Liu , Jixiu Bao 
Published: May 2019

Abstract
Reactive power control of hybrid DC asynchronous interconnection system has a vital impact on the safety, reliability and high quality of AC/DC power transmission system. The LCC-HVDC unit and MMC-HVDC unit share the same station control system in the hybrid DC asynchronous interconnected system. Firstly, this paper studies the reactive power switching control of LCC-HVDC system, including five subfunctions and control strategies of the reactive power switching control. Secondly, the reactive power auxiliary control of LCC-HVDC system including low load reactive power regulation function and Gamma-Kick function is studied. And the shortcomings of using reactive power auxiliary control are pointed out. Finally, the reactive power control of MMC-HVDC system is deeply studied. The mathematical model of MMC-HVDC control system is established. Reactive power control of MMC-HVDC can be used to replace reactive power auxiliary control of LCC-HVDC to improve the converter utilization and service life
A Line Loss Calculation Method for Arbitrary Partition of Power Grid Based on Measurement Resource and Matpower
Authors: Yi Kai , Wang WeiZhou , Bai RunQing , He Xin , Jing TianJun 
Published: May 2019

Abstract
The existing four-division management method for line loss in smart grids has problems such as the inability to verify line loss contemporaneity and low application flexibility. Considering that the rich data resources provided by data acquisition devices such as measurement meters in the smart grid are not fully utilized, an arbitrary partitioning line loss calculation method that fully utilizes measurement data resources is proposed. The method classifies the grid nodes according to the type of measurement data, obtains complete line power data, and then formulates the boundary equivalence principle of grid partition to realize arbitrary region partition of the power network. On the basis of network partition, the power loss of each subnetwork is calculated by using the power flow of matpower, which greatly increases the flexibility of smart grids line loss management. Taking a power grid in a certain area of Gansu as a case study, the effectiveness of the calculation method is verified.
Support Vector Machine based on clustering algorithm for interruptible load forecasting
Authors: Yu Xiang , Bu Guangfeng , Peng Bingyue , Zhang Chen , Yang Xiaolan , Wu Jun , Ruan Wenqing , Yu Yu , Tang Liangcai , Zou Ziqing 
Published: May 2019

Abstract
Accurately forecast interruptible load can help to alleviate the power supply tension during peak load and make scheduling more flexible. Support vector machine (SVM) method which has been widely used in load forecasting usually selects a period of date close to the forecast day without considering the information characteristics of itself. An interruptible load forecasting method based on clustering algorithm is proposed in this paper. This method puts forward a new idea to select the sample of prediction model which takes full account of the weather and date information of the forecast day and solve the problem that the traditional SVM method cannot properly reflect it. In this paper, the principles of clustering algorithm and support vector machine are introduced firstly. Then K-means clustering algorithm is used to classify the historical data, and the support vector machine forecasting model is constructed by using the categories of the forecast day membership. Finally, the prediction is carried out by combining with the actual data. The results show that the prediction accuracy of this method is more than 95%, and it has higher precision.
Research on Position Sensorless Control of PMSM Based on Improved SMO
Authors: Guoqing Zhang , Xinhong Xiong , Yousheng Zheng , Yanhui Zhang , Lianbo Chen , Xinyu Wu , Wei Feng 
Published: May 2019

Abstract
The sliding mode observer (SMO) can effectively achieve the permanent magnet synchronous motor (PMSM) to perform position sensorless control, but there are still drawbacks of system chattering and high complexity. In this paper, an improved SMO is established based on hyperbolic tangent function and Kalman filter. The system chattering is effectively suppressed, and the accuracy of position and speed observation error is significantly improved without phase compensation. It is found that the convergence rate of the hyperbolic tangent function has a strong correlation with the system chattering degree and the speed observation error. When a is between 3 and 4, the speed error accuracy of the improved SMO is the optimum situation.
Prediction of Bearing Remaining Useful Life based on Mutual Information and Support Vector Regression Model
Authors: Sui Wentao , Zhang Dan , Qiu Xiaomei , Zhang Wei , Yuan Lin 
Published: May 2019

Abstract
In order to evaluate the degradation state of the mechanical equipment and master the information of the remaining useful life (RUL) of the bearing accurately, this paper presents a method for predicting the remaining useful life of bearings based on mutual information (MI) and support vector regression (SVR) model. The proposed method includes two steps of online and offline, the offline step is used to build a degradation model of the bearing by learning, the online step uses the degradation model to predict the remaining useful life. By analyzing the experimental data of bearing full lifetime degradation, the results show that the method can effectively simulate the bearing degradation process and predict the remaining useful life of the bearing.
Research on Optimal placement for GIC mitigation with Blocking Device
Authors: Ning Xiaoliang , Liu Qing , Cui Xikai , Wang Chendong , Wang Yinglan 
Published: May 2019

Abstract
Geomagnetically induced current (GIC) caused by geomagnetic storms flows between the power grid and the earth would threaten the stable operation of the power system. Capacitor blocking device connected in series at transformer neutral point can directly block the DC path. However, due to the complexity of the DC path in the power system, before the installation of the blocking device, if global considerations are not taken into account, the adverse effects of GIC will not be reduced. Therefore, to study the position optimization of the capacitor blocking device is of great value. This optimization of placement of capacitor blocking device is proposed in this paper. Applying the idea of genetic algorithm, the installation quantity and installation position of the blocking device were calculated and compared with the traditional GIC non-optimal method, which verified the superiority of the genetic algorithm optimization solution.
Influence Maximization: A Time-Space Efficient Algorithm
Authors: Xia Ganming 
Published: May 2019

Abstract
Influence maximization is the problem of finding a small subset of nodes (seed nodes) in a social network that could maximize the spread the influence. The algorithm problem of computing influence estimation and influence maximization have been extensively studied for decades. In this paper, we studied the reverse influence sampling method proposed by Byogs et al. in 2014, and some other improved algorithms. We proposed a new algorithm TESA (Time-Space Efficient Algorithm). On large social networks, TESA saves more space than existing algorithms and runs faster. We used data sets tested in the literature to evaluate TESA experimentally and showed that it was superior to the most advanced solutions in terms of running time and memory footprint.
DA-U-Net: Densely Connected Convolutional Networks and Decoder with Attention Gate for Retinal Vessel Segmentation
Authors: Wu Cong , Zou Yixuan , Zhan Jinhao 
Published: May 2019

Abstract
The segmentation of retinal vessels is greatly significant for doctors to diagnose the fundus diseases. However, existing methods have various problems in the segmentation of the retinal vessels, such as insufficient segmentation of retinal vessels, weak anti-noise interference ability. Aiming to the shortcomings of existed methods, this paper proposes an improved model based on the U-Net networks, which contains densely-connected convolutional network and a novel attention gate (AG) model, referred as Densely-Attention-U-Net (DA-U-Net), to automatically segment the retinal blood vessels. The method can alleviate the vanishing-gradient problem, strengthen feature propagation, substantially reduce the number of parameters, and automatically learn to focus on target structures without additional supervision. By verifying the method on the DRIVE datasets, the segmentation accuracy rate is 96.09%, higher than that of U-Net and R2U-Net.
A Gait Patterns Recognition Approach Based on Surface Electromyography and Three-axis Acceleration Signals
Authors: Hao Jinghan , Yang Peng , Chen Lingling , Geng Yanli 
Published: May 2019

Abstract
In this paper, an approach based on combining surface electromyography(sEMG) and three-axis acceleration(ACC) signal was proposed to recognize 5 different kinds basis daily gait patterns, including walking on the ground, going up stairs, going down stairs, going up slope and going down slope. Firstly, the gait related sEMG signal and three-axis ACC signal were collected from the lower limbs of subjects. Secondly, the de-noising of sEMG signal was finished and the segmentation of the fusion signal was done. Thirdly, the features of fusion signal were extracted. Finally, a classifier based on 2-stream hidden Markov model (HMM) was built to recognize 5 kinds of basis daily gait patterns. The experiment obtained an average recognition accuracy of 94.32%, which is 4.15% higher than the accuracy by adopting sEMG signal only (Average 90.17%), and 9.60% higher than the accuracy by adopting ACC signal only (Average 84.72%). The result demonstrated that it can improve the recognition accuracy of gait patterns effectively to combine sEMG signal and three-axis ACC signal.
Implementing smooth functions of a Hermitian matrix on a quantum computer
Authors: Subramanian Sathyawageeswar , Brierley Stephen , Jozsa Richard 
Published: May 2019

Abstract
We consider methods for implementing smooth functions f(A) of a sparse Hermitian matrix A on a quantum computer, and analyse a further combination of these techniques which has advantages of simplicity and resource consumption in some cases. Our construction uses the linear combination of unitaries method with Chebyshev polynomial approximations. The query complexity we obtain is



log

C

ϵ

where ϵ is the approximation precision, and C > 0 is an upper bound on the magnitudes of the derivatives of the function f over the domain of interest. The success probability depends on the 1-norm of the Taylor series coefficients of f, the sparsity d of the matrix, and inversely on the smallest singular value of the target matrix f(A).
Selective vs Complete Sampling in Hysterectomy Specimens Performed for Atypical Hyperplasia
Authors: Bryant Bronwyn H , Doughty Elizabeth , Kalof Alexandra N 
Published: May 2019

Abstract

Objectives
Atypical hyperplasia of the endometrium is a significant risk factor for uterine endometrioid carcinoma (EC) and an indication for hysterectomy. Standard sampling of these specimens includes evaluation of the entire endometrium to identify possible EC. We evaluated a method of selective sampling in an effort to balance resource utilization with diagnostic accuracy in the detection of EC.

Methods
Histologic diagnoses based on selective sampling (exclusion of every other block of endometrium) were compared with the original diagnosis based on complete sampling.

Results
Double-blinded review of these cases using selective sampling detected EC in 92% of hysterectomies, including all high-grade/high-stage carcinomas. Selective sampling had an 82% agreement with the original diagnoses, with most discordant diagnoses attributable to interobserver variability. Adjusting for interobserver variability increased diagnostic agreement between selective and complete sampling to 96%.

Conclusions
Selective sampling is a feasible method to save time and resources while maintaining diagnostic accuracy.
MTTFsite: cross-cell type TF binding site prediction by using multi-task learning
Authors: Zhou Jiyun , Lu Qin , Gui Lin , Xu Ruifeng , Long Yunfei , Wang Hongpeng 
Published: May 2019

Abstract

Motivation
The prediction of transcription factor binding sites (TFBSs) is crucial for gene expression analysis. Supervised learning approaches for TFBS predictions require large amounts of labeled data. However, many TFs of certain cell types either do not have sufficient labeled data or do not have any labeled data.

Results
In this paper, a multi-task learning framework (called MTTFsite) is proposed to address the lack of labeled data problem by leveraging on labeled data available in cross-cell types. The proposed MTTFsite contains a shared CNN to learn common features for all cell types and a private CNN for each cell type to learn private features. The common features are aimed to help predicting TFBSs for all cell types especially those cell types that lack labeled data. MTTFsite is evaluated on 241 cell type TF pairs and compared with a baseline method without using any multi-task learning model and a fully shared multi-task model that uses only a shared CNN and do not use private CNNs. For cell types with insufficient labeled data, results show that MTTFsite performs better than the baseline method and the fully shared model on more than 89% pairs. For cell types without any labeled data, MTTFsite outperforms the baseline method and the fully shared model by more than 80 and 93% pairs, respectively. A novel gene expression prediction method (called TFChrome) using both MTTFsite and histone modification features is also presented. Results show that TFBSs predicted by MTTFsite alone can achieve good performance. When MTTFsite is combined with histone modification features, a significant 5.7% performance improvement is obtained.

Availability and implementation
The resource and executable code are freely available at http://hlt.hitsz.edu.cn/MTTFsite/ and http://www.hitsz-hlt.com:8080/MTTFsite/.

Supplementary information
Supplementary data are available at Bioinformatics online.
DeepSymmetry: using 3D convolutional networks for identification of tandem repeats and internal symmetries in protein structures
Authors: Pagès Guillaume , Grudinin Sergei 
Published: May 2019

Abstract

Motivation
Thanks to the recent advances in structural biology, nowadays 3D structures of various proteins are solved on a routine basis. A large portion of these structures contain structural repetitions or internal symmetries. To understand the evolution mechanisms of these proteins and how structural repetitions affect the protein function, we need to be able to detect such proteins very robustly. As deep learning is particularly suited to deal with spatially organized data, we applied it to the detection of proteins with structural repetitions.

Results
We present DeepSymmetry, a versatile method based on 3D convolutional networks that detects structural repetitions in proteins and their density maps. Our method is designed to identify tandem repeat proteins, proteins with internal symmetries, symmetries in the raw density maps, their symmetry order and also the corresponding symmetry axes. Detection of symmetry axes is based on learning 6D Veronese mappings of 3D vectors, and the median angular error of axis determination is less than one degree. We demonstrate the capabilities of our method on benchmarks with tandem-repeated proteins and also with symmetrical assemblies. For example, we have discovered about 7800 putative tandem repeat proteins in the PDB.

Availability and implementation
The method is available at https://team.inria.fr/nano-d/software/deepsymmetry. It consists of a C++ executable that transforms molecular structures into volumetric density maps, and a Python code based on the TensorFlow framework for applying the DeepSymmetry model to these maps.

Supplementary information
Supplementary data are available at Bioinformatics online.
NX4: a web-based visualization of large multiple sequence alignments
Authors: Solano-Roman A , Cruz-Castillo C , Offenhuber D , Colubri A 
Published: May 2019

AbstractSummaryMultiple Sequence Alignments (MSAs) are a fundamental operation in genome analysis. However, MSA visualizations such as sequence logos and matrix representations have changed little since the nineties and are not well suited for displaying large-scale alignments. We propose a novel, web-based MSA visualization tool called NX4, which can handle genome alignments comprising thousands of sequences. NX4 calculates the frequency of each nucleotide along the alignment and visually summarizes the results using a color-blind friendly palette that helps identifying regions of high genetic diversity. NX4 also provides the user with additional assistance in finding these regions with a ‘focus + context’ mechanism that uses a line chart of the Shannon entropy across the alignment. The tool offers geneticists an easy-to-use and scalable analysis for large MSA studies.Availability and implementationNX4 is freely available at https://www.nx4.io, and its source code at https://github.com/NX4/nx4.Supplementary informationSupplementary data are available at Bioinformatics online
Morphological variation in genetically divergent populations of the common whelk, Buccinum undatum (Gastropoda: Buccinidae), across the North Atlantic
Authors: Magnúsdóttir Hildur , Pálsson Snæbjörn , Westfall Kristen Marie , Jónsson Zophonías O , Örnólfsdóttir Erla Björk 
Published: May 2019

Abstract
The variation in shelled marine gastropod morphology across small spatial scales can reflect restricted population connectivity, resulting in evolution or plastic responses to environmental heterogeneity. The common whelk, Buccinum undatum, is a subtidal gastropod, ubiquitous in the North Atlantic, that exhibits considerable spatial variation in shell morphology and colour. Given that species delimitation in shelled marine gastropods is often based on shell characteristics, such morphological variation can lead to taxonomic confusion. Phylogeographical analysis based on mitochondrial DNA and microsatellites suggested cryptic species composed of Western and Eastern North Atlantic common whelk populations, the separation of which dates to the onset of the Pleistocene glaciation ~2.1 Mya. Divergence within the Eastern North Atlantic is more recent and characterized by isolation by distance. In the present study, phenotypic variation in shell morphology across the North Atlantic range is analysed and compared with molecular divergence. The morphological variation of B. undatum populations reflected the pattern observed for the molecular markers only for certain comparisons of populations and might, in other cases, reflect larger constraints on the morphological variation and, possibly, the impact of environmental influences.
Twenty Years of the Rome Statute of the International Criminal Court: Appraising the State of National Implementing Legislation in Asia
Authors: Birkett Daley J 
Published: May 2019

Abstract
The International Criminal Court relies on its State Parties to incorporate, or implement, its constituent instrument, the Rome Statute, into their domestic legal systems to enable its effective functioning. First, State Parties are obliged to give effect to their explicit obligation to cooperate with the Court under the Rome Statute. Second, although not required to do so, to avoid their national legal systems being found by the Court to be unable to investigate and/or prosecute the crimes under its jurisdiction in accordance with the principle of complementarity, they should also implement the definition and prohibition of these offences in their national legal frameworks. This article appraises the status of the domestic implementation of the Rome Statute, both crimes and cooperation, in Asia. The article concludes that few Asian State Parties to the Rome Statute have incorporated the treaty’s provisions into their domestic laws in a holistic manner, with the absence of cooperation legislation, enabling State Parties to assist the Court, particularly striking.
Cryptococcal Meningitis Screening and Community-based Early Adherence Support in People With Advanced Human Immunodeficiency Virus Infection Starting Antiretroviral Therapy in Tanzania and Zambia: A Cost-effectiveness Analysis
Authors: Kimaro Godfather Dickson , Guinness Lorna , Shiri Tinevimbo , Kivuyo Sokoine , Chanda Duncan , Bottomley Christian , Chen Tao , Kahwa Amos , Hawkins Neil , Mwaba Peter , Mfinanga Sayoki Godfrey , Harrison Thomas S , Jaffar Shabbar , Niessen Louis W 
Published: May 2019

Abstract

Background
A randomized trial demonstrated that among people living with late-stage human immunodeficiency virus (HIV) infection initiating antiretroviral therapy, screening serum for cryptococcal antigen (CrAg) combined with adherence support reduced all-cause mortality by 28%, compared with standard clinic-based care. Here, we present the cost-effectiveness.

Methods
HIV-infected adults with CD4 count &lt;200 cells/μL were randomized to either CrAg screening plus 4 weekly home visits to provide adherence support or to standard clinic-based care in Dar es Salaam and Lusaka. The primary economic outcome was health service care cost per life-year saved as the incremental cost-effectiveness ratio (ICER), based on 2017 US dollars. We used nonparametric bootstrapping to assess uncertainties and univariate deterministic sensitivity analysis to examine the impact of individual parameters on the ICER.

Results
Among the intervention and standard arms, 1001 and 998 participants, respectively, were enrolled. The annual mean cost per participant in the intervention arm was US$339 (95% confidence interval [CI], $331–$347), resulting in an incremental cost of the intervention of US$77 (95% CI, $66–$88). The incremental cost was similar when analysis was restricted to persons with CD4 count &lt;100 cells/μL. The ICER for the intervention vs standard care, per life-year saved, was US$70 (95% CI, $43–$211) for all participants with CD4 count up to 200 cells/μL and US$91 (95% CI, $49–$443) among those with CD4 counts &lt;100 cells /μL. Cost-effectveness was most sensitive to mortality estimates.

Conclusions
Screening for cryptococcal antigen combined with a short period of adherence support, is cost-effective in resource-limited settings.