bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient three-dimensional shape measurement: avoiding matrix inversion
Authors: Zhang Chenbo , Zhang Mingde , Chen Chen 
Published: August 2023

Abstract
The matrix inversion used to derive the 3D point cloud from the phase is a key factor that limits the reconstruction speed improvement in 3D imaging technique based on phase-shift fringe analysis. To avoid computing matrix inversion, we generate two offline loadable matrices determined solely by the calibration parameters of the triangulation model. Compared with the original method that requires matrix inversion, online computation was accelerated by about 15 times without incurring additional memory overhead. Experimental results demonstrated that the proposed method significantly improves the speed of 3D shape measurement and ensures high accuracy.
Three-dimensional measurement of fringe projection based on the camera response function of the quantified exposure time
Authors: Zhu Zhenmin , Ye Yinsong , Wang Mengyao , Cai Longcheng , Zheng Weihua 
Published: August 2023

Abstract
Fringe projection technology is usually used for three-dimensional (3D) measurement, but there will be large errors when the measurement is overexposed or the surface is too dark. Polarizing filters can be used to eliminate the highlights of the image, but they may also cause the image to be too dark and affect the measurement accuracy. Otherwise, to ensure measurement accuracy, the complexity of the operation of the polarization system will be increased. In order to ensure the measurement accuracy and improve the measurement efficiency, a 3D measurement method of quantified exposure time is proposed in this paper, and the intensity response function of the light intensity captured by the camera and the exposure time is established, and more meaningful variable value intervals can be selected by the method of this paper. It can avoid the complex polarization bidirectional reflectance distribution function model, and the required exposure time can be calculated quantitatively within the already screened intervals. Then it is combined with the image fusion algorithm to generate the optimal fringe pattern. Experimental results demonstrate that this method significantly eliminates the effects of highlights in the image. The fuzzy transition area between the black and white fringes is effectively reduced, and the edge information of the fringes is correctly restored.
Effective estimation model of coal dust characterization parameters with image sensing
Authors: Wang Zheng , Liu Xufei , Ji Zhaoxiang , Yang Shukai , Zhang Jiaxing 
Published: August 2023

Abstract
Coal dust leakage occurs most often during transportation to a power plant. Owing to the transportation method, the transported high-pressure coal dust can damage weak points in the pipeline wall and leak into the air, leading to serious safety hazards. To address this, this study proposes a coal dust parameter estimation model that combines domain-adaptive segmentation with extreme corrosion and a particle mass prediction regression model to extract the key characteristic signals of leaking coal dust and evaluate the production environment safety status. First, the connected domain is applied to segment the overlapping particles and extract two-dimensional image information. Subsequently, a regression model was constructed to predict the particle mass, which was mapped with the coal dust thickness model, density, and projected area and applied to environmental dust concentration characterization. The experiment samples included 3000 coal dust images captured from production links in power plants. A statistical analysis showed that the proposed model improved the accuracy and reliability of coal dust detection.
Growth kinetics and substrate stability during high-temperature molecular beam epitaxy of AlN nanowires
Authors: John P , Gómez Ruiz M , van Deurzen L , Lähnemann J , Trampert A , Geelhaar L , Brandt O , Auzelle T 
Published: August 2023

Abstract
We study the molecular beam epitaxy of AlN nanowires between 950 °C and 1215 °C, well above the usual growth temperatures, to identify optimal growth conditions. The nanowires are grown by self-assembly on TiN(111) films sputtered onto Al2O3. Above 1100 °C, the TiN film is seen to undergo grain growth and its surface exhibits {111} facets where AlN nucleation preferentially occurs. Modeling of the nanowire elongation rate measured at different temperatures shows that the Al adatom diffusion length maximizes at 1150 °C, which appears to be the optimum growth temperature. However, analysis of the nanowire luminescence shows a steep increase in the deep-level signal already above 1050 °C, associated with O incorporation from the Al2O3 substrate. Comparison with AlN nanowires grown on Si, MgO and SiC substrates suggests that heavy doping of Si and O by interdiffusion from the TiN/substrate interface increases the nanowire internal quantum efficiency, presumably due to the formation of a SiN
x
or AlO
x
passivation shell. The outdiffusion of Si and O would also cause the formation of the inversion domains observed in the nanowires. It follows that for optoelectronic and piezoelectric applications, optimal AlN nanowire ensembles should be prepared at 1150 °C on TiN/SiC substrates and will require an ex situ surface passivation.
The effect of inter-dot Coulomb interaction on the charge and energy transport properties of a five-terminal system consisting of three Coulomb-coupled quantum dots
Authors: Safdari Sayedreza , Soltani Morteza , Rashedi Gholamreza 
Published: August 2023

Abstract
We have studied a 5-terminal system consisting of three single level quantum dots (QDs) that are in contact with their respective reservoirs. In addition to the intra-dot Coulomb interaction, the electron in the dot affected by an inter-dot Coulomb repulsion from its adjacent QD. We describe this system by an Anderson type model Hamiltonian and apply the Greens function method to study the transport properties of the system. Since we are interested in temperatures higher than the Kondo temperature, we use the equations of motion technique to calculate Green’s functions. Numerical analysis shows that there is a correlation between the transport characteristics of the lower and upper dot and we can change the conductivity of the lower dot only by varying the parameters of the upper dot and vice versa. We demonstrated that the middle dot play the role of the switch on/off of this correlation. Also, we investigated the effect of thermoelectric properties. We found that the inter-dot Coulomb interaction can improve the thermoelectric performance of the system.
Geometric evaluations of CT and MRI based deep learning segmentation for brain OARs in radiotherapy
Authors: Alzahrani Nouf , Henry Ann , Clark Anna , Murray Louise , Nix Michael , Al-Qaisieh Bashar 
Published: August 2023

Abstract

Objective. Deep-learning auto-contouring (DL-AC) promises standardisation of organ-at-risk (OAR) contouring, enhancing quality and improving efficiency in radiotherapy. No commercial models exist for OAR contouring based on brain magnetic resonance imaging (MRI). We trained and evaluated computed tomography (CT) and MRI OAR autosegmentation models in RayStation. To ascertain clinical usability, we investigated the geometric impact of contour editing before training on model quality. Approach. Retrospective glioma cases were randomly selected for training (n = 32, 47) and validation (n = 9, 10) for MRI and CT, respectively. Clinical contours were edited using international consensus (gold standard) based on MRI and CT. MRI models were trained (i) using the original clinical contours based on planning CT and rigidly registered T1-weighted gadolinium-enhanced MRI (MRIu), (ii) as (i), further edited based on CT anatomy, to meet international consensus guidelines (MRIeCT), and (iii) as (i), further edited based on MRI anatomy (MRIeMRI). CT models were trained using: (iv) original clinical contours (CTu) and (v) clinical contours edited based on CT anatomy (CTeCT). Auto-contours were geometrically compared to gold standard validation contours (CTeCT or MRIeMRI) using Dice Similarity Coefficient, sensitivity, and mean distance to agreement. Models’ performances were compared using paired Student’s t-testing. Main results. The edited autosegmentation models successfully generated more segmentations than the unedited models. Paired t-testing showed editing pituitary, orbits, optic nerves, lenses, and optic chiasm on MRI before training significantly improved at least one geometry metric. MRI-based DL-AC performed worse than CT-based in delineating the lacrimal gland, whereas the CT-based performed worse in delineating the optic chiasm. No significant differences were found between the CTeCT and CTu except for optic chiasm. Significance. T1w-MRI DL-AC could segment all brain OARs except the lacrimal glands, which cannot be easily visualized on T1w-MRI. Editing contours on MRI before model training improved geometric performance. MRI DL-AC in RT may improve consistency, quality and efficiency but requires careful editing of training contours.
Monte Carlo-calculated beam quality and perturbation correction factors validated against experiments for Farmer and Markus type ionization chambers in therapeutic carbon-ion beams
Authors: Urago Yuka , Sakama Makoto , Sakata Dousatsu , Fukuda Shigekazu , Katayose Tetsurou , Chang Weishan 
Published: August 2023

Abstract

Objective. In current dosimetry protocols, the estimated uncertainty of the measured absorbed dose to water D
w in carbon-ion beams is approximately 3%. This large uncertainty is mainly contributed by the standard uncertainty of the beam quality correction factor k
Q. In this study, the k
Q values in four cylindrical chambers and two plane-parallel chambers were calculated using Monte Carlo (MC) simulations in the plateau region. The chamber-specific perturbation correction factor P of each chamber was also determined through MC simulations. Approach. k
Q for each chamber was calculated using MC code Geant4. The simulated k
Q ratios in subjected chambers and reference chambers were validated through comparisons against our measured values. In the measurements in Heavy-Ion Medical Accelerator in Chiba, k
Q ratios were obtained from D
w values of 60Co, 290- and 400 MeV u−1 carbon-ion beams that were measured with the subjected ionization chamber and the reference chamber. In the simulations, f
Q (the product of the water-to-air stopping power ratio and P) was acquired from D
w and the absorbed dose to air calculated in the sensitive volume of each chamber. k
Q values were then calculated from the simulated f
Q and the literature-extracted W
air and compared with previous publications. Main results. The calculated k
Q ratios in the subjected chambers to the reference chamber agreed well with the measured k
Q ratios. The k
Q uncertainty was reduced from the current recommendation of approximately 3% to 1.7%. The P values were close to unity in the cylindrical chambers and nearly 1% above unity in the plane-parallel chambers. Significance. The k
Q values of carbon-ion beams were accurately calculated in MC simulations and the k
Q ratios were validated through ionization chamber measurements. The results indicate a need for updating the current recommendations, which assume a constant P of unity in carbon-ion beams, to recommendations that consider chamber-induced differences.
CTA-UNet: CNN-transformer architecture UNet for dental CBCT images segmentation
Authors: Chen Zeyu , Chen Senyang , Hu Fengjun 
Published: August 2023

Abstract
In view of the limitations of current deep learning models in segmenting dental cone-beam computed tomography (CBCT) images, specifically dealing with complex root morphological features, fuzzy boundaries between tooth roots and alveolar bone, and the need for costly annotation of dental CBCT images. We collected dental CBCT data from 200 patients and annotated 45 of them for network training, and proposed a CNN-Transformer Architecture UNet network, which combines the advantages of CNN and Transformer. The CNN component effectively extracts local features, while the Transformer captures long-range dependencies. Multiple spatial attention modules were included to enhance the network’s ability to extract and represent spatial information. Additionally, we introduced a novel Masked image modeling method to pre-train the CNN and Transformer modules simultaneously, mitigating limitations due to a smaller amount of labeled training data. Experimental results demonstrate that the proposed method achieved superior performance (DSC of 87.12%, IoU of 78.90%, HD95 of 0.525 mm, ASSD of 0.199 mm), and provides a more efficient and effective approach to automatically and accurately segment dental CBCT images, has real-world applicability in orthodontics and dental implants.
Colored reflectors to improve coincidence timing resolution of BGO-based time-of-flight PET detectors
Authors: Lee Daehee , Cherry Simon R , Kwon Sun Il 
Published: August 2023

Abstract
Time-of-flight (TOF) positron emission tomography (PET) detectors improve the signal-to-noise ratio of PET images by limiting the position of the generation of two 511 keV gamma-rays in space using the arrival time difference between the two photons. Unfortunately, bismuth germanate (BGO), widely used in conventional PET detectors, was limited as a TOF PET scintillator due to the relatively slow decay time of the scintillation photons. However, prompt Cerenkov light in BGO has been identified in addition to scintillation photons. Using Cerenkov photons for timing has significantly improved the coincidence timing resolution (CTR) of BGO. Based on this, further research on improving the CTR for a BGO-based TOF PET system is being actively conducted. Wrapping materials for BGO pixels have primarily employed white reflectors to most efficiently collect scintillation light. White reflectors have customarily been used as reflectors for BGO pixels even after Cerenkov light began to be utilized for timing calculations in pixel-level experiments. However, when the arrival-time differences of the two 511 keV annihilations photons were measured with pure Cerenkov radiators, painting the lateral sides of the radiators black can improve CTR by suppressing the reflection of Cerenkov photons. The use of BGO for TOF PET detectors requires simultaneously minimizing scintillation loss for good energy information and suppressing reflected Cerenkov photons for better timing performance. Thus, reflectors for BGO pixels should be optimized for better timing and energy performance. In this study, colored polytetrafluoroethylene (PTFE) tapes with discontinuous reflectance values at specific wavelengths were applied as a BGO reflector. We hypothesized that CTR could be enhanced by selectively suppressing reflected Cerenkov photons with an optimum colored reflector on the BGO pixel while minimizing scintillation photon loss. CTRs were investigated utilizing white and three colors (yellow, red, and green) PTFE tapes as a reflector. In addition, black-painted PTFE tape and enhanced specular reflector film were investigated as reference reflector materials. When 3 × 3 × 20 mm3 BGO pixels were wrapped with the yellow PTFE reflector, the CTR was significantly improved to 365 ± 5 ps from 403 ± 14 ps measured with the conventional white PTFE reflector. Adequate energy information was still obtained with only 4.1% degradation in light collection compared to the white reflector. Colored reflectors show the possibility to further improve CTR for BGO pixels with optimum reflectance design.
Surface effects on elastohydrodynamic lubrication contact of piezoelectric materials with non-Newtonian fluid
Authors: Su Jie , Song Hong-Xia , Ke Liao-Liang 
Published: August 2023

Abstract
Using surface piezoelectricity theory, this article investigates the elastohydrodynamic lubrication (EHL) line contact of a transversely isotropic piezoelectric half-plane with consideration of the surface effect under a rigid cylindrical punch. The surface effect in the surface piezoelectricity theory is mainly described by the following parameters: surface piezoelectric constant, surface dielectric constant, surface elastic constant, and residual surface stress. The punch is treated as an electrical insulator. The lubricant, whose viscosity and density are dependent on fluid pressure, is chosen as a non-Newtonian fluid. Firstly, by analyzing the frictionless dry contact of piezoelectric materials vith the surface effect, the dry contact pressure distribution and the EHL film thickness equation are obtained. Then, an iterative method is proposed to obtain the fluid pressure and film thickness in the lubricant contact region by calculating the fluid–solid coupled nonlinear equations. The effects of the surface dielectric constant, surface piezoelectric constant, surface elastic constant, residual surface stress, punch radius, entraining velocity, and slide/roll ratio on the film thickness and fluid pressure are examined. Our analysis indicates that the surface effect has an essential effect on the EHL contact behavior of piezoelectric materials at micro-/nano-scales.
Multi-scale insight into key factors affecting stress perception of smart aggregates
Authors: Wang Ning , Zhang Chao , Ma Tao , Ding Xunhao , Huang Feiyu , Wu Jianyi , Ye Zhongyun 
Published: August 2023

Abstract
Smart aggregate (SA) is a multi-module integrated embedded monitoring sensor that has been employed in the construction, operation and maintenance of civil infrastructure. However, the differences in the shape and Yong’s modulus of the SA and the host matrix lead to the matching errors between the SA sensor readings and the actual in-situ stress values. A systematic analysis of how the modulus ratio of the SA to the host matrix (E
p/E
m), the length-to-height ratio of the sensor (L/H), and the non-homogeneity of the particle media interfere with the sensor monitoring data has been conducted in this paper using the finite element method and the discrete element method. In addition, the differences of the stress response from SA sensor under different load contact areas have been further investigated. Simultaneously, the numerical analysis has been validated by means of both theoretical derivations and laboratory tests. The analysis results show that E
p/E
m and L/H are the two key factors affecting the matching error. In particular, when E
p/E
m > 1, the matching error is positive and vice versa, while the L/H of the sensor is negatively correlated with the matching error. It is also noteworthy that the errors in the SA sensor monitoring data due to media inhomogeneity can only be negligible when the sensor diameter is larger than 20 times of the largest particle size in the host matrix. This study provides a theoretical guidance for optimizing the design of SA sensors and improving the accuracy of their measurement results.
Experimental investigation on 4D printed intelligent assembly cushion with adjustable pre-tightening force
Authors: Li Tengjie , Li Jian , Huang Xicheng 
Published: August 2023

Abstract
In order to design an intelligent assembly cushion with an adjustable pre-tightening force, a reentrant honeycomb structure was printed by additive manufacturing to realize the active and intelligent assembly process of filling gaps. The thermo-mechanical deformation experiments of the reentrant honeycomb structure were conducted at different pre-compressions, constrained displacements, and recovery temperatures. The recovery force and the force recovery ratio under semi-constrained conditions are explored emphatically. The results show that pre-compression, constrained displacement, and recovery temperature affect the recovery force and force recovery ratio under semi-constrained conditions. The recovery force and force recovery ratio increase with pre-compression, decrease with constrained displacement, and increase with recovery temperature below the glass transition temperature. Based on these results, the adjustability of the recovery force of a reentrant honeycomb cushion can be controlled by changing the thermo-mechanical deformation processes. Finally, the reentrant honeycomb cushion is applied to the mimetic assembly environment for corresponding testing, achieving the design of an active and intelligent assembly cushion with an adjustable pre-tightening force.
Experimental investigation on interfacial defect detection for SCCS with conventional and novel contact NDT techniques
Authors: Chen Hongbing , Chalise Gokarna , Gan Shiyu , Nie Xin 
Published: August 2023

Abstract
In order to ensure the mechanical performance and structural safety of steel–concrete composite structures (SCCS), advanced nondestructive testing (NDT) technique for bonding status at steel–concrete interfaces needs to be developed. In this study, the feasibility of multichannel analysis of surface waves (MASW)-based interfacial debonding detection is validated using the contact sensors array. Herein, the multichannel sensor arrays are composed of piezoceramic lead zirconate titanate patches and high-frequency acceleration meters, respectively. For comparison, the impact-response (IR) method and impact-transmission (IT) method are performed utilizing a force hammer and high-frequency acceleration meters, and corresponding damage imaging algorithms are developed. The applicability of ultrasonic computed tomography (CT) scanning test, scanning impact echo (IE) method, ultrasonic tomography (UT) technique on interfacial debonding detection is further discussed in depth. Research findings indicate that the developed contact MASW measurement can fully capture the variation of dispersion characteristics of surface waves induced by debonding defects in SCCS. The developed IR and IT methods are suitable for detecting interfacial debondings in different dimensions. Besides, the damage nephogram resolution of IR is higher than that of the IT method. In addition, the practicability of traditional ultrasonic CT scanning tests, scanning IE method, and UT techniques using commercial equipment is investigated. Experimental observations show that classical NDT testing techniques are incapable of effectively identifying the existence of interfacial damage and are unsuitable for NDT tests on SCCS. The research findings in this study clearly exhibit the precision and limitation of various contact NDT techniques and lay a solid foundation for interfacial debonding detection in practical SCCS.
Dissipative quantum many-body dynamics in (1+1)D quantum cellular automata and quantum neural networks
Authors: Boneberg Mario , Carollo Federico , Lesanovsky Igor 
Published: August 2023

Abstract
Classical artificial neural networks, built from elementary units, possess enormous expressive power. Here we investigate a quantum neural network (QNN) architecture, which follows a similar paradigm. It is structurally equivalent to so-called (1+1)D quantum cellular automata, which are two-dimensional quantum lattice systems on which dynamics takes place in discrete time. Information transfer between consecutive time slices—or adjacent network layers—is governed by local quantum gates, which can be regarded as the quantum counterpart of the classical elementary units. Along the time-direction an effective dissipative evolution emerges on the level of the reduced state, and the nature of this dynamics is dictated by the structure of the elementary gates. We show how to construct the local unitary gates to yield a desired many-body dynamics, which in certain parameter regimes is governed by a Lindblad master equation. We study this for small system sizes through numerical simulations and demonstrate how collective effects within the quantum cellular automaton can be controlled parametrically. Our study constitutes a step towards the utilization of large-scale emergent phenomena in large QNNs for machine learning purposes.