bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fast detection of geometric errors for three-axis machine tools with combined double-ball bars based on spatial circle detection
Authors: Wang Wen , Yue Shuqing , Yang He , Xu Kaifei , Sun Tao , Lu Keqing , Chen Zhanfeng , Wang Chuanyong , Cui Xueguang , Ju Bingfeng 
Published: November 2023

Abstract
The geometric accuracy of the CNC machine tools determines the quality of the sculptured mechanical parts. Measuring and compensating the geometric errors of machine tools can effectively improve the machining accuracy. However, traditional measurement methods using a double-ball bar (DBB) can only detect the error along the rod length direction and thus require multiple measurements in three orthogonal planes of the machine tool. This work proposes a fast error detection method for the three-axis machine tools using combined double-ball bars (C-DBBs) based on the spatially circular detection (SCD) path. The test path of this method requires the simultaneous linkage of three linear axes of the machine tools and thus could identify 21 geometric errors of three-axis machine tool. Firstly, the measuring principle of the SCD method is introduced, and the mathematical model for detecting 21 geometric errors of the machine tool based on the SCD method is established. Then, the detection experiment based on the SCD method is carried out, and it is shown that 21 geometric errors of the three-axis machine tool are obtained. Finally, the verification experiment using a traditional DBB is conducted to validate the effectiveness of the proposed SCD method. The radial errors in three orthogonal planes measured by traditional DBB exhibit a good agreement with those predicted using 21 geometric errors obtained by the SCD method. Compared with the traditional DBB method, the proposed SCD method could detect 21 geometric errors of three-axis machine tools in a single measurement. This work provides an effective and efficient methodology for detecting all geometric errors of the three-axis machine tool.
LiDAR point cloud quality optimization method based on BIM and affine transformation
Authors: Liu Jinyue , Gao Chao , Li Tiejun , Wang Xin , Jia Xiaohui 
Published: November 2023

Abstract
Laser Detection and Ranging (LiDAR) systems possess the capability to generate high-resolution three-dimensional (3D) data of indoor environments. The inherent uncertainties pertaining to relative spatial positioning and the centimeter-level precision of LiDAR ranging, however, contribute to discernible constraints within contexts requiring elevated degrees of precision, particularly in the domain of high-precision sensing applications. In response to this concern, this paper introduces an approach designed to mitigate and appraise the uncertainty associated with plane positioning through the utilization of point cloud fitting methodologies, concurrently integrating principles of building information modeling (BIM) and anisotropic affine transformations (AAT). Primarily, the methodology involves the extraction of precise plane characteristics employing the tenets of robustly weighted total least squares theory within the context of point cloud fitting. Subsequently, the method synergistically incorporates geometric information emanating from the Building Information Model alongside the accurately determined plane positioning data derived from LiDAR point clouds via AAT. This integration markedly enhances the precision of the ranging system’s datasets. Ultimately, the assessment of ranging uncertainty is conducted by quantifying the deviations of individual points from the conforming plane and employing a probability approximative scheme grounded in higher-order moments. Experimental results demonstrate the method’s precision and efficacy, offering a solution to the challenge of achieving higher perception precision in LiDAR-based ranging systems.
A simple strategy to obtain graphitic carbon nitride modified TiO2 layer for efficient perovskite solar cells
Authors: Guo Yanru , Zhao Dandan , Yu Man , Liu Manying , Zhang Yange , Zheng Zhi 
Published: November 2023

Abstract
The power conversion efficiency (PCE) of perovskite solar cells (PSCs) can be improved through the concurrent strategies of enhancing charge transfer and passivating defects. Graphite carbon nitride (g-C3N4) has been demonstrated as a promising modifier for optimizing energy level alignment and reducing defect density in PSCs. However, its preparation process can be complicated. A simple one-step calcination approach was used in this study to prepare g-C3N4-modified TiO2 via the incorporation of urea into the TiO2 precursor. This modification simultaneously tunes the energy level alignment and passivates interface defects. The comprehensive research confirms that the addition of moderate amounts of g-C3N4 to TiO2 results in an ideal alignment of energy levels with perovskite, thereby enhancing the ability to separate and transfer charges. Additionally, the g-C3N4-modified perovskite films exhibit an increase in grain size and crystallinity, which reduces intrinsic defects density and extends charge recombination time. Therefore, the g-C3N4-modified PSC achieves a champion PCE of 20.00%, higher than that of the control PSC (17.15%). Our study provides a systematic comprehension of the interfacial engineering strategy and offers new insights into the development of high-performance PSCs.
TiCl4 precursor affecting the performance of HTM-free carbon-based perovskite solar cell
Authors: Yang Yuanbo , Wang Shuo , Ji Wenjie , Li Tiantian , Li Simiao , Zhao Qian , Li Guoran 
Published: November 2023

Abstract
The presence of TiO2 used as an efficient electron transport layer is crucial to achieving high-performance solar cells, especially for a hole transport material (HTM)-free carbon-based perovskite solar cell (PSC). The hydrolysis of TiCl4 is one of the most widely used routes for forming TiO2 layer in solar cells, which includes the stock solution preparation from TiCl4 initial precursor and the thermal hydrolysis of the stock solution. The second thermal hydrolysis step has been extensively studied, while the initial hydrolysis reaction in the first step is not receiving sufficient attention, especially for its influence on the photovoltaic performance of HTM-free carbon-based devices. In this study, the role of TiCl4 stock solution in the growth process of TiO2 layer is examined. Based on the analysis of the Ti(IV) intermediate states for different TiCl4 concentrations from Raman spectra, 2 M TiCl4 precursor exhibits moderate nucleation and growth kinetics without generating too many intermediates which occurs in 3 M TiCl4 precursor, yielding ∼300 nm size spherical TiO2 agglomerates with a rutile phase. In the aspect of devices, the HTM-free carbon-based PSCs fabricated using 2 M TiCl4 precursor deliver a conversion efficiency beyond 17%, which may be attributed to the reduced defect in compact TiO2 layer.
Controllable interface-tailored strategy to reduce the nanotribological properties of Ti3C2T
x
by depositing MoS2 using atomic layer deposition
Authors: Fan Xiaojian , Xing Youqiang , Wu Ze , Li Bingjue , Huang Peng , Liu Lei 
Published: November 2023

Abstract
Ti3C2T
x
MXene has attracted widespread attention in lubrication owing to its unique structure and surface properties. However, the inferior nanotribological properties of Ti3C2T
x
still limit its applications in nano lubricants. Herein, we propose a controllable interface-tailored strategy to reduce the nanotribological properties of Ti3C2Tx by depositing MoS2 nano-sheet on its surface using atomic layer deposition (ALD). The nanotribological properties of the MoS2/Ti3C2T
x
nanocomposites synthesized by ALD are studied by atomic force microscope for the first time. At the optimal 20 ALD MoS2 cycles, the nanofriction of MoS2/Ti3C2T
x
has been reduced by 57%, 46%, and 44% (at 5, 10, and 15 nN load, respectively), while the adhesion has been reduced by 59%, compared to the original Ti3C2T
x
. The results can contribute to understanding of the nanotribological mechanisms of Ti3C2T
x
composites and provide the potential prospects for Ti3C2T
x
as a nanoscale adjustable lubricant.
Hippocampus substructure segmentation using morphological vision transformer learning
Authors: Lei Yang , Ding Yifu , Qiu Richard L J , Wang Tonghe , Roper Justin , Fu Yabo , Shu Hui-Kuo , Mao Hui , Yang Xiaofeng 
Published: November 2023

Abstract
The hippocampus plays a crucial role in memory and cognition. Because of the associated toxicity from whole brain radiotherapy, more advanced treatment planning techniques prioritize hippocampal avoidance, which depends on an accurate segmentation of the small and complexly shaped hippocampus. To achieve accurate segmentation of the anterior and posterior regions of the hippocampus from T1 weighted (T1w) MR images, we developed a novel model, Hippo-Net, which uses a cascaded model strategy. The proposed model consists of two major parts: (1) a localization model is used to detect the volume-of-interest (VOI) of hippocampus. (2) An end-to-end morphological vision transformer network (Franchi et
al 2020 Pattern Recognit. 102 107246, Ranem et
al 2022 IEEE/CVF Conf. on Computer Vision and Pattern Recognition Workshops (CVPRW) pp 3710–3719) is used to perform substructures segmentation within the hippocampus VOI. The substructures include the anterior and posterior regions of the hippocampus, which are defined as the hippocampus proper and parts of the subiculum. The vision transformer incorporates the dominant features extracted from MR images, which are further improved by learning-based morphological operators. The integration of these morphological operators into the vision transformer increases the accuracy and ability to separate hippocampus structure into its two distinct substructures. A total of 260 T1w MRI datasets from medical segmentation decathlon dataset were used in this study. We conducted a five-fold cross-validation on the first 200 T1w MR images and then performed a hold-out test on the remaining 60 T1w MR images with the model trained on the first 200 images. In five-fold cross-validation, the Dice similarity coefficients were 0.900 ± 0.029 and 0.886 ± 0.031 for the hippocampus proper and parts of the subiculum, respectively. The mean surface distances (MSDs) were 0.426 ± 0.115 mm and 0.401 ± 0.100 mm for the hippocampus proper and parts of the subiculum, respectively. The proposed method showed great promise in automatically delineating hippocampus substructures on T1w MR images. It may facilitate the current clinical workflow and reduce the physicians’ effort.
Vertical stray field measurements using an electron beam in the MEPhIST-0 tokamak
Authors: Vinitskiy E A , Efimov N E , Prishvitsyn A S , Sorokin I A , Krat S A 
Published: November 2023

Abstract
In the MEPhIST-0 tokamak, toroidal magnetic coil system is implemented as a single continuous toroidal solenoid. This design ensures synchronized operation of each segment of the solenoid and requires only one power supply line to operate. However, this configuration has the downside of introducing stray vertical and radial magnetic field components, which result from the inclination of the solenoid segments. Such stray fields can be measured using an electron beam, as previously demonstrated in experiments on T-15, TEXTOR, KSTAR, and SST-1. This paper describes the parameters of the experiment and presents the main results obtained from the MEPhIST-0 tokamak. Two experimental techniques for measuring the vertical magnetic field are discussed: one with a change in the current direction in the toroidal solenoid and one without. The ratio of the stray vertical field to the toroidal field was found to be approximately 0.5%. The conducted experiments highlight the necessity of compensating for the stray vertical field using additional poloidal coils.
Numerical and experimental study of ion energy distribution function in a dual-frequency capacitively coupled oxygen discharge
Authors: Luo Han , Kenney Jason , Rauf Shahid , Korolov Ihor , Schulze Julian 
Published: November 2023

Abstract
The plasma dynamics of a low pressure oxygen capacitively coupled plasma driven by dual frequencies (27.12 MHz and 271.2 kHz) is studied experimentally and numerically in this work. A retarding field energy analyzer system is employed in the experiment to measure the ion energy distribution function (IEDF) at the grounded electrode for different combinations of low-frequency voltages and pressures. One-dimensional particle-in-cell simulations of the oxygen plasma are conducted at the experimental conditions. A typical bimodal IEDF is observed and good agreement is obtained between experiments and simulations. A semi-analytical model based on the Child law sheath and fitted sheath voltage is constructed to study the structure of the IEDF. It is found that for the investigated conditions the low-energy peak of the IEDF is independent of the low frequency (LF) voltage but determined by the minimum sheath voltage during the sheath collapse; the energy spread of IEDF scales linearly with the LF voltage; both an increase of LF voltage and pressure create more low-energy ions.
MetaVision: enabling independent wavefront control for diverse/oblique illumination angles
Authors: Satti Azhar Javed , Javed Isma , Naveed Muhammad Asher , Aldaghri Osamah , Cabrera Humberto , Ibnaouf Khalid H , Madkhali Nawal , Mehmood Muhammad Qasim 
Published: November 2023

Abstract
The potential of metasurface holography holds significant promise for revolutionary breakthroughs and groundbreaking advancements in imaging, chip-integrated AR/VR technology, and flat optical displays. Traditional diffractive systems, including metasurfaces, display fixed angular behavior due to the grating period defining incidence angles and diffraction limited response. To break this limit, we offer spin-encoded spatially multiplexed metaholograms designing technique facilitating efficient modulation of geometric phases. The proposed technique gives independent control over polarization states, permitting separate optical modifications for different oblique incident angles. Our suggested metasurface illustrates a multifunctional design method using traditional single-resonator geometry, effectively generating three high-fidelity far-field holographic images. Due to simple geometry and dense information multiplexing proposed approach holds potential for different applications, such as holographic optical elements (HOEs), enhanced optical storage, and anti-counterfeiting techniques.
Comparison of log-derivative and renormalized Numerov methods in low-energy two-body collisions
Authors: Xie Ting , Li Lihang , Sun Zhigang 
Published: November 2023

Abstract
The log-derivative (LOGD) and renormalized Numerov (RN) methods are popularly used in inelastic and reactive scattering calculations. The computational precision of two methods and their improved versions are compared in two-body diatomic and bimolecular collisions at low temperatures. In diatomic 40K-133Cs collision example the single-channel calculations show the solution-improved RN method has the advantage over others when large fixed propagating interval used. The relative error of local scattering length in different propagating sectors are explored. In multi-channel 40K-133Cs collisions the predicted positions of Feshbach resonances by using mapping grid points indicate strong potential-following character in LOGD methods, which is consistent with the analysis on local scattering length in single-channel calculations. In multiple open-channel calculations the elastic and inelastic scatterings and their dependence on collision energy are compared as well. In bimolecular 23Na87Rb-23Na87Rb long-range reactive scattering example the elastic and reactive rate coefficients are investigated. The original LOGD method displays surprisingly relatively high accuracy with less mapping grid points and a wide range of mapping parameters. By increasing the number of mapping grid points the improved LOGD exhibits definitely superiority on precision with proper mapping parameters. We demonstrate our consequent is applicable in other colliding systems.
Diffusion mediated growth of superconducting Nb-Ti composite films by high temperature annealing
Authors: Sawle Deepika , Awana V P S , Sahoo Sangeeta 
Published: November 2023

Abstract
The fabrication of superconducting Nb-Ti alloy by high temperature annealing of Nb/Ti bilayer thin films is reported here. During the annealing process, Nb and Ti diffuse into each other and Nb-Ti composite film formation occurs at the interface of the bilayer. Two types of substrates, namely, SiO2/Si and Si3N4/Si are used to grow the bilayers of Nb/Ti by using dc magnetron sputtering. Annealing at temperature about 820 °C leads the substrates to take part into the diffusion process. The alloying of Nb-Ti and the effect of substrates on the structural properties are studied by x-ray diffraction (XRD) and x-ray photoelectron spectroscopy (XPS). Ti-rich Nb-Ti phases are present in the XRD while interface studies through XPS confirms the interdiffusion of the two elements Nb and Ti along with the presence of the decomposed elements from the substrates. Appearance of nitride phases in case of Si3N4/Si substrate confirms the substrate’s involvement in the diffusion process. Further low temperature transport measurements are carried out to study the superconducting properties of the Nb-Ti composite films grown on both oxide (SiO2/Si) and nitride (Si3N4/Si) substrates. Nb-Ti composite films offer higher transition temperature (T

C
) compared to that of pure Nb with similar thickness used in Nb/Ti bilayer films. Higher normal state resistance (R

N
) with wider transition width for Nb-Ti on nitride substrate in comparison with the oxide substrate indicates a possible role of N atoms in tuning the disorder and hence controlling the transport properties. Finally, the presented method can be used to fabricate superconducting stoichiometric NbTi and NbTiN thin films for future phase slip and superconducting single photon detector-based applications.
Development of some novel resistance distance based topological indices for certain special types of graph networks
Authors: Zaman Shahid , Kamboh Aisha , Ullah Asad , Liu Jia-Bao 
Published: November 2023

Abstract
A graph network consisting of nodes and edges, forms an electrical network if its edges are replaced by a unit resistor. The resistance distance between any two nodes of a connected network is defined as the net effective resistance between them. This work derives mathematical closed form expressions for the resistance distance based topological indices of four families of graph networks such as

S

n

,

S

n

+

,

S

n

2

and

S

n

*

.

Firstly, we compute the multiplicative eccentricity resistance-distance sum index, multiplicative degree-Kirchhoff index and the reciprocal degree resistance-distance index for the four families of graphs. Secondly, we introduce some new versions of resistance distance based topological indices viz. the additive reciprocal degree-Kirchhoff index, the additive reciprocal eccentric resistance-distance index, the reciprocal eccentric resistance distance index, modified eccentric resistance distance index and the modified degree resistance distance index for the above four families of graph networks. These resistance distance based topological indices are introduced for the first time in the literature, which can surely be useful to investigate the electrical networks.
An unsupervised real-time spike sorting system based on optimized OSort
Authors: Wu Yingjiang , Li Ben-Zheng , Wang Liyang , Fan Shaocan , Chen Changhao , Li Anan , Lin Qin , Wang Panke 
Published: November 2023

Abstract

Objective. The OSort algorithm, a pivotal unsupervised spike sorting method, has been implemented in dedicated hardware devices for real-time spike sorting. However, due to the inherent complexity of neural recording environments, OSort still grapples with numerous transient cluster occurrences during the practical sorting process. This leads to substantial memory usage, heavy computational load, and complex hardware architectures, especially in noisy recordings and multi-channel systems. Approach. This study introduces an optimized OSort algorithm (opt-OSort) which utilizes correlation coefficient (CC), instead of Euclidean distance as classification criterion. The CC method not only bolsters the robustness of spike classification amidst the diverse and ever-changing conditions of physiological and recording noise environments, but also can finish the entire sorting procedure within a fixed number of cluster slots, thus preventing a large number of transient clusters. Moreover, the opt-OSort incorporates two configurable validation loops to efficiently reject cluster outliers and track recording variations caused by electrode drifting in real-time. Main results. The opt-OSort significantly reduces transient cluster occurrences by two orders of magnitude and decreases memory usage by 2.5–80 times in the number of pre-allocated transient clusters compared with other hardware implementations of OSort. The opt-OSort maintains an accuracy comparable to offline OSort and other commonly-used algorithms, with a sorting time of 0.68 µs as measured by the hardware-implemented system in both simulated datasets and experimental data. The opt-OSort’s ability to handle variations in neural activity caused by electrode drifting is also demonstrated. Significance. These results present a rapid, precise, and robust spike sorting solution suitable for integration into low-power, portable, closed-loop neural control systems and brain–computer interfaces.
A leptin-loaded poly-ϵ-caprolactone 3D printing scaffold for odontoblastic differentiation in human dental pulp cells
Authors: Cho Eun-Hyo , Kim Ye-Seul , Kim Young-Ran , Kang Jin-Ho , Park Sang-Won , Lim Hyun-Pil , Yun Kwi-Dug , Jang Woo-Hyung , Koh Jeong-Tea , Park Chan , Lee Bin-Na 
Published: November 2023

Abstract
This study investigated the effects on odontoblast differentiation of a 3D-printed poly-ϵ-caprolactone (PCL) scaffold that incorporated leptin. Material extrusion-type 3D printing with a 43 000-molecular weight PCL material was used to fabricate a PCL scaffold with a 6 mm diameter, 1 mm height, and 270–340 µm pore size. The experimental groups were PCL scaffolds (control group), PCL scaffolds with aminated surfaces (group A), and PCL scaffolds with leptin on the aminated surface (group L). The aminated surface was treated with 1,6-hexanediamine and verified by ninhydrin analysis. Leptin loading was performed using Traut’s reagent and 4-(N-Maleimidomethyl)cyclohexane-1-carboxylic acid 3-sulfo-N-hydroxysuccinimide ester sodium salt (Sulfo-SMCC). Groups A and L showed significantly higher surface wettability, pulp cell adhesion, and proliferation than the control group. Group L exhibited increased alkaline phosphatase, calcification deposits, and mRNA and protein expression of dentin sialophosphoprotein and dentin matrix acidic phosphoprotein 1 compared with the control group. In this study, a 3D-printed PCL scaffold containing leptin was enhanced odontoblast differentiation and dental pulp cells adhesion and proliferation.