bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diagnostic study of capacitively coupled neon rf plasma with traces of O2/H2 at intermediate pressure
Authors: Baghel S S , Şahin N , Agrawal A , Gangwar R K , Tanışlı M , Srivastava R 
Published: April 2022

Abstract
In this work, we have performed the non-invasive diagnostic study of capacitively coupled Ne–O2/H2 mixture plasma through the optical emission spectroscopy (OES) coupled with a suitable collisional radiative (CR) model. Capacitively coupled neon radio-frequency (rf) discharge (flowing downstream) with small admixture of O2/H2 have been generated in a vacuum chamber using 13.56 MHz rf signal and 120 W power supply. Keeping O2 and H2 flow rates fixed at 0.01 and 0.015 LPM respectively, the neon flow rate has been varied as 0.3, 0.4, 0.5, 0.6, 0.7 and 0.8 LPM to obtain different mixture concentration of Ne–O2 and Ne–H2 discharge. The pressure in the chamber has been observed in intermediate range (∼500–25 000 Pa) for different mixture concentrations. OES measurements are recorded at various operating conditions in the wavelength range from 200 to 1200 nm. To extract the information of plasma parameters from the OES measurements, a comprehensive fine-structure resolved CR model has been developed. In the diagnostic process, five intense Ne–I emission lines at 594.48, 607.43, 633.44, 638.30, 703.24 nm are used. The CR model considers all the important processes i.e. electron impact excitation, electron impact de-excitation, radiative decay, ionization, two–three body recombination, and diffusion. The quenching process of 1s (1s5,1s4,1s3) levels of neon by the O2/H2 molecule has been included in the model. The radiative transitions from the upper levels to the ground state (1S0) as well as to the 1s levels of neon are corrected for self-absorption. The electron temperature (T
e) and electron density (n
e) of the plasma have been extracted for all the mixture concentrations of Ne–O2 and Ne–H2. Also, with the different mixture concentrations of O2/H2 in neon discharge, the variation of population of metastable levels (1s5, 1s3) of neon as well as intensities of 656.28 nm of hydrogen and 777.4 nm of oxygen lines have been reported and discussed.
Determining spin-orbit torque in a single ferrimagnetic film without heavy metal via spin-torque ferromagnetic resonance
Authors: Wang Junshuai , Li Chaozhong , Liu Fufu , Jiang Changjun 
Published: April 2022

Abstract
We report spin-orbit torque (SOT) in a single ferrimagnetic (FIM) GdFeCo alloy based on spin-torque ferromagnetic resonance (ST FMR). Thickness-dependent anomalous Hall resistance shows a bulk perpendicular magnetic anisotropy, which lead double peaks of ST FMR spectra at a larger thickness of 50 nm. Oblique-angle-dependent ST FMR is performed to study SOT, and the spin torque efficiency in the y axis is evaluated. This phenomenon is explained by the relationship between SOT and saturation magnetization. This finding provides an alternative method to modulate SOT in a single ferrimagnetic spintronic device.
Generalization of the Landau–Lifshitz–Gilbert equation by multi-body contributions to Gilbert damping for non-collinear magnets
Authors: Brinker Sascha , dos Santos Dias Manuel , Lounis Samir 
Published: April 2022

Abstract
We propose a systematic and sequential expansion of the Landau–Lifshitz–Gilbert equation utilizing the dependence of the Gilbert damping tensor on the angle between magnetic moments, which arises from multi-body scattering processes. The tensor consists of a damping-like term and a correction to the gyromagnetic ratio. Based on electronic structure theory, both terms are shown to depend on e.g. the scalar, anisotropic, vector-chiral and scalar-chiral products of magnetic moments: e

i
⋅ e

j
, (n

ij
⋅ e

i
)(n

ij
⋅ e

j
), n

ij
⋅ (e

i
× e

j
),

(

e

i

⋅

e

j

)

2

, e

i
⋅ (e

j
× e

k
) …, where some terms are subjected to the spin–orbit field n

ij
in first and second order. We explore the magnitude of the different contributions using both the Alexander–Anderson model and time-dependent density functional theory in magnetic adatoms and dimers deposited on Au(111) surface.
Advances in phosphor two-color ratio method thermography for full-field surface temperature measurements
Authors: Jones E M C , Jones A R , Hoffmeister K N G , Winters C 
Published: April 2022

Abstract
Thermographic phosphors can be employed for optical sensing of surface, gas phase, and bulk material temperatures through different strategies including the time-decay method, time-integrated method, and frequency-domain method. We focus on the time-integrated method, also known as the ratio method, as it can be more practical in many situations. This work advances the ratio method using two machine vision cameras with CMOS detectors for full-field temperature measurements of a solid surface. A phosphor calibration coupon is fabricated using aerosol deposition and employed for in situ determination of the temperature-versus-intensity ratio relationship. Algorithms from digital image correlation are employed to determine the stereoscopic imaging system intrinsic and extrinsic parameters, and accurately register material points on the sample to subpixel locations in each image with 0.07 px or better accuracy. Detector nonlinearity is carefully characterized and corrected. Temperature-dependent, spatial non-uniformity of the full-field intensity ratio—posited to be caused by a blue-shift effect of the bandpass filter for non-collimated light and/or a wavelength-dependent transmission efficiency of the lens—is assessed and treated for cases where a standard flat-field correction fails to correct the non-uniformity. In sum, pixel-wise calibration curves relating the computed intensity ratio to temperature in the range of T = 300–430 K are generated, with an embedded error of less than 3 K. This work offers a full calibration methodology and several improvements on two-color phosphor thermography, opening the door for full-field temperature measurements in dynamic tests with deforming test articles.
Lead-doped scintillator dosimeters for detection of ultrahigh dose-rate x-rays
Authors: Hart Alexander , Cecchi Daniel , Giguère Cloé , Larose Frédérique , Therriault-Proulx François , Esplen Nolan , Beaulieu Luc , Bazalova-Carter Magdalena 
Published: April 2022

Abstract

Objective. Lead-doped scintillator dosimeters may be well suited for the dosimetry of FLASH-capable x-ray radiotherapy beams. Our study explores the dose rate dependence and temporal resolution of scintillators that makes them promising in the accurate detection of ultrahigh dose-rate (UHDR) x-rays. Approach. We investigated the response of scintillators with four material compositions to UHDR x-rays produced by a conventional x-ray tube. Scintillator output was measured using the HYPERSCINT-RP100 dosimetry research platform. Measurements were acquired at high frame rates (400 fps) which allowed for accurate dose measurements of sub-second radiation exposures from 1 to 100 ms. Dose-rate dependence was assessed by scaling tube current of the x-ray tube. Scintillator measurements were validated against Monte Carlo simulations of the probe geometries and UHDR x-ray system. Calibration factors converting dose-to-medium to dose-to-water were obtained from simulation data of plastic and lead-doped scintillator materials. Main Results. The results of this work suggest that lead-doped scintillators were dose-rate independent for UHDR x-rays from 1.1 to 40.1 Gy s−1 and capable of measuring conventional radiotherapy dose-rates (0.1 Gy s−1) at extended distance from the x-ray focal spot. Dose-to-water measured with a 5% lead-doped scintillator detector agreed with simulations within 0.6%. Significance. Lead-doped scintillators may be a valuable tool for the accurate real-time dosimetry of FLASH-capable UHDR x-ray beams.
NiTi shape memory alloy pipe couplers for ultra-high vacuum systems: development and implementation
Authors: Niccoli F , Giovinco V , Garion C , Maletta C , Chiggiato P 
Published: April 2022

Abstract
Novel Nickel–Titanium (NiTi)-based shape memory alloy (SMA) pipe couplers were designed and developed. They are suitable for room-temperature ultrahigh vacuum (UHV) systems and provide a quick and compact solution at reasonable cost. Their use is particularly interesting for restricted-access areas of particle accelerators as their installation/dismounting can be performed remotely by temperature variations. A NiTi SMA with suitable composition was selected. NiTi couplers with different diameters in the range 30–135 mm were manufactured and thermo-mechanically trained to exhibit a proper two-way shape memory behaviour which comply with the strict operative constraints for coupling applications in room temperature vacuum sectors. The connectors are easily implementable as they were designed to be compatible with commercially available flanges (DN16, DN25, DN100) used worldwide in vacuum systems. The effect of the SMA joint geometry on the thermo-mechanical response and vacuum performance was investigated by numerical studies and experimental analyses such as strain-gauge, extensometer and leak-tightness tests performed under different operating conditions including static axial loads and multiple thermal cycles. It was demonstrated that NiTi-based connectors can be thermally mounted upon heating and can guarantee the leak tightness of the vacuum pipe within a suitable temperature window. The thermal dismounting was also verified by cooling the couplers down to subzero temperatures (lower than −40 °C). Possible use of these connections at European Organization for Nuclear Research (CERN) is foreseen in vacuum assemblies installed in high radioactive areas, like those nearby particle collision points and beam collimators. Thanks to their compactness, SMA couplers are also of great interest for connecting beam pipes with small aperture such as those studied for the electron–positron future circular collider (FCC-ee) and next-generation synchrotron light facilities.
Comprehensive review on topological superconducting materials and interfaces
Authors: Sharma M M , Sharma Prince , Karn N K , Awana V P S 
Published: April 2022

Abstract
Superconductivity in topological materials has drawn significant interest from the scientific community as these materials provide a hint of the existence of Majorana fermions conceived from the quantized thermal conductivity, a zero-biased conduction peak and the anomalous Josephson effect. In this review, we make a systematic study of recent advances in the field of topological superconductivity. The article comprises of both bulk systems as well as heterostructures. A brief description of Majorana fermions and their relationship with topological superconductors and heterostructures is also carried out. This review also consists of details of key experimental techniques to characterize candidates for topological superconductivity. Moreover, we summarize the potential material candidate that may demonstrate topological superconductivity. We also consider some intrinsic odd-parity superconductors, non-centrosymmetric, centrosymmetric superconductors, doped topological insulators, doped topological crystalline insulators and some other materials that are expected to show superconductivity along with topological non-trivial states in bulk form. The effects of pressure, emergence of superconductivity in topological materials and muon spin rotation studies are also summarized in this article.
Spin Hall conductivity and anomalous Hall conductivity in full Heusler compounds
Authors: Ji Yimin , Zhang Wenxu , Zhang Hongbin , Zhang Wanli 
Published: April 2022

Abstract
The spin Hall conductivity (SHC) and anomalous Hall conductivity (AHC) in about 120 full Heusler compounds are calculated using the density functional theory in a high-throughput way. The electronic structures are mapped to the Wannier basis and the linear response theory is used to get the conductivity. Our results show that the mechanism under the SHC or AHC cannot be simply related to the valence electron numbers or atomic weights. It is related to the very details of the electronic structures, which can only be obtained by calculations. A high-throughput calculation is efficient to screen out the desired materials. According to our present results, Rh2MnAl and Cu2CoSn, as well as Co2MnAl and Co2MnGa are candidates in spintronic materials regarding their high SHC and AHC values, which can benefit the spin-torque-driven nanodevices.
Conserved charges in Chern-Simons modified theory and memory effects
Authors: Hou Shaoqi , Zhu Tao , Zhu Zong-Hong 
Published: April 2022

Abstract
In this work, conserved charges and fluxes at the future null infinity are determined in the asymptotically flat spacetime for Chern-Simons modified gravity.
The flux-balance laws are used to constrain the memory effects.
For tensor memories, the Penrose's conformal completion method is used to analyze the asymptotic structures and asymptotic symmetries, and then, conserved charges for the Bondi-Metzner-Sachs algebra are constructed with the Wald-Zoupas formalism.
These charges take very similar forms to those in Brans-Dicke theory. For the scalar memory, Chern-Simons modified gravity is rewritten in the first-order formalism, and the scalar field is replaced by a 2-form field dual to it. With this dual formalism, the scalar memory is described by the vacuum transition induced by the large gauge transformation of the 2-form field.
The Integrated Sachs Wolfe effect: unWISE and Planck constraints on dynamical dark energy
Authors: Krolewski Alex , Ferraro Simone 
Published: April 2022

Abstract
CMB photons redshift and blueshift
as they move through gravitational potentials Φ
while propagating across the Universe. If the potential is not constant in time, the photons will pick up a net redshift or blueshift, known as the Integrated Sachs-Wolfe (ISW) effect.
In the z ≪ 1000 universe, Φ̇ is nonzero on large scales when the Universe transitions from matter to dark energy domination. This effect is only detectable in cross-correlation with large-scale structure at z ∼ 1. In this paper we present a 3.2σ detection of the ISW effect using cross-correlations between unWISE infrared galaxies and Planck CMB temperature maps. We use 3 tomographic galaxy samples spanning 0 < z < 2, allowing us to fully probe the dark energy domination era and the transition into matter domination. This measurement is consistent with ΛCDM (AISW = 0.96 ± 0.30).
We study constraints on a particular class of dynamical dark energy models
(where the dark energy equation of state is different in matter and dark energy domination),
finding that unWISE-ISW improves constraints
from type Ia supernovae due to improved constraints on the time evolution of dark energy. When combining with BAO measurements, we obtain the tightest constraints on specific dynamical dark energy models. In the context of a phenomenological model for freezing quintessence, the Mocker model, we constrain the dark energy density within 10% at z < 2 using ISW, BAO and supernovae. Moreover, the ISW measurement itself provides an important independent check when relaxing assumptions about the theory of gravity, as it is sensitive to the gravitational potential rather than the expansion history.
Learning Reaching Tasks Using an Arm Robot Equipped with MACMSA
Authors: Akikawa Motohiro , Yamamura Masayuki 
Published: April 2022

Abstract
In recent years, models that integrate multimodal information to control robots have been actively developed. Memorizing and Associating Converted Multimodal Signal Architecture (MACMSA) was proposed to integrate multimodal information obtained from robots with Hopfield networks as associators and independent feed-forward neural networks as encoders and decoders. The performance of MACMSA has thus far been investigated only using pseudo-data. Notably, MACMSA exhibits high resistance to noise. However, it cannot generate signals for robot control. The purpose of this study was to improve MACMSA to generate signals for robot control and optimize it using real data on reaching tasks. The results of the generated control signals on a real machine are presented to demonstrate that the improved model can be effectively used in a real environment. The results also show that the proposed model can perform well with real data.
Defect detection in the textile industry using image-based machine learning methods: a brief review
Authors: Shahrabadi Somayeh , Castilla Yusbel , Guevara Miguel , Magalhães Luís G. , Gonzalez Dibet , Adão Telmo 
Published: April 2022

Abstract
Traditionally, computer vision solutions for detecting elements of interest (e.g., defects) are based on strict context-sensitive implementations to address contained problems with a set of well-defined conditions. On the other hand, several machine learning approaches have proven their generalization capacity, not only to improve classification continuously, but also to learn from new examples, based on a fundamental aspect: the separation of data from the algorithmic setup. The findings regarding backward-propagation and the progresses built upon graphical cards technologies boost the advances in machine learning towards a subfield known as deep learning that is becoming very popular among many industrial areas, due to its even greater robustness and flexibility to map and deal knowledge that is typically handled by humans, with, also, incredible scalability proneness. Fabric defect detection is one of the manual processes that has been progressively automatized resorting to the aforementioned approaches, as it is an essential process for quality control. The goal is manifold: reduce human error, fatigue, ergonomic issues and associated costs, while simultaneously improving the expeditiousness and preciseness of the involved tasks, with a direct impact on profit. Following such research line with a specific focus in the textile industry, this work aims to constitute a brief review of both defect types and Automated Optical Inspection (AOI) mostly based on machine learning techniques, which have been proving their effectiveness in identifying anomalies within the context of textile material analysis. The inclusion of Convolutional Neural Network (CNN) based on known architectures such as AlexNet or Visual Geometry Group (VGG16) on computerized defect analysis allowed to reach accuracies over 98%. A short discussion is also provided along with an analysis of the current state characterizing this field of intervention, as well as some future challenges.
Anomaly Detection and Analysis Based on Deep Autoencoder for the Storage Tank Liquid Level of Oil Depot
Authors: Cheng Long , Dong Guishan , Ren Linlin , Yang Ruirui , Liu Bo , Rong Yan , Li Dayong 
Published: April 2022

Abstract
In the industrial control system of oil depot, the change of storage tank liquid level is closely related to the transportation process and site management of oil depot. It is of great significance to detect the abnormality of storage tank liquid level data for the safe and stable production of oil depot. A data-driven anomaly detection strategy is proposed by analyzing the non-periodic time series data of the oil storage tank liquid level. Based on the convolutional autoencoder algorithm to learn the features and patterns of a large number of samples, the strategy is carried out by reconstructing the samples and calculating the reconstruction error, which not only does not rely on the labeled samples, but also improves the detection precision. This paper chooses three algorithms of convolutional autoencoder, RNN (Recurrent Neural Network) autoencoder and LSTM (Long Short-Term memory) autoencoder for experimental analysis. Experiments were carried out on the oil tank historical data set and NAB (Numenta Anomaly Benchmark) simulation data set respectively. The results show that the accuracy of convolutional autoencoder is 98% and the F1 score is 82%, which is more practical for the scenes with real-time requirements.
An Intelligent Dosing Algorithm Model for Wastewater Treatment Plant
Authors: Fang Xusheng , Zhai Zhengang , Zang Jian , Zhu Yunya 
Published: April 2022

Abstract
The precise coagulation add-in in the wastewater process treatment is key for efficient contamination removal. However, the complexity of the coagulant chemical theory and affected by many factors (turbidity, pH, conductivity, flow rate, etc.) that it is difficult to determine the optimal dosage. The traditional method in the production process, such as PID controller had a bad adaptability on the complex systems and high performance required systems due to its inefficient parameter coordination, and it has a large time delay, difficult to achieve precise control. Excessive dosage will lead to waste and cost-waste, insufficient dosage could not guarantee the quality of effluent water. In this research study, we proposed an intelligent precisely dosing prediction algorithm based on LightGBM, using the characteristics of the influent water quality parameters PH, turbidity, electrical conductivity and flow rate to predict the dosage of coagulant. Perform experiments based on the actual data collected from the sewage treatment plant. Compared to experimental results with the optimal dosage solution, it demonstrated that the proposed approach could predict the dosage more accurate, resulting in intelligent and precise dosing add-in in water treatment process.
Marking and Cutting of Non-metallic Products with CO2 Laser
Authors: Dolchinkov Nikolay Todorov 
Published: April 2022

Abstract
Since the discovery of the laser more than 60 years ago, research has begun on its application in various fields of technology. One of the most commonly used applications of laser technology is the cutting and marking of various materials. And while the use of different metals has been studied and used much better, the use of lasers in non-metallic materials has been studied much less. Research has been conducted with a CO2 laser on various materials -various types of textiles, felt, transparent and opaque Plexiglas and other materials that have wide application in technology and economics. The optimal parameters for performing various operations on this type of materials have been found and are shown in tabular and graphical form. Studies with different power and speed of the laser beam have been made. Based on the obtained results, the relevant conclusions are shown. These materials are widely used in industry, the manufacture of automobiles, aircraft, ships and other vehicles and machinery and the results prove the effectiveness of laser cutting and marking compared to the methods used so far to perform these operations.