bluuebunny/crossref_metadata_2025_split huggingface dataset:
Joint localization algorithm of TDOA and FDOA considering the position error of underwater sensors
Authors: Meng Tianci , Zhang Zhenkai , Lin Yunhang 
Published: May 2022

AbstractThe joint localization method of TDOA and FDOA is widely used because it can estimate the underwater moving source well. Usually, a two‐step weighted least squares (TSWLS) algorithm is used to estimate the source. However, the noise square term is always neglected in the TSWLS algorithm. In order to improve this situation, an improved TSWLS algorithm is proposed under the circumstance of sensor position inaccuracy. First, a new localization equation is constructed by the time difference equation, and the source position and velocity are initially estimated. The intermediate variables are then Taylor expanded and inserted into the localization equation of the algorithm's first step to modify the initial estimate value. Finally, the source's precise position and velocity are determined, and the proposed method was demonstrated to achieve the Cramer–Rao lower bound (CRLB) accuracy through simulations.
Remineralizing Potential of Milk and GC Tooth Mousse on Demineralized Human Enamel: An In Vitro Comparative Evaluation
Authors: Shetty Vabitha , Bhandary Srikala , Vakil Ishani 
Published: May 2022

Abstract
Introduction Caries initiation is associated with demineralization of the subsurface tooth enamel. Today, bioactive agents based on milk products have been developed to enhance remineralization under cariogenic conditions. However, there is limited information on the remineralization potential of milk.
Materials and Methods Fifty enamel specimens were prepared from sound human premolars. All enamel specimens were then placed in demineralizing solution for 4 days at 37°C to produce artificial carious lesion. Baseline surface microhardness (SMH) was evaluated using Vickers indenter. Enamel specimens were then randomly divided into three groups. Group 1 specimens were kept in artificial saliva, whereas group 2 and 3 enamel specimens were treated with milk and GC tooth mousse, respectively, for 5 minutes twice daily for 21 days. Post-treatment SMH measurements of all specimens were evaluated on the 7th, 14th, and 21st day. Data was statistically analyzed using one-way analysis of variance test and Tukey honest significant difference post-hoc test.
Results There were no significant differences in the SMH values in the control group at any time interval. There were statistically significant increases in the post-SMH values in milk and GC tooth mousse (p < 0.001) at the end of 21st day of remineralization.
Conclusion Milk showed remineralization potential comparable to that of GC tooth mousse.
RETRACTED ARTICLE: Developing emotional intelligence in student teachers in universities
Authors: Tuyakova Ulbossyn , Baizhumanova Bibianar , Mustapaeva Talshyn , Alekeshova Lyazzat , Otarbaeva Zhansaya 
Published: May 2022

AbstractEmotional intelligence is a relatively new concept. Hence, it appears crucial to investigate its short-term and long-term effect on educational process. The primary aim of this study is to identify how teaching emotional intelligence affects the emotional competence of social pedagogue students by measuring their levels of emotional intelligence before and after training. For this, the Hall Emotional Intelligence Test was used. The focus lies on these aspects of emotional intelligence (emotional competencies): Emotional Awareness, Managing your Emotions, Self-motivation, Empathy, and Managing the Emotions of Other People. The results demonstrate a substantial improvement in all these measures. The present findings may be valuable for further research on emotional intelligence in education. In addition, the paper proves that raising teacher’s emotional intelligence is beneficial to teaching and learning.
Study of beamlets extracted from a multi-aperture and five-stage acceleration system
Authors: Kashiwagi M. , Kisaki M. , Saquilayan G. Q. , Kojima A. , Hiratsuka J. , Ichikawa M. , Shimabukuro Y. , Murayama M. , Tobari H. 
Published: May 2022

A beam optics study using the ITER-relevant high intense negative ion beams, such as 1 MeV, 200 A/m2, has been performed experimentally and analytically using a multi-aperture and five-stage accelerator. Initially, multi-beamlets generated from this accelerator were deflected in various directions due to the magnetic field and space charge repulsion between beams and showed various divergences. These had limited the pulse length and the beam energy. Compensation methods of the beamlet deflections have worked effectively and contributed to achieving the ITER requirement, the divergence angle of &lt;7 mrad, and the deflection angle of &lt;1 mrad for 1 MeV beam. The beam pulse has been gradually extended from 1 to 100 s and is now going to a longer pulse based on these results. One of the remaining issues is to understand and suppress peripheral components of the beam, namely, the halo, and to reduce the local heat loads observed around the aperture edge. This halo component has been successfully distinguished from the beam core by using a newly developed beam emittance measurement system for high intense beams. By combining this measured beam emittance and the beam simulation, it was clarified for the first time that the halo components are generated in an area of 1 mm width from the aperture edge.
Controlling energy conservation in quantum dynamics with independently moving basis functions: Application to multi-configuration Ehrenfest
Authors: Asaad Mina , Joubert-Doriol Loïc , Izmaylov Artur F. 
Published: May 2022

Application of the time-dependent variational principle to a linear combination of frozen-width Gaussians describing the nuclear wavefunction provides a formalism where the total energy is conserved. The computational downside of this formalism is that trajectories of individual Gaussians are solutions of a coupled system of differential equations, limiting implementation to serial propagation algorithms. To allow for parallelization and acceleration of the computation, independent trajectories based on simplified equations of motion were suggested. Unfortunately, within practical realizations involving finite Gaussian bases, this simplification leads to breaking the energy conservation. We offer a solution for this problem by using Lagrange multipliers to ensure the energy and norm conservation regardless of basis function trajectories or basis completeness. We illustrate our approach within the multi-configurational Ehrenfest method considering a linear vibronic coupling model.
Aspects of three-dimensional higher curvature gravities
Authors: Bueno Pablo , Cano Pablo A , Llorens Quim , Moreno Javier , van der Velde Guido 
Published: May 2022

Abstract
We present new results involving general higher-curvature gravities in three dimensions. The most general Lagrangian of that kind can be written as a function of

R
,

S

2

,

S

3

, where R is the Ricci scalar,

S

2

≡

R

~

a

b

R

~

b

a

,

S

3

≡

R

~

a

b

R

~

b

c

R

~

c

a

, and

R

~

a
b

is the traceless part of the Ricci tensor. First, we provide a general formula for the exact number of independent order-n densities, #(n). This satisfies the identity #(n − 6) = #(n) − n. Then, we show that, linearized around a general Einstein solution, a generic order-n ⩾ 2 density can be written as a linear combination of R

n
, which by itself would not propagate the generic massive graviton, plus a density which by itself would not propagate the generic scalar mode,

R

n

−
12
n

(

n
−
1

)

R

n
−
2

S

2

, plus #(n) − 2 densities which contribute trivially to the linearized equations. Next, we obtain an analytic formula for the quasinormal modes and frequencies of the BTZ black hole as a function of the masses of the graviton and scalar modes for a general theory. Then, we provide a recursive formula as well as a general closed expression for order-n densities which non-trivially satisfy an holographic c-theorem, clarify their relation with Born–Infeld gravities and prove that the scalar mode is always absent from their spectrum. We show that, at each order n ⩾ 6, there exist #(n − 6) densities which satisfy the holographic c-theorem in a trivial way and that all of them are proportional to a single sextic density

Ω

(

6

)

≡
6

S

3

2

−

S

2

3

. Next, we show that there are also #(n − 6) order-n generalized quasi-topological densities in three dimensions, all of which are ‘trivial’ in the sense of making no contribution to the metric function equation. Remarkably, the set of such densities turns out to coincide exactly with the one of theories trivially satisfying the holographic c-theorem. We comment on the meaning of Ω(6) and its relation to the Segre classification of three-dimensional metrics.
Analysis of size dependence and the behavior under ultrahigh current density injection condition of GaN-based Micro-LEDs with pixel size down to 3 μm
Authors: Liu Yibo , Feng Feng , Zhang Ke , Jiang Fulong , Chan Ka-Wah , Kwok Hoi-Sing , Liu Zhaojun 
Published: May 2022

Abstract
In this paper, the GaN-based green micro light-emitting diodes (Micro-LEDs) with various sizes (from 3 to 100 μm) were fabricated and electro-optically characterized. Atom layer deposition (ALD) passivation and potassium hydroxide (KOH) treatment were applied to eliminate the sidewall damage. The size dependence of Micro-LED was systematically analyzed with current-versus-voltage and current density-versus-voltage relationship. According to the favorable ideality factor results (<1.5), the optimized sidewall treatment was achieved when the device size shrank down to <10 μm. In addition, the external quantum efficiency (EQE) droop phenomenon, luminance and output power density characteristics were depicted up to the highest current density injection condition to date (120 kA cm−2), and 6 μm device exhibited an improved EQE performance with the peak EQE value of 16.59% at 20 A cm−2 and over 600k and 6M cd cm−2 at 1 and 10 A cm−2, indicating a greater brightness quality for over 3000 PPI multiple display application. Lastly, the blue shift of 6 μm device with elevating current density was observed in electroluminescence spectra and converted to CIE 1931 color space. The whole shifting track and color variation from 1 A cm−2 to 120 kA cm−2 were demonstrated by color coordinates.
Discussion on the mechanism leading to positive synergism in SF6 mixtures with HFO1234ze(E)
Authors: Egüz E A , Pachin J , Franck C M 
Published: May 2022

Abstract
The electric strength in HFO1234ze(E)/SF6 mixtures is investigated with swarm and breakdown experiments. The density-reduced critical electric field as well as the breakdown voltage measured with both techniques, are found to be higher than that of the pure gases in mixtures with more than 10% SF6. The underlying mechanism for the observed positive synergy is investigated and the explanation proposed by Hunter and Christophorou (1985 J. Appl. Phys.
57 4377–85) is discussed for this mixture. The pressure-dependent attachment rate is found to increase with SF6 ratio thus satisfying the main requirement of the proposed mechanism in Hunter and Christophorou’s study. It appears nevertheless that due to the fast saturation with pressure and low rates in the mixtures, the three-body attachment processes account only for a small increase in the electric strength. An alternative hypothesis is proposed which considers the strong reduction of electron energies via inelastic processes in HFO1234ze(E), and is qualitatively demonstrated based on measurements and simulations.
Intermolecular interaction and cooperativity in an Fe(II) spin crossover molecular thin film system
Authors: Hao Guanhua , Dale Ashley S , N’Diaye Alpha T , Chopdekar Rajesh V , Koch Roland J , Jiang Xuanyuan , Mellinger Corbyn , Zhang Jian , Cheng Ruihua , Xu Xiaoshan , Dowben Peter A 
Published: May 2022

Abstract
Compact domain features have been observed in spin crossover [Fe{H2B(pz)2}2(bipy)] molecular thin film systems via soft x-ray absorption spectroscopy and photoemission electron microscopy. The domains are in a mixed spin state that on average corresponds to roughly 2/3 the high spin occupation of the pure high spin state. Monte Carlo simulations support the presence of intermolecular interactions that can be described in terms of an Ising model in which interactions beyond nearest-neighbors cannot be neglected. This suggests the presence of short-range order to permit interactions between molecules beyond nearest neighbor that contribute to the formation of largely high spin state domains structure. The formation of a spin state domain structure appears to be the result of extensive cooperative effects.
Terahertz transverse electric modes in graphene with DC current in hydrodynamic regime
Authors: Moiseenko I M , Popov V V , Fateev D V 
Published: May 2022

Abstract
The dispersion, excitation, and amplification of electromagnetic transverse electric (TE) modes at terahertz (THz) frequencies in graphene in the hydrodynamic (HD) regime, with a direct electric current flowing perpendicular to the TE mode wavevector, were theoretically investigated. The expression for the nonlocal HD conductivity of graphene with a direct electric current flowing perpendicular to the TE mode wavevector was derived. The direct electric current in graphene leads to the capacitive nature of the graphene HD conductivity at THz frequencies, which makes TE modes exist in this frequency range. The excitation of TE modes in graphene by an incident THz wave was modeled for the attenuated total reflection geometry. A new physical mechanism of TE mode amplification in graphene effective for a low value of carrier drift velocity was predicted. THz lasing regimes with TE modes in graphene structure with direct electric current were found. The results of this work can be used to create miniature technologically feasible sources and amplifiers of THz radiation.
Higher Chern number states in curved periodic nanowires
Authors: Siu Zhuo Bin , Tan Seng Ghee , Jalil Mansoor B A 
Published: May 2022

Abstract
The coupling between the spin and momentum degrees of freedom due to spin–orbit interactions (SOI) suggests that the strength of the latter can be modified by controlling the motion of the charge carriers. In this paper, we investigate how the effective SOI can be modulated by constraining the motion of charge carriers to curved waveguides thereby introducing real-space geometric curvature in their motion. The change in the SOI can in turn induce topological phase transitions in the system. Specifically, we study how the introduction of periodic sinusoidal curvature in nanowires with intrinsic SOC can induce the onset of mid-gap topologically protected edge states, which can be characterized by a topological invariant or Chern number. The Chern number corresponds to the number of discrete charges that would be pumped across the length of the nanowire when the phase of a sliding gate potential relative to that of the sinusoidal curvature is varied adiabatically over a complete period. In addition, coupling to an external magnetization can be utilized as an experimental knob to modify the Chern number by displacing the energies of the curvature-induced bands relative to one another. The magnetization can be tuned to achieve large discrete jumps in the number of pump charges per phase period.
Prediction of electrical properties of FDSOI devices based on deep learning
Authors: Zhao Rong , Wang Shulong , Duan Xiaoling , Liu Chenyu , Ma Lan , Chen Shupeng , Liu Hongxia 
Published: May 2022

Abstract
Fully depleted Silicon on insulator technology (FDSOI) is proposed to solve the various non-ideal effects when the process size of integrated circuits is reduced to 45 nm. The research of traditional FDSOI devices is mostly based on simulation software, which requires a lot of calculation and takes a long time. In this paper, a deep learning (DL) based electrical characteristic prediction method for FDSOI devices is proposed. DL algorithm is used to train the simulation data and establish the relationship between the physical parameters and electrical characteristics of the device. The network structure used in the experiment has high prediction accuracy. The mean square error of electrical parameters and transfer characteristic curve is only 4.34 × 10–4 and 2.44 × 10–3 respectively. This method can quickly and accurately predict the electrical characteristics of FDSOI devices without microelectronic expertise. In addition, this method can be extended to study the effects of various physical variables on device performance, which provides a new research method for the field of microelectronics.
Deep learning for dose assessment in radiotherapy by the super-localization of vaporized nanodroplets in high frame rate ultrasound imaging
Authors: van der Heyden Brent , Heymans Sophie V , Carlier Bram , Collado-Lara Gonzalo , Sterpin Edmond , D’hooge Jan 
Published: May 2022

Abstract

Objective. External beam radiotherapy is aimed to precisely deliver a high radiation dose to malignancies, while optimally sparing surrounding healthy tissues. With the advent of increasingly complex treatment plans, the delivery should preferably be verified by quality assurance methods. Recently, online ultrasound imaging of vaporized radiosensitive nanodroplets was proposed as a promising tool for in vivo dosimetry in radiotherapy. Previously, the detection of sparse vaporization events was achieved by applying differential ultrasound (US) imaging followed by intensity thresholding using subjective parameter tuning, which is sensitive to image artifacts. Approach. A generalized deep learning solution (i.e. BubbleNet) is proposed to localize vaporized nanodroplets on differential US frames, while overcoming the aforementioned limitation. A 5-fold cross-validation was performed on a diversely composed 5747-frame training/validation dataset by manual segmentation. BubbleNet was then applied on a test dataset of 1536 differential US frames to evaluate dosimetric features. The intra-observer variability was determined by scoring the Dice similarity coefficient (DSC) on 150 frames segmented twice. Additionally, the BubbleNet generalization capability was tested on an external test dataset of 432 frames acquired by a phased array transducer at a much lower ultrasound frequency and reconstructed with unconventional pixel dimensions with respect to the training dataset. Main results. The median DSC in the 5-fold cross validation was equal to ∼0.88, which was in line with the intra-observer variability (=0.86). Next, BubbleNet was employed to detect vaporizations in differential US frames obtained during the irradiation of phantoms with a 154 MeV proton beam or a 6 MV photon beam. BubbleNet improved the bubble-count statistics by ∼30% compared to the earlier established intensity-weighted thresholding. The proton range was verified with a −0.8 mm accuracy. Significance. BubbleNet is a flexible tool to localize individual vaporized nanodroplets on experimentally acquired US images, which improves the sensitivity compared to former thresholding-weighted methods.
Effect of temporal resolution on the detection of cardiac arrhythmias using HRV features and machine learning
Authors: Ben Itzhak Sagi , Ricon Shir Sharony , Biton Shany , Behar Joachim A , Sobel Jonathan A 
Published: May 2022

Abstract

Objective. Arrhythmia is an abnormal cardiac rhythm that affects the pattern and rate of the heartbeat. Wearable devices with the functionality to measure and store heart rate (HR) data are growing in popularity and enable diagnosing and monitoring arrhythmia on a large scale. The typical sampling resolution of HR data available from non-medical grade wearable devices varies from seconds to several minutes depending on the device and its settings. However, the impact of sampling resolution on the performance and quality of arrhythmia detection has not yet been quantified. Approach. In this study, we investigated the detection and classification of three arrhythmias, namely atrial fibrillation, bradycardia, tachycardia, from down-sampled HR data with various temporal resolution (5-, 15-, 30- and 60 s averages) in 1 h segments extracted from an annotated Holter ECG database acquired at the University of Virginia Heart Station. For the classification task, a total of 15 common heart rate variability (HRV) features were engineered based on the HR time series of each patient. Three different types of machine learning classifiers were evaluated, namely logistic regression, support vector machine and random forest. Main results. A decrease in temporal resolution drastically impacted the detection of atrial fibrillation but did not substantially affect the detection of bradycardia and tachycardia. A HR resolution up to 15 s average demonstrated reasonable performance with a sensitivity of 0.92 and a specificity of 0.86 for a multiclass random forest classifier. Significance. HRV features extracted from low resolution long HR recordings have the potential to increase the early detection of arrhythmias in undiagnosed individuals.
Mathematical modelling of haemorrhagic transformation within a multiscale microvasculature network
Authors: Wang Jiayu , Van Kranendonk Katinka R , El-Bouri Wahbi K , Majoie Charles B L M , Payne Stephen J 
Published: May 2022

Abstract

Objective. Haemorrhagic transformation (HT) is one of the most common complications after ischaemic stroke, caused by damage to the blood–brain barrier (BBB) that could be the result of stroke progression or a complication of stroke treatment with reperfusion therapy. The aim of this study is to develop further a previous simple HT mathematical model into an enlarged multiscale microvasculature model in order to investigate the effects of HT on the surrounding tissue and vasculature. In addition, this study investigates the relationship between tissue displacement and vascular geometry. Approach. By modelling tissue displacement, capillary compression, hydraulic conductivity in tissue and vascular permeability, we establish a mathematical model to describe the change of intracranial pressure (ICP) surrounding the damaged vascular bed after HT onset, applied to a 3D multiscale microvasculature. The use of a voxel-scale model then enables us to compare our HT simulation with available clinical imaging data for perfusion and cerebral blood volume (

C
B
V

) in the multiscale microvasculature network. Main results. We showed that the haematoma diameter and the maximum tissue displacement are approximately proportional to the diameter of the breakdown vessel. Based on the voxel-scale model, we found that perfusion reduces by approximately

13
–
17
%

and

C
B
V

reduces by around

20
–
25
%

after HT onset due to the effect of capillary compression caused by increased interstitial pressure. The results are in good agreement with the limited experimental data. Significance. This model, by enabling us to bridge the gap between the microvascular scale and clinically measurable parameters, providing a foundation for more detailed validation and understanding of HT in patients.