bluuebunny/crossref_metadata_2025_split huggingface dataset:
The WISSH quasars project
Authors: Bischetti M. , Feruglio C. , Piconcelli E. , Duras F. , Pérez-Torres M. , Herrero R. , Venturi G. , Carniani S. , Bruni G. , Gavignaud I. , Testa V. , Bongiorno A. , Brusa M. , Circosta C. , Cresci G. , D’Odorico V. , Maiolino R. , Marconi A. , Mingozzi M. , Pappalardo C. , Perna M. , Traianou E. , Travascio A. , Vietri G. , Zappacosta L. , Fiore F. 
Published: October 2020

Context. Sources at the brightest end of the quasi-stellar object (QSO) luminosity function, during the peak epoch in the history of star formation and black hole accretion (z ∼ 2−4, often referred to as “Cosmic noon”) are privileged sites to study the cycle of feeding & feedback processes in massive galaxies.
Aims. We aim to perform the first systematic study of cold gas properties in the most luminous QSOs, by characterising their host-galaxies and environment. These targets exhibit indeed widespread evidence of outflows at nuclear and galactic scales.
Methods. We analyse ALMA, NOEMA and JVLA observations of the far-infrared continuum, CO and [CII] emission lines in eight QSOs (bolometric luminosity LBol ≳ 3 × 1047 erg s−1) from the WISE-SDSS selected hyper-luminous (WISSH) QSOs sample at z ∼ 2.4−4.7.
Results. We report a 100% emission line detection rate and a 80% detection rate in continuum emission, and we find CO emission to be consistent with the steepest CO ladders observed so far. Sub-millimetre data reveal presence of (one or more) bright companion galaxies around ∼80% of WISSH QSOs, at projected distances of ∼6−130 kpc. We observe a variety of sizes for the molecular gas reservoirs (∼1.7−10 kpc), mostly associated with rotating disks with disturbed kinematics. WISSH QSOs typically show lower CO luminosity and higher star formation efficiency than infrared matched, z ∼ 0−3 main-sequence galaxies, implying that, given the observed SFR ∼170−1100 M⊙ yr−1, molecular gas is converted into stars in ≲50 Myr. Most targets show extreme dynamical to black-hole mass ratios Mdyn/MBH ∼ 3−10, two orders of magnitude smaller than local relations. The molecular gas fraction in the host-galaxies of WISSH is lower by a factor of ∼10−100 than in star forming galaxies with similar M*.
Conclusions. Our analysis reveals that hyper-luminous QSOs at Cosmic noon undergo an intense growth phase of both the central super-massive black hole and of the host-galaxy. These systems pinpoint the high-density sites where giant galaxies assemble, where we show that mergers play a major role in the build-up of the final host-galaxy mass. We suggest that the observed low molecular gas fraction and short depletion timescale are due to AGN feedback, whose presence is indicated by fast AGN-driven ionised outflows in all our targets.
Apparent modification of the jet-like yield in proton–proton collisions with large underlying event
Authors: Bencédi Gyula , Ortiz Antonio , Tripathy Sushanta 
Published: October 2020

Abstract
This paper presents the production of charged particles associated with high-p
T trigger particles (

8
<

p

T

t
r
i
g
.

<
15

GeV/c) at midrapidity in proton–proton collisions at

s

=
5.02

TeV simulated with PYTHIA 8.244. The study is performed as a function of the relative transverse activity classifier, R
T, which is the relative charged-particle multiplicity in the transverse region (π/3 < |ϕ
trig. − ϕ
assoc.| < 2π/3) of the di-hadron correlations, and it is sensitive to the multi-parton interactions. The evolution of the yield of associated particles on both the towards and the away regions (

3
⩽

p

T

a
s
s
o
c
.

<
8

GeV/c) as a function of R
T is investigated. We propose a strategy which allows for the modelling and subtraction of the underlying event contribution from the towards and the away regions in challenging environments like those characterised by large R
T. We found that the signal in the away region becomes broader with increasing R
T, while its corresponding yield is independent of R
T. Contrarily, the yield increases with R
T in the towards region. This effect is reminiscent of that seen in heavy-ion collisions, where an enhancement of the yield in the towards region for 0%–5% central Pb–Pb collisions at

s

N
N

=
2.76

TeV was reported. A discussion on the origin of these effects in PYTHIA, as well as their implications for the interpretation of recent LHC results for pp collisions, is presented.
Many-body tunneling and nonequilibrium dynamics in double quantum dots with capacitive coupling
Authors: Hou Wenjie , Wang Yuandong , Zhao Weisheng , Zhu Zhengang , Wei Jianhua , Luo Honggang , Yan Yijing 
Published: October 2020

Abstract
Double quantum dots (DQDs) systems may be the minimal setups for realization of QD-based qubits and quantum computation. Pauli spin blockade (PSB) and a kind of novel many-body tunneling (MBT) are identified to play important roles in these systems, and dominate the quantum tunneling at moderate and weak interdot coupling t, respectively. On the other hand, inter-dot Coulomb interaction U′ and related inter-dot Coulomb blockade (IDCB) is inevitable in DQDs. However, what would happen on the effect of U′ in DQDs has not been touched, in particular for PSB and MBT. Here, we study the tunneling processes and transport properties with various U′ in series-coupled DQDs, and find MBT process is rather robust against U′ within U′/U < 0.1, where U is the intra-dot Coulomb interaction. Meanwhile, the linearity relationship between the carrier doublon number and MBT current remains valid. These findings enrich the understanding of the many-body tunneling in the DQDs and may shed light on the manipulation of the QD-based qubits.
Minimal entropy production rate of interacting systems
Authors: Wolpert David H 
Published: October 2020

Abstract
Many systems are composed of multiple, interacting subsystems, where the dynamics of each subsystem only depends on the states of a subset of the other subsystems, rather than on all of them. I analyze how such constraints on the dependencies of each subsystem’s dynamics affects the thermodynamics of the overall, composite system. Specifically, I derive a strictly nonzero lower bound on the minimal achievable entropy production rate of the overall system in terms of these constraints. The bound is based on constructing counterfactual rate matrices, in which some subsystems are held fixed while the others are allowed to evolve. This bound is related to the ‘learning rate’ of stationary bipartite systems, and more generally to the ‘information flow’ in bipartite systems. It can be viewed as a strengthened form of the second law, applicable whenever there are constraints on which subsystem within an overall system can directly affect which other subsystem.
Finite-range viscoelastic subdiffusion in disordered systems with inclusion of inertial effects
Authors: Goychuk Igor , Pöschel Thorsten 
Published: October 2020

Abstract
This work justifies further paradigmatic importance of the model of viscoelastic subdiffusion in random environments for the observed subdiffusion in cellular biological systems. Recently, we showed (2018, PCCP, 20, 24140) that this model displays several remarkable features, which makes it an attractive paradigm to explain the physical nature of subdiffusion occurring in biological cells. In particular, it combines viscoelasticity with distinct non-ergodic features. We extend this basic model to make it suitable for physical phenomena such as subdiffusion of lipids in disordered biological membranes upon including the inertial effects. For lipids, the inertial effects occur in the range of picoseconds, and a power-law decaying viscoelastic memory extends over the range of several nanoseconds. Thus, in the absence of disorder, diffusion would become normal on a time scale beyond this memory range. However, both experimentally and in some molecular-dynamical simulations, the time range of lipid subdiffusion extends far beyond the viscoelastic memory range. We study three 1d models of correlated quenched Gaussian disorder to explain the puzzle: singular short-range (exponentially correlated), smooth short-range (Gaussian-correlated), and smooth long-range (power-law correlated) disorder. For a moderate disorder strength, transient viscoelastic subdiffusion changes into the subdiffusion caused by the randomness of the environment. It is characterized by a time-dependent power-law exponent of subdiffusion α(t), which can show nonmonotonous behavior, in agreement with some recent molecular-dynamical simulations. Moreover, the spatial distribution of test particles in this disorder-dominated regime is shown to be a non-Gaussian, exponential power distribution with index χ = 1.45–2.3, which also correlates well with molecular-dynamical findings and experiments. Furthermore, this subdiffusion is nonergodic with single-trajectory averages showing a broad scatter, in agreement with experimental observations for viscoelastic subdiffusion of various particles in living cells.
Multi-objective Planning for Distributed Generation with Consideration of the Randomness of DG output
Authors: Yu-Dong Bai , Hao Wang 
Published: October 2020

Abstract
DG as an alternative clean energy has a rapid development with the advantages of economy, environment protection and so on. But the randomness of power output has an influence on the security and stability of power system. At the same time, the trade-off among multiple optimization goals is often involved in the actual planning process. Therefore, using multi-objective optimization method to plan DG has wider application prospects. In this paper, a multi-objective optimization model of DG planning is established from three aspects of economy, safety and environmental protection. The flexible parameters of power system are introduced to represent the multi-objective optimization sub-functions and constraint conditions. Considering the influence of the stochastic feature of DG output, the multi-objective programming model is transformed into a flexible integrated optimization problem. One of the goals is lower cost, the others are safety and environmental protection. At the same time the objectives of economy, security and environmental protection are optimized comprehensively after DG integration, which are greatly adapted to the actual needs of the power grid planning department. In addition, the introduction of the static voltage stability margin optimization sub objective is of great significance for solving the problems caused by the uncertainty of load forecasting during the planning process.
Influence of VSC Converter Station on Switching Overvoltage of LCC Converter Station in LCC-VSC Hybrid DC System
Authors: Wang Lei , He Huiwen , Wang Dongju , Zhou Jiao 
Published: October 2020

Abstract
LCC-VSC hybrid DC system combines the advantages of LCC in transmitting large-capacity electric energy and VSC in power transmitting to weak AC power system without commutation failure, which makes the transmission form more flexible. A HVDC overvoltage calculation model of VSC converter station with LCC converter at the sending end and MMC converter at the receiving end is established in this paper. The principle of influence which is exerted by VSC converter station on LCC converter station is researched. The differences of Overvoltage of LCC converter station in hybrid DC System with blocking diode and not are compared and analyzed. The reason for larger overvoltage energy of LCC converter station is obtained. The necessity of blocking VSC station reverse DC voltage output is presented. The results show that the blocking diode plays an important role in limiting the overvoltage energy of LCC converter station in Hybrid DC system, which needs to be equipped in Hybrid DC system. After the blocking diode is installed, the insulation coordination of the LCC converter station at the transmission end can be the same as that of the conventional LCC HVDC transmission system.
An New Method for Detecting Harmonic Currents
Authors: Chen Xianfeng , Guo Lin , Gong Jie 
Published: October 2020

Abstract
The widespread use of power electronics has led to increasing problems with harmonics in power systems. The ip-iq detection method is a common method to detect harmonics. If there is a symmetry of the three phases of the power system, the ip-iq detection method can have very large errors in detecting the harmonic current. To solve this problem, an new method for detecting harmonic currents is proposed in this paper. The method solves the phase between the positive sequence voltage of each phase and the actual voltage by using the delay method to obtain the positive sequence fundamental signal of the fundamental current error problem. The simulation was then carried out using MATLAB/SIMULINK, and the simulation results confirmed the method still accurately detects harmonic currents in all cases. Therefore, this method is of great research importance for the elimination of harmonics.
Physical Layer Secure Data Transmission for Mobile Edge Computing: Beamforming and Artificial Noise
Authors: Xu Aidong , Tang Jie , Zeng Yonggang , Li Li Cheng , Jiang Yixin , Zhang Yunan , Wen Hong 
Published: October 2020

Abstract
As increasing threat to wireless data communication for mobile edge computing and high cost of conventional encryption implement in wireless environments, the physical layer security has aroused widespread concern to increase the security of data transmission in mobile edge computing. However, too much idealistic and unrealistic assuming in this area’s research result in security can hardly guarantee in the reality. This paper proposed a secure communications for mobile edging computing, which is using the sequcece combining with physical layer beamforming and artificial noise. By contrast to conventional schemes, the proposed scheme could enhance the security with probability 1 in two adverse situation. An advantage of the proposed scheme is that the upper layer can help the physical layer to defend each other, while up-layer system break by opponent, natural randomness of physical channel will play role to ensure system safety. We conduct simulations to verity the effectiveness of the proposed scheme for mobile edging computing.
A Low Voltage Governance and Optimization Strategy for Distribution Network Based on Multi-objective Particle Swarm Optimization Algorithm
Authors: Lu Zhu , Shasha Chen , Wenxiong Mo , Yong Wang , Guangmao Li , Guoyan Chen 
Published: October 2020

Abstract
With the increase of residential power consumption and the expansion of power system, distribution networks may face low voltage problem. The low voltage problem affects the normal power consumption of user and the safe and stable operation of power system. To solve it, a low voltage governance and optimization strategy for distribution network is proposed in this paper. First, a low-voltage identification method is proposed to determine low voltage governance objects and form the low-voltage database. Then, an optimization model considering multiple governance measures is derived and finally the multi-objective particles swarm optimization method is applied to solve it. The proposed method has been tested by a local distribution network system in Guangzhou. The simulation results show good governance effect of reducing low voltage area and improving the economy and stability of power grid, which can be used in the low voltage governance and power flow optimization for the distribution network.
Pin Defect Detection Method of UAV Patrol Overhead Line Based on Cascaded Convolution Network
Authors: Chaoyue Gu , Zhe Li , Jintao Shi , Gehao Sheng , Xiuchen Jiang 
Published: October 2020

Abstract
Pin plays the role of fixing power equipment on the overhead line. Once it is missing, it will lay a serious hidden danger for the normal operation of the overhead line. In order to improve the efficiency of UAV patrol transmission line and improve the detection rate of pin defect of transmission line, this paper proposes a pin defect detection method based on cascaded convolution network. In view of the complex background of inspection image and the small size of pin, the overall detection method is divided into two parts: positioning and diagnosis. Firstly, all fastener positions including pins are located by the improved Faster-RCNN network, and then RetinaNet network is cascaded to diagnose the defects of the fastener. The difficulty of learning is decreased and the generalization ability is improved in this way. Finally the experiment shows that this method can effectively detect the pin defects in the UAV patrol image.
Construction and Application of Distribution Network Grid Planning System
Authors: Yaolei Wang , Rong Liang , Kuihua Wu , Ren Zhao , Zhao Liu 
Published: October 2020

Abstract
For the problems of complex structure, unclear network and fuzzy boundary of power distribution network, grid planning is carried out in the power distribution network according to the idea of “Divide it into small grids, and manage separately”. Firstly, according to the modularization idea and the rule of land use and time development, a three-level grid planning system of power supply functional area, power supply mesh and power supply unit is constructed. Secondly, in the grid planning system, the spatial load forecasting method is given at three levels from bottom to top: at the level of power supply unit, the recommended value of saturated load density index is given, and the calculation method of the simultaneity rate in power supply unit is put forward. At the level of power supply mesh, based on the land nature of each power supply unit, the simultaneity rate of different land is given. Finally, based on the actual planning case of a certain region, the effectiveness of the grid planning method is verified.
Wind Turbine Power Curve Modelling Based on Hybrid Relevance Vector Machine
Authors: Jing Bo , Qian Zheng , Wang Anqi , Chen Tianyang , Zhang Fanghong 
Published: October 2020

Abstract
Wind turbine power curve (WTPC) is important for energy assessment, condition monitoring and abnormal detection. In recent years, researchers proposed a number of WTPC modelling approaches to continuously improve the model performance. In this paper, Relevance Vector Machine (RVM) is applied for WTPC modelling for the first time. Combine single-input RVM and multi-input RVM, this paper proposes a hybrid RVM method (HRVM) to further improve the fitting accuracy. Firstly, we analyse the features of model outputs of both single-input RVM and multi-input RVM. According to the analysis, the confidence interval of single-input RVM is used to limit the power output range of multi-input RVM. At last, SCADA data collected from three wind turbines are used to test the model performance. The results show that, compared with typical WTPC model approaches, HRVM achieves a good balance between fitting accuracy and computation cost.
Demand Response Business Process Design Considering Ubiquitous Functionality
Authors: Chen Zhang 
Published: October 2020

Abstract
The reformation of the electric power market and the application of new technology of source network load storage provide the basic conditions for the user side resources to participate in the grid interaction. More and more flexible resources, such as air conditioner, water heater and other smart home appliances, as well as new resources such as electric vehicles, distributed power supplies and energy storage, can participate in the demand response market. It is necessary to systematically analyse and design the whole process of demand response business. This paper aims at the demand response business, this paper sorts out the correlation among the participants, and designs the static relations and dynamic relations business processes of demand response based on the functional tree decomposition model. Taking the business flow as the main line, the paper designs the four-link demand response business implementation system architecture that contains energy flow, information flow and business flow.
LDA Optimized Multi-scale Texture Features Based Diagnosis Method of Defects inside Insulated Tubular Busbars
Authors: Li S Q , Zhou L B , Liu J H , Zhou Y W 
Published: October 2020

Abstract
In this paper, a method for diagnosing defects inside insulated tubular busbars based on LDA optimized multi-scale texture features is proposed to help to guarantee stable operation of the tubular busbars and the whole power grid. Firstly, multi-scale PRPD spectrum space was built with the UHF discharge signals of different defects by image pyramid theory. Then first-order, second-order and higher-order texture statistics were extracted from each image in the multi-scale PRPD spectrum space to form multi-scale texture features and LDA algorithm was used to optimize the features. The method was used to make texture features contain more information about partial discharge and help to improve the accuracy of diagnosis. Experiments were conducted on a 40.5kV insulated tubular busbar and CART classification trees were established as a classifier to identify the types of defects. The results of experiments show that this method can identify the defects of insulated tubular busbars accurately.
Very Short-Term Solar Irradiance Forecasting at a Sub-Minute Scale Based on WT-Cnns
Authors: zhu Zengwei , Xu Guoan , Zhang Zhen , Jiang Yongfen , Liu Ming 
Published: October 2020

Abstract
with the increasing of penetration of photovoltaic power, the solar irradiance forecasting has become a concern for power management. Due to the non-stationary and stochastic feature of the solar irradiance in a very time-term scale, the solar irradiance is difficult to accurately forecast. In this paper, the second-level solar irradiance is predicted using a deep-learning-based convolutional neural network (CNN) with the help of wavelet transformation (WT) and bootstrap sampling methods in time-frequency domain. The proposed method extracts the useful information from the reconstructed solar irradiance ‘image’ matrix in the frequency domain to form the next second level solar irradiance. The results show that the proposed model can learn the past features comprehensively, indicating significant potential for further study.
User Compensation Mechanism and Benefit Analysis under Orderly Charging Mode
Authors: Qian B , Luo X E , Lin X M , Xiao Y 
Published: October 2020

Abstract
With the vigorous promotion of national and local policies, the number of electric vehicles has been greatly increased, and orderly charging has gradually become an effective means to relieve the pressure of charging and capacity. In order to enhance the participation of charging load aggregators and charging users, improve the effectiveness of orderly charging, and realize the win-win situation between the aggregators and users, in this paper, firstly, the analysis of charging station benefit model is carried out from two aspects of charging station operation cost and compensation price, and then the user charging supplement mechanism based on response mechanism is studied and finally through simulation examples, different scenarios of charging equipment utilization are set, and the benefits of charging load aggregators and charging users are analysed, which provides suggestions for charging load aggregators to choose appropriate user compensation scheme under orderly charging mode.