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Hui Zhang

Publications and source records attributed to Hui Zhang.

At least 433 records · Page 24Linked to original sources
arXiv2020

Performance of CMOS pixel sensor prototypes in ams H35 and aH18 technology for the ATLAS ITk upgrade

Pixel sensors based on commercial high-voltage CMOS processes are an exciting technology that is considered as an option for the outer layer of the ATLAS inner tracker upgrade at the High Luminosity LHC. Here, charged particles are detected using deep n-wells as sensor diodes with the depleted region extending into the silicon bulk. Both analog and digital readout electronics can be added to achieve different levels of integration up to a fully monolithic sensor. Small scale prototypes using the ams CMOS technology have previously demonstrated that it can achieve the required radiation tolerance of $10^{15}~\text{n}_\text{eq}/\text{cm}^2$ and detection efficiencies above $99.5~\%$. Recently, large area prototypes, comparable in size to a full sensor, have been produced that include most features required towards a final design: the H35demo prototype produced in ams H35 technology that supports both external and integrated readout and the monolithic ATLASPix1 pre-production design produced in ams aH18 technology. Both chips are based on large fill-factor pixel designs, but differ in readout structure. Performance results for H35DEMO with capacitively-coupled external readout and first results for the monolithic ATLASPix1 are shown.

physics.ins-det↗
arXiv2020

Evidence the ferromagnetic order on CoSb layer of LaCoSb$_2$

The emergence of unconventional superconductivity is generally considered to be related to spin fluctuations. Unveiling the intriguing behaviors of spin fluctuations in parent compounds with layered transition-metal ions may shed light on the search for exotic unconventional superconductors. Here, based on the framework of the first-principles calculations, we theoretically propose that LaCoSb$_2$ is a weak antiferromagnetic layered metal with an in-plane ferromagnetic moment of 0.88 $μ_B$ at the Co sites, as a candidate parent compound of the cobalt-based superconductors. Importantly, this theoretical finding is experimentally supported by our magnetization measurements on polycrystalline samples of LaCo$_{0.78}$Sb$_2$. Following the symmetry analysis, we suggest a possible $p$-wave superconductivity hosted in doped LaCoSb$_2$ emerging at the verge of ferromagnetic spin fluctuations, which implies potential applications in topological quantum computing in future.

cond-mat.supr-con↗
arXiv2020

Extracting the magnitude of magnetic field at freeze-out in heavy-ion collisions

A strong magnetic field influences significantly the masses of the charged light mesons. For example, the mass of charged pion increases with the magnetic field increasing. We propose this mechanism as a possible way to extract the magnitude of magnetic field at freeze-out in heavy ion collisions and thus help constrain its lifetime which is currently a major open question to resolve. Specifically we show that the ratio between the yield of charged pions and that of charged rhos is very sensitive to the magnetic field value at freeze-out. By using a viscous-hydrodynamic framework (iEBE-VISHNU) to simulate heavy ion collisions and implementing magnetic-field-dependent meson masses, we compute their yields and predict the dependence of such ratio on the magnetic field. We suggest to use this ratio of charged rho yield over charged pion yield as an experimental observable to extract the possible magnetic field at freeze-out in heavy ion collisions.

hep-ph↗
arXiv2020

SANDI: a compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI

This work introduces a compartment-based model for apparent soma and neurite density imaging (SANDI) using non-invasive diffusion-weighted MRI (DW-MRI). The existing conjecture in brain microstructure imaging trough DW-MRI presents water diffusion in white (WM) and grey (GM) matter as restricted diffusion in neurites, modelled by infinite cylinders of null radius embedded in the hindered extra-neurite water. The extra-neurite pool in WM corresponds to water in the extra-axonal space, but in GM it combines water in the extra-cellular space with water in soma. While several studies showed that this microstructure model successfully describe DW-MRI data in WM and GM at b<3 ms/{\mum^2}, it has been also shown to fail in GM at high b values (b>>3 ms/{\mum^2}). Here we hypothesize that the unmodelled soma compartment may be responsible for this failure and propose SANDI as a new model of brain microstructure where soma (i.e. cell body of any brain cell type: from neuroglia to neurons) is explicitly included. We assess the effects of size and density of soma on the direction-averaged DW-MRI signal at high b values and the regime of validity of the model using numerical simulations and comparison with experimental data from mouse (bmax = 40 ms/{/mum^2}) and human (bmax = 10 ms/{\mum^2}) brain. We show that SANDI defines new contrasts representing new complementary information on the brain cyto- and myelo-architecture. Indeed, we show for the first-time maps from 25 healthy human subjects of MR soma and neurite signal fractions, that remarkably mirror contrasts of histological images of brain cyto- and myelo-architecture. Although still under validation, SANDI might provide new insight into tissue architecture by introducing a new set of biomarkers of potential great value for biomedical applications and pure neuroscience.

physics.med-ph↗
arXiv2020

Learning Alignment for Multimodal Emotion Recognition from Speech

Speech emotion recognition is a challenging problem because human convey emotions in subtle and complex ways. For emotion recognition on human speech, one can either extract emotion related features from audio signals or employ speech recognition techniques to generate text from speech and then apply natural language processing to analyze the sentiment. Further, emotion recognition will be beneficial from using audio-textual multimodal information, it is not trivial to build a system to learn from multimodality. One can build models for two input sources separately and combine them in a decision level, but this method ignores the interaction between speech and text in the temporal domain. In this paper, we propose to use an attention mechanism to learn the alignment between speech frames and text words, aiming to produce more accurate multimodal feature representations. The aligned multimodal features are fed into a sequential model for emotion recognition. We evaluate the approach on the IEMOCAP dataset and the experimental results show the proposed approach achieves the state-of-the-art performance on the dataset.

cs.CL↗
arXiv2020

A positivity-preserving second-order BDF scheme for the Cahn-Hilliard equation with variable interfacial parameters

We present and analyze a new second-order finite difference scheme for the Macromolecular Microsphere Composite hydrogel, Time-Dependent Ginzburg-Landau (MMC-TDGL) equation, a Cahn-Hilliard equation with Flory-Huggins-deGennes energy potential. This numerical scheme with unconditional energy stability is based on the Backward Differentiation Formula (BDF) method time derivation combining with Douglas-Dupont regularization term. In addition, we present a point-wise bound of the numerical solution for the proposed scheme in the theoretical level. For the convergent analysis, we treat three nonlinear logarithmic terms as a whole and deal with all logarithmic terms directly by using the property that the nonlinear error inner product is always non-negative. Moreover, we present the detailed convergent analysis in $\ell^\infty (0,T; H_h^{-1}) \cap \ell^2 (0,T; H_h^1)$ norm. At last, we use the local Newton approximation and multigrid method to solve the nonlinear numerical scheme, and various numerical results are presented, including the numerical convergence test, positivity-preserving property test, spinodal decomposition, energy dissipation and mass conservation properties.

math.NA↗
arXiv2020

ConFiG: Contextual Fibre Growth to generate realistic axonal packing for diffusion MRI simulation

This paper presents Contextual Fibre Growth (ConFiG), an approach to generate white matter numerical phantoms by mimicking natural fibre genesis. ConFiG grows fibres one-by-one, following simple rules motivated by real axonal guidance mechanisms. These simple rules enable ConFiG to generate phantoms with tuneable microstructural features by growing fibres while attempting to meet morphological targets such as user-specified density and orientation distribution. We compare ConFiG to the state-of-the-art approach based on packing fibres together by generating phantoms in a range of fibre configurations including crossing fibre bundles and orientation dispersion. Results demonstrate that ConFiG produces phantoms with up to 20% higher densities than the state-of-the-art, particularly in complex configurations with crossing fibres. We additionally show that the microstructural morphology of ConFiG phantoms is comparable to real tissue, producing diameter and orientation distributions close to electron microscopy estimates from real tissue as well as capturing complex fibre cross sections. Signals simulated from ConFiG phantoms match real diffusion MRI data well, showing that ConFiG phantoms can be used to generate realistic diffusion MRI data. This demonstrates the feasibility of ConFiG to generate realistic synthetic diffusion MRI data for developing and validating microstructure modelling approaches.

physics.med-ph↗
arXiv2020

Rotation Effects on Mesonic Condensations in Isospin Matter

We investigate the rotation effects on the mesonic condensation in isospin matter . Using the two-flavor NJL effective model with a global rotation, we demonstrate two important effects of the rotation on its phase structure: a rotational suppression of the scalar-channel condensates, in particular the pion condensation region; and a rotational enhancement of the rho condensation region with vector-channel condensate. A new phase diagram for isospin matter under rotation is mapped out on the $ω-μ_I$ plane where three distinctive phases, corresponding to $σ$, $π$, $ρ$ dominated regions respectively, are separated by a second-order line at low isospin chemical potential and a first-order line at high rotation which are further connected at a tri-critical point.

nucl-th↗
arXiv2020

Single Channel Speech Enhancement Using Temporal Convolutional Recurrent Neural Networks

In recent decades, neural network based methods have significantly improved the performace of speech enhancement. Most of them estimate time-frequency (T-F) representation of target speech directly or indirectly, then resynthesize waveform using the estimated T-F representation. In this work, we proposed the temporal convolutional recurrent network (TCRN), an end-to-end model that directly map noisy waveform to clean waveform. The TCRN, which is combined convolution and recurrent neural network, is able to efficiently and effectively leverage short-term ang long-term information. Futuremore, we present the architecture that repeatedly downsample and upsample speech during forward propagation. We show that our model is able to improve the performance of model, compared with existing convolutional recurrent networks. Futuremore, We present several key techniques to stabilize the training process. The experimental results show that our model consistently outperforms existing speech enhancement approaches, in terms of speech intelligibility and quality.

cs.SD↗
arXiv2020

Oxygen depletion hypothesis remains controversial: a mathematical model of oxygen depletion during FLASH radiation

Background: Experiments have reported low normal tissue toxicities during FLASH radiation, but the mechanism has not been elaborated. Several hypotheses have been proposed to explain the mechanism. The oxygen depletion hypothesis has been introduced and mostly studied qualitatively. Methods: We present a computational model to describe the time-dependent change of oxygen concentration in the tissue. The kinetic equation of the model is solved numerically using the finite difference method. The model is used to analyze the FLASH effect with the oxygen depletion hypothesis, and the brain tissue is chosen as an example. Results: The oxygen distribution is determined by the oxygen consumption rate of the tissue and the distance between capillaries. The change of oxygen concentration with time after radiation has been found to follow a negative exponential function, and the time constant is determined by the distance between capillaries. When the dose rate is high enough, the same dose results in the same change of oxygen concentration regardless of dose rate. The analysis of FLASH effect in the brain tissue based on this model does not support the explanation of the oxygen depletion hypothesis. Conclusions: The oxygen depletion hypothesis remains controversial because oxygen in most normal tissues cannot be depleted by FLASH radiation according to the mathematical analysis with this model and experiments on the expression and distribution of the hypoxia-inducible factors.

physics.med-ph↗
arXiv2020

Polar Rectification Effect in Electro-Fatigued SrTiO3 Based Junctions

Rectifying semiconductor junctions are crucial to electronic devices. They convert alternating current into direct one by allowing unidirectional charge flows. In analogy to the current-flow rectification for itinerary electrons, here, a polar rectification that based on the localized oxygen vacancies (OVs) in a Ti/fatigued-SrTiO3 (fSTO) Schottky junction is first demonstrated. The fSTO with OVs is produced by an electro-degradation process. The different movability of localized OVs and itinerary electrons in the fSTO yield a unidirectional electric polarization at the interface of the junction under the coaction of external and built-in electric fields. Moreover, the fSTO displays a pre-ferroelectric state located between paraelectric and ferroelectric phases. The pre-ferroelectric state has three sub-states and can be easily driven into a ferroelectric state by external electric field. These observations open up opportunities for potential polar devices and may underpin many useful polar-triggered electronic phenomena.

physics.app-ph↗
arXiv2019

Edge-Epitaxial Growth of InSe Nanowires toward High-Performance Photodetectors

Semiconducting nanowires offer many opportunities for electronic and optoelectronic device applications due to their special geometries and unique physical properties. However, it has been challenging to synthesize semiconducting nanowires directly on SiO2/Si substrate due to lattice mismatch. Here, we developed a catalysis-free approach to achieve direct synthesis of long and straight InSe nanowires on SiO2/Si substrate through edge-homoepitaxial growth. We further achieved parallel InSe nanowires on SiO2/Si substrate through controlling growth conditions. We attributed the underlying growth mechanism to selenium self-driven vapor-liquid-solid process, which is distinct from conventional metal-catalytic vapor-liquid-solid method widely used for growing Si and III-V nanowires. Furthermore, we demonstrated that the as-grown InSe nanowire-based visible light photodetector simultaneously possesses an extraordinary photoresponsivity of 271 A/W, ultrahigh detectivity of 1.57*10^14 Jones and a fast response speed of microsecond scale. The excellent performance of the photodetector indicates that as-grown InSe nanowires are promising in future optoelectronic applications. More importantly, the proposed edge-homoepitaxial approach may open up a novel avenue for direct synthesis of semiconducting nanowire arrays on SiO2/Si substrate.

physics.app-ph↗
arXiv2019

KELT-25b and KELT-26b: A Hot Jupiter and a Substellar Companion Transiting Young A-stars Observed by TESS

We present the discoveries of KELT-25b (TIC 65412605, TOI-626.01) and KELT-26b (TIC 160708862, TOI-1337.01), two transiting companions orbiting relatively bright, early A-stars. The transit signals were initially detected by the KELT survey, and subsequently confirmed by \textit{TESS} photometry. KELT-25b is on a 4.40-day orbit around the V = 9.66 star CD-24 5016 ($T_{\rm eff} = 8280^{+440}_{-180}$ K, $M_{\star}$ = $2.18^{+0.12}_{-0.11}$ $M_{\odot}$), while KELT-26b is on a 3.34-day orbit around the V = 9.95 star HD 134004 ($T_{\rm eff}$ =$8640^{+500}_{-240}$ K, $M_{\star}$ = $1.93^{+0.14}_{-0.16}$ $M_{\odot}$), which is likely an Am star. We have confirmed the sub-stellar nature of both companions through detailed characterization of each system using ground-based and \textit{TESS} photometry, radial velocity measurements, Doppler Tomography, and high-resolution imaging. For KELT-25, we determine a companion radius of $R_{\rm P}$ = $1.64^{+0.039}_{-0.043}$ $R_{\rm J}$, and a 3-sigma upper limit on the companion's mass of $\sim64~M_{\rm J}$. For KELT-26b, we infer a planetary mass and radius of $M_{\rm P}$ = $1.41^{+0.43}_{-0.51}$ $M_{\rm J}$ and $R_{\rm P}$ = $1.940^{+0.060}_{-0.058}$ $R_{\rm J}$. From Doppler Tomographic observations, we find KELT-26b to reside in a highly misaligned orbit. This conclusion is weakly corroborated by a subtle asymmetry in the transit light curve from the \textit{TESS} data. KELT-25b appears to be in a well-aligned, prograde orbit, and the system is likely a member of a cluster or moving group.

astro-ph.EP↗
arXiv2019

All You Need Is Boundary: Toward Arbitrary-Shaped Text Spotting

Recently, end-to-end text spotting that aims to detect and recognize text from cluttered images simultaneously has received particularly growing interest in computer vision. Different from the existing approaches that formulate text detection as bounding box extraction or instance segmentation, we localize a set of points on the boundary of each text instance. With the representation of such boundary points, we establish a simple yet effective scheme for end-to-end text spotting, which can read the text of arbitrary shapes. Experiments on three challenging datasets, including ICDAR2015, TotalText and COCO-Text demonstrate that the proposed method consistently surpasses the state-of-the-art in both scene text detection and end-to-end text recognition tasks.

cs.CV↗
arXiv2019

A Generalized and Robust Method Towards Practical Gaze Estimation on Smart Phone

Gaze estimation for ordinary smart phone, e.g. estimating where the user is looking at on the phone screen, can be applied in various applications. However, the widely used appearance-based CNN methods still have two issues for practical adoption. First, due to the limited dataset, gaze estimation is very likely to suffer from over-fitting, leading to poor accuracy at run time. Second, the current methods are usually not robust, i.e. their prediction results having notable jitters even when the user is performing gaze fixation, which degrades user experience greatly. For the first issue, we propose a new tolerant and talented (TAT) training scheme, which is an iterative random knowledge distillation framework enhanced with cosine similarity pruning and aligned orthogonal initialization. The knowledge distillation is a tolerant teaching process providing diverse and informative supervision. The enhanced pruning and initialization is a talented learning process prompting the network to escape from the local minima and re-born from a better start. For the second issue, we define a new metric to measure the robustness of gaze estimator, and propose an adversarial training based Disturbance with Ordinal loss (DwO) method to improve it. The experimental results show that our TAT method achieves state-of-the-art performance on GazeCapture dataset, and that our DwO method improves the robustness while keeping comparable accuracy.

cs.CV↗
arXiv2019

Minerva-Australis I: Design, Commissioning, & First Photometric Results

The Minerva-Australis telescope array is a facility dedicated to the follow-up, confirmation, characterisation, and mass measurement of bright transiting planets discovered by the Transiting Exoplanet Survey Satellite (TESS) -- a category in which it is almost unique in the southern hemisphere. It is located at the University of Southern Queensland's Mount Kent Observatory near Toowoomba, Australia. Its flexible design enables multiple 0.7m robotic telescopes to be used both in combination, and independently, for high-resolution spectroscopy and precision photometry of TESS transit planet candidates. Minerva-Australis also enables complementary studies of exoplanet spin-orbit alignments via Doppler observations of the Rossiter-McLaughlin effect, radial velocity searches for non-transiting planets, planet searches using transit timing variations, and ephemeris refinement for TESS planets. In this first paper, we describe the design, photometric instrumentation, software, and science goals of Minerva-Australis, and note key differences from its Northern hemisphere counterpart -- the Minerva array. We use recent transit observations of four planets--WASP-2b, WASP-44b, WASP-45b, and HD 189733b to demonstrate the photometric capabilities of Minerva-Australis.

astro-ph.IM↗
arXiv2019

Proximal-Like Incremental Aggregated Gradient Method with Linear Convergence under Bregman Distance Growth Conditions

We introduce a unified algorithmic framework, called proximal-like incremental aggregated gradient (PLIAG) method, for minimizing the sum of a convex function that consists of additive relatively smooth convex components and a proper lower semi-continuous convex regularization function, over an abstract feasible set whose geometry can be captured by using the domain of a Legendre function. The PLIAG method includes many existing algorithms in the literature as special cases such as the proximal gradient method, the Bregman proximal gradient method (also called NoLips algorithm), the incremental aggregated gradient method, the incremental aggregated proximal method, and the proximal incremental aggregated gradient method. It also includes some novel interesting iteration schemes. First we show the PLIAG method is globally sublinearly convergent without requiring a growth condition, which extends the sublinear convergence result for the proximal gradient algorithm to incremental aggregated type first order methods. Then by embedding a so-called Bregman distance growth condition into a descent-type lemma to construct a special Lyapunov function, we show that the PLIAG method is globally linearly convergent in terms of both function values and Bregman distances to the optimal solution set, provided that the step size is not greater than some positive constant. These convergence results derived in this paper are all established beyond the standard assumptions in the literature (i.e., without requiring the strong convexity and the Lipschitz gradient continuity of the smooth part of the objective). When specialized to many existing algorithms, our results recover or supplement their convergence results under strictly weaker conditions.

math.OC↗