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Chen Yang

Publications and source records attributed to Chen Yang.

At least 253 records · Page 14Linked to original sources
arXiv2023

ggpicrust2: an R package for PICRUSt2 predicted functional profile analysis and visualization

Microbiome research is now moving beyond the compositional analysis of microbial taxa in a sample. Increasing evidence from large human microbiome studies suggests that functional consequences of changes in the intestinal microbiome may provide more power for studying their impact on inflammation and immune responses. Although 16S rRNA analysis is one of the most popular and a cost-effective method to profile the microbial compositions, marker-gene sequencing cannot provide direct information about the functional genes that are present in the genomes of community members. Bioinformatic tools have been developed to predict microbiome function with 16S rRNA gene data. Among them, PICRUSt2 has become one of the most popular functional profile prediction tools, which generates community-wide pathway abundances. However, no state-of-art inference tools are available to test the differences in pathway abundances between comparison groups. We have developed ggpicrust2, an R package, to do extensive differential abundance(DA) analyses and provide publishable visualization to highlight the signals.

stat.AP↗
arXiv2023

SPIDR: SDF-based Neural Point Fields for Illumination and Deformation

Neural radiance fields (NeRFs) have recently emerged as a promising approach for 3D reconstruction and novel view synthesis. However, NeRF-based methods encode shape, reflectance, and illumination implicitly and this makes it challenging for users to manipulate these properties in the rendered images explicitly. Existing approaches only enable limited editing of the scene and deformation of the geometry. Furthermore, no existing work enables accurate scene illumination after object deformation. In this work, we introduce SPIDR, a new hybrid neural SDF representation. SPIDR combines point cloud and neural implicit representations to enable the reconstruction of higher quality object surfaces for geometry deformation and lighting estimation. meshes and surfaces for object deformation and lighting estimation. To more accurately capture environment illumination for scene relighting, we propose a novel neural implicit model to learn environment light. To enable more accurate illumination updates after deformation, we use the shadow mapping technique to approximate the light visibility updates caused by geometry editing. We demonstrate the effectiveness of SPIDR in enabling high quality geometry editing with more accurate updates to the illumination of the scene.

cs.CV↗
arXiv2023

Gravitational Waves Produced by Domain Walls During Inflation

We study the properties of the stochastic gravitational wave background (SGWB) produced by domain walls (DWs) during inflation without forming a network. We numerically simulate the DW production caused by a second-order phase transition and calculate the SGWB spectrum using a $1000\times1000\times1000$ lattice. We show that the SGWB can be observed directly by future terrestrial and spatial gravitational wave detectors and through the B-mode spectrum in CMB. This signal can also explain the common noise process observed by pulsar timing array experiments. With numerical simulations, we derive an empirical formula for the strength and qualitative features of the SGWB spectrum. The details of the SGWB spectrum also contain information about the later evolution of the universe.

hep-ph↗
arXiv2023

Solving Multi-Dimensional Schrödinger Equations Based on EPINNs

Due to the good performance of neural networks in high-dimensional and nonlinear problems, machine learning is replacing traditional methods and becoming a better approach for eigenvalue and wave function solutions of multi-dimensional Schrödinger equations. This paper proposes a numerical method based on neural networks to solve multiple excited states of multi-dimensional stationary Schrödinger equation. We introduce the orthogonal normalization condition into the loss function, use the frequency principle of neural networks to automatically obtain multiple excited state eigenfunctions and eigenvalues of the equation from low to high energy levels, and propose a degenerate level processing method. The use of equation residuals and energy uncertainty makes the error of each energy level converge to 0, which effectively avoids the order of magnitude interference of error convergence, improves the accuracy of wave functions, and improves the accuracy of eigenvalues as well. Comparing our results to the previous work, the accuracy of the harmonic oscillator problem is at least an order of magnitude higher with fewer training epochs. We complete numerical experiments on typical analytically solvable Schrödinger equations, e.g., harmonic oscillators and hydrogen-like atoms, and propose calculation and evaluation methods for each physical quantity, which prove the effectiveness of our method on eigenvalue problems. Our successful solution of the excited states of the hydrogen atom problem provides a potential idea for solving the stationary Schrödinger equation for multi-electron atomic molecules.

physics.comp-ph↗
arXiv2023

Multifunctional fiber-based optoacoustic emitter for non-genetic bidirectional neural communication

A bidirectional brain interface with both "write" and "read" functions can be an important tool for fundamental studies and potential clinical treatments for neurological diseases. Here we report a miniaturized multifunctional fiber based optoacoustic emitter (mFOE) that first integrates simultaneous non-genetic optoacoustic stimulation for "write" and electrophysiology recording of neural circuits for "read". The non-genetic feature addresses the challenges of the viral transfection required by optogenetics in primates and human. The orthogonality between optoacoustic waves and electrical field provides a solution to avoid the interference between electrical stimulation and recording. We first validated the non-genetic stimulation function of the mFOE in rat cultured neurons using calcium imaging. In vivo application of mFOE for successful simultaneous optoacoustic stimulation and electrical recording of brain activities was confirmed in mouse hippocampus in both acute and chronical applications up to 1 month. Minimal brain tissue damage has been confirmed after these applications. The capability of non-genetic neural stimulation and recording enabled by mFOE opens up new possibilities for the investigation of neural circuits and brings new insights into the study of ultrasound neurostimulation.

q-bio.NC↗
arXiv2022

Video Interpolation by Event-driven Anisotropic Adjustment of Optical Flow

Video frame interpolation is a challenging task due to the ever-changing real-world scene. Previous methods often calculate the bi-directional optical flows and then predict the intermediate optical flows under the linear motion assumptions, leading to isotropic intermediate flow generation. Follow-up research obtained anisotropic adjustment through estimated higher-order motion information with extra frames. Based on the motion assumptions, their methods are hard to model the complicated motion in real scenes. In this paper, we propose an end-to-end training method A^2OF for video frame interpolation with event-driven Anisotropic Adjustment of Optical Flows. Specifically, we use events to generate optical flow distribution masks for the intermediate optical flow, which can model the complicated motion between two frames. Our proposed method outperforms the previous methods in video frame interpolation, taking supervised event-based video interpolation to a higher stage.

cs.CV↗
arXiv2022

A K-variate Time Series Is Worth K Words: Evolution of the Vanilla Transformer Architecture for Long-term Multivariate Time Series Forecasting

Multivariate time series forecasting (MTSF) is a fundamental problem in numerous real-world applications. Recently, Transformer has become the de facto solution for MTSF, especially for the long-term cases. However, except for the one forward operation, the basic configurations in existing MTSF Transformer architectures were barely carefully verified. In this study, we point out that the current tokenization strategy in MTSF Transformer architectures ignores the token uniformity inductive bias of Transformers. Therefore, the vanilla MTSF transformer struggles to capture details in time series and presents inferior performance. Based on this observation, we make a series of evolution on the basic architecture of the vanilla MTSF transformer. We vary the flawed tokenization strategy, along with the decoder structure and embeddings. Surprisingly, the evolved simple transformer architecture is highly effective, which successfully avoids the over-smoothing phenomena in the vanilla MTSF transformer, achieves a more detailed and accurate prediction, and even substantially outperforms the state-of-the-art Transformers that are well-designed for MTSF.

cs.LG↗
arXiv2022

Magnetic activities and parameters of 43 flare stars in the GWAC archive

In the archive of the Ground Wide Angle Camera (GWAC), we found 43 white light flares from 43 stars, among which, three are sympathetic or homologous flares, and one of them also has a quasi-periodic pulsation with a period of $13.0\pm1.5$ minutes. Among these 43 flare stars, there are 19 new active stars and 41 stars that have available TESS and/or K2 light curves, from which we found 931 stellar flares. We also obtained rotational or orbital periods of 34 GWAC flare stars, of which 33 are less than 5.4 days, and ephemerides of three eclipsing binaries from these light curves. Combining with low resolution spectra from LAMOST and the Xinglong 2.16m telescope, we found that $L_{\rm Hα}/L_{\rm bol}$ are in the saturation region in the rotation-activity diagram. From the LAMOST medium-resolution spectrum, we found that Star \#3 (HAT 178-02667) has double H$α$ emissions which imply it is a binary, and two components are both active stars. Thirteen stars have flare frequency distributions (FFDs) from TESS and/or K2 light curves. These FFDs show that the flares detected by GWAC can occur at a frequency of 0.5 to 9.5 yr$^{-1}$. The impact of flares on habitable planets was also studied based on these FFDs, and flares from some GWAC flare stars may produce enough energetic flares to destroy ozone layers, but none can trigger prebiotic chemistry on their habitable planets.

astro-ph.SR↗
arXiv2022

Optically-generated focused ultrasound for noninvasive brain stimulation with ultrahigh precision

High precision neuromodulation is a powerful tool to decipher neurocircuits and treat neurological diseases. Current non-invasive neuromodulation methods offer limited precision at the millimeter level. Here, we report optically-generated focused ultrasound (OFUS) for non-invasive brain stimulation with ultrahigh precision. OFUS is generated by a soft optoacoustic pad (SOAP) fabricated through embedding candle soot nanoparticles in a curved polydimethylsiloxane film. SOAP generates a transcranial ultrasound focus at 15 MHz with an ultrahigh lateral resolution of 83 um, which is two orders of magnitude smaller than that of conventional transcranial-focused ultrasound (tFUS). Here, we show effective OFUS neurostimulation in vitro with a single ultrasound cycle. We demonstrate submillimeter transcranial stimulation of the mouse motor cortex in vivo. An acoustic energy of 0.6 mJ/cm^2, four orders of magnitude less than that of tFUS, is sufficient for successful OFUS neurostimulation. OFUS offers new capabilities for neuroscience studies and disease treatments by delivering a focus with ultrahigh precision non-invasively.

q-bio.NC↗
arXiv2022

Harmonics-assisted optical phase amplifier

The change in the relative phase between two light fields serves as a basic principle for the measurement of the physical quantity that guides this change. It would therefore be highly advantageous if the relative phase could be amplified to enhance the measurement resolution. One well-known method for phase amplification involves the use of the multi-photon number and path entangled state known as the NOON state; however, a high-number NOON state is very difficult to prepare and is highly sensitive to optical losses. Here we propose and experimentally demonstrate in principle a phase amplifier scheme with the assistance of a harmonic generation process. The relative phase difference between two polarization modes in a polarized interferometer is amplified coherently four times with cascaded second-harmonic generation processes. We demonstrate that these amplification processes can be recycled and therefore have the potential to realize much higher numbers of multiple amplification steps. The phase amplification method presented here shows considerable advantages over the method based on NOON states and will be highly promising for use in precision optical measurements.

physics.optics↗
arXiv2022

Tail maximal dependence in bivariate models: estimation and applications

Assessing dependence within co-movements of financial instruments has been of much interest in risk management. Typically, indices of tail dependence are used to quantify the strength of such dependence, although many of the indices underestimate the strength. Hence, we advocate the use of a statistical procedure designed to estimate the maximal strength of dependence that can possibly occur among the co-movements. We illustrate the procedure using simulated and real data-sets.

stat.ME↗
arXiv2022

Multi tasks RetinaNet for mitosis detection

The account of mitotic cells is a key feature in tumor diagnosis. However, due to the variability of mitotic cell morphology, it is a highly challenging task to detect mitotic cells in tumor tissues. At the same time, although advanced deep learning method have achieved great success in cell detection, the performance is often unsatisfactory when tested data from another domain (i.e. the different tumor types and different scanners). Therefore, it is necessary to develop algorithms for detecting mitotic cells with robustness in domain shifts scenarios. Our work further proposes a foreground detection and tumor classification task based on the baseline(Retinanet), and utilizes data augmentation to improve the domain generalization performance of our model. We achieve the state-of-the-art performance (F1 score: 0.5809) on the challenging premilary test dataset.

cs.CV↗
arXiv2022

Modeling Two-Way Selection Preference for Person-Job Fit

Person-job fit is the core technique of online recruitment platforms, which can improve the efficiency of recruitment by accurately matching the job positions with the job seekers. Existing works mainly focus on modeling the unidirectional process or overall matching. However, recruitment is a two-way selection process, which means that both candidate and employer involved in the interaction should meet the expectation of each other, instead of unilateral satisfaction. In this paper, we propose a dual-perspective graph representation learning approach to model directed interactions between candidates and jobs. To model the two-way selection preference from the dual-perspective of job seekers and employers, we incorporate two different nodes for each candidate (or job) and characterize both successful matching and failed matching via a unified dual-perspective interaction graph. To learn dual-perspective node representations effectively, we design an effective optimization algorithm, which involves a quadruple-based loss and a dual-perspective contrastive learning loss. Extensive experiments on three large real-world recruitment datasets have shown the effectiveness of our approach.

cs.IR↗
arXiv2022

Parallel measurements of vibrational modes in a few-layer graphene nanomechanical resonator using software-defined radio dongles

Software-defined radio dongles are small and inexpensive receivers well known to amateur radio enthusiasts. When connected to an antenna, they enable monitoring of a wide range of the radio spectrum by conditioning the input signal and transferring a downconverted version of it to a personal computer for software processing. Here, we employ a composite of two such dongles, interfaced with codes written in MATLAB and GNU Radio, as a measuring instrument to study the flexural vibrations of a few-layer graphene nanomechanical resonator. Instead of an antenna, we connect the dongles to the split output of a photodetector used to detect vibrations optically. We first perform a quantitative analysis of the dynamics of the first vibrational mode. We then measure the response of the first two vibrational modes in parallel. To illustrate our technique, we detect changes in the vibrational amplitude of both modes induced by periodic strain modulation with a delay of $\approx1$ ms between measurements. Last, we show that our software-based instrument can be employed to demodulate human voice encoded in the vibrations of our resonator. For parallel measurements of several frequency channels, and provided that the input signal is not too weak, our composite system may offer an alternative to the use of multiple lock-in amplifiers or multiple spectrum analyzers, with the distinct advantage of being cost-effective per frequency channel.

cond-mat.mes-hall↗
arXiv2022

Data-Driven Energy Levels Calculation of Neutral Ytterbium ($Z$ = 70)

In view of the difficulty in calculating the atomic structure parameters of high-$Z$ elements, the HFR (Hartree-Fock with relativistic corrections) theory in combination with the ridge regression (RR) algorithm rather than the Cowan code's least squares fitting (LSF) method is proposed and applied. By analyzing the energy level structure parameters of the HFR theory and using the fitting experimental energy level extrapolation method, some excited state energy levels of the {Yb~I} ($Z=70$) atom including the $4f$ open shell are calculated. The advantages of the ridge regression algorithm are demonstrated by comparing it with Cowan's least squares results. In addition, the results obtained by the new method are compared with the experimental results and other theoretical results to demonstrate the reliability and accuracy of our approach.

physics.atom-ph↗
arXiv2022

RecBole 2.0: Towards a More Up-to-Date Recommendation Library

In order to support the study of recent advances in recommender systems, this paper presents an extended recommendation library consisting of eight packages for up-to-date topics and architectures. First of all, from a data perspective, we consider three important topics related to data issues (i.e., sparsity, bias and distribution shift), and develop five packages accordingly: meta-learning, data augmentation, debiasing, fairness and cross-domain recommendation. Furthermore, from a model perspective, we develop two benchmarking packages for Transformer-based and graph neural network (GNN)-based models, respectively. All the packages (consisting of 65 new models) are developed based on a popular recommendation framework RecBole, ensuring that both the implementation and interface are unified. For each package, we provide complete implementations from data loading, experimental setup, evaluation and algorithm implementation. This library provides a valuable resource to facilitate the up-to-date research in recommender systems. The project is released at the link: https://github.com/RUCAIBox/RecBole2.0.

cs.IR↗
arXiv2022

Up-conversion detection of mid-infrared light carrying orbital angular momentum

Frequency up-conversion is an effective method of mid-infrared (MIR) detection by converting the long-wavelength photons to the visible domain, where efficient detectors are readily available. Here, we generate the MIR light carrying orbital angular momentum (OAM) from a difference frequency generation process and perform the up-conversion of it via sum frequency conversion in a bulk quasi-phase-matching crystal. The maximum quantum conversion efficiencies from MIR to visible are 34.0%, 10.4%, and 3.5% for light with topological charges of 0, 1, and 2, respectively, which is achieved by utilizing an optimized strong pump light. We also verify the OAM conservation with a specially designed interferometer, and the results agree well with the numerical simulations. Our study opens up the possibilities for generating, manipulating, and detecting MIR light that carries OAM, and will have great potential for optical communications and remote sensing in the MIR regime.

physics.optics↗