bluuebunny/crossref_metadata_2025_split huggingface dataset:
A multi-modal vision-language pipeline strategy for contour quality assurance and adaptive optimization
Authors: Luan Shunyao , Ou-yang Jun , Yang Xiaofei , Wei Wei , Xue Xudong , Zhu Benpeng 
Published: February 2024

Abstract

Objective. Accurate delineation of organs-at-risk (OARs) is a critical step in radiotherapy. The deep learning generated segmentations usually need to be reviewed and corrected by oncologists manually, which is time-consuming and operator-dependent. Therefore, an automated quality assurance (QA) and adaptive optimization correction strategy was proposed to identify and optimize ‘incorrect’ auto-segmentations. Approach. A total of 586 CT images and labels from nine institutions were used. The OARs included the brainstem, parotid, and mandible. The deep learning generated contours were compared with the manual ground truth delineations. In this study, we proposed a novel contour quality assurance and adaptive optimization (CQA-AO) strategy, which consists of the following three main components: (1) the contour QA module classified the deep learning generated contours as either accepted or unaccepted; (2) the unacceptable contour categories analysis module provided the potential error reasons (five unacceptable category) and locations (attention heatmaps); (3) the adaptive correction of unacceptable contours module integrate vision-language representations and utilize convex optimization algorithms to achieve adaptive correction of ‘incorrect’ contours. Main results. In the contour QA tasks, the sensitivity (accuracy, precision) of CQA-AO strategy reached 0.940 (0.945, 0.948), 0.962 (0.937, 0.913), and 0.967 (0.962, 0.957) for brainstem, parotid and mandible, respectively. The unacceptable contour category analysis, the

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of CQA-AO strategy reached (0.901, 0.763, 0.862, 0.822), (0.855, 0.737, 0.837, 0.784), and (0.907, 0.762, 0.858, 0.821) for brainstem, parotid and mandible, respectively. After adaptive optimization correction, the DSC values of brainstem, parotid and mandible have been improved by 9.4%, 25.9%, and 13.5%, and Hausdorff distance values decreased by 62%, 70.6%, and 81.6%, respectively. Significance. The proposed CQA-AO strategy, which combines QA of contour and adaptive optimization correction for OARs contouring, demonstrated superior performance compare to conventional methods. This method can be implemented in the clinical contouring procedures and improve the efficiency of delineating and reviewing workflow.
HoloTile light engine: new digital holographic modalities and applications
Authors: Glückstad Jesper , Gejl Madsen Andreas Erik 
Published: February 2024

Abstract
HoloTile is a patented computer generated holography approach with the aim of reducing the speckle noise caused by the overlap of the non-trivial physical extent of the point spread function in Fourier holographic systems from adjacent frequency components. By combining tiling of phase-only of rapidly generated sub-holograms with a PSF-shaping phase profile, each frequency component—or output ‘pixel’— in the Fourier domain is shaped to a desired non-overlapping profile. In this paper, we show the high-resolution, speckle-reduced reconstructions that can be achieved with HoloTile, as well as present new HoloTile modalities, including an expanded list of PSF options with new key properties. In addition, we discuss numerous applications for which HoloTile, its rapid hologram generation, and the new PSF options may be an ideal fit, including optical trapping and manipulation of particles, volumetric additive printing, information transfer and quantum communication.
Analysis of torsional buckling of a cylindrical sandwich shell with a magnetorheological fluid core layer
Authors: Kashipazha Masoud , Kheirikhah Mohammadmehdi , Meshkinabadi Saeed 
Published: February 2024

Abstract
This study is an attempt to analyze the torsion buckling of a structure consisting of a cylindrical sandwich shell with two isotropic face sheets that surround a magnetorheological fluid (MRF) core layer. In this analysis, the simply supported boundary conditions were considered for the edges of the face sheets and the core layer. The components of displacement were calculated using the first-order shear deformation theory, and the governing equations were derived using Hamilton’s principle and were solved drawing upon the Galerkin method. The parameters of interest were magnetic field, buckling analysis, torsional buckling convergence, h/L ratio, ht/h ratio, and rt/L ratio. The equations obtained from MATLAB were verified using ABAQUS owing to the absence of any similar study in the existing literature. A good agreement was observed in terms of torsional buckling, indicating the robustness of the proposed structure. As smart sandwich structures are broadly used in robotics and aerospace, this structure can be a good choice thanks to its lightness (resulting from the thinness of the face sheets and hollowness) and strength and resistance (contributed by MRF core layer), which can be modified with the application of different magnetic fields.
Simulation and analysis of inverse-mode operation of single event transient mechanisms on NPN-SiGe HBT
Authors: Adekoya Mathew Adefusika , Liu Shuhuan , Wang Xuan , Xing Tian , Li Haodi , Meng Fanjun , Du Xiaozhi , Li Zhuoqi , Huang Taiyi 
Published: February 2024

Abstract
This work presents the characteristics of the single event transient (SET) induced by a single heavy ion in the inverse mode NPN-SiGe HBT simulated with the Silvaco TCAD toolkit. The designed SiGe HBT technology structure was built on the DevEdit simulator and simulated on Deckbuild using device and radiation effect simulations. The characteristics of device SET distribution, including transient pulse current, corresponding collection charge, pulse current peak, and full width at half maximum (FWHM) levels, etc, were simulated and compared as they changed with heavy ion LETs (0.2 pC μm−1 ∼ 1.0 pC μm−1), striking angles (30° ∼ 120°), and device emitter bias voltage settings (0.6 V ∼ 1.8 V). Meanwhile, the electrostatic potential distribution was found to be impacted by the heavy ion SET at the initial time moment when the heavy ion began to strike the surface of the device. The mechanisms for SET variation and its influence on the device potential under different conditions were primarily analyzed and discussed.
Teukolsky-like equations with various spins in spherically symmetric spacetime*
Authors: Guo 郭 Ya 亚 , Nakajima Hiroaki , Lin 林 Wenbin 文斌 
Published: February 2024

Abstract
We study wave equations with various spins on the background of a general spherically symmetric spacetime. We obtain the unified expression of the Teukolsky-like master equations and the corresponding radial equations with the general spins. We also discuss the gauge dependence in the gravitational-wave equations, which have appeared in previous studies.
Morphological Classification of Infrared Galaxies Based on WISE
Authors: Pan Zhi-Ren , Qiu Bo , Liu Cui-Xiang , Luo A-Li , Jiang Xia , Guo Xiao-Yu 
Published: February 2024

Abstract
This study introduces a novel convolutional neural network, the WISE Galaxy Classification Network (WGC), for classifying spiral and elliptical galaxies using Wide-field Infrared Survey Explorer (WISE) images. WGC attains an accuracy of 89.03%, surpassing the combined use of K-means or SVM with the Color–Color method in more accurately identifying galaxy morphologies. The enhanced variant, WGC_mag, integrates magnitude parameters with image features, further boosting the accuracy to 89.89%. The research also delves into the criteria for galaxy classification, discovering that WGC primarily categorizes dust-rich images as elliptical galaxies, corresponding to their lower star formation rates, and classifies less dusty images as spiral galaxies. The paper explores the consistency and complementarity of WISE infrared images with SDSS optical images in galaxy morphology classification. The SDSS Galaxy Classification Network (SGC), trained on SDSS images, achieved an accuracy of 94.64%. The accuracy reached 99.30% when predictions from SGC and WGC were consistent. Leveraging the complementarity of features in WISE and SDSS images, a novel variant of a classifier, namely the Multi-band Galaxy Morphology Integrated Classifier, has been developed. This classifier elevates the overall prediction accuracy to 95.39%. Lastly, the versatility of WGC was validated in other data sets. On the HyperLEDA data set, the distinction between elliptical galaxies and Sc, Scd and Sd spiral galaxies was most pronounced, achieving an accuracy of 90%, surpassing the classification results of the Galaxy Zoo 2 labeled WISE data set. This research not only demonstrates the effectiveness of WISE images in galaxy morphology classification but also represents an attempt to integrate multi-band astronomical data to enhance understanding of galaxy structures and evolution.
Reflector Deformation Measurement and Correction Methodology of Large Antenna Based on Phased Array Feed
Authors: Wang Zan , Kong De-Qing , Zhang Hong-Bo , Su Yan , Zhu Xin-Ying , Wang Cong-Si , Liu Yu-Chen 
Published: February 2024

Abstract
To solve the problem of time-consuming measurement and correction of large antennas’ reflector deformation, a new microwave holography methodology based on a Phased Array Feed (PAF) is proposed. Starting from the known expression of receiving signals in microwave holography, the theory of PAF holography is derived through Geometrical Optics. Reflector deformation, as well as pointing deviation and subreflector offset, can be calculated out by applying the derived equations. A measurement and correction system based on PAF holography is depicted, and two kinds of measurement methods are illustrated. The proposed measurement methodology is verified by numerical simulation, and its measurement error is analyzed. The results indicate that our proposed methodology is feasible, especially for Cassegrain antennas.
Research on new energy power prediction technology based on privacy protection
Authors: Zhou Ziguan , Zhu Yaping , Liu Zhu , Li Xuming , Huang Chao , Wang Miao 
Published: February 2024

Abstract
New energy power prediction is an important part of the transition process from the traditional power system to the new power system. How to improve the power prediction accuracy while ensuring that data privacy is not leaked is an issue that needs to be focused on. Based on this, this paper constructs a new energy power prediction model integrating NGBoost and LSTM by screening the optimal feature sequences as model inputs, then encrypting the transmission aggregation process of model parameters and finally testing and evaluating the scheme based on a real data set. Experiments show that the scheme proposed in this paper not only improves data confidentiality to a certain extent compared with a single prediction model, but also the model is characterized by robustness and high prediction accuracy.
Transmission line fault detection based on anchor frame a priori and attention mechanism
Authors: Zhao Yang 
Published: February 2024

Abstract
YOLO target detection algorithm is the mainstream method for image-based defect detection of transmission line insulators. However, the existing model complexity is large. A reasonable and effective parameter compression method is urgently needed as a prerequisite to lay the foundation for solving the dilemma of UAV edge equipment deployment. At the same time, the insulator defect images taken by UAVs have complex backgrounds and small defect sizes, which are prone to misdetection and omission. It is needed to improve the channel domain of the CBAM (convolution block attention module) attention mechanism and solve its problem of missing channel information due to dimensionality reduction. The improved CBAM is added to the backbone network of YOLOv5s. The goal is to enable the model to identify and pinpoint the critical objectives with greater precision. The model is combined with Cross Entropy Loss and Lovasz-Softmax Loss weighting, which makes the network converge more stably during the training process, and the accuracy rate is also somewhat improved.
Identification of Intermittent Ground Fault Lines in Medium Voltage Shipboard Power Systems
Authors: Song Yawei , Luo Yuwen , Yan Kai , Zhu Pei , Ye Zehao , He Chengwei 
Published: February 2024

Abstract
To locate increasingly frequent intermittent ground faults in medium-voltage shipboard power systems, this study proposes a fault branch selection method using wavelet analysis. By analyzing transient fault current characteristics in ship medium-voltage grids, this method utilizes wavelet analysis tools to extract features and obtain modulus maxima of branch currents. Based on a dual threshold detection strategy, the fault branch is then identified. The feasibility and validity of the proposed method are verified through simulations on the Matlab/Simulink platform. The simulation results demonstrate the capability of the wavelet analysis approach to accurately locate intermittent ground faults in ship medium-voltage power systems. This research provides an effective solution for fault branch selection of intermittent grounding faults in ship medium-voltage grids.
Rapid Recovery Technology of SF6/N2 Mixed Insulation Gas in Electrical Equipment
Authors: Fu Lijun , Guan Yanling , Zhang Liang , Wei Bing , Li Guoxin , Chi Jingyuan , Wang Han 
Published: February 2024

Abstract
SF6 mixed gas is widely used as an insulation and arc extinguishing medium in electrical equipment in cold regions of northern China. Due to its low liquefaction temperature, existing gas recovery technologies are unable to achieve efficient and rapid recovery of SF6/N2 mixed insulation gases. In response to this challenge, a two-stage membrane separation and recovery technology has been proposed, which can efficiently and quickly separate SF6 and N2 from the mixed gas. The volume fraction (V/V) of obtained product SF6 gas reaches 90%, and the use of compression and refrigeration units can achieve rapid filling of 50 m3/h mixed gas. At the same time, the enrichment and recovery of trace SF6 gas in the exhaust gas are achieved. After enrichment, the volume fraction (V/V) of SF6 gas reaches 92%, and the volume fraction (V/V) of SF6 gas in the emptied mixed gas is 600 μL/L, far below the national standard value, solving the problems in actual production.
Simulation analysis of energy metering error of non-vehicle charger
Authors: Lu An , Yuan Jing , Gao Zhang , Yu Ling 
Published: February 2024

Abstract
This paper studies three methods of DC energy measurement for non-vehicle chargers, namely, the average value method, effective value method, and time domain integration method, introduces the definition of ripple, and analyzes the characteristics of constant voltage, constant current charging mode and pulse charging mode of electric vehicles, providing an algorithm basis for the establishment of DC energy metering error model and simulation analysis. This paper studies high-power DC energy measurement algorithms with ripple parameters, analyzes the error characteristics of various algorithms, summarizes the relevant laws, and provides a theoretical basis for the design of a high-precision DC metering module under the influence of ripple.
Research on performance state evaluation of circuit breaker energy storage spring based on intelligent algorithm
Authors: Xie Lingdong , Zhou Honghui , Zhao Tielin , Zhang Xibo , Ying Jianguo , Wang Junhua 
Published: February 2024

Abstract
The performance state evaluation method of circuit breaker energy storage spring mainly judges its performance state indirectly by measuring the pre-tightening force or pre-pressure of the spring. However, there may be some errors in this indirect measurement method, which will affect the accuracy of the evaluation results. Therefore, the performance state evaluation based on intelligent algorithm is proposed. Select the evaluation characteristic quantity of performance state, calculate the energy storage spring impulse according to the momentum theorem, and obtain the pressure value of the closing energy storage spring through the pressure sensor as the evaluation quantity reflecting the energy storage spring performance state. The BP neural network is established, and the fireworks algorithm is applied to the BP neural network to optimize the initial weight and threshold, so as to realize the performance state evaluation of energy storage spring based on BP neural network. The experimental results show that the spring energy release speed of the proposed method is in the range of 0 - 1.0m/s, and the estimated spring pressure value is basically consistent with the actual value.
Experimental study on damping characteristics of the particle dampers with damping rod and soft inside wall
Authors: Guo Yangyang , Liu Kai , Hou Gaoyan 
Published: February 2024

Abstract
In the perpendicular simple sinusoidal excitation, the damping characteristics of the soft-wall particle damper with a damping rod were experimentally investigated by controlling the acceleration amplitude and vibration frequency of the damper motion and measuring the force and acceleration signals. The experimental results show that the loss power of the damper increases monotonically with the rise of the excitation acceleration amplitude, and the effective mass shows the change of “gentle decrease-critical point-decrease”. As the driving frequency rises, the loss power progressively decreases, and the effective mass does not change significantly. By analyzing the damping characteristics of different dampers, it shows that the damping effectiveness of the soft inside wall particle damper with a damping rod is obviously better.
Design and Implementation of Automatic Airport Inspection System of Vehicle-mounted Rotor UAV
Authors: Yao Shaocan , Zhang Yong , Xi Xiaopeng , Li Xueling , Li Zhilin 
Published: February 2024

Abstract
A distributed UAV automatic airport inspection system, with the advantages of unmanned autonomous inspection operation, is widely used in power patrol, highway inspection, forest fire monitoring, and other fields. The disadvantage is that the operating radius distance is limited, with the multi-fixed site layout and high cost. In this paper, a vehicle-mounted rotor UAV automatic airport inspection system is designed, which can flexibly move the operation site and increase the operation radius. This inspection system is based on 5G wireless communication control technology and can remotely control the UAV. After the operation is completed, the UAV is automatically stored, charged, and maintained, and other functions have a good application prospect.
Deposition of carbon nanolayers by PECVD on ceramic substrates
Authors: Ivanov I , Marinov S , Popov G , Abrashev M , Kirilov K , Kiss’ovski Zh 
Published: February 2024

Abstract
Graphene layers and nanostructures were deposited on silicon dioxide (SiO2/Si) and silicon carbide (SiC) substrates at low gas pressure (1 – 5 torr) by microwave discharge PECVD (Plasma Enhanced Chemical Vapor Deposition). The advantage of this method is the relatively low temperature (600-700°C) of the substrate in the deposition process. The diffusion processes of hydrocarbon radicals on the surface of the substrates have a significant effect on the homogeneity of deposited structures. The deposited graphene nanotubes on SiC were analyzed by scanning electron microscope (SEM) and Raman spectroscopy is applied for characterization of the graphene layers. The deposited carbon layers on SiO2 were analyzed by atomic force microscope and their thickness (12-20 nm) were determined.
Surface structuring and in situ synthesis of nanoparticles by ultrashort laser processing on hydroxyapatite
Authors: Aceti D M , Filipov E , Lasgorceix M , Daskalova A 
Published: February 2024

Abstract
Ultrashort laser pulses represent a versatile tool that finds application in a variety of fields allowing precise and controlled modification of any kind of materials. The material surface modification, by inducing the formation of micro and nanostructures or providing chemical changes, or its functionalization with other materials, in form of nanoparticles, strongly affects the behavior and performances of such materials. The surface structuring and the synthesis and deposition of metallic nanoparticles has both been obtained by laser exposure. The two processes are performed consecutively, on hydroxyapatite sample surface. The synthesis of silver nanoparticles (AgNPs) takes place on the sample surface, while immersed in a solution of silver nitrate (AgNO3), by laser-induced multiphoton photoreduction of silver ions (Ag+).
A study of cavitation erosion resistance of an ion nitrided titanium alloy by means of the vibration and rotating disk methods
Authors: Safonov V , Zykova A , Steller J , Szkodo M , Gajowiec G , Chmiel J , Varhoshkov A , Klimenko I 
Published: February 2024

Abstract
In this work, a comparative analysis of the cavitation erosion resistance of the Ti–6.7Al–2.5Mo–1.8Cr–0.5Fe–0.25Si alloy (known as brand VT3-1) before and after low-temperature ion nitriding is carried out. Two test methods were applied, using vibrative (ASTM G-32) and rotating disk rigs, respectively. The kinetic dependences of the erosive destruction of samples of titanium alloy VT3-1 in the initial state, after ion nitriding and stainless steel AISI 321 were obtained. A study of the microstructure, hardness and surface morphology was carried out. The samples were examined using optical and scanning electron microscopy. The relationship between mass loss and cavitation erosion duration was experimentally determined and analyzed. The erosion rate on a rotating disk stand is much higher than during vibration tests. A large cavitation load gradient provides additional opportunities for analyzing the durability of materials and coatings using this method.
Elemental composition and structural characteristics of Bio-active™ orthodontic archwire
Authors: Stoyanova-Ivanova A , Mihaylov V , Georgiev V , Georgieva M , Petrov V , Andreeva L , Petrova N , Mikli V 
Published: February 2024

Abstract
The Bio-active™ archwires are the latest generation multi-force orthodontic archwires made of a Ni-Ti alloy. It is of particular importance to orthodontists to know what their composition and structural characteristics are so that they can determine which one is suitable for a given stage of orthodontic treatment. The aim of this work is to characterize as-received Bio-active™ archwires, consisting of three segments (anterior, bicuspid and posterior), by determining their physicochemical properties. Laser-induced breakdown spectroscopy (LIBS) was used to determine the elemental composition in the three different segments of the archwires, along with X-ray diffraction analysis (XRD), scanning electronic microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and differential scanning calorimetry (DSC). A LIBS and EDX analysis of the elemental composition showed that nickel (55wt.%) and titanium (45wt.%) are the main elements, and in some segments Fe and Cr registered as trace elements. A XRD analysis, at room temperature, showed two similar peaks, characteristic of a Ni-Ti alloy, proof that the archwire is an austenite phase. The DSC data was obtained by measuring the Af temperatures for each segment (heated up to +80°C and cooled down to -80°C), showing that they can be classified as martensite-active wires (heat-activated). Based on that a recommendation can be made to cool down the unused, as-received archwires before clinical use to ensure that they will fit in the brackets easier. On the surface of the as-received archwires small grains can be seen from the SEM micrographs. The obtained results provide orthodontists important information regarding the physicochemical properties of the as-received Bio-active™ archwires. The results can also serve as a foundation for future research on the elemental composition and morphology of clinically applied Bio-active™ archwires.