bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing dynamic measurement accuracy for machine tools and industrial robots with unscented Kalman filter and particle swarm optimization methods
Authors: Xing Kanglin , Bonev Ilian A , Champliaud Henri , Liu Zhaoheng 
Published: May 2024

Abstract
The telescoping ballbar is widely utilized for diagnosing accuracy and identifying faults in machine tools and industrial robots. Currently, there are no established standards for determining the optimal feed rate for ballbar tests. This lack of clear guidelines results in time inefficiency in measurements and inconsistencies in dynamic measurements, which complicates the comparison of ballbar test results under various conditions or across different machine platforms. To mitigate dynamic variations in ballbar results, an updated ballbar data processing method that integrates the unscented Kalman filter (UKF) and particle swarm optimization (PSO) was developed and validated using real ballbar data measured at multiple feed rates and simulated data with varying vibration magnitudes generated through the Renishaw ballbar simulator. Experimental results revealed that the dynamic components extracted from the ballbar results were observed to increase in correlation with the vibration measured at different feed rates and from the simulations. Moreover, the variations in the results measured at different feed rates after PSO-UKF processing were significantly reduced. The findings confirm the effectiveness of the proposed method in minimizing the dynamics of the ballbar results. Ultimately, this approach enhances the efficiency and accuracy of ballbar testing and offers a general method for improved diagnostics.
2D materials-based photodetectors combined with ferroelectrics
Authors: Bai Chongyang , Wu Guangjian , Yang Jing , Zeng Jinhua , Liu Yihan , Wang Jianlu 
Published: May 2024

Abstract
Photodetectors are essential optoelectronic devices that play a critical role in modern technology by converting optical signals into electrical signals, which are one of the most important sensors of the informational devices in current ‘Internet of Things’ era. Two-dimensional (2D) material-based photodetectors have excellent performance, simple design and effortless fabrication processes, as well as enormous potential for fabricating highly integrated and efficient optoelectronic devices, which has attracted extensive research attention in recent years. The introduction of spontaneous polarization ferroelectric materials further enhances the performance of 2D photodetectors, moreover, companying with the reduction of power consumption. This article reviews the recent advances of materials, devices in ferroelectric-modulated photodetectors. This review starts with the introduce of the basic terms and concepts of the photodetector and various ferroelectric materials applied in 2D photodetectors, then presents a variety of typical device structures, fundamental mechanisms and potential applications under ferroelectric polarization modulation. Finally, we summarize the leading challenges currently confronting ferroelectric-modulated photodetectors and outline their future perspectives.
N-doped TiO2/rGO: synthesis, structure, optical characteristics, and humidity sensing applications
Authors: Morsy Mohamed , Gomaa Islam , Mokhtar Mahmoud , Kamoun Elbadawy A , Ali Ahmed I 
Published: May 2024

Abstract
In the current study, the effect of rGO ratio on the N-dopped TiO2 has been synthesized through sol–gel method. The prepared N-doped TiO2/rGO composites were examined for humidity sensing applications. The relationship between optical properties and the humidity sensing properties was studied. The structure, morphology, and bonding interaction have been examined using XRD, FT-IR, PL and HRTEM respectively. The average particle size as estimated from XRD and HRTEM was found to be about 9 nm. The optical properties have been studied using UV/ Vis. Spectroscopy. Further, optical parameters including refractive index and optical band gap energy have been estimated. The humidity sensing behavior of the resultant composites were evaluated in a wide range of humidity (7%–97% RH) at different testing frequencies. The optical band gap was found to be decreased as the amount of rGO increase. Among all prepared samples, both the optical parameters and humidity sensing experiments confirmed that the 0.5% rGO@N-dopped TiO2 sample is the best candidate for the humidity sensing applications. The best optimum testing frequency was demonstrated to be 50 Hz. The sensor demonstrates a fast response and recovery times of 13 s and 33 s with low hysteresis and large sensitivity. The humidity sensing mechanism was studied using complex impedance spectroscopy at different RH levels under testing frequency range from 50 Hz to 5 MHz and testing voltage of 1 VAC. The produced structure demonstrated a promising material for humidity measuring devices.
High responsivity photodetector based on MEH-PPV/CsPbBr3 heterojunction
Authors: Fu Zhendong , Wang Fuguo , Liu Jiangnan , Sun Wenbao , Zhang Haiting , Song Xiaoxian , Yao Jianquan 
Published: May 2024

Abstract
Perovskite quantum dots (QDs) and organic materials have great research potential in the field of optoelectronic devices. In this paper, MEH-PPV/CsPbBr3 heterojunction photodetectors (PDs) are prepared by spin coating method based on the good photoelectric properties of CsPbBr3 perovskite QDs and MEH-PPV. The MEH-PPV/CsPbBr3 heterojunction improves the energy level arrangement, and CsPbBr3 QDs can passivate the surface defects of MEH-PPV films to achieve effective charge separation and transfer, thus inhibiting the dark current and improving the photoelectric performance of the device. Under 532 nm laser irradiation, the responsivity (R) of MEH-PPV/CsPbBr3 heterojunction PD is 11.98 A W−1, the specific detectivity (D*) is 6.98 × 1011 Jones, and the response time is 15/16 ms. This work provides experience for the study of perovskite QDs and organic materials heterojunction optoelectronic devices.
The potential of mixed carbon–helium beams for online treatment verification: a simulation and treatment planning study
Authors: Hardt Jennifer J , Pryanichnikov Alexander A , Homolka Noa , DeJongh Ethan A , DeJongh Don F , Cristoforetti Remo , Jäkel Oliver , Seco Joao , Wahl Niklas 
Published: May 2024

Abstract

Objective. Recently, a new and promising approach for range verification was proposed. This method requires the use of two different ion species. Due to their equal magnetic rigidity, fully ionized carbon and helium ions can be simultaneously accelerated in accelerators like synchrotrons. At sufficiently high treatment energies, helium ions can exit the patient distally, reaching approximately three times the range of carbon ions at an equal energy per nucleon. Therefore, the proposal involves adding a small helium fluence to the carbon ion beam and utilizing helium as an online range probe during radiation therapy. This work aims to develop a software framework for treatment planning and motion verification in range-guided radiation therapy using mixed carbon–helium beams. Approach. The developed framework is based on the open-source treatment planning toolkit matRad. Dose distributions and helium radiographs were simulated using the open-source Monte Carlo package TOPAS. Beam delivery system parameters were obtained from the Heidelberg Ion Therapy Center, and imaging detectors along with reconstruction were facilitated by ProtonVDA. Methods for reconstructing the most likely patient positioning error scenarios and the motion phase of 4DCT are presented for prostate and lung cancer sites. Main results. The developed framework provides the capability to calculate and optimize treatment plans for mixed carbon–helium ion therapy. It can simulate the treatment process and generate helium radiographs for simulated patient geometry, including small beam views. Furthermore, motion reconstruction based on these radiographs seems possible with preliminary validation. Significance. The developed framework can be applied for further experimental work with the promising mixed carbon–helium ion implementation of range-guided radiotherapy. It offers opportunities for adaptation in particle therapy, improving dose accumulation, and enabling patient anatomy reconstruction during radiotherapy.
Dynamic CBCT imaging using prior model-free spatiotemporal implicit neural representation (PMF-STINR)
Authors: Shao Hua-Chieh , Mengke Tielige , Pan Tinsu , Zhang You 
Published: May 2024

Abstract

Objective. Dynamic cone-beam computed tomography (CBCT) can capture high-spatial-resolution, time-varying images for motion monitoring, patient setup, and adaptive planning of radiotherapy. However, dynamic CBCT reconstruction is an extremely ill-posed spatiotemporal inverse problem, as each CBCT volume in the dynamic sequence is only captured by one or a few x-ray projections, due to the slow gantry rotation speed and the fast anatomical motion (e.g. breathing). Approach. We developed a machine learning-based technique, prior-model-free spatiotemporal implicit neural representation (PMF-STINR), to reconstruct dynamic CBCTs from sequentially acquired x-ray projections. PMF-STINR employs a joint image reconstruction and registration approach to address the under-sampling challenge, enabling dynamic CBCT reconstruction from singular x-ray projections. Specifically, PMF-STINR uses spatial implicit neural representations to reconstruct a reference CBCT volume, and it applies temporal INR to represent the intra-scan dynamic motion of the reference CBCT to yield dynamic CBCTs. PMF-STINR couples the temporal INR with a learning-based B-spline motion model to capture time-varying deformable motion during the reconstruction. Compared with the previous methods, the spatial INR, the temporal INR, and the B-spline model of PMF-STINR are all learned on the fly during reconstruction in a one-shot fashion, without using any patient-specific prior knowledge or motion sorting/binning. Main results. PMF-STINR was evaluated via digital phantom simulations, physical phantom measurements, and a multi-institutional patient dataset featuring various imaging protocols (half-fan/full-fan, full sampling/sparse sampling, different energy and mAs settings, etc). The results showed that the one-shot learning-based PMF-STINR can accurately and robustly reconstruct dynamic CBCTs and capture highly irregular motion with high temporal (∼ 0.1 s) resolution and sub-millimeter accuracy. Significance. PMF-STINR can reconstruct dynamic CBCTs and solve the intra-scan motion from conventional 3D CBCT scans without using any prior anatomical/motion model or motion sorting/binning. It can be a promising tool for motion management by offering richer motion information than traditional 4D-CBCTs.
Time conditioning for arbitrary contrast phase generation in interventional computed tomography
Authors: Pinnock Mark A , Hu Yipeng , Bandula Steve , Barratt Dean C 
Published: May 2024

Abstract
Minimally invasive ablation techniques for renal cancer are becoming more popular due to their low complication rate and rapid recovery period. Despite excellent visualisation, one drawback of the use of computed tomography (CT) in these procedures is the requirement for iodine-based contrast agents, which are associated with adverse reactions and require a higher x-ray dose. The purpose of this work is to examine the use of time information to generate synthetic contrast enhanced images at arbitrary points after contrast agent injection from non-contrast CT images acquired during renal cryoablation cases. To achieve this, we propose a new method of conditioning generative adversarial networks with normalised time stamps and demonstrate that the use of a HyperNetwork is feasible for this task, generating images of competitive quality compared to standard generative modelling techniques. We also show that reducing the receptive field can help tackle challenges in interventional CT data, offering significantly better image quality as well as better performance when generating images for a downstream segmentation task. Lastly, we show that all proposed models are robust enough to perform inference on unseen intra-procedural data, while also improving needle artefacts and generalising contrast enhancement to other clinically relevant regions and features.
Phase angle and impedance ratio as meta-inflammation biomarkers after a colon cleansing protocol in a group of overweight young women
Authors: Tapasco-Tapasco L O , Gonzalez-Correa C A , Letourneur A 
Published: May 2024

Abstract

Objective. Blood C-reactive protein (CRP) and the electrical bioimpedance spectroscopy (EBIS) variables phase angle (PhA) and impedance ratio (IR) have been proposed as biomarkers of metainflammation in overweight/obesity. CRP involves taking blood samples, while PhA and IR imply a less-than-2-minute-non-invasive procedure. In this study, values for these variables and percent body fat mass (PBFM) were obtained and compared before and immediately after a colon cleansing protocol (CCP), aimed at modulating intestinal microbiota and reducing metainflammation, as dysbiosis and the latter are intrinsically related, as well as along a period of 8 weeks after it. Approach. 20 female volunteers (20.9–24.9 years old) participated: 12 in an overweight group (OG), and 8 in a lean group (LG). The OG was divided in two subgroups (n= 6, each): control (CSG) and experimental (ESG). The ESG underwent a 6-day CCP at week 2, while 5 volunteers in the CSG underwent it at week 9. Main results. Pre/post-CCP mean values for the variables in the OG were: PBFM (34.3/31.3%), CRP (3.7/0.6 mg dl−1), PhA (6.9/7.5°) and IR*10 (0.78/0.77). Calculated R
2 correlation factors among these variables are all above 0.89. The favourable changes first seen in the ESG were still present 8 weeks after the CCP. Significance. (a) the CCP drastically lowers meta-inflammation, (b) EBIS can be used to measure metainflammation, before and after treatment, (c) for microbiota modulation, CCP could be a good alternative to more drastic procedures like faecal microbiota transplantation; (d) reestablishing eubiosis by CCP could be an effective coadjutant in the treatment of overweight young adult women.
ELRL-MD: a deep learning approach for myocarditis diagnosis using cardiac magnetic resonance images with ensemble and reinforcement learning integration
Authors: Mirzaee Moghaddam Kasmaee Adele , Ataei Alireza , Moravvej Seyed Vahid , Alizadehsani Roohallah , Gorriz Juan M , Zhang Yu-Dong , Tan Ru-San , Acharya U Rajendra 
Published: May 2024

Abstract

Objective. Myocarditis poses a significant health risk, often precipitated by viral infections like coronavirus disease, and can lead to fatal cardiac complications. As a less invasive alternative to the standard diagnostic practice of endomyocardial biopsy, which is highly invasive and thus limited to severe cases, cardiac magnetic resonance (CMR) imaging offers a promising solution for detecting myocardial abnormalities. Approach. This study introduces a deep model called ELRL-MD that combines ensemble learning and reinforcement learning (RL) for effective myocarditis diagnosis from CMR images. The model begins with pre-training via the artificial bee colony (ABC) algorithm to enhance the starting point for learning. An array of convolutional neural networks (CNNs) then works in concert to extract and integrate features from CMR images for accurate diagnosis. Leveraging the Z-Alizadeh Sani myocarditis CMR dataset, the model employs RL to navigate the dataset’s imbalance by conceptualizing diagnosis as a decision-making process. Main results. ELRL-DM demonstrates remarkable efficacy, surpassing other deep learning, conventional machine learning, and transfer learning models, achieving an F-measure of 88.2% and a geometric mean of 90.6%. Extensive experimentation helped pinpoint the optimal reward function settings and the perfect count of CNNs. Significance. The study addresses the primary technical challenge of inherent data imbalance in CMR imaging datasets and the risk of models converging on local optima due to suboptimal initial weight settings. Further analysis, leaving out ABC and RL components, confirmed their contributions to the model’s overall performance, underscoring the effectiveness of addressing these critical technical challenges.
VSHPIC: a particle-in-cell algorithm based on vector spherical harmonics expansion
Authors: Wang Jianzhao , An Weiming , Tang Rong , Meng Weiyu , Zhong Jiayong 
Published: May 2024

Abstract
The particle-in-cell (PIC) method has been widely used for studying plasma physics. However, fully three-dimensional PIC simulations always require huge computational resources. For problems with near azimuthal symmetry, recent work (Lifschitz et al 2009 J. Comput. Phys.
228 1803–14, Davidson et al 2015 J. Comput. Phys.
281 1063–77, Li et al 2021 Comput. Phys. Commun.
261 107784, Li et al 2022 J. Comput. Phys.
470 111599) has shown that expanding all the quantities defined on the grid in azimuthal harmonics and truncating the expansion can improve the code efficiency. In this paper, we describe a novel parallel algorithm for efficiently simulating three-dimensional near-spherical symmetry problems. Our approach expands all physical quantities in the

θ

and

ϕ

directions in spherical coordinates using vector spherical harmonics. The code is capable of simulating three-dimensional asymmetric scenarios by accurately tracking the evolution of distinct individual modes while preserving the charge conservation law. The fundamental dispersion relation of EM waves in the plasma has been obtained using VSHPIC simulation results. The code also shows a well strong scalability up to more than 1000 cores.
Determining sheath edge electric field around cylindrical pins of a DC-biased hairpin resonator probe
Authors: Singh Pawandeep , Pandey Avnish Kumar , Dahiya Swati , Karkari Shantanu 
Published: May 2024

Abstract
The sheath-edge electric field (

E

s

) is an important parameter to patch the quasi-neutral pre-sheath and non-neutral sheath regions. The choice of

E

s

significantly influences the theoretically estimated values of the sheath width, potential, and ion density distribution inside the sheath, as determined by the Poisson equation. The precise nature of

E

s

has been a persistent subject of investigation, giving rise to the question of whether it should be zero or possess a finite value, as proposed by various authors. In this study, we determine the values of

E

s

by solving Poisson’s equation as a boundary-value problem, utilizing experimentally determined values of sheath radius from a DC-biased hairpin probe. The obtained values of

E

s

are found to be finite and closely align with the analytical expressions presented by Riemann (1991 J. Phys. D: Appl. Phys.
24 493) and Kaganovich (2002 Phys. Plasmas
9 4788). Additionally, the impact of electron-penetrating sheaths and interacting sheaths on the applicability of the hairpin probe in low-pressure plasmas is briefly discussed.
Electric field measurement in DC corona discharge in atmospheric pressure air using E-FISHG and laser-triggering methods
Authors: Nakamura Shin , Sogame Masataka , Sato Masahiro , Fujii Takashi , Kumada Akiko 
Published: May 2024

Abstract
Electric field measurement using electric-field-induced second-harmonic generation (E-FISHG) draws attention because of its non-invasiveness and is increasingly being applied to various discharge plasmas. However, measurement accuracy of previous studies is unclear since approximations in calibration are inadequate. Therefore, we have developed a measurement and analysis method that does not require approximations and can furthermore obtain the distribution of the electric field. To demonstrate the applicability of the proposed method to discharge plasmas, in this paper, we measure the electric field as a result of the space charge generated by DC corona discharge in atmospheric pressure air and validate the results by comparing them with those obtained using the laser-triggering method. We demonstrate that the electrostatic field and electric field resulting from the space charge can be measured with a difference of about 10% between the results obtained from the laser triggering method and E-FISHG method. The proposed method holds potential for applications in discharge plasmas.
Repetitively pulsed streamer discharge with laser-induced surface trapped electron desorption to exploit residual charges in situ
Authors: Zhao Zheng , Gao Qiuyu , Li Xiaoran , Zhang Haowei , Bai Luying , Zhu Yifei , Sun Anbang , Li Jiangtao 
Published: May 2024

Abstract
Positive streamer behaviors under repetitive pulses are predominantly dependent on the availability of free electrons. If surface residual electrons stored from previous discharges could be intentionally released and involved into the next discharge, an alternative control freedom is provided apart from voltage waveform tailoring methods that mainly attract or repel gaseous residual charges. Evolutions of repetitively pulsed surface streamers in compressed (0.2 MPa) air were investigated after low-photon-energy pulsed visible (532 nm) and infrared (1064 nm) laser irradiations. Pulse-sequence and temporally resolved diagnostics were implemented to investigate effects of laser parameters (irradiation moment, wavelength, energy) and gas composition. A 2D surface streamer fluid simulation was performed to qualitatively unveil impacts of localized plasma patches. The surface streamer morphology and emission light are significantly and repeatably affected by the laser irradiation before the streamer inception, while, variations totally disappear without the solid surface. The secondary streamer is prolonged accompanied by a higher flashover probability after the pulsed laser irradiation in compressed air. Intriguingly, influences of the infrared laser persist for tens of microseconds before the next voltage pulse. Residual charge dynamics under the laser irradiation are analyzed, where the additional increase of

O

2
−

of low electron bound energy is emphasized. The laser induced surface trapped electron desorption is achieved through the direct or the step-wise process, dependent on the laser energy and the surface trap state distribution.
Nucleic acid liquids
Authors: Abraham Gabrielle R , Chaderjian Aria S , N Nguyen Anna B , Wilken Sam , Saleh Omar A 
Published: May 2024

Abstract
The confluence of recent discoveries of the roles of biomolecular liquids in living systems and modern abilities to precisely synthesize and modify nucleic acids (NAs) has led to a surge of interest in liquid phases of NAs. These phases can be formed primarily from NAs, as driven by base-pairing interactions, or from the electrostatic combination (coacervation) of negatively charged NAs and positively charged molecules. Generally, the use of sequence-engineered NAs provides the means to tune microsopic particle properties, and thus imbue specific, customizable behaviors into the resulting liquids. In this way, researchers have used NA liquids to tackle fundamental problems in the physics of finite valence soft materials, and to create liquids with novel structured and/or multi-functional properties. Here, we review this growing field, discussing the theoretical background of NA liquid phase separation, quantitative understanding of liquid material properties, and the broad and growing array of functional demonstrations in these materials. We close with a few comments discussing remaining open questions and challenges in the field.