bluuebunny/crossref_metadata_2025_split huggingface dataset:
LiDAR-based SLAM pose estimation via GNSS graph optimization algorithm
Authors: He Wei , Li Rui , Liu Tianyue , Yu Yaoyao 
Published: May 2024

Abstract
LiDAR simultaneous localization and mapping (SLAM) is widely used in positioning and navigation. By illuminating a series of light spots on the surface of an object, orientation and pose information is obtained. However, improving the accuracy of the pose optimization algorithm without affecting the position information is difficult. Therefore, this study combines the graph optimization algorithm and the Global Navigation Satellite System (GNSS) to optimize the coordinates of the target object in the LiDAR SLAM pose. A GNSS pose estimation algorithm is proposed to show the relationship between positioning algorithms with and without GNSS pose optimization by analyzing the deviation of the distance, level, and height laser point cloud coordinates. The results show that with GNSS pose optimization, the deviations in distance, level, and height are 99% smaller than those without GNSS pose optimization. Furthermore, we demonstrate the effectiveness of the proposed graph optimization algorithm and GNSS optimization of LiDAR SLAM. Finally, this study highlights the directions for the application of wireless communication technology in the field of LiDAR SLAM.
Space-time image velocimetry in blurred scenes based on BSTI-DCGAN data augmentation
Authors: Hu Qiming , Jiang Dongjin , Zhang Guo , Zhang Ya , Wang Jianping 
Published: May 2024

Abstract
Due to the limited sample quantity and the complex data collection process of the blurred space-time image (BSTI) dataset, the deep learning-based space-time image velocimetry (STIV) results in larger errors when applied to blurry videos. To enhance the measurement accuracy, we propose the use of STIV in blurred scenes based on BSTI-deep convolutional generative adversarial network (DCGAN) data augmentation. Firstly, BSTI-DCGAN is developed based on the DCGAN. This network utilizes a bilinear interpolation-convolution module for upsampling and integrates coordinated attention and multi-concatenation attention to enhance the resemblance between generated and real images. Next, further expanding the dataset by using artificially synthesized space-time images subsequently, all space-time images are transformed into spectrograms to create a training dataset for the classification network. Finally, the primary spectral direction is detected using the classification network. The experimental results indicate that our approach effectively augments the dataset and improves the accuracy of practical measurements. Under the condition of video blur, the relative errors of the average flow velocity and discharge are 3.92% and 2.72%, respectively.
Wasserstein local slow feature analysis and its application to process monitoring
Authors: Fu Yuanjian , Wu Zhichao , Luo Chaomin , Xu Xue 
Published: May 2024

Abstract
Complex industrial processes are commonly characterized by dynamics, which results from compensation of the closed-loop control and complex reflux during process operations. In this work, we propose a novel method termed the Wasserstein local slow feature analysis approach (WLSFA), used to monitor the dynamic process, which can learn slowly varying information to capture the trend of process variations and characterize dynamics. Specifically, Wasserstein graph embedding based on optimal transport is proposed to preserve the local geometrical structure of raw data so that the reduced-dimensionality representations can more faithfully reveal the underlying information of data, enhancing monitoring performance. Moreover, the

l
2

-norm orthogonal constraint is incorporated into the objective function to improve the generalization ability and alleviate the false alarm rate. Based on the WLSFA model, a contribution plot denoting reconstruction is developed to locate the fault variables, which is beneficial for regulating abnormal conditions toward normal levels. Finally, the efficiency of the proposed approach is illustrated by a benchmark process and application to a real-world fractionation process.
Numerical investigation on the convergence of self-consistent Schrödinger-Poisson equations in semiconductor device transport simulation
Authors: Zhu Junyan , Cao Jiang , Song Chen , Li Bo , Han Zhengsheng 
Published: May 2024

Abstract
Semiconductor devices at the nanoscale with low-dimensional materials as channels exhibit quantum transport characteristics, thereby their electrical simulation relies on the self-consistent solution of the Schrödinger-Poisson equations. While the non-equilibrium Green’s function (NEGF) method is widely used for solving this quantum many-body problem, its high computational cost and convergence challenges with the Poisson equation significantly limit its applicability. In this study, we investigate the stability of the NEGF method coupled with various forms of the Poisson equation, encompassing linear, analytical nonlinear, and numerical nonlinear forms Our focus lies on simulating carbon nanotube field-effect transistors (CNTFETs) under two distinct doping scenarios: electrostatic doping and ion implantation doping. The numerical experiments reveal that nonlinear formulas outperform linear counterpart. The numerical one demonstrates superior stability, particularly evident under high bias and ion implantation doping conditions. Additionally, we investigate different approaches for presolving potential, leveraging solutions from the Laplace equation and a piecewise guessing method tailored to each doping mode. These methods effectively reduce the number of iterations required for convergence.
Nano-enabled smart and functional materials toward human well-being and sustainable developments
Authors: Rajeev Ashna , Yin Lu , Kalambate Pramod K , Khabbaz Mahsa Barjini , Trinh Binh , Kamkar Milad , Mekonnen Tizazu H , Tang Shirley , Zhao Boxin 
Published: May 2024

Abstract
Fabrication and operation on increasingly smaller dimensions have been highly integrated with the development of smart and functional materials, which are key to many technological innovations to meet economic and societal needs. Along with researchers worldwide, the Waterloo Institute for Nanotechnology (WIN) has long realized the synergetic interplays between nanotechnology and functional materials and designated ‘Smart & Functional Materials’ as one of its four major research themes. Thus far, WIN researchers have utilized the properties of smart polymers, nanoparticles, and nanocomposites to develop active materials, membranes, films, adhesives, coatings, and devices with novel and improved properties and capabilities. In this review article, we aim to highlight some of the recent developments on the subject, including our own research and key research literature, in the context of the UN Sustainability development goals.
Terahertz communication: detection and signal processing
Authors: Lu Guanxuan , Wang Jiaqi , Zhou Rui , Xie Zhemiao , Yuan Yifei , Huang Lin , Yeow John T W 
Published: May 2024

Abstract
The development of 6 G networks has promoted related research based on terahertz communication. As submillimeter radiation, signal transportation via terahertz waves has several superior properties, including non-ionizing and easy penetration of non-metallic materials. This paper provides an overview of different terahertz detectors based on various mechanisms. Additionally, the detailed fabrication process, structural design, and the improvement strategies are summarized. Following that, it is essential and necessary to prevent the practical signal from noise, and methods such as wavelet transform, UM-MIMO and decoding have been introduced. This paper highlights the detection process of the terahertz wave system and signal processing after the collection of signal data.
Quantitative derivation of a two-phase porous media system from the one-velocity Baer–Nunziato and Kapila systems
Authors: Crin-Barat Timothée , Shou Ling-Yun , Tan Jin 
Published: May 2024

Abstract
We derive a novel two-phase flow system in porous media as a relaxation limit of compressible multi-fluid systems. Considering a one-velocity Baer–Nunziato system with friction forces, we first justify its pressure-relaxation limit toward a Kapila model in a uniform manner with respect to the time-relaxation parameter associated with the friction forces. Then, we show that the diffusely rescaled solutions of the damped Kapila system converge to the solutions of the new two-phase porous media system as the time-relaxation parameter tends to zero. In addition, we also prove the convergence of the Baer–Nunziato system to the same two-phase porous media system as both relaxation parameters tend to zero. For each relaxation limit, we exhibit sharp rates of convergence in a critical regularity setting. Our proof is based on an elaborate low-frequency and high-frequency analysis via the Littlewood–Paley decomposition and includes three main ingredients: a refined spectral analysis of the linearized problem to determine the frequency threshold explicitly in terms of the time-relaxation parameter, the introduction of an effective flux in the low-frequency region to overcome the loss of parameters due to the overdamping phenomenon, and renormalized energy estimates in the high-frequency region to cancel higher-order nonlinear terms. To justify the convergence rates, we discover several auxiliary unknowns allowing us to recover crucial

O

(
ε
)

bounds.
Spectral structure of Moran Sierpinski-type measure on

R

2
Authors: Cao Jian , Lu Jian-Feng , Zhang Min-Min 
Published: May 2024

Abstract
Let

M
n

=

diag

[
3

p
n

,
3

q
n

]

with

p
n

,

q
n

⩾
1

for all

n
⩾
1

and let

D
=

{
(
0
,
0

)
t

,
(
1
,
0

)
t

,
(
0
,
1

)
t

}

. One can generate a Borel probability measure

μ

{

M
n

}

,
D

=

δ

M
1

−
1

D

∗

δ

(

M
2

M
1

)

−
1

D

∗

δ

(

M
3

M
2

M
1

)

−
1

D

∗
⋯
.

Such measure

μ

{

M
n

}
,
D

is called a Moran Sierpinski-type measure. It is known Deng et al (Acta Math. Sin. submitted) that the associated Hilbert space

L
2

(

μ

{

M
n

}
,
D

)

has an exponential orthonormal basis. In this paper, we first characterize all the maximal exponential orthogonal sets for

L
2

(

μ

{

M
n

}
,
D

)

. For such a maximal orthogonal set, we then give some sufficient conditions to determine whether it is an orthonormal basis of

L
2

(

μ

{

M
n

}
,
D

)

or not.
The diffusive limit of Boltzmann equation in torus
Authors: Liu Zhengrong , Yu Hongjun 
Published: May 2024

Abstract
The Boltzmann equation of kinetic theory gives a statistical description of a gas of interacting particles. It is well known that the Boltzmann equation is related to the Euler and Navier–Stokes equations in the field of gas dynamics. In this paper we are concerned with the incompressible Navier–Stokes–Fourier limit of the Boltzmann equation. We prove the incompressible Navier–Stokes–Fourier limit globally in time and the time decay rate of the solution to the rescaled Boltzmann equation in a torus. For ɛ small, by using the truncated expansion and

L

x
,
v

2

–

L

x
,
v

∞

method, we prove such a limit for the general potentials

γ
∈
(
−
3
,
1
]

.
A landmark-supervised registration framework for multi-phase CT images with cross-distillation
Authors: Rao Fan , Lyu Tianling , Feng Zhan , Wu Yuanfeng , Ni Yangfan , Zhu Wentao 
Published: May 2024

Abstract

Objective. Multi-phase computed tomography (CT) has become a leading modality for identifying hepatic tumors. Nevertheless, the presence of misalignment in the images of different phases poses a challenge in accurately identifying and analyzing the patient’s anatomy. Conventional registration methods typically concentrate on either intensity-based features or landmark-based features in isolation, so imposing limitations on the accuracy of the registration process. Method. We establish a nonrigid cycle-registration network that leverages semi-supervised learning techniques, wherein a point distance term based on Euclidean distance between registered landmark points is introduced into the loss function. Additionally, a cross-distillation strategy is proposed in network training to further improve registration performance which incorporates response-based knowledge concerning the distances between feature points. Results. We conducted experiments using multi-centered liver CT datasets to evaluate the performance of the proposed method. The results demonstrate that our method outperforms baseline methods in terms of target registration error. Additionally, Dice scores of the warped tumor masks were calculated. Our method consistently achieved the highest scores among all the comparing methods. Specifically, it achieved scores of 82.9% and 82.5% in the hepatocellular carcinoma and the intrahepatic cholangiocarcinoma dataset, respectively. Significance. The superior registration performance indicates its potential to serve as an important tool in hepatic tumor identification and analysis.
Numerical characterization of capacitively coupled CF4 plasmas modulated by anion beam injection
Authors: Zhou Youyou , Xu Jingwen , Wang Yu , Wu Hao , Wang Hongyu , Jiang Wei , Zhang Ya 
Published: May 2024

Abstract
In the study of electronegative CF4 capacitively coupled plasmas (CCP), plasma modulation is typically achieved by varying parameters such as pressure and voltage. In this work, the particle-in-cell/Monte Carlo (PIC/MC) method is used to simulate modulation of CF4 CCP with injection of anions (F−) ion beam (FB). The results demonstrate that FB injection effectively enhances the dissociation collision process between F− ions and neutral molecules, thus altering the densities of electrons and ions. An effective modulation of the characteristic parameters of the plasma of CF4 can be achieved by controlling the current and energy of FB. Particularly noteworthy is the transition of the heating mode from the DA mode to the dissociation mode as the FB current increases to 0.038 A (energy fixed at 10 keV) or when the FB energy exceeds 10 keV (current fixed on 0.038 A). This transition is attributed to the generation of a substantial number of electrons through dissociative collisions. This approach provides insight into the controlled modulation of plasma characteristics in CF4 CCP, offering potential applications in various plasma-based technologies.
Characteristics of laser induced plasma near a flat gas-liquid interface and its effect on the performance of laser induced breakdown spectroscopy (LIBS) detection
Authors: Xue Yuanyuan , Tian Ye , Li Jiamin , Sui Mingda , Pan Kezeng , Zhong Shilei 
Published: May 2024

Abstract
Moving the laser focus to the vicinity of the gas-liquid interface is the key point for many new enhanced and new methods to improve the quality of spectral signals in water Laser induced breakdown spectroscopy (LIBS) detection. Understanding the generation and evolution characteristics of the plasma induced by pulsed laser near the gas–liquid interface is of great significance for the establishment of evolution models and improvement of these new LIBS methods. In this paper, a set of slow horizontal flow auxiliary system is established to provide an ideal flat gas–liquid two-phase interface experimental condition. Experimental research on vertical incidence flat system was conducted using techniques such as time-resolved imaging, plasma characterization diagnosis, and spectral analysis. And the detection capabilities of the system were also tested. The characteristics and mechanisms of LIBS near the gas-liquid two-phase interface were investigated with the laser incident on the sample along the vertical direction. Simulation of the laser beam focusing process and observation of laser beam spot images show that the shift of plasma generation position relative to the focal point results from the refraction of the laser beam entering the solution from the air and the ‘interface effect’ of propagation on the vertical direction. Moreover, the plasma forms only the optical power density surpasses the breakdown threshold. In this work, plasma with smaller size, rounder shape, stronger radiation, higher temperature, and higher density can be produced when the focus position is in the liquid column 0.3 mm away from the upper interface. Simultaneously, for example, the Mg ion line at 285.213 nm, the obtained spectral intensity to signal-to-background ratio reaches the maximum value, and a better spectral signal can be obtained, which is 2–4 times of other positions, and the detection limits of the elements Na, Mg, and Ca also reach the lowest level, with 1.6–2.4 times of the detection limit of other focusing positions for Mg and 1.4–1.7 times for Ca, respectively.
Characterization of OH species in kHz air/H2O atmospheric pressure dielectric barrier discharges
Authors: Huang Cheng-Liang , Liao Tzu-Yi , He Yi-Ting , Lin Guan-Jung , Lai Wei-Hong , Chen Yi-Chi , Lin Kun-Mo 
Published: May 2024

Abstract
This work numerically studies densities and reaction mechanisms of OH species generated in atmospheric–pressure air dielectric barrier discharges with the model validated by experiments. The power consumption is measured, and the number of microdischarges (MDs) generated within a half period is captured by an intensified charge-coupled device (CCD) camera. The OH densities of cases with various H2O concentrations are measured using ultraviolet absorption spectroscopy. The numerical model integrating the 1.5D discharge fluid model and 3D background gas model (BGM) is adopted to predict the MD behavior and the generation of species related to OH generation. The simulated OH densities cover the range of 1.1 × 1019 and 1.6 × 1019 m−3 in the cases studied, agreeing with those measured. The simulated results show that most OH radicals are generated in MDs, while the reactive section contributes around 2% of the total OH generation. The detailed analysis shows that atomic oxygen (O(1D) and O) and O3 contribute most of the OH generation in the MDs. In contrast, the self-association reactions (i.e. 2OH + M → H2O2 + M and 2OH → O + H2O) and NO
x
species consume more than 64% of OH radicals generated in MDs. In the BGM, it is interesting to find that reactive species NO
x
play significant roles in both the OH generation and depletion in the reactive section. The distributions of species related to the OH species obtained by the BGM are presented to elucidate the detailed chemistry of OH species in the reactive section.
Comparing the mean inner potential of Zn-VI semiconductor nanowires using off-axis electron holography
Authors: Jose Anitha , Al-Turk Sarry , Ruda Harry E , Watkins Simon P , McCartney Martha R , Cordoba Cristina , Kavanagh Karen L 
Published: May 2024

Abstract
The mean inner potential (MIP), V
0, for a series of Zn group VI semiconductor nanostructures were measured experimentally using off-axis electron holography. Values for ZnS, ZnTe and ZnO were remeasured and new values were added for ZnSe and ZnSSe nanowires. We confirm that the MIP increases non-linearly with mass density beginning at 12.4 ± 0.2 V for the lowest density ZnS and slowly increasing with composition to 12.9 ± 0.2 V for ZnSe, more rapidly for ZnTe and with a significant increase to 14.8 ± 0.3 V for ZnO with the highest density. Published results from DFT calculations compared well to these measurements with similar trends apparent for other cation families such as the Ga-III-V.
Effect of distributed Bragg reflectors on optoelectronic characteristics of GaN-based flip-chip light-emitting diodes
Authors: Sun Yuechang , Shi Lang , Cui Yongjin , Tang Bin , Zhou Qianxi , Zhuang Jiaming , Zhou Shengjun 
Published: May 2024

Abstract
Distributed Bragg reflectors have been widely utilized in GaN-based flip-chip light-emitting diodes (FCLEDs) owing to their excellent reflection performance. Recently, wide reflected angle DBR (WRA-DBR) has been suggested to enhance the optical characteristics of GaN-based FCLEDs by incorporating multiple sub-DBRs with varying central wavelengths. However, the reflectivity of WRA-DBR decreases at large incident angle from 425 nm to 550 nm, which restricts further optical performance improvement of FCLEDs. Here, we demonstrate a quintuple-stack DBR comprised of five sub-DBRs. The quintuple-stack DBR possesses a high reflectivity (>97.5%) for incident angles below 50° within the blue and green light wavelength ranges. Compared to WRA-DBR, quintuple-stack DBR exhibits a higher reflectivity in wavelength range of 425 nm to 550 nm and thinner multilayer thicknesses. Furthermore, stronger electric field intensities exist in the top facet and sidewalls of FCLED with quintuple-stack DBR, revealing that quintuple-stack DBR is beneficial for enhancing the light extraction efficiency. As a result, the light output power of FCLED with quintuple-stack DBR is ∼3% higher than that of FCLED with WRA-DBR at 750 mA.
Enhancing light absorption of deep ultraviolet photodiodes through intelligent algorithm-guided design of resonant nano-optical structures
Authors: Zhu Yifan , Lu Huimin , Wang Jianping , Feng Liya , Ma Jianhua , Yu Tongjun , Li Junze 
Published: May 2024

Abstract
The surface of the deep ultraviolet (DUV) photodiodes requires an enhanced light absorption to improve wall-plug efficiency. The resonant Mie scatterer has a high optical mode density with a high refractive index all-dielectric resonant structure, which causes strong light coupling and improves forward scattering, providing a new perspective for efficient light absorption on the surface of the DUV photodiodes. In this work, a method is proposed for the design of nano-optical structures that is capable of supporting forward light scattering across the resonant bandwidth. This is achieved by utilizing intelligent algorithms in conjunction with Maxwell’s equations. The results show that the average light absorption coefficient of the optimized optical structure is improved to more than 96% with angle-independent and polarization-independent characteristics. Based on intelligent algorithms, a reverse design approach can be employed to maximize this effect, thereby offering novel avenues for enhancing the wall-plug efficiency of the DUV photodiodes.
Rotating coupling of chiral identical twins in multimodal Kresling metamaterials for achieving ultra-high energy absorption
Authors: Yang Haiying , Shu Dong-Wei , Lu Haibao , Tao Ran 
Published: May 2024

Abstract
Origami structures have been widely applied for various engineering applications due to their extraordinary mechanical properties. However, the relationship between in-plane rotating coupling and energy absorption of these Origami structures is seldom studied previously. The study proposes a design strategy that utilizes identical-twin rotation (i.e. simultaneous rotation with the same chirality) and fraternal-twin rotation (i.e. simultaneous rotation with the opposite chirality) of Kresling metamaterials to achieve multimodal rotation coupling and enhanced energy absorption. Deformation mode and energy absorption properties of 3D-printed Kresling metamaterials have been studied using both quasi-static compression tests and finite element analysis. Furthermore, effects of polygon units and their connections to 2D and 3D arrangements, which generate 4 × 4 arrays and 2 × 2 × 2 arrays, have been investigated to identify the optimized structures for achieving ultra-high energy absorption of chiral Kresling metamaterials. Results showed that rotating coupling of chiral identical twins in multimodal Kresling metamaterials possesses diverse deformation patterns and ultra-high energy absorption. This study provides a novel strategy to optimize structural designs and mechanical properties of the Kresling metamaterials.