bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of the temperature-dependent superelastic and elastocaloric effects of a NiTi tube under compression at 293–330 K
Authors: Cheng Siyuan , Yan Xu , Li Xueshi , Zhang Jiongjiong 
Published: May 2024

Comprehensive characterizations of the superelastic and elastocaloric effects of NiTi and NiTi-based shape memory alloys (SMA) in the operation temperature region are highly desirable for using them in elastocaloric coolers with a large temperature lift. In this article, we report the superelastic and elastocaloric effects of a commercially available superelastic polycrystalline NiTi SMA tube with an outer diameter of 5 mm and a wall thickness of 1 mm between 293 and 330 K. The NiTi tube sample was subjected to a training of 250 cycles to stabilize its superelastic and elastocaloric effects. We observed that temperature dependencies existed for both superelastic and elastocaloric effects of the NiTi tube, and stress–strain curves differed much between isothermal and adiabatic loading conditions. The largest temperature rise and temperature drop measured at 293 K under an applied strain of 3.66% and a strain rate of 0.1 s−1 during loading and unloading were 21 and 11 K, respectively. The loading conditions (loading function and holding time) also impacted the superelastic effect of the NiTi tube. We identified two major reasons for the irreversibility of the adiabatic temperature change: the hysteresis heat dissipation and the temporary residual strain after unloading, and they affected the cooling performance of the elastocaloric cooler in different ways. We investigated the dependencies of the superelastic and elastocaloric effects on the maximum applied strain and the temperature distribution on the NiTi tube during loading and unloading. The results are beneficial to the modeling of elastocaloric coolers with large temperature lifts.
Exploring the effective P-type dopants in two-dimensional Ga2O3 by first-principles calculations
Authors: Zeng H. , Ma C. , Wu M. 
Published: May 2024

Exploring effective p-type doping in Ga2O3 is crucial for both fundamental science and emerging applications. Recently, N and Zn elements have been shown to exhibit considerable contributions to effective p-type doping in 3D Ga2O3 experimentally and theoretically, whereas the studies of their doping behaviors in 2D Ga2O3 are rare. In this study, we investigate the possibilities of N and Zn elements to achieve effective p-type doping, manifesting in the introduction of shallow acceptor levels typically less than 0.5 eV in 2D Ga2O3 using first-principles calculations with the generalized gradient approximation + U method. The calculated defect formation energies suggest that the N-doped 2D Ga2O3 structures are more easily formed under Ga-rich conditions, while the Zn-doped structures are more readily generated under O-rich conditions. Moreover, the introduced N and Zn atoms preferentially incorporate on the threefold coordinated OII and pyramidally coordinated GaI sites, accompanying with N3− and Zn2+ oxidation states in 2D Ga2O3, respectively. In particular, the electronic structures indicate that the occupied N-2p and semi-occupied Zn-3d orbitals produce shallow hole levels ranging from 0.09 to 0.33 eV, demonstrating that N and Zn atoms can behave as effective p-type dopants in 2D Ga2O3. The magnetic moments for N- and Zn-doped 2D Ga2O3 are 1.00 μB due to the doping of one hole, where the magnetic moments can be mainly attributed to the N atom and the nearest O atoms, respectively. Our work may offer theoretical guidance for the design of p-type 2D Ga2O3 materials and shed light on its potential optoelectronic and magnetic applications.
When legal interpretation is not about language
Authors: Spaić Bojan , Isibor Roberto 
Published: May 2024

Abstract
Linguistic arguments are paramount in legal interpretation. They are widely used by judges and considered to be
ubiquitous across jurisdictions. It is claimed that they are decisive and limitative in the judicial interpretation of the law.
The claims have long been subject to theoretical scrutiny and, recently, testing within experimental jurisprudence. In this paper,
we analyse the judicial reasoning in a landmark Italian case from the end of the nineteenth century concerning Lidia Poët, an
aspiring practising female lawyer. The case was decided in the last instance by the Turin Court of Cassation. We give a detailed
argumentative analysis of the reasoning of the Court of Cassation in Turin in the Lidia Poët case and show that the crucial
linguistic and systematic arguments used are not grounds for the interpretative decision to exclude women from the denotation of
the word “lawyer.” We conclude that the linguistic arguments employed by courts often do not do the argumentative work they are
expected to do. Instead, they cover the substantial views that have determined the ascription of normative meaning to a term or
sentence.
Tone sandhi in Nuosu Yi at the interface
Authors: Lee Seunghun J. , Shen Hong 
Published: May 2024

Abstract
Nuosu Yi, a Tibeto-Burman language, has a tone sandhi pattern, where a lexical [33] -tone is realized
as [44]-tone on the surface. This tone sandhi pattern in Nuosu Yi is described as having a “weak phonological status
(Gerner, 2013: 28)”. In this study, we confirm this observation and further show
the role of phonological length in the tone sandhi patterns. A closer examination of the sandhi contexts, however, reveals an
intricate interplay between phonology and morphology of various aspects of Nuosu Yi grammar. Tone sandhi is conditioned by word
size and morphological processes. Monosyllabic words, but not multi-syllabic words, tend to undergo tone sandhi, and tone sandhi
is sensitive to morphological operations such as compounding.
Emergence of differential object marking in Asia Minor Greek
Authors: Atlamaz Ümit , Bagriacik Metin 
Published: May 2024

Abstract
This paper investigates the emergence of differential object marking (DOM) in the Asia Minor Greek dialect of
Pharasa (PhG) under contact with Turkish. We show that DOM in Turkish and PhG are both instances of structural accusative case and
DOM can be formally modeled as context sensitive dependent case. We propose that two factors caused the emergence of DOM in PhG,
namely (i) case neutralization in indefinite contexts, and (ii) an increase in the number of V-NP idioms borrowed from Turkish
where the NP is in bare form. These perturbations led to a significant change in the overall data created by the community
resulting in mixed input for the younger generations. Once the amount of bare NPs passed a certain threshold, a divergent grammar
became inevitable. We test our proposal using an abductive generalization learning algorithm based on the Tolerance Principle and
running a number of simulations. Our simulation results confirm our hypothesis.
Neural Audio Coding with Deep Complex Networks
Authors: Ru Jiawei , Wang Lizhong , Jia Maoshen , Wen Liang , Wang Chunxi , Zhao Yuhao , Wang Jing 
Published: May 2024

Abstract
This paper proposes a transform domain audio coding method based on deep complex networks. In the proposed codec, the time-frequency spectrum of the audio signal is fed to the encoder which consists of complex convolutional blocks and a frequency-temporal modeling module to obtain the extracted features which are then quantized with a target bitrate by the vector quantizer. The structure of the decoder which reconstruct the time-frequency spectrum of the audio from quantized features is symmetrical to the encoder. In this paper, a structure combining the complex multi-head self-attention module and the complex long short-term memory is proposed to capture both frequency and temporal dependencies. Subjective and objective evaluation tests show the advantage of the proposed method.
An Improved P-wave Peak Location Method Based on Pan-Tompkins Algorithm
Authors: Liu Runjie , Ma Chaoqi , Zhang Qionggui , Gao Xu , Zhang Lianji 
Published: May 2024

Abstract
Electrocardiogram (ECG) signal can reflect the health of the heart, and P wave is an important part of ECG signal, which reflects the excitatory conduction process of the heart. By precisely locating the P waves in the ECG signal, important information about heart disease can be obtained. In this paper, a method of P-wave peak localization based on Pan-Tompkins algorithm is proposed. Firstly, the ECG signal is decomposed by wavelet transform, and the coefficients of each layer are processed to filter out the noise such as baseline drift and electromyographic interference in the ECG signal. After the location of R wave in the signal was found by the Pan-Tompkins algorithm, the QRS wave was eliminated, and then the possible P wave location was found by the improved Pan-Tompkins algorithm. Finally, the correct P wave was screened by a screening strategy. Experimental results show that the sensitivity and accuracy of the P-wave localization algorithm proposed in this paper reach 94.78% and 95.10%, respectively. It shows that the proposed algorithm has good performance for P-wave localization.
Distilling Structural Knowledge for Platform-Aware Semantic Segmentation
Authors: Li Guilin , Wang Qiang , Zheng Xiawu 
Published: May 2024

Abstract
Knowledge Distillation (KD) aims to distill the dark knowledge of a high-powered teacher network into a student network, which can improve the capacity of student network and has been successfully applied to semantic segmentation. However, the standard knowledge distillation approaches merely represent the supervisory signal of teacher network as the dark knowledge, while ignoring the impact of network architecture during distillation. In this paper, we found that the student network with a more similar architecture against the teacher network obtains more performance gain from distillation. Therefore, a more generalized paradigm for knowledge distillation is to distill both the soft-label and the structure of the teacher network. We propose a novel Structural Distillation (SD) method which introduces the structural similarity constraints into vanilla knowledge distillation. We leverage Neural Architecture Search technique to search optimal student structure for semantic segmentation from a well-designed search space, which mimics the given teacher both in terms of soft-label and network structure. Experiment results make clear that our proposed method outperforms both the NAS with conventional Knowledge Distillation and human-designed methods, and achieves sota performance on the Cityscapes dataset under various platform-aware latency constraints. Furthermore, the best architecture discovered on Cityscapes also transfers well to the PASCAL VOC2012 dataset.
The influence of ripple on DC energy measurement and the improvement of wavelet threshold function filtering method
Authors: Bai Jingfen , Meng Jing , Yang Yubo , He Yunlong 
Published: May 2024

Abstract
DC energy has been applied in the construction of DC power grids, photovoltaic power generation, energy storage, and rapid charging of electric vehicles. The application of DC energy is of great significance for energy conservation, emission reduction, carbon reduction, and efficiency increase. In this paper, the reasons for the decrease in DC energy measurement accuracy caused by ripples in voltage and current are analyzed. The minimum requirements of ripples for DC energy meters are analyzed, and the traditional filtering method based on wavelet threshold is studied. An optimized and fast iterative wavelet threshold function was designed, the current signal of electric vehicle charging was selected, and the effectiveness of the algorithm proposed in this paper was verified through simulation.
Chaos control of Superbuck converter based on resonant parametric perturbation method
Authors: Gao Hongzhi , Han Guangyuan , Zhang Ran , Liu Yi , Wang Lihua 
Published: May 2024

Abstract
As a current control method, valley current mode (VCM) control is widely applied in DC-DC converters due to its absence of dead time restrictions and excellent transient response performance. This paper constructs a discrete iterative model of the VCM-controlled Superbuck converter. The bifurcation diagram is employed to analyze the impact of the reference current variation on the converter, and further validation is conducted through phase portraits and Poincaré sections. By introducing the resonant parametric perturbation method, a small perturbation signal is applied to the reference current to achieve chaos control. Simulation results demonstrate that this method effectively suppresses the chaotic behaviour of the Superbuck converter with the variation of reference current, significantly improving the performance and output ripple of the converter.
A novel pose calibration method for laser displacement sensor in the five-axis on-machine measurement system
Authors: Wang Dongfang , Huang Xiaoshuai , Xu Wei , Li Wenlong 
Published: May 2024

Abstract
The five-axis on-machine measurement system, equipped with a laser displacement sensor, offers an effective approach for conducting on-site inspections of freeform surface parts. It is crucial to address the calibration error pertaining to the sensor’s pose, encompassing both the beam direction and the zero position, as it directly impacts the measurement accuracy. This paper presents a new approach for the calibration of a laser displacement sensor’s pose, which is mounted on the spindle of a five-axis gantry machine tool. The proposed method utilizes measurements taken from multiple angles of a standard ball. Through the utilization of spherical constraints and coordinate translation transformation, the Levenberg-Marquardt iteration method is employed to derive the sensor’s beam direction, while the least square method is used to determine the sensor’s zero position. Applying this proposed method, the maximum error in the distance between the centers of the standard double ball is below 0.008 mm, which can meet the precision requirements of on-site inspection of freeform surface parts.
Simulation study on hydraulic lifting mechanism of lift-sliding mechanical parking system
Authors: Gong Wen 
Published: May 2024

Abstract
A mechanical parking system is an important parking equipment that can improve the utilization rate of urban space. In China, the lift-sliding mechanical parking system is the most widely used. Among many types of drives, the hydraulic pump-hydraulic cylinder type has advantages such as convenient system integration and expansion, energy saving, etc. The system is prone to vibration and pressure shock during operation. This paper focuses on the causes of vibration and hydraulic impact, constructs a simulation model, and analyzes the causes of vibration and hydraulic impact through simulation results, guiding equipment optimization.
Phase external calibration in interferometric microwave radiometer
Authors: Li Xin , Li Hao , Li Pengfei 
Published: May 2024

Abstract
The receiver error of the interferometric microwave radiometer can be calibrated by injecting the correlated noise into the receiver’s calibration port. However, in the antenna part without the internal calibration link, the residual phase error can be calibrated by an external noise source in an anechoic chamber and the significance of phase external calibration [1][2] is also verified by imaging the anechoic chamber.
Real-time Finite Element Analysis based on surrogate model
Authors: Xie Xiaoxuan , Ma Liping , Zhang Qingmeng , Zhang Jianyong , Dong Wendi , Chen Rumeng 
Published: May 2024

Abstract
In the field of engineering, Finite Element Analysis (FEA) serves as a pivotal numerical simulation tool. Nevertheless, its inherent offline nature and dependency on real-time data pose limitations on its versatility. To confront this challenge, a real-time FEA approach centered on surrogate modeling has been developed. This method enables the instantaneous prediction of critical performance parameters, thereby providing crucial support for real-time decision-making and process monitoring. In the context of this study, the focus is on the glass compression molding process, a process that is not easily observable. The research commences with preliminary thermal conduction simulations conducted using ABAQUS software. Subsequently, a surrogate model is constructed to facilitate real-time FEA for the temperature field of the glass preform. Finally, Unity 3D software is harnessed for visualization, offering an effective tool for the real-time monitoring and control of the glass-forming process.
Adversarial sample detection for EEG-based brain-computer interfaces
Authors: Zhang Hao , Gu Zhenghui 
Published: May 2024

Abstract
Deep neural networks (DNNs) play a pivotal role within the domain of brain-computer interfaces (BCIs). Nevertheless, DNNs are demonstrated to exhibit susceptibility to adversarial attacks. In BCIs, researchers have been concerned about the security of DNNs and have devised various adversarial defense methods to resist adversarial attacks. However, most defense methods encounter performance degradation when dealing with normal samples due to changes in the original model. As an alternative strategy, adversarial detection aims to devise additional modules or use statistical properties to identify potentially adversarial samples without changing the original model. Hence, the present study provides a comprehensive evaluation of several typical adversarial detection methods applied to EEG datasets. The experiments indicate that the detection method based on the kernel density estimation (KDE) shows the best performance under various adversarial attacks.
Passive imaging in composite plates using Green’s function reconstruction from the diffuse field
Authors: Wang Chao , Li Haicheng , Zhu Qi , Wu Chenchen , Su Zhan 
Published: May 2024

Abstract
Aiming at the problem that enables damage detection in real-time without any active excitation sources, we propose a new passive detection way based on diffuse field for structural health monitoring of CFRP structures. In this work, the wave propagation was first simulated with a k-space pseudo-spectra method in CFRPs. A diffuse field can be generated after multiple scattering from fibers and boundary reflections. After that, the reconstruction of Green’s function was investigated through different parameters including the number of noise sources, pulse bandwidth, transducer distance, etc. The delamination inspection process was explored by contrasting the reconstructed Green’s function with the referenced Green’s function on the composite plate. Finally, a probability distribution-based imaging algorithm was further applied for delamination imaging.
Total Plate Count of Traditionally Produced Smoked Skipjack in Ambon
Authors: Marthina Tapotubun Alfonsina , Rieuwpassa Fredrik , Matrutty Theodora E.A.A. , Nanlohy Hellen , Apituley Yolanda M.T.N 
Published: May 2024

Abstract
In Ambon City, smoked skipjack is very popular and is one of the people’s daily sources of protein. Smoked skipjack is classified as a ready-to-eat food ingredient. As a ready-to-eat product, the food safety aspect of smoked skipjack is a scientific fact that must be identified and disclosed so that people can consume it safely. The aim of this research was to determine the safety of smoked skipjack products produced in three production center villages in Ambon City based on the total plate count (TPC) value. The research applied exploratory method and was carried out in two stages: 1) conducting observations at six smoked skipjack home industries in three villages; 2) performing an analysis of the total plate count (TPC) of the smoked skipjack. The TPC analysis was carried out in the Fisheries Products Technology laboratory at Pattimura University. The total plate count (TPC) of smoked skipjack from three home industries in Ambon City is at a safe level for consumption, namely from TPC 3,8 x 102 CFU g−1 to 1,4 x 104 CFU g−1. Smoking is done traditionally with the same facilities and processes except for the form of smoked fish and the way it is displayed when sold.
Growth and addition in a herding model with fractional orders of derivatives
Authors: Yap Yee Jiun , bin Segi Rahmat Mohamad Rafi , Hui Pak Ming 
Published: May 2024

Abstract
This work involves an investigation of the mechanics of the herding behavior using a non-linear timescale, with the aim to generalize the herding model which helps to explain frequently occurring complex behavior in the real world, such as the financial markets. A herding model with fractional orders of derivatives was developed. This model involves the use of derivatives of order α where

0
<
α
⩽
1

. We have found the generalized result which indicates that number of groups of agents with size k increases linearly with time as

n

k

=

p
(
2
p
−
1
)
(
2
−
α
)

p
(
1
−
α
)
+
1

Γ

(
α
+

2
−
α

1
−
p

)

Γ
(
k
)

Γ

(
k
−
1
+
α
+

2
−
α

1
−
p

)

t

for

α
∈
(
0
,
1
]

, where p is a growth parameter. The result reduces to that in a previous herding model with a derivative order of 1 for α = 1. The results corresponding to various values of α and p are presented. The group-size distribution at long time is found to decay as a generalized power law, with an exponent depending on both α and p, thereby demonstrating that the scale invariance property of a complex system holds regardless of the order of the derivatives. The physical interpretation of fractional calculus is also explored based on the results of this work.
Perceptual Learning
Authors: Doyon Maxime 
Published: May 2024

Abstract
Over a lifetime, our perceptual capacities undergo transformations that impact our ability to recognize and process complex perceptual information. The result is ‘perceptual plasticity’, the ability to adapt and reorganize one’s sensory processing mechanisms and perceptual abilities in response to changes in sensory input, experiences, or dispositions. Progress in our understanding of perceptual plasticity’s first-personal manifestations is made by drawing insights from the phenomenological repertoire. This chapter makes this case by drawing attention to one specific class of phenomena—perceptual learning, viz. long-lasting perceptual change that results from practice or experience—and shows how phenomenology can contribute to the discussion over its nature and scope. It begins by analysing Husserl’s genetic phenomenology and shows how perceptions are informed by the weight of our experiential history. Starting from Merleau-Ponty, the chapter then analyses the body-schematic changes perceivers undergo when they develop perceptual skills and habits in response to changing situations and conditions.
Seasonality drives leaf solute potential independently from drought in grapevines. A commentary on ‘Grape cultivars adapted to hotter, drier growing regions exhibit greater photosynthesis in hot conditions despite less drought-resistant leaves’
Authors: Carlos Herrera Jose , Hochberg Uri 
Published: May 2024

This article comments on:
Gabriela Sinclair, Erin R. Galarneau, Josh F. Hnizdor, Andrew J. McElrone, Michael Andrew Walker and Megan K. Bartlett, Grape cultivars adapted to hotter, drier growing regions exhibit greater photosynthesis in hot conditions despite less drought-resistant leaves, Annals of Botany, Volume 134, Issue 2, 1 August 2024, Pages 205–217 https://doi.org/10.1093/aob/mcae032