bluuebunny/crossref_metadata_2025_split huggingface dataset:
An item-based, Rasch-calibrated approach to assessing translation quality
Authors: Han Chao , Shang Xiaoqi 
Published: September 2022

AbstractItem-based scoring has been advocated as a psychometrically robust approach to translation quality assessment, outperforming traditional neo-hermeneutic and error analysis methods. The past decade has witnessed a succession of item-based scoring methods being developed and trialed, ranging from calibration of dichotomous items to preselected item evaluation. Despite this progress, these methods seem to be undermined by several limitations, such as the inability to accommodate the multifaceted reality of translation quality assessment and inconsistent item calibration procedures. Against this background, we conducted a methodological exploration, utilizing what we call anitem-based, Rasch-calibrated method, to measure translation quality. This new method, built on the sophisticated psychometric model of many-facet Rasch measurement, inherits the item concept from its predecessors, but addresses previous limitations. In this article, we demonstrate its operationalization and provide an initial body of empirical evidence supporting its reliability, validity, and utility, as well as discuss its potential applications.
Nernst coefficient measurements in two-dimensional materials
Authors: Feng Qi , Zhu Tianhui , Jian Yu , Yuan Wei , Peng Huimin , Zhong Jinrui , Duan Junxi , Zebarjadi Mona 
Published: September 2022

Abstract
The discovery of two-dimensional (2D) ferromagnets and antiferromagnets with topologically nontrivial electronic band structures makes the study of the Nernst effect in 2D materials of great importance and interest. To measure the Nernst coefficient of 2D materials, the detection of the temperature gradient is crucial. Although the micro-fabricated metal wires provide a simple but accurate way for temperature detection, a linear-response assumption that the temperature gradient is a constant is still necessary and has been widely used to evaluate the temperature gradient. However, with the existence of substrates, this assumption cannot be precise. In this study, we clearly show that the temperature gradient strongly depends on the distance from the heater by both thermoelectric transport and thermoreflectance measurements. Fortunately, both measurements show that the temperature gradient can be well described by a linear function of the distance from the heater. This linearity is further confirmed by comparing the measured Nernst coefficient to the value calculated from the generalized Mott’s formula. Our results demonstrate a precise way to measure the Nernst coefficient of 2D materials and would be helpful for future studies.
High switching ratio and inorganic gas sensing performance in BeN4 based nanodevice: a first-principles study
Authors: Xie Luzhen , Chen Tong , Dong Xiansheng , Liu Guogang , Wang Haipeng , Xiao Xianbo 
Published: September 2022

Abstract
Recently, Dirac material BeN4 has been synthesized by using laser-heated diamond anvil-groove technology (Bykov et al 2021 Phys. Rev. Lett.
126 175501). BeN4 layer, i.e. beryllonitrene, represents a qualitatively class of two-dimensional (2D) materials that can be built of a metal atom and polymeric nitrogen chains, and hosts anisotropic Dirac fermions. Enlighten by this discovered material, we study the electronic structure, anisotropic transport properties and gas sensitivity of 2D BeN4 using the density functional theory combined with non-equilibrium Green’s function method. The results manifest that the 2D BeN4 shows a typical semi-metallic property. The electronic transport properties of the intrinsic BeN4 devices show a strong anisotropic behavior since electrons transmitting along the armchair direction is much easier than that along the zigzag direction. It directly results in an obvious switching characteristic with the switching ratio up to 105. Then the adsorption characteristics indicate that H2S, CO, CO2 and H2 molecules are physisorption, while the NH3, NO, NO2, SO2 molecules are chemisorption. Among these chemisorption cases, the 2D gas sensor devices show an extremely high response for SO2 recognition, and the high anisotropy of the original 2D BeN4 device still maintains after adsorbing gas molecules. Finally, high switching ratio and inorganic gas sensing performance of BeN4 monolayer could be clearly understood with local density of states, bias-dependent spectra, scattered state distribution. In general, the results indicate that the designed BeN4 devices have potential practical application in high-ratio switching devices and high gas-sensing molecular devices.
Efficient calculation of continuous trajectory spherical center displacements by using non-contact R-test
Authors: Lyu Dun , Zhang Jiahui , Chen Yinhui , Zhang Huijie , Guo Junkang 
Published: September 2022

Abstract
The non-contact R-test is used for the dynamic measurement of five-axis machine tools. However, due to spherical curvature, calculating the spherical center displacement (SCD) using the non-contact R-test is challenging and inefficient. Thus, in this paper, an efficient calculation method based on multiple Gaussian process regression (GPR) is proposed to calculate the SCDs of the continuous trajectory by using the non-contact R-test. In the proposed method, first, the transformation matrix is constructed to roughly calculate the SCD. Second, the measurement error caused by the spherical curvature is solved and compensated by using the GPR model. Next, the threshold is set to remove some of the set points and reconstruct GPR to improve the model accuracy. Finally, the transformation matrix and the GPR model are outputted to calculate the SCDs of the continuous trajectory. We constructed a micro S trajectory to verify the proposed method. Experimental results showed that compared with the neural network method, the proposed method achieves higher model accuracy with shorter model construction time and improves the calculation efficiency by 99%.
Synthesis and design of asymmetric cul-de-sac structure HTS filter with transmission zero introduced in Pairs
Authors: Zhou Liguo , Zhang Wen , Wong Ping Kwan Johnny , Bai Xudong , Long Zhihe , Zhang Tianliang 
Published: September 2022

Abstract
An asymmetric prototype of a cul-de-sac topology filter to introduce finite frequency transmission zeros (FTZs) in pairs with the least cross-coupling is synthesized and designed in this paper, which is suitable for the design of the high temperature superconducting (HTS) narrowband filter with high selectivity sideband suppression and symmetrical frequency response about the central frequency, especially. The resonator in the cul-de-sac structure filter can adopt the same frequency resonator without self-coupling so that the cul-de-sac structure filter can have fewer coupling coefficients and fewer resonator types. These characteristics of cul-de-sac structure filters are convenient for the design of high-order HTS filters with temperature shifts. A typical 7-order HTS filter with a central frequency of 4000 MHz, 5% relative bandwidth, five coupling coefficients, one cross-coupling, and one pair of FTZs is designed and fabricated on a 0.5 mm-thick MgO wafer with double-sided YBa2Cu3O7 (YBCO) thin films employing this cul-de-sac filter theory. The analyzed frequency response characteristic obtained with full-wave tools of this filter agrees well with the synthesis results and measured results at 77 K (Kelvin temperature).
Magnetic transport in laterally coupled layers
Authors: Exner Pavel 
Published: September 2022

AbstractWe discuss magnetic transport in the system of two adjacent hard-wall layers exposed to a homogeneous field perpendicular to the layer plane and coupled laterally through a strip-shaped window in the common boundary. We show that the spectrum is a combination of absolutely continuous and flat bands, the latter being present only if the widths of the two layers are commensurate, and derive their properties. We also analyze the one-sided geometry in which the barrier separating the two layers is a halfplane.
Magnetic field back reaction on the matter power spectrum
Authors: Kunze Kerstin E. 
Published: September 2022

Abstract
At lowest order comoving magnetic fields which are frozen-into the expanding cosmic fluid
do not evolve in time. At next-to-leading order the induction equation is sourced by the
interaction term between the baryon velocity and the magnetic field amplitude which leads to a
non-trivial evolution of the comoving magnetic field. Moreover, it induces non-trivial cross
correlations between the adiabatic curvature mode and the magnetic mode. This cross correlation
together with the evolution of the induced matter perturbation leads to interesting effects on the
total matter power spectrum at small scales.
Environment-assisted quantum state and distribution entanglement restoration in spin chain
Authors: Wang Qiong , He Zhi 
Published: September 2022

Abstract
We propose a novel scheme to realize perfect state transfer and entanglement distribution in the spin chain. With the assistance of environment-assisted measurement, we get the exact analytical expression of the optimal final restoration, show that the quantum state and distribution entanglement can exactly be recovered with a certain probability, i.e. the fidelity of a general pure state can reach 100%, which is independent of the size of the spin chain. Comparing with the results obtained by the method of weak measurement, our results show notable superiorities on restoration scope and success probability.
Modelling mouse auditory response dynamics along a continuum of consciousness using a deep recurrent neural network
Authors: O’Reilly Jamie A 
Published: September 2022

Abstract

Objective. Understanding neurophysiological changes that accompany transitions between anaesthetized and conscious states is a key objective of anesthesiology and consciousness science. This study aimed to characterize the dynamics of auditory-evoked potential morphology in mice along a continuum of consciousness. Approach. Epidural field potentials were recorded from above the primary auditory cortices of two groups of laboratory mice: urethane-anaesthetized (A, n = 14) and conscious (C, n = 17). Both groups received auditory stimulation in the form of a repeated pure-tone stimulus, before and after receiving 10 mg kg−1 i.p. ketamine (AK and CK). Evoked responses were then ordered by ascending sample entropy into AK, A, CK, and C, considered to reflect physiological correlates of awareness. These data were used to train a recurrent neural network (RNN) with an input parameter encoding state. Model outputs were compared with grand-average event-related potential (ERP) waveforms. Subsequently, the state parameter was varied to simulate changes in the ERP that occur during transitions between states, and relationships with dominant peak amplitudes were quantified. Main results. The RNN synthesized output waveforms that were in close agreement with grand-average ERPs for each group (r
2 > 0.9, p < 0.0001). Varying the input state parameter generated model outputs reflecting changes in ERP morphology predicted to occur between states. Positive peak amplitudes within 25–50 ms, and negative peak amplitudes within 50–75 ms post-stimulus-onset, were found to display a sigmoidal characteristic during the transition from anaesthetized to conscious states. In contrast, negative peak amplitudes within 0–25 ms displayed greater linearity. Significance. This study demonstrates a method for modelling changes in ERP morphology that accompany transitions between states of consciousness using an RNN. In future studies, this approach may be applied to human data to support the clinical use of ERPs to predict transition to consciousness.
EMHapp: a pipeline for the automatic detection, localization and visualization of epileptic magnetoencephalographic high-frequency oscillations
Authors: Cui Wei , Cao Miao , Wang Xiongfei , Zheng Li , Cen Zhehang , Teng Pengfei , Luan Guoming , Gao Jia-Hong 
Published: September 2022

Abstract

Objective. High-frequency oscillations (HFOs) are promising biomarkers for localizing epileptogenic brain tissue. Previous studies have revealed that HFOs that present concurrence with interictal epileptic discharges (IEDs) better delineate epileptogenic brain tissue, particularly for epilepsy patients with multitype interictal discharges. However, the analysis of noninvasively recorded epileptic HFOs involves many complex procedures, such as data preprocessing, detection and source localization, impeding the translation of this approach to clinical practice. Approach. To address these problems, we developed a graphical user interface (GUI)-based pipeline called EMHapp, which can be used for the automatic detection, source localization and visualization of HFO events concurring with IEDs in magnetoencephalography (MEG) signals by using a beamformer-based virtual sensor (VS) technique. An improved VS reconstruction method was developed to enhance the amplitudes of both HFO and IED VS signals. To test the capability of our pipeline, we collected MEG data from 11 complex focal epilepsy patients with surgical resections or seizure onset zones (SOZs) that were identified by intracranial electroencephalography. Main results. Our results showed that the HFO sources of eight patients were concordant with their resection margins or SOZs. Our proposed VS signal reconstruction approach achieved an 83.2% improvement regarding the number of detected HFO events and a 17.3% improvement in terms of the spatial overlaps between the HFO sources and the resection margins or SOZs in comparison with conventional VS reconstruction approaches. Significance. EMHapp is the first GUI-based pipeline for the analysis of epileptic magnetoencephalographic HFOs, which conveniently obtains HFO source locations using clinical data and enables direct translation to clinical applications.
An ultra-wideband monopole antenna for skin cancer detection
Authors: Rizwan Shaik , Phani Kumar Kanaparthi V 
Published: September 2022

Abstract
a low-profile modified elliptical structure ultra-wide-band monopole antenna for skin cancer detection is presented in this paper. The antenna is developed over an FR-4 lossy substrate with permittivity 4.3 and a height of 1.6 mm. The dimensions of antenna is 20 × 28 × 1.6 mm3 and it covers a frequency range of 2.82-12.56 GHz. The proposed antenna consists of elliptical and circular shaped radiators with partial ground plane, to achieve an optimized low profile structure with ultra-wide band. The proposed ultra-wideband antenna(UWB) is used to detect the unhealthy tumor in the skin with the help of time-domain and SAR analysis. The rectangular human skin model with skin, fat, muscle, and bone layers is developed in fullwave simulator. The Proposed UWB antenna is safe for skin exposure as it shows SAR [1g] of 0.296 W/Kg (on skin phantom) at the frequency of 3.4 GHz, respectively. Using time-domain and SAR analysis, the suggested UWB antenna offers a potential alternative to validate the presence of unhealthy tissue in the human body.
A Terahertz/Millimeter-Wave Based Detection and Imaging System Using Antenna-Coupled Microbolometer
Authors: Ahmad Beig Mirza Tanweer , Kumar Mukesh , Sharma Yogesh , Sharma Bhoopesh Kumar 
Published: September 2022

Abstract
The Terahertz (THz) region lie in the range 0.1 THz to 10 THz. It can pass easily through fog, smoke, thin walls, and clothes and be focused as a light wave to create images of objects. Terahertz waves are applied in imaging technology, such as safety, navigation, and non-destructive evaluation (NDE) technique used for materials analysis. A microbolometer is a micromachined device to measure the inherent power of incident electromagnetic radiation. The resistance of bolometer is temperature-dependent, and it varies with changes in the temperature of the exposed surface. Bolometric detectors dominate the market due to their affordability and ease of manufacturing. Despite their slow response time, the systems are still actively employed in the research area, aiming at improved terahertz detection. The antenna and bolometer are coupled. The chosen antenna has a resonance at desired frequency leading to the development of fast response time bolometers without compromising the collection area of the bolometer. The system has low cost, easy fabrication, and better isolation. Antenna simulations were conducted to design and optimize the spiral antenna for 1 to 2.5 THz using HFSS (high-frequency structure simulator) simulation software. The antenna simulation results are presented and discussed.
Multiband Monopole Antenna Design for 2G-5G Applications
Authors: Vincy Lumina A , Sangeetha M 
Published: September 2022

Abstract
Multi frequency antennas are in high demand as the wireless communication system is developing rapidly. To access internet in a mobile device, 2G-5G and WLAN are used that covers 1.8 GHz – 6 GHz. This paper proposes a design of low profile multiband monopole antenna for all 2G-5G communications, WLAN and for WiMAX application. The antenna design has a diamond shaped radiator, a cylinder to achieve better resonance, and a defective ground. The proposed antenna has a compact size of 30 mm x 44.5 mm. This antenna covers 2G (1.8 GHz), 3G (2.1 GHz), 4G (2.4 GHz), 5G (3.5 GHz), WLAN (2.4/3.6/5 GHz) and WiMAX (2.3/3.5/5.8 GHz) and is shown from the measured results. From these results it is shown that the produced antenna produces six distinct bands with good the simulation outcomes.
Generation of adjustable micro-scale optical bottle beam by an axicon-lens system with asymmetric elliptical aperture
Authors: Chien Shuo-Chih , Chen Wei-Yu , Liu Cheng-Yang 
Published: September 2022

Abstract
The purpose of this study is to examine an optimal configuration of optical bottle beam generation. The proposed bottle beam is generated by casting a laser beam through an elliptical aperture and then through an axicon optical system. Simulation is performed by using multiphysics-capable wavefront technique, and the distance between the axicon and the focus lens can be adjusted. Two-dimensional Poincaré maps are employed to show the distribution of light. By combining Poincaré maps and expected position of the bottle beam, the relationship between the beam intensity and range is obtained. The simulated results can act as a reference for positioning optical components and expecting the effective zone of the bottle beam.
Transformational Perceptive of Data Recorder for UAV Flight Automation Control System using Image Processing Techniques
Authors: Dharamvir  , Hemanth K S 
Published: September 2022

Abstract
Flight Data Recorders (FDRs) are readily available in the market, to be used on the Unmanned Aerial Vehicles (UAV) for onboard data recording. They have their own inbuilt sensors and characteristics and can be easily placed within the cockpit of the UAV. However, they have umpteen drawbacks. They do not have sufficient sampling rate for rapid and accurate flight automation, are either very bulky, or do not incorporate some of the necessary sensors required for post-flight analysis and are very costly. Hence, the need arises where the FDR needs to be designed to suit the requirements. We go about designing one such FDR. Our FDR incorporates a MicroStrain’s 3DM- GX1 Gyro Enhanced Orientation Sensor, a Texas Instrument’s GPS module and four servo motors each controlling the rudder, elevator, ailerons. The data from these devices are interpolated to increase the sampling rate and are simultaneously stored into a Secure Digital (SD) / Micro Memory Card (MMC) during the flight of the UAV. Greater sampling rates allow more rapid and accurate flight automation. SD/MMC cards allow faster and efficient data retrieval for post flight processing. Our FDR is designed to be compact, cheap and overcomes most of the drawbacks mentioned above. Therefore, we call this FDR as Smart Data Recorder(SDR).
Performance evaluation of MDKF based on state estimations for path tracking applications
Authors: Babu Praveenkumar , Parthasarathy Eswaran 
Published: September 2022

Abstract
One of the most difficult tasks for tracking in control systems in the presence of uncertainty is estimating the accuracy and efficiency of hidden variables. For tracking applications, the Kalman filter is the most extensively used estimation algorithm. However, tracking several objects remains a difficult effort in order to improve prediction and corrective results. For tracking several objects, a multi-dimensional Kalman filter (MDKF) based on state estimations is offered as a solution. This research also includes a performance analysis of the MDKF for tracking paths by modifying co-efficients of the steady-state and covariance equations. For linear dynamic systems, MDKF is evaluated. Path tracking using the Kalman filter and MDKF is also investigated. The true and filtered responses of MDKF filtering algorithm for path tracking are observed. After four trials, the output covariance yields steady state values. The simulation results reveal that our proposed filtering algorithm performs 2x better than a typical Kalman filter for objects moving in linear motion, indicating that it is suitable for real-time implementation.
RETRACTED: Design and Implementation of Acquire Carriage for Disabled people in a Visual Surveillance Using Character Recognition
Authors: Nivash S , Ganesh E N , Manikandan T. 
Published: September 2022

Abstract
In certain cases, persons with disabilities may be forced to rely on others for the performance of their duties. Blindness is one of the impairments that might be encountered. Up to this point, there has been N number of solutions presented that make life easier for visually impaired individuals. One of the problems they face on a daily basis is making an independent purchase of a product they need. To solve this issue, the approach is to utilize a camera to record a picture, which is then processed using the tesseract method to extract text from the image, which is then transformed into an audio file that can be heard using headphones. Following the implementation of this strategy, during this shopping trolley technology to detect the item put with machine learning and precision location discover a person will be used to locate a person in the shopping trolley.
Investigation and Implementation of Convolutional Neural Networks with Transfer Learning for Detection of Covid-19
Authors: Raghavendra Ch , Phani Sriram S , Sravan Kumar V , Sudheksha K , Bhavya Sri P 
Published: September 2022

Abstract
This paper aims to present a robust model which uses Artificial Intelligence in the rapid and accurate detection of Covid-19. The Proposed Project uses Deep Learning techniques for the detection of Covid-19 as well as Pneumonia with the help of Digitalized Chest X-rays. By Applying Pre-Trained Networks which are also known as Convolutional Neural Networks, this can be made possible. Also, with the help of Transfer Learning Techniques the Neural Networks can be trained and validated faster and better thus providing a significantly higher chance in the correct and accurate detection. The CNNs taken into consideration are VGG-19 and ResNet-50 with the former providing an accuracy of over 95% and the latter with an accuracy of 92% proving that such a high accuracy computer-aided diagnostic tool can be used at a time like this. Also, further improvements in the future with advancements in technology can provide even astonishing results.