bluuebunny/crossref_metadata_2025_split huggingface dataset:
Uniqueness, stability and algorithm for an inverse wave-number-dependent source problem
Authors: Zhao Mengjie , Si Suliang , Hu Guanghui 
Published: October 2024

Abstract
This paper is concerned with an inverse wave-number-/frequency-dependent source problem for the Helmholtz equation. In two and three dimensions, the unknown source term is supposed to be compactly supported in spatial variables but independent on one spatial variable. The dependence of the source function on wave-number/frequency is supposed to be unknown. Based on the Fourier-transform and Dirichlet-Laplacian methods, we develop two efficient non-iterative numerical algorithms to recover the wave-number-dependent source. Uniqueness proof and increasing stability analysis are carried out if the boundary measurement data of Dirichlet kind are available. Numerical experiments are conducted to illustrate the effectiveness and efficiency of the proposed methods.
Direct and inverse scattering in an optical waveguide*
Authors: Chang Yan , Guo Yukun , Zhao Yue 
Published: October 2024

Abstract
In this paper, we study the direct and inverse scattering of the Schrödinger equation in a three-dimensional optical planar waveguide. For the direct problem, we derive a resonance-free region and resolvent estimates for the resolvent of the Schrödinger operator in such a geometry. Based on the analysis of the resolvent, several inverse problems are investigated. First, given the potential function, we prove the uniqueness of the inverse source problem with multi-frequency data. We also develop a Fourier-based method to reconstruct the source function. The capability of this method is numerically illustrated by examples. Second, the uniqueness and increased stability of an inverse potential problem from data generated by incident waves are achieved in the absence of the source function. To derive the stability estimate, we use an argument of quantitative analytic continuation in complex theory. Third, we prove the uniqueness of simultaneously determining the source and potential by active boundary data generated by incident waves. In these inverse problems, we only use the limited lateral Dirichlet boundary data at multiple wavenumbers within a finite interval.
High-refractive-index glass device fabricated by room temperature bonding
Authors: Yamamoto Koki , Ito Yuri , Tanaka Nobuyuki , Tanaka Yo , Ota Nobutoshi 
Published: October 2024

Abstract
Wafer bonding is an essential technology for attaching various materials, including glass. Glass–glass bonding has been applied to fabricate glass micro/nanofluidic devices that work as analytical tools for chemical and biological research. Here, we report the fabrication of micro/nanofluidic devices consisting of a high refractive index (HRI) glass as a component of the device for the first time. Although HRI glass has been used for high-sensitivity and high-resolution imaging in microscopy, it has not been used for glass fluidic devices due to the lack of bonding method for HRI glass. The glass fluidic devices were made through glass–glass bonding at room temperature, which could avoid severe damage to bonded substrates of two glass types due to different rates of thermal expansion. The pressure endurance of these devices was measured to find the correlation with the surface properties of glass substrates. The measured results indicated that chemical groups other than SiOH enhanced the pressure endurance of the devices. Thus, these chemical groups helped to form the fluidic devices consisting of HRI glass and another glass type, borosilicate or fused silica, to achieve practical pressure endurance up to 270 kPa. The HRI glass-incorporating device showed 8-fold higher sensitivity and 30% narrower spatial resolution of fluorescence signals than the other devices with non-HRI glass.
Temperature modeling of wave rotor refrigeration process based on variable time-delay compensation and SDAE-GRU
Authors: Li Qi , Wang Yiming , Ba Wei 
Published: October 2024

Abstract
Aiming at the problem of noise and time-delay in temperature prediction modeling of large wave rotor refrigeration process, this paper proposes a novel modeling algorithm that combines the advantages of stacked denoising autoencoder (SDAE) network and Gate Recurrent Unit (GRU) algorithm and utilizes the Maximal Information Coefficient (MIC) algorithm to solve the targeting problem. The MIC algorithm is utilized to calculate the delay time of each input variable and output variable, and the input matrix is reconstructed to compensate for the time-delay, thus solving the problem afterwards. The SDAE network is utilized for denoising the input data and feature extraction to solve the problem of presence of noise in the data. The simulation results show that the proposed MIC-SDAE-GRU algorithm achieves a Root Mean Squared Error of 0.6432 and an R-squared (R
2) value of 0.9638, outperforming traditional machine learning methods and other deep learning approaches. Specifically, compared to the standard GRU algorithm, it improves the accuracy of temperature prediction for the wave rotor refrigeration process by 24.7% and exhibits strong generalization ability across various operating conditions.
Efficient indoor 3D object detection in point clouds using the Kinect sensor
Authors: Zhang Xuesong , Guo Jiaqi , Song Cunli , Zhuang Yan 
Published: October 2024

Abstract
Only using the point clouds collected by a Kinect sensor to perform 3D object detection is a very challenging task for indoor sense understanding. In this paper, we propose a novel point clouds based 3D object detection framework named Weighted VoteNet (W-VoteNet), which systematically enhances seed points, voting points, and proposal objects to varying degree, thereby enhancing the detection accuracy of indoor scene point clouds. Firstly, a new neighborhood feature enhancement module was designed to enhance the features of the seed point, which can better utilize the neighborhood feature of the seed point. Secondly, a weighted voting module is implemented to increase the accuracy of voting, allowing more prospect seed points to participate in voting. Finally, a new semantic relation reasoning module is proposed to get the semantic relationship features of the proposal object, which can further decrease false alarm rate. The three modules we proposed all contribute to more accurate voting and more effective proposals. The experimental results on two benchmark indoor 3D object detection datasets, SUN RGB-D and ScanNet V2, demonstrate the effectiveness of our approach. The source code is available at: https://github.com/Guo-JQ/W-VoteNet.
Enhancing the diffusion capabilities of oxygen ions and hydrogen protons in protonic ceramic fuel cells at intermediate temperatures through doping material and ratio adjustments
Authors: Chan Yen-Hsin 
Published: October 2024

Abstract
This study aims to investigate the changes in the diffusion capabilities of oxygen ions and hydrogen protons within the electrolyte materials of protonic ceramic fuel cells (PCFC) under various doping materials, doping ratios, and temperature effects. It utilizes molecular dynamics methods combined with the ReaxFF force field to analyze the reactivity and transport characteristics of oxygen ions and hydrogen protons in the BZY (Yttria-doped barium zirconates) microstructure of PCFCs. The research finds that for intermediate temperature ranges (573 K–773 K), the optimal doping ratio of Y2O3 is 13.6%, and at an operating temperature of 673 K, using MgO as a doping material for BZY can enhance the diffusion coefficient of hydrogen protons in the electrolyte, thereby optimizing the performance of PCFC.
Treatment envelope of transcranial histotripsy: challenges and strategies to maximize the treatment location profile
Authors: Lu Ning , Yeats Ellen M , Sukovich Jonathan R , Hall Timothy L , Pandey Aditya S , Xu Zhen 
Published: October 2024

Abstract
A 750 kHz, 360-element ultrasound array has been built for transcranial histotripsy applications. This study aims to evaluate its performance to determine whether this array is adequate for treating a wide range of brain locations through a human skull. Treatment location profiles in 2 excised human skulls were experimentally characterized based on passive cavitation mapping. Full-wave acoustic simulations were performed in 8 human skulls to analyze the ultrasound propagation at shallow targets in skulls with different properties. Results showed that histotripsy successfully generated cavitation from deep to shallow targets within 5 mm from the skull surface in the skull with high SDR and small thickness, whereas in the skull with low SDR and large thickness, the treatment envelope was limited up to 16 mm from the skull surface. Simulation results demonstrated that the treatment envelope was highly dependent on the skull acoustic properties. Pre-focal pressure hotspots were observed in both simulation and experiments when targeting near the skull. For each skull, the acoustic pressure loss increases significantly for shallow targets compared to central targets due to high attenuation, large incident angles, and pre-focal pressure hotspots. Strategies including array design optimization, pose optimization, and amplitude correction, are proposed to broaden the treatment envelope. This study identifies the capabilities and limitations of the 360-element transcranial histotripsy array and suggests strategies for designing the next-generation transcranial histotripsy array to expand the treatment location profile for a future clinical trial.
Novel Bragg peak characterization method using proton flux measurements on plastic scintillators
Authors: Guerreiro D R , Saraiva J G , Peralta L , Rodrigues C , Rovituso M , van der Wal E , R Schaart Dennis , Crespo P , Simões H , Sampaio J M 
Published: October 2024

Abstract

Objective. Bragg peak measurements play a key role in the beam quality assurance in proton therapy. Used as base data for the treatment planning softwares, the accuracy of the data is crucial when defining the range of the protons in the patient. Approach. In this paper a protocol to reconstruct a Pristine Bragg Peak exploring the direct correlation between the particle flux and the dose deposited by particles is presented. Proton flux measurements at the HollandPTC and FLUKA Monte Carlo simulations are used for this purpose. This new protocol is applicable to plastic scintillator detectors developed for Quality Assurance applications. In order to obtain the Bragg curve using a plastic fiber detector, a PMMA phantom with a decoupled and moveable stepper was designed. The step phantom allows to change the depth of material in front of the fiber detector during irradiations. The Pristine Bragg Peak reconstruction protocol uses the measured flux of particles at each position and multiplies it by the average dose obtained from the Monte Carlo simulation at each position. Main results. The results show that with this protocol it is possible to reconstruct the Bragg Peak with an accuracy of about 470 µm, which is in accordance with the tolerances set by the AAPM. Significance. It has the advantage to be able to overcome the quenching problem of scintillators in the high ionization density region of the Bragg peak.
The influence of daily imaging and target margin reduction on secondary cancer risk in image-guided and adaptive proton therapy
Authors: Smolders A , Czerska K , Celicanin Z , Lomax A , Albertini F 
Published: October 2024

Abstract

Objective. Image-guided and adaptive proton therapy rely on daily CBCT or CT imaging, which increases radiation dose and radiation-induced cancer risk. Online adaptation however also reduces setup uncertainty, and the additional risk might be compensated by reducing the setup robustness margin. This work developed a framework to investigate how much this robustness margin should be reduced to offset the secondary cancer risk from additional imaging dose and applied it to proton therapy for head-and-neck cancer. Approach. For five patients with head-and-neck cancer, voxel-wise CT and CBCT imaging doses were estimated with Monte Carlo radiation transport simulations, calibrated with air and PMMA phantom measurements. The total dose of several image-guided and adaptive treatments protocols was calculated by summing the planning CT dose, daily and weekly CBCT or CT dose, and therapy dose, robustly optimized with setup margins between 0 and 4 mm. These were compared to a reference protocol with 4 mm setup margin without daily imaging. All plans further used 3% range robustness. Organ-wise excess absolute risk (EAR) of cancer was calculated with three models to determine at which setup margin the total EAR of image-guided and adaptive treatment protocols was equal to the total EAR of the reference. Results. The difference between the simulated and measured CT and CBCT doses was within 10%. Using the Monte Carlo models, we found that a 1 mm setup margin reduction was sufficient for most patients, treatment protocols, and cancer risk models to compensate the additional risk imposed by daily and weekly imaging. For some protocols, even a smaller reduction sufficed, depending on the imaging frequency and type. The risk reduction by reducing the margin was mainly due to reducing the risk for carcinomas in the brain and, for some patients, the oral cavity. Significance. Our framework allows to compare an increased imaging dose with the reduced treatment dose from margin reductions in terms of radiation-induced cancer risk. It is extendable to different treatment sites, modalities, and imaging protocols, in clinic-specific or even patient-specific assessments.
Exploring machine learning models for predicting meson mass and width
Authors: Akan Tarik 
Published: October 2024

Abstract
This paper explores the application of various machine learning models to predict the mass and width of mesons based on their quark content and quantum numbers. Using deep neural networks (DNNs), ensemble methods, and traditional regression models, we demonstrate the effectiveness of these approaches in providing accurate predictions. By utilizing the relationship between isospin, charge conjugation, G-parity, we achieve more precise predictions and reveal the unique differences in meson properties. Additionally, we investigate the effects of incorporating quantum numbers into different ML algorithms, highlighting how these features impact the predictive performance of each model.
Stability and convergence computational analysis of a new semi analytical-numerical method for fractional order linear inhomogeneous integro-partial-differential equations
Authors: Iqbal Javed , Shabbir Khurram , Guran Liliana 
Published: October 2024

Abstract
The aim of this research is to develop a semi-analytical numerical method for solving fractional order linear integro partial differential equations (FOLIPDEs), particularly focusing on inhomogeneous FOLIPDEs of various types, such as fractional versions of Fredholm and Volterra type integral equations. To achieve this goal, we will explore existing fractional formulations of linear model integral equations. We will then outline of the proposed semi-analytical numerical procedure, including an analysis of its stability and convergence properties. Through specific numerical examples, we will demonstrate that this approach is not only clear and efficient but also accurate. The results obtained will indicate that this method holds significant potential for addressing a wide range of FOLIPDEs. Finally, we will summarize the contributions of this work to the advancement of semi-analytical numerical method for FOLIPDEs and discuss directions for future research in this area.
Gravitational waves from a curvature-induced phase transition of a Higgs-portal dark matter sector
Authors: Mantziris Andreas , Bertolami Orfeu 
Published: October 2024

Abstract
The study of interactions between dark matter and the Higgs field opens an exciting connection between cosmology and particle physics, since such scenarios can impact the features of dark matter as well as interfering with the spontaneous breaking of the electroweak symmetry. Furthermore, such Higgs-portal models of dark matter should be suitably harmonised with the various epochs of the universe and the phenomenological constraints imposed by collider experiments. At the same time, the prospect of a stochastic gravitational wave background offers a promising new window into the primordial universe, which can complement the insights gained from accelerators. In this study, we examined whether gravitational waves can be generated from a curvature-induced phase transition of a non-minimally coupled dark scalar field with a portal coupling to the Higgs field. The main requirement is that the phase transition is of first order, which can be achieved through the introduction of a cubic term on the scalar potential and the sign change of the curvature scalar. This mechanism was investigated in the context of a dynamical spacetime during the transition from inflation to kination, while also considering the possibility for inducing electroweak symmetry breaking in this manner for a sufficiently low reheating temperature when the Higgs-portal coupling is extremely weak. We considered a large range of inflationary scales and both cases of positive and negative values for the non-minimal coupling, while taking into account the bound imposed by Big Bang Nucleosythesis. The resulting gravitational wave amplitudes are boosted by kination and thus constrain the parameter space of the couplings significantly. Even though the spectra lie at high frequencies for the standard high inflationary scales, there are combinations of parameter space where they could be probed with future experiments.
The effect of vertical displacements on the runaway electron avalanche in ITER mitigated disruptions
Authors: Wang C. , Nardon E. , Artola F.J. , Bandaru V. , Hoelzl M. ,   the JOREK team
Published: October 2024

Abstract
In order to prepare the operation of ITER, it is important to estimate the amplitude of the runaway electron (RE) current that could appear following disruptions at large plasma currents. Theoretically, the avalanche gain of RE population on a toroidal flux surface (TFS) is an exponential function of the change in the poloidal magnetic flux Δψ on that TFS. However, once a TFS is open, REs on it escape rapidly and can no longer proliferate. It is expected that the vertical motion of the plasma during a disruption could lead to the opening of TFSs as the plasma cross-section is pushed into the wall. The influence of this vertical motion on the RE avalanche gain was rarely considered in previous studies. This study investigates the RE generation in ITER major disruptions and hot vertical displacement events mitigated by the injection of neon and hydrogen, using an axisymmetric 2D model on the JOREK code. Compared to those with a stationary plasma, our simulations show a smaller Δψ on a given TFS by the time it becomes open as a result of the vertical motion. The maximum potential avalanche gain is thus reduced from

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without considering the vertical motion to

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, depending on the plasma dynamics during the disruption. In addition, the RE current produced by a typical nuclear seed (∼ 10 mA) at ITER is investigated.
A bio-inspired looming detection for stable landing in unmanned aerial vehicles*
Authors: Xie Yupeng , Li Zhiteng , Song Linkun , Zhao Jiannan 
Published: October 2024

Abstract
Flying insects, such as flies and bees, have evolved the capability to rely solely on visual cues for smooth and secure landings on various surfaces. In the process of carrying out tasks, micro unmanned aerial vehicles (UAVs) may encounter various emergencies, and it is necessary to land safely in complex and unpredictable ground environments, especially when altitude information is not accurately obtained, which undoubtedly poses a significant challenge. Our study draws on the remarkable response mechanism of the Lobula Giant Movement Detector to looming scenarios to develop a novel UAV landing strategy. The proposed strategy does not require distance estimation, making it particularly suitable for payload-constrained micro aerial vehicles. Through a series of experiments, this strategy has proven to effectively achieve stable and high-performance landings in unknown and complex environments using only a monocular camera. Furthermore, a novel mechanism to trigger the final landing phase has been introduced, further ensuring the safe and stable touchdown of the drone.
Health implications of cooking energy transition: Evidence from rural China
Authors: Yu Lu , Lin Bin , Jin Songqing , Wang Xiaoxi 
Published: October 2024

Abstract
The transition towards advanced residential energy sources is a pressing priority for many countries. Despite this, solid fuels remain the dominant form of cooking energy for rural households in developing countries. This study investigates the physical and mental health impacts of cooking energy choices by using endogenous switching models to address selection bias associated with cooking energy adoption and to distinguish the health impacts of different types of cooking energy. Using country-representative household survey data from rural China, our results indicate that adopting advanced forms of energy, not only enhances physical health in terms of reducing the rates of chronic diseases but also improves mental health. We further delve into the heterogenous impacts of advanced energy adoption across different groups and find that women, old adults, and economically disadvantaged groups are more likely to experience greater mental health benefits compared to their counterparts, while the opposite results are observed for the physical health. Additionally, we differentiate the health impacts by distinguishing between various energy types. This study provides insights for policy making aimed at improving public health and promoting health equality, contributing to efforts towards achieving sustainable development goals by prioritizing clean and efficient residential energy solutions.
Effects of grain size, dislocation density, and texture type on the etching behavior of Cu target in magnetron sputtering process
Authors: Zhao Xueyang , Yuan Junping , Zhou Xiang , Lu Huanxun , Hu Bowen , Zhu Jiayi 
Published: October 2024

Abstract
Copper thin film is commonly applied in the microelectronics and battery industries, and environmentally friendly magnetron sputtering process is one of the main coating processes. The effects of grain size, dislocation density, and texture type of Cu target on sputtering efficiency were researched in this work. High-purity copper cast ingots were rolled into plates. Pieces were then cut from different surfaces of the plates and assembled into the targets named as Target 1, Target 2, and Target 3 for magnetron sputtering. To investigate the etching behavior of the three targets, EBSD technology was utilized for analysis, and the micro-morphologies of the etching grooves were observed using SEM. After the sputtering process, the weight loss rate and etching depth of the various targets were measured to compare the respective sputtering efficiency. Target 1 exhibited the highest sputtering weight loss rate at any time period compared to Target 2 and Target 3, and reached its maximum depth after every 15 minutes of sputtering. In the first 45 minutes, the etching depth of Target 2 was slightly greater than that of Target 3. While the etching depth of Target 3 increased significantly in the last 15 minutes compared to that of Target 2. The most significant factor influencing the sputtering efficiency of the target material was grain size, with finer grains leading to higher sputtering efficiency. The dislocation density had a greater impact in the first 30 minutes, but the texture type became more important as the sputtering process continued.