bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection and identification of bad data in AC/DC hybrid systems with LCC and MMC
Authors: Zhao Huashi , Huang Yaohui , Song Zhiqiang , Xu Jianzhong , Zheng Kexin , Liang Kangkang 
Published: May 2024

Abstract
Based on the CIM/XML and CIM/E documents exported from the regional dispatching system, this paper focuses on data generation and starts by converting the exported documents into raw input data for state estimation. Considering the interactions between the AC system, LCC, MMC, and LCC-MMC interfaces, a unified iterative method is proposed to model the state estimation of the 500 kV subnetwork. Subsequently, Gaussian noise is added to the original measurement data, and the maximum residual test method is employed for detecting and identifying bad data. Finally, the effectiveness of the proposed models for AC/DC state estimation and the detection and identification of bad data are validated through simulation data.
An online detection method for the mechanical fault of circuit breakers of rural distribution lines based on continuous wavelet transform and vibration signal characteristics
Authors: Li Xuejun , Cheng Ming , Chen Wei , Luo Yanxin 
Published: May 2024

Abstract
Rural distribution lines are widely distributed and dispersed, involving numerous circuit breaker equipment. Detecting mechanical faults on each circuit breaker requires significant time and human resources. It can bring significant interference and power outage risks to the operation of the line. Therefore, an online detection method is studied for mechanical faults in rural distribution line circuit breakers. Continuous wavelet transform technology is used to extract the characteristics of circuit breaker vibration signals. This feature is used to locate the faulty section. The PNN neural network is introduced to identify fault feature samples and achieve online detection of mechanical faults. To test the application performance of this method, a comparative experiment is designed. The results verified that when using this method to extract the vibration signal of circuit breaker mechanical faults, the error is low, and the fault detection accuracy is high.
Dual three-phase permanent magnet synchronous motors model predictive torque control based on zero common-mode voltage
Authors: Zhang Yangdong , Huang Qiaoliang 
Published: May 2024

Abstract
This article proposes a multi-vector model predictive torque control strategy based on zero common-mode voltage to suppress common-mode voltage and harmonic currents in a dual three-phase permanent magnet synchronous motor. Firstly, 20 zero common-mode voltage vectors are selected from the traditional 64 basic voltage vectors. By synthesizing these 20 vectors into 6 virtual voltage vectors (VVV), control over the harmonic plane is achieved, reducing harmonic currents and eliminating common-mode voltage. Then, the control error of the flux is reduced by increasing the number of vectors to achieve the purpose of reducing the flux ripple. Finally, through duty cycle modulation, multi-vector model predictive torque control extends the modulation range to the entire sector plane. Simulation results confirm that this strategy can effectively suppress harmonic currents and common mode voltage.
Power system planning considering demand side response
Authors: Miao Linxin , Qi Yuchen , Li Haoen , Jiang Yumeng , Huang Ruanming , Song Tianli , Xue Kun , Cui Min , Liu Ziqiu 
Published: May 2024

Abstract
The large-scale integration of wind power into the grid requires the redesign and expansion of the transmission network. The volatility of wind power and the limited application of energy storage have prompted the inclusion of demand-side response in transmission planning to improve the resilience of the grid. In this paper, a power system planning model that incorporates demand-side response is developed and the model is solved by using a greedy stochastic adaptive search process. Based on the results of the Garver 6-node test, the old and new models are compared to validate the effectiveness of the power system planning model considering demand side response.
A single-objective optimization model for power systems with the introduction of line-heavy load rate index constraints
Authors: Han Xingning , Zhao Feifei , Zhang Wenjia , Qi Wanchun 
Published: May 2024

Abstract
The increasing penetration of new energy sources in new power systems has exacerbated the volatility and complexity of power system currents. Grid planning is facing higher challenges. Established grid planning models usually use the upper and lower limits of grid transmission capacity as constraints, but this may lead to long-term heavy load operation of certain lines and increase system risks. Therefore, this paper designs a line-heavy load rate constraint and establishes a single-objective optimization model for grid planning based on this constraint. Example analyses verify the effectiveness of adding line-heavy load rate constraints in planning and the reasonableness of the single-objective optimization model.
Outer Barrel services chain characterisation for the ATLAS ITk Pixel detector
Authors: Flores Sanz de Acedo Leyre ,   the ATLAS ITk Pixel collaboration
Published: May 2024

Abstract
For the high-luminosity upgrade of the ATLAS Inner Tracking detector of the ATLAS experiment, a new pixel detector will be installed to allow for a bigger bandwidth and cope with the increased radiation among other challenges. This contribution will present the evaluation of the Outer Barrel Pixel layer services chains. A full data transmission study covering data merging will be presented from the pixel module all the way to the FELIX data acquisition system, using most of the components foreseen for the detector. Challenges and results of the services chain of the Outer Barrel will be highlighted.
Testing and characterisation of the prototype readout chip for the High-Luminosity
LHC upgrade of the CMS Inner Tracker
Authors: Grippo Michael ,   the CMS Tracker Group
Published: May 2024

Abstract
This contribution describes the characterisation and validation campaign of the prototype
of the CMS Readout Chip (CROC), a 65 nm CMOS pixel readout ASIC for the CMS Inner Tracker upgrade
for High Luminosity LHC. This validation campaign includes tests with single-chip and multi-chip
modules, irradiation campaigns, test beams and wafer-level tests. The main results obtained in the
testing of the CROC prototype will be outlined. Key improvements and fixes that have been
implemented in the final version of the chip before the October 2023 submission will be described.
Investigation of low gain avalanche detectors exposed to proton fluences beyond 1015
n
eq cm-2
Authors: Sorenson J. , Hoeferkamp M.R. , Kramberger G. , Seidel S. , Si J. 
Published: May 2024

Abstract
Low gain avalanche detectors (LGADs) deliver excellent
timing resolution, which can mitigate mis-assignment of vertices
associated with pileup at the High Luminosity LHC and other future
hadron colliders. The most highly irradiated LGADs will be subject
to 2.5 × 1015
n
eq cm-2
of hadronic fluence during HL-LHC operation; their performance must
tolerate this. Hamamatsu Photonics K.K. and Fondazione Bruno Kessler
LGADs have been irradiated with 400 and 500 MeV protons
respectively in several steps up to
1.5 × 1015
n
eq cm-2. Measurements of the acceptor removal constants of
the gain layers, evolution of the timing resolution and charge
collection with damage, and inter-channel isolation characteristics,
for a variety of design options, are presented here.
Multi-scale deep residual shrinkage networks with a hybrid attention mechanism for rolling bearing fault diagnosis
Authors: Zhang Xinliang , Wang Yanqi , Wei Shengqiang , Zhou Yitian , Jia Lijie 
Published: May 2024

Abstract
The fault diagnosis of rolling bearings based on deep
networks is hindered by the unexpected noise involved with
accessible vibration signals and global information abatement in
deepened networks. To combat the degradation, a multi-scale deep
residual shrinkage network with a hybrid attention mechanism
(MH-DRSN) is proposed in this paper. First, a spatial domain
attention mechanism is introduced into the residual shrinkage module
to represent the distance dependence of the feature maps. Then, a
hybrid attention mechanism considering both the inner-channeled and
cross-channeled characteristics is constructed. Through the
comprehensive evaluation of the feature map, it provides a soft
threshold for the activation function and realizes the feature-map
selection adaptively. Second, the dilated convolution with different
dilation rates is implemented for multi-scale context information
extraction. Through the feature combination of the DRSN and the
dilated convolution, the global information of the rolling bearing
fault is strengthened and preserved as the fault diagnosis network
is deepened. Finally, the performance of the proposed
fault-diagnosis model is validated on the dataset from Case Western
Reserve University (CWRU). The experimental results show that,
compared with common convolution neural networks, the proposed
neural diagnosis model provides a higher identification accuracy and
better robustness under noise interference.
Imaging of low Z masked with high Z (Pb, U) materials using 14 MeV neutron
Authors: Bishnoi Saroj , Patel Tarun , Sarkar P.S. , Pant L.M. 
Published: May 2024

Abstract
An experimental study has been performed using 14 MeV neutrons for imaging of low Z material (particularly composed of C, H, O elements) masked with thick layers of dense and high Z materials. The experimental setup consists of a D-T neutron generator, a metallic collimator and an imaging system. The imaging system is designed with a polypropylene zinc sulphide scintillator screen integrated with a lens coupled 16-bit ICCD camera. Imaging capability of the system was investigated using iron test samples with holes and line pair features. The minimum hole size of 2 mm could be imaged at a contrast of 36% and a line of 2 mm width visible at a contrast of 24% indicating the system's resolution of ∼ mm. Low Z samples such as water (H2O) and polyethylene (C2H2)
n
placed behind thick layers of Pb (40 mm) and Uranium (35 mm), were imaged successfully. These images reveal the system's ability towards low Z material imaging in the presence of heavier metals. Good contrast images acquired at a lower neutron yield of ∼ 5 × 108 n/sec of D-T neutron generator has provided a possibility to realise fast neutron imaging having moderate resolution (∼ mm) with a smaller footprint and an economical system design for field applications.
Performance of a first full-size WOM-based liquid scintillator detector cell as prototype for the SHiP Surrounding Background Tagger
Authors: Alt J. , Bezshyyko O. , Böhles M. , Brignoli A. , Conaboy A. , Deucher P. , Eckardt C. , Ernst A. , Fischer H. , Hollnagel A. , Jadidi M. , Lacker H. , Lyons F. , Molzberger T. , Ochoa S. , Orlov V. , Reghunath A. , Rehbein F. , Schaaf M. , Scharf C. , Schmidt J. , Schumann M. , Vagts A. , Wurm M. 
Published: May 2024

Abstract
As a prototype detector for the SHiP Surrounding Background
Tagger (SBT), we constructed a cell
(120 cm × 80 cm × 25 cm) made from corten steel that is filled with liquid
scintillator (LS) composed of linear alkylbenzene (LAB) and
2,5-diphenyloxazole (PPO). The detector is equipped with two
Wavelength-shifting Optical Modules (WOMs) for light collection of
the primary scintillation photons. Each WOM consists of an acrylic
tube that is dip-coated with a wavelength-shifting layer on its
surface. Via internal total reflection, the secondary photons
emitted by the molecules of the wavelength shifter are guided to a
ring-shaped array of 40 silicon photomultipliers (SiPMs) coupled to
the WOM for light detection. The granularity of these SiPM arrays
provides an innovative method to gain spatial information on the
particle crossing point. Several improvements in the detector design
significantly increased the light yield with respect to earlier
proof-of-principle detectors.

We report on the performance of this prototype detector during an
exposure to high-energy positrons at the DESY II test beam facility
by measuring the collected integrated yield and the signal
time-of-arrival in each of the SiPM arrays. The resulting detection
efficiency and reconstructed energy deposition of the incident
positrons are presented, as well as the spatial and time resolution
of the detector. These results are then compared to Monte Carlo
simulations.
Gradients of properties increase the morphing and stiffening performance of bioinspired synthetic fin rays
Authors: Das Saurabh , Kunjam Prashant , Ebeling Jona Faye , Barthelat Francois 
Published: May 2024

Abstract
State-of-the-art morphing materials are either very compliant to achieve large shape changes (flexible metamaterials, compliant mechanisms, hydrogels), or very stiff but with infinitesimal changes in shape that require large actuation forces (metallic or composite panels with piezoelectric actuation). Morphing efficiency and structural stiffness are therefore mutually exclusive properties in current engineering morphing materials, which limits the range of their applicability. Interestingly, natural fish fins do not contain muscles, yet they can morph to large amplitudes with minimal muscular actuation forces from the base while producing large hydrodynamic forces without collapsing. This sophisticated mechanical response has already inspired several synthetic fin rays with various applications. However, most ‘synthetic’ fin rays have only considered uniform properties and structures along the rays while in natural fin rays, gradients of properties are prominent. In this study, we designed, modeled, fabricated and tested synthetic fin rays with bioinspired gradients of properties. The rays were composed of two hemitrichs made of a stiff polymer, joined by a much softer core region made of elastomeric ligaments. Using combinations of experiments and nonlinear mechanical models, we found that gradients in both the core region and hemitrichs can increase the morphing and stiffening response of individual rays. Introducing a positive gradient of ligament density in the core region (the density of ligament increases towards the tip of the ray) decreased the actuation force required for morphing and increased overall flexural stiffness. Introducing a gradient of property in the hemitrichs, by tapering them, produced morphing deformations that were distributed over long distances along the length of the ray. These new insights on the interplay between material architecture and properties in nonlinear regimes of deformation can improve the designs of morphing structures that combine high morphing efficiency and high stiffness from external forces, with potential applications in aerospace or robotics.
Research of biomimetic corrugation on the blade flutter suppression in large-scale wind turbine systems
Authors: Zhang Lijun , Wang Kaifei , Zhang Xu , Liu Shibo , Jing Zhengjun , Lu Jiahui , Cui Xudong , Liu Jing 
Published: May 2024

Abstract
Aiming at the blade flutter of large horizontal-axis wind turbines, a method by utilizing biomimetic corrugation to suppress blade flutter is first proposed. By extracting the dragonfly wing corrugation, the biomimetic corrugation airfoil is constructed, finding that mapping corrugation to the airfoil pressure side has better aerodynamic performance. The influence of corrugation type, amplitude λ, and intensity on airfoil flutter is analyzed using orthogonal experiment, which determines that the λ has the greatest influence on airfoil flutter. Based on the fluctuation range of the moment coefficient ΔC
m, the optimal airfoil flutter suppression effect is obtained when the type is III, λ= 0.6, and intensity is denser (n = 13). The effective corrugation layout area in the chord direction is determined to be the leading edge, and the ΔC
m of corrugation airfoil is reduced by 7.405%, compared to the original airfoil. The application of this corrugation to NREL 15 MW wind turbine 3D blades is studied, and the influence of corrugation layout length in the blade span direction on the suppressive effect is analyzed by fluid-structure interaction. It is found that when the layout length is 0.85 R, the safety margin S
f reaches a maximum value of 0.3431 Hz, which is increased 2.940%. The results show that the biomimetic corrugated structure proposed in this paper can not only improve the aerodynamic performance by changing the local flow field on the surface of the blade, but also increase the structural stiffness of the blade itself, and achieve the effect of flutter suppression.
Distinct responses of tropical cyclone activity to spatio-uniform and nonuniform SST warming patterns
Authors: Xu Mingrui , Zhan Ruifen , Zhao Jiuwei 
Published: May 2024

Abstract
Most previous studies have reported a decrease in global tropical cyclone (TC) genesis frequency (TCGF) under anthropogenic warming. However, little attention has been drawn to the influence of sea surface temperature (SST) warming patterns on TCGF changes. Here, we investigate the impacts of three distinct SST warming patterns on global TCGF: uniform SST warming, nonuniform (El Niño-like) SST warming, and a combination of both. Results show that spatio-uniform SST warming has a limited impact on global TCGF, instead redistributing the TC genesis locations. Conversely, nonuniform SST warming significantly suppresses global TCGF. The combined warming produces a similar decrease in TCGF to nonuniform warming albeit with differences in spatial distribution. This indicates the dominant role of nonuniform SST warming in affecting TCGF and highlights the nonlinearity of the process. Further analysis shows that these differences in TCGF primarily stem from the distinct responses of tropical circulations to the three warming patterns.
Anomalous and ultraslow diffusion of a particle driven by power-law-correlated and distributed-order noises
Authors: Tomovski Z , Górska K , Pietrzak T , Metzler R , Sandev T 
Published: May 2024

Abstract
We study the generalised Langevin equation (GLE) approach to anomalous diffusion for a harmonic oscillator and a free particle driven by different forms of internal noises, such as power-law-correlated and distributed-order noises that fulfil generalised versions of the fluctuation-dissipation theorem. The mean squared displacement and the normalised displacement correlation function are derived for the different forms of the friction memory kernel. The corresponding overdamped GLEs for these cases are also investigated. It is shown that such models can be used to describe anomalous diffusion in complex media, giving rise to subdiffusion, superdiffusion, ultraslow diffusion, strong anomaly, and other complex diffusive behaviours.
An algebraic formulation of nonassociative quantum mechanics
Authors: Schupp Peter , Szabo Richard J 
Published: May 2024

Abstract
We develop a version of quantum mechanics that can handle nonassociative algebras of observables and which reduces to standard quantum theory in the traditional associative setting. Our algebraic approach is naturally probabilistic and is based on using the universal enveloping algebra of a general nonassociative algebra to introduce a generalized notion of associative composition product. We formulate properties of states together with notions of trace, and use them to develop Gel’fand–Naimark–Segal constructions. We describe Heisenberg and Schrödinger pictures of completely positive dynamics, and we illustrate our formalism on the explicit examples of finite-dimensional matrix Jordan algebras as well as the octonion algebra.
Machine learning for parameters diagnosis of spark discharge by electro-acoustic signal
Authors: XIONG 熊 Jun 俊 , LU 卢 Shiyu 诗宇 , LIU 刘 Xiaoming 晓明 , ZHOU 周 Wenjun 文俊 , ZHA 查 Xiaoming 晓明 , PEI 裴 Xuekai 学凯 
Published: May 2024

Abstract
Discharge plasma parameter measurement is a key focus in low-temperature plasma research. Traditional diagnostics often require costly equipment, whereas electro-acoustic signals provide a rich, non-invasive, and less complex source of discharge information. This study harnesses machine learning to decode these signals. It establishes links between electro-acoustic signals and gas discharge parameters, such as power and distance, thus streamlining the prediction process. By building a spark discharge platform to collect electro-acoustic signals and implementing a series of acoustic signal processing techniques, the Mel-Frequency Cepstral Coefficients (MFCCs) of the acoustic signals are extracted to construct the predictors. Three machine learning models (Linear Regression, k-Nearest Neighbors, and Random Forest) are introduced and applied to the predictors to achieve real-time rapid diagnostic measurement of typical spark discharge power and discharge distance. All models display impressive performance in prediction precision and fitting abilities. Among them, the k-Nearest Neighbors model shows the best performance on discharge power prediction with the lowest mean square error (MSE = 0.00571) and the highest

-squared value (

). The experimental results show that the relationship between the electro-acoustic signal and the gas discharge power and distance can be effectively constructed based on the machine learning algorithm, which provides a new idea and basis for the online monitoring and real-time diagnosis of plasma parameters.
Temporal properties of the stochastic fractional heat equation with spatially-colored noise
Authors: Wang Ran , Xiao Yimin 
Published: May 2024

Consider the stochastic partial differential equation

∂

∂
t

u
t

(
x
)
=
−
(
−
Δ

)

α
2

u
t

(
x
)
+
b

(

u
t

(
x
)
)

+
σ

(

u
t

(
x
)
)

F
˙

(
t
,
x
)
,

t
≥
0
,

x
∈

R

d

,

\begin{equation*} \frac {\partial }{\partial t}u_t(\boldsymbol {x})= -(-\Delta )^{\frac {\alpha }{2}}u_t(\boldsymbol {x}) +b\left (u_t(\boldsymbol {x})\right )+\sigma \left (u_t(\boldsymbol {x})\right ) \dot F(t, \boldsymbol {x}), \quad t\ge 0,\: \boldsymbol {x}\in \mathbb R^d, \end{equation*}

where

−
(
−
Δ

)

α
2

-(-\Delta )^{\frac {\alpha }{2}}

denotes the fractional Laplacian with power

α
2

∈
(

1
2

,
1
]

\frac {\alpha }{2}\in (\frac 12,1]

, and the driving noise

F
˙

\dot F

is a centered Gaussian field which is white in time and has a spatial homogeneous covariance given by the Riesz kernel. We study the detailed behavior of the approximation of the temporal gradient

u

t
+

ε

(
x
)
−

u
t

(
x
)

u_{t+{\varepsilon }}(\boldsymbol {x})-u_t(\boldsymbol {x})

at any fixed

t
>
0

t > 0

and

x
∈

R

d

\boldsymbol {x}\in \mathbb R^d

, as

ε

↓
0

{\varepsilon }\downarrow 0

. As applications, we deduce Khintchin’s law of iterated logarithm, Chung’s law of iterated logarithm, and a result on the

q
q

-variations of the temporal process

{

u
t

(
x
)

}

t
≥
0

\{u_t(\boldsymbol {x})\}_{ t \ge 0}

of the solution, where

x
∈

R

d

\boldsymbol {x}\in \mathbb R^d

is fixed.
The Responsibility to Protect
Authors: Williams Abiodun 
Published: May 2024

AbstractChapter 5 explores Kofi Annan’s approach to the issue of humanitarian intervention, and his idea of two sovereignties—of states and of people. His conviction that sovereignty was not absolute but contingent, and was vested in a state’s citizenry, not just in the state itself, is central to understanding his Secretary-Generalship. He produced a UN Action Plan to Prevent Genocide and supported the establishment of the International Criminal Court. As a norm entrepreneur, he challenged member states to find a consensus on the vital issue of the international community’s responsibility in the face of mass atrocities. At the 2005 World Summit, all member states unanimously accepted their Responsibility to Protect civilians from four types of mass atrocity crimes: genocide, war crimes, ethnic cleansing, and crimes against humanity.