bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abrasive slurry jet machining system using polyurethane@silica core–shell particles for internal surfaces of axisymmetric x-ray mirrors
Authors: Yokomae Shunya , Takeo Yoko , Shimamura Takenori , Senba Yasunori , Kishimoto Hikaru , Ohashi Haruhiko , Mimura Hidekazu 
Published: January 2023

Abrasive machining has been used for inner surface processing of various hollow components. In this study, we applied an in-air fluid jet as a precision machining method for the inner surface of an axisymmetric x-ray mirror whose inner diameter was less than 10 mm. We employed an abrasive with a polyurethane@silica core–shell structure, which has a low density of about 1.2 g/cm3 and a relatively large particle size of about 15 µm. By using this abrasive, a practical removal rate and a smooth machined surface were simultaneously obtained. We performed figure corrections for an axisymmetric mirror and improved the circumferential figure accuracy to a sub-10 nm root mean square level. To evaluate the machining performance in the longitudinal direction of the ellipsoidal surface, we also performed periodic figure fabrication on the inner surface of a 114 mm-long nickel ellipsoidal mirror. X-ray ptychography, an optical phase retrieval method, was also employed as a three-dimensional figure measurement technique of the mirror. The wavefield of the x-ray beam focused by the processed ellipsoidal mirror was observed with the ptychographic system at SPring-8, a synchrotron radiation facility. The retrieval calculations for the wavefront error confirmed that a sinusoidal waveform with a period of 12 mm was fabricated on the mirror surface. These experimental results suggest that a nanoscale figure fabrication cycle for the inner surface consisting of jet machining and wavefront measurement has been successfully constructed. We expect this technique to be utilized in the fabrication of error-free optical mirrors and various parts having hollow shapes.
Hadamard states on spherically symmetric characteristic surfaces, the semi-classical Einstein equations and the Hawking effect
Authors: Janssen Daan W , Verch Rainer 
Published: January 2023

Abstract
We investigate quasi-free Hadamard states defined via characteristic initial data on null cones centred at the axis of symmetry in spherically symmetric space-times. We characterize the necessary singular behaviour of null boundary two-point functions such that one can define non-linear observables at this null boundary and give formulas for the calculation of these observables. These results extend earlier characterizations of null boundary states defining Hadamard states in the bulk of the null cone. As an application of our derived formulas, we consider their implications for the semi-classical Einstein equations and calculate the vacuum polarization associated with Hawking radiation near a collapsing body.
Probing system size dependence at high baryon density by systematic comparison of Ag+Ag and Au+Au reactions at 1.23A GeV
Authors: Reichert Tom , Kittiratpattana Apiwit , Li Pengcheng , Steinheimer Jan , Bleicher Marcus 
Published: January 2023

Abstract
We present UrQMD predictions for the comparison of the recently measured Ag+Ag and Au+Au runs at a beam energy of E
lab = 1.23A GeV explored by the HADES experiment. To this aim, different centrality definitions are investigated: We suggest that in the case of particle production, both systems should be compared at the same number of participating nucleons, while for a comparison of the (elliptic) flow, a selection on the initial state eccentricity—as in high energy reactions—is better suited. Generally, we find good agreement between both systems, if these centrality criteria are used. Specifically, the deuteron yields per participant and the pion to proton ratios are shown to scale with A
part except for very central Ag+Ag reactions due to stronger stopping in such reactions. The elliptic flow in both systems follows initial state eccentricity scaling, albeit with the opposite sign as compared to high energies, suggesting a strong relation between final flows and the initial state also at the low energies explored here. The observation of this scaling might then allow to obtain further information on the expansion properties (and the EoS) of matter at high baryon densities.
Linear and nonlinear dimensionality reduction from fluid mechanics to machine learning
Authors: Mendez Miguel A 
Published: January 2023

Abstract
Dimensionality reduction is the essence of many data processing problems, including filtering, data compression, reduced-order modeling and pattern analysis. While traditionally tackled using linear tools in the fluid dynamics community, nonlinear tools from machine learning are becoming increasingly popular. This article, halfway between a review and a tutorial, introduces a general framework for linear and nonlinear dimensionality reduction techniques. Differences and links between autoencoders and manifold learning methods are highlighted, and popular nonlinear techniques such as kernel principal component analysis, isometric feature learning and locally linear embedding are placed in this framework. These algorithms are benchmarked in three classic problems: (a) filtering, (b) identification of oscillatory patterns, and (c) data compression. Their performances are compared against the traditional proper orthogonal decomposition to provide a perspective on their diffusion in fluid dynamics.
Acoustic emission source localisation for structural health monitoring of rail sections based on a deep learning approach
Authors: Mahajan Harsh , Banerjee Sauvik 
Published: January 2023

Abstract
An acoustic emission (AE) approach for non-destructive evaluation of structures has been developed over the last two decades. In complex structures, one of the limitations of AE testing is to find the location of the AE source. Time of flight and wave velocity are typically employed to localise AE sources. However, complex rail structures generate multiple wave modes travelling at varying speeds, making localisation difficult. In this paper, the challenge of localisation has been split into two parts: (a) identification of the AE source zone, i.e. head, web or foot, and (b) identification of location along the length of the rail. AE events are simulated using a pencil lead break (PLB) as the source. Three models including an artificial neural network and 1D and 2D convolutional neural networks (CNNs) are trained and tested using AE signals generated by PLB sources. The accuracy of zone identification is reported as 94.79% when using the 2DCNN algorithm. For location classification it is also found that 2DCNN performed best with 73.12%, 79.37% and 67.50% accuracy of localising the AE source along the length in the head, web and foot, respectively. For AE signal generation from actual damage in a rail, a bending test on an inverted damaged rail section was then performed with loads of 100 kN, 150 kN and 200 kN. For all loads, the 2DCNN model resulted in accurate prediction of the zone of the AE source, and it accurately predicted the AE source location along the length for the loads of higher intensity (150 kN, 200 kN). It is envisaged that the deep learning approach presented in this research work will be helpful in developing a real-time monitoring system for rail inspection based on AE.
A multitask cascading convolutional neural network for high-accuracy pointer meter automatic recognition in outdoor environments
Authors: Liu Fang , Pan Lei , Gao Rui , Zhang Liyang , Pang Yi , Ning Xucheng , Zhang Hao , Liu Kunlei 
Published: January 2023

Abstract
Pointer meter automatic recognition (PMAR) in outdoor environments is a challenging task. Due to variable weather and uneven lighting factors, hand-crafted features or shallow learning techniques have low accuracy in meter recognition. In this paper, a multitask cascading convolutional neural network (MC-CNN) is proposed to improve the accuracy of meter recognition in outdoor environments. The proposed MC-CNN uses cascaded CNN, including three stages of meter detection, meter cropping and meter reading. Firstly, the YOLOV4 Network is used for meter detection to quickly determine the meter location from captured images. In order to accurately cluster pointer meter prior boxes in the YOLOV4 Network, an improved K-means algorithm is presented to further enhance the detection accuracy. Then, the detected meter images are cropped out of the captured images to remove redundant backgrounds. Finally, a meter-reading network based on an adaptive attention residual module (AARM) is proposed for reading meters from cropped images. The proposed AARM not only contains an attention mechanism to focus on essential information and efficiently diminish useless information, but also extracts information features from meter images adaptively. The experimental results show that the proposed MC-CNN can effectively achieve outdoor meter recognition, with high recognition accuracy and low relative error. The recognition accuracy can reach 92.6%. The average relative error is 2.5655%, which is about 3% less than the error in other methods. What is more, the proposed approach can obtain rich information about the type, limits, units and readings of the pointer meter and can be used when multiple pointer meters exist in one captured image simultaneously. Additionally, the proposed approach can significantly improve the accuracy of the recognized readings, and is also robust to natural environments.
CCPNet136: automated detection of schizophrenia using carbon chain pattern and iterative TQWT technique with EEG signals
Authors: Baygin Mehmet , Barua Prabal Datta , Chakraborty Subrata , Tuncer Ilknur , Dogan Sengul , Palmer Elizabeth , Tuncer Turker , Kamath Aditya P , Ciaccio Edward J , Acharya U Rajendra 
Published: January 2023

Abstract

Objective. Schizophrenia (SZ) is a severe, chronic psychiatric-cognitive disorder. The primary objective of this work is to present a handcrafted model using state-of-the-art technique to detect SZ accurately with EEG signals. Approach. In our proposed work, the features are generated using a histogram-based generator and an iterative decomposition model. The graph-based molecular structure of the carbon chain is employed to generate low-level features. Hence, the developed feature generation model is called the carbon chain pattern (CCP). An iterative tunable q-factor wavelet transform (ITQWT) technique is implemented in the feature extraction phase to generate various sub-bands of the EEG signal. The CCP was applied to the generated sub-bands to obtain several feature vectors. The clinically significant features were selected using iterative neighborhood component analysis (INCA). The selected features were then classified using the k nearest neighbor (kNN) with a 10-fold cross-validation strategy. Finally, the iterative weighted majority method was used to obtain the results in multiple channels. Main results. The presented CCP-ITQWT and INCA-based automated model achieved an accuracy of 95.84% and 99.20% using a single channel and majority voting method, respectively with kNN classifier. Significance. Our results highlight the success of the proposed CCP-ITQWT and INCA-based model in the automated detection of SZ using EEG signals.
Localized absorption of laser energy in X-mode configuration of magnetized plasma
Authors: Vashistha Ayushi , Mandal Devshree , Maity Srimanta , Das Amita 
Published: January 2023

Abstract
The heating of ions via lower hybrid (LH) waves has been observed in several astrophysical as well as laboratory plasmas. We have conducted particle-in-cell simulations to demonstrate absorption of the incident laser pulse at a chosen localized point in the plasma target by manipulating its density profile. We show that a part of the incident laser propagates inside the plasma target when its frequency lies below the LH resonance frequency. Thereafter, as it experiences a negative density gradient, it approaches the resonance point where its group velocity approaches zero. This is where the electromagnetic (EM) energy prominently gets converted into the electrostatic and eventually the kinetic energy of ions. Thus, by tailoring the plasma density profile one can have the absorption of incident EM wave energy at a designated location inside the plasma. This may be important in various applications where energy deposition/heating of plasma in a localized region is desirable.
Influence of oxygen on the ro-vibrational kinetics of a non-equilibrium discharge in CO2–O2 mixtures
Authors: Vervloedt S C L , Budde M , Engeln R 
Published: January 2023

Abstract
Storing excess renewable energy in hydrocarbons produced from CO2 potentially solves the intermittency issue of renewable energy sources in a green manner. The required reduction of CO2 to CO can be efficiently accomplished with non-equilibrium plasma conversion. On an industrial scale, effects of impurities on the reduction must be taken into account. During this study, the effects of oxygen are considered, as the impurity O2 is both a product of the reduction reaction and abundant in air. In this paper, the influence of O2 addition on the ro-vibrational kinetics of a pulsed DC CO2 glow discharge at 2.5–6.0 Torr—serving as a model non-equilibrium system—is studied in situ with quantum cascade laser infrared absorption spectroscopy. The temporal evolution of the ro-vibrational temperatures is measured, as well as the conversion of CO2 to CO. Trends in the temperature evolutions when increasing the flow rate from 7.4 to 30.0 sccm, varying the pressure, and increasing the O2 admixture up to 90% in increments of 10% are utilised to determine the underlying kinetic processes. Our results show that any decrease in the conversion of CO2 to CO caused by increasing O2 addition cannot be attributed to an induced change in the vibrational kinetics, since the asymmetric stretch mode of CO2—which is associated with dissociation via vibrational excitation—is not quenched. Measured changes in the temporal temperature trends are explained by species-dependent intra- and intermolecular collisional energy transfer processes.
An exact one-particle theory of bosonic excitations: from a generalized Hohenberg–Kohn theorem to convexified N-representability
Authors: Liebert Julia , Schilling Christian 
Published: January 2023

Abstract
Motivated by the Penrose–Onsager criterion for Bose–Einstein condensation we propose a functional theory for targeting low-lying excitation energies of bosonic quantum systems through the one-particle picture. For this, we employ an extension of the Rayleigh–Ritz variational principle to ensemble states with spectrum
w
and prove a corresponding generalization of the Hohenberg–Kohn theorem: the underlying one-particle reduced density matrix determines all properties of systems of N identical particles in their
w
-ensemble states. Then, to circumvent the v-representability problem common to functional theories, and to deal with energetic degeneracies, we resort to the Levy–Lieb constrained search formalism in combination with an exact convex relaxation. The corresponding bosonic one-body
w
-ensemble N-representability problem is solved comprehensively. Remarkably, this reveals a complete hierarchy of bosonic exclusion principle constraints in conceptual analogy to Pauli’s exclusion principle for fermions and recently discovered generalizations thereof.
Teleportation of unknown states of a qubit and a single-mode field in strong coupling regime without Bell-state measurement
Authors: Jahanbakhsh F , Tavassoly M K 
Published: January 2023

Abstract
In this paper, we develop the teleportation scheme in [Zheng in Phys Rev A 69, 064302, 2004], in the sense that, we work in the strong atom-field coupling regime wherein the rotating wave approximation (RWA) is no longer valid. To achieve the purpose, a scheme consisting of a qubit interacting with a single-mode quantized field is described via the Rabi model (counter rotation terms are taken into account). Our first aim is to teleport an unknown atomic state of a qubit (which interacts with the quantized field in a cavity) to a second qubit (exists in another distant cavity field), beyond the RWA and without the Bell-state measurement method. In the continuation, in a similar way, we teleport an unknown state of a single-mode field too. In fact, it is shown that, in this regime, after applying some particular conditions, containing the interaction time of atom-field in the cavities, adjusting the involved frequencies, as well as the atom-field coupling in the model, if a proper measurement is performed on the state of the first qubit (the related field in the cavity), the unknown states of the qubit (field) can be teleported from the first qubit (cavity field) to the second qubit (cavity field), appropriately. We show that in both considered cases, the teleportation protocol is successfully performed with the maximum possible fidelity, 1, and the acceptable success probability, 0.25.
Bilayer scaffold from PLGA/fibrin electrospun membrane and fibrin hydrogel layer supports wound healing in vivo
Authors: Bastidas Juliana Girón , Maurmann Natasha , Oliveira Luiza , Alcantara Bruno , Pinheiro Camila Vieira , Leipnitz Guilhian , Meyer Fabíola , Oliveira Maikel , Rigon Paula , Pranke Patricia 
Published: January 2023

Abstract
Hybrid scaffolds from natural and synthetic polymers have been widely used due to the complementary nature of their physical and biological properties. The aim of the present study, therefore, has been to analyze in vivo a bilayer scaffold of poly(lactide-co-glycolide)/fibrin electrospun membrane and fibrin hydrogel layer on a rat skin model. Fibroblasts were cultivated in the fibrin hydrogel layer and keratinocytes on the electrospun membrane to generate a skin substitute. The scaffolds without and with cells were tested in a full-thickness wound model in Wistar Kyoto rats. The histological results demonstrated that the scaffolds induced granulation tissue growth, collagen deposition and epithelial tissue remodeling. The wound-healing markers showed no difference in scaffolds when compared with the positive control. Activities of antioxidant enzymes were decreased concerning the positive and negative control. The findings suggest that the scaffolds contributed to the granulation tissue formation and the early collagen deposition, maintaining an anti-inflammatory microenvironment.
The gauge coupled two-body problem in a ring
Authors: Priestley Joel , Valentí-Rojas Gerard , Wright Ewan M , Öhberg Patrik 
Published: January 2023

Abstract
We study the properties of two quantum particles which are confined in a ring. The particles interact via a long-range gauge potential proportional to the distance between the particles. It is found that the two-body ground state corresponds to a state with non-zero angular momentum provided that the interaction between the particles is strong enough. In addition, the particles are correlated in the sense that depending on the interaction strength there is a propensity to be found close together or separated in the ring. We discuss the effect of measuring the position of one of the particles and thereby removing the particle from the ring, where we show that the remaining particle can be prepared in a non-dispersive state with non-zero angular momentum.
A divide and conquer approach for machined surface topography reconstruction in peripheral milling inconel 718
Authors: Lyu Wenjun , Liu Zhanqiang , Cai Yukui , Wang Bing , Song Qinghua 
Published: January 2023

Abstract
This paper proposes a reconstruction procedure to characterize the texture of milled surfaces following the principle of a divide and conquer algorithm. It is a combination of a numerical simulation of the systematic component of the surface topography with the stochastic features of surface roughness. Firstly, the milled surface topographies are decomposed into kinematic and random components, both of them are calculated separately. Then, the kinematic components are numerically simulated based on relative motion between milling tool and workpiece. The random components are numerically simulated by fast Fourier transform (FFT) and the Johnson transform system. The measured and kinematic topographies are aligned fitting orientation and position by point clouds registration. Finally, the milled surface topographies are reconstructed by superposition of kinematic and random components based on the alignment datum. The proposed approach is applied to surface topography simulation and surface roughness prediction in peripheral milling Inconel 718. The milled surface topographies can be simulated by using the milling parameters as input parameters of the proposed model. The validation tests were carried out in Inconel 718 peripheral milling. The results show that the proposed approach has high accuracy in topography simulation and roughness prediction. The relative errors of predicted S

a
values are less than 7.55% in all the case studies of this paper. The effect of cutting parameters on roughness S

a
is sorted as follows, radial cutting depth > cutting speed > feed rate. In addition, the feed rate greater than 0.01 mm tooth−1 should be selected as far as possible in milling Inconel 718.
Distribution of human papilloma virus genotypes and treatment outcomes in definitive radiotherapy for cervical cancer
Authors: Kinoshita Rumiko , Mitamura Takashi , Kato Fumi , Hattori Takahiro , Higaki Hajime , Takahashi Shuhei , Fujita Yoshihiro , Otsuka Manami , Koizumi Fuki , Uchinami Yusuke , Mori Takashi , Nishioka Kentaro , Hashimoto Takayuki , Ito Yoichi M , Watari Hidemichi , Aoyama Hidefumi 
Published: January 2023

AbstractMost oncogenic human papilloma virus (HPV) genotypes stratify into two species, α-7 HPV and α-9 HPV. There are several studies that evaluate the relationship between HPV species and treatment outcomes and reports that HPV species is prognostic. The HPV genotyping was conducted using biopsy specimens which had been stored in these studies. We conducted the study using the HPV test performed by cytology specimens which is less invasive and more useful in clinical settings. This study enrolled 46 patients who received HPV genotyping before the definitive radiotherapy. The results of the HPV genotyping were classified into HPVα-7, HPVα-9 and negatives. Of the 46 patients, 10 were positive for HPVα-7, 21 positive for HPVα-9 and 15 were negative. The median follow-up period was 38 months (range 4–142). The HPVα-7, HPVα-9 and negative groups showed the 3-year overall survival (OS; 59.3%, 80.4% and 72.2% [P = 0.25]); local control (LC; 67.5%, 81% and 80% [P = 0.78]); pelvic control (PC) (50%, 81% and 72.7% [P = 0.032]); pelvic lymph node (PLN) control (78.7%, 95% and 92.3% [P = 0.012]); distant metastasis free (DMF) survival (50%, 75.4% and 42.8% [P = 0.098]); and progression free survival (PFS) rate of patients (30%, 66.7% and 38.9% [P = 0.085]), respectively. Patients with HPVα-7 showed statistically significant poorer PC than the HPVα-9 group, in multivariate analysis. This result is consistent with previous studies for HPV positive patients. The HPV negativity rate was higher in this study than in other studies and further work on this may be needed for clinical use.