arXiv subjects

Fei Xiang

Publications and source records attributed to Fei Xiang.

10 recordsLinked to original sources

arXiv2025

Towards real-time additive-free dopamine detection at $10^{-8}$ mM with hardware accelerated platform integrated on camera

Tracing physiological neurotransmitters such as dopamine (DA) with detection limits down to $\mathrm{1\times10^{-8}}$ mM is a critical goal in neuroscience for studying brain functions and progressing the understanding of cerebral disease. Addressing this problem requires enhancing the current state-of-the-art additive-free electrochemical workstation methods by over two orders of magnitude. In this work, we implement an ultra-sensitive, additive-free platform exploiting suitably engineered light-scattering membranes and optical accelerators integrated into commercial vision cameras, reporting real-time detection of DA in uric and ascorbic acid below the concentration of $\mathrm{10^{-8}}$ mM. These performances improve the current best technology by over two orders of magnitude in resolution while providing continuous, real-time detection at video rates. This technology also upgrades the bulk form factor of an electrochemical workstation with an imaging camera's compact and portable footprint. The optical accelerator implemented in this work is universal and trainable to detect a wide range of biological analytes. This technology's wide adoption could help enable early disease detection and personalized treatment adjustments while improving the management of neurological, mental, and immune-related conditions.

physics.ins-det↗

arXiv2024

Quantum-activated neural reservoirs on-chip open up large hardware security models for resilient authentication

Quantum artificial intelligence is a frontier of artificial intelligence research, pioneering quantum AI-powered circuits to address problems beyond the reach of deep learning with classical architectures. This work implements a large-scale quantum-activated recurrent neural network possessing more than 3 trillion hardware nodes/cm$^2$, originating from repeatable atomic-scale nucleation dynamics in an amorphous material integrated on-chip, controlled with 0.07 nW electric power per readout channel. Compared to the best-performing reservoirs currently reported, this implementation increases the scale of the network by two orders of magnitude and reduces the power consumption by six, reaching power efficiencies in the range of the human brain, dissipating 0.2 nW/neuron. When interrogated by a classical input, the chip implements a large-scale hardware security model, enabling dictionary-free authentication secure against statistical inference attacks, including AI's present and future development, even for an adversary with a copy of all the classical components available. Experimental tests report 99.6% reliability, 100% user authentication accuracy, and an ideal 50% key uniqueness. Due to its quantum nature, the chip supports a bit density per feature size area three times higher than the best technology available, with the capacity to store more than $2^{1104}$ keys in a footprint of 1 cm$^2$. Such a quantum-powered platform could help counteract the emerging form of warfare led by the cybercrime industry in breaching authentication to target small to large-scale facilities, from private users to intelligent energy grids.

cond-mat.dis-nn↗

arXiv2023

The year-scale X-ray variations in the core of M87

The analysis of light variation of M87 can help us understand the disc evolution. In the past decade, M87 has experienced several short-term light variabilities related to flares. We also find there are year-scale X-ray variations in the core of M87. Their light variability properties are similar to clumpy-ADAF. By re-analyzing 56 $\it Chandra$ observations from 2007 to 2019, we distinguish the `non-flaring state' from `flaring state' in the light variability. After removing flaring state data, we identify 4 gas clumps in the nucleus and all of them can be well fitted by the clumpy-ADAF model. The average mass accretion rate is $\sim 0.16 \rm M_{\odot} yr^{-1}$. We analyze the photon index($\Gamma$)-flux(2-10keV) correlation between the non-flaring state and flaring state. For the non-flaring states, the flux is inversely proportional to the photon index. For the flaring states, we find no obvious correlation between the two parameters. In addition, we find that the flare always occurs at a high mass accretion rate, and after the luminosity of the flare reaches the peak, it will be accompanied by a sudden decrease in luminosity. Our results can be explained as that the energy released by magnetic reconnection destroys the structure of the accretion disc, thus the luminosity decreases rapidly and returns to normal levels thereafter.

astro-ph.HE↗

arXiv2021

Lightweight Dual-channel Target Speaker Separation for Mobile Voice Communication

Nowadays, there is a strong need to deploy the target speaker separation (TSS) model on mobile devices with a limitation of the model size and computational complexity. To better perform TSS for mobile voice communication, we first make a dual-channel dataset based on a specific scenario, LibriPhone. Specifically, to better mimic the real-case scenario, instead of simulating from the single-channel dataset, LibriPhone is made by simultaneously replaying pairs of utterances from LibriSpeech by two professional artificial heads and recording by two built-in microphones of the mobile. Then, we propose a lightweight time-frequency domain separation model, LSTM-Former, which is based on the LSTM framework with source-to-noise ratio (SI-SNR) loss. For the experiments on Libri-Phone, we explore the dual-channel LSTMFormer model and a single-channel version by a random single channel of Libri-Phone. Experimental result shows that the dual-channel LSTM-Former outperforms the single-channel LSTMFormer with relative 25% improvement. This work provides a feasible solution for the TSS task on mobile devices, playing back and recording multiple data sources in real application scenarios for getting dual-channel real data can assist the lightweight model to achieve higher performance.

cs.SD↗

arXiv2021

A Coupled Random Projection Approach to Large-Scale Canonical Polyadic Decomposition

We propose a novel algorithm for the computation of canonical polyadic decomposition (CPD) of large-scale tensors. The proposed algorithm generalizes the random projection (RAP) technique, which is often used to compute large-scale decompositions, from one single projection to multiple but coupled random projections (CoRAP). The proposed CoRAP technique yields a set of tensors that together admits a coupled CPD (C-CPD) and a C-CPD algorithm is then used to jointly decompose these tensors. The results of C-CPD are finally fused to obtain factor matrices of the original large-scale data tensor. As more data samples are jointly exploited via C-CPD, the proposed CoRAP based CPD is more accurate than RAP based CPD. Experiments are provided to illustrate the performance of the proposed approach.

cs.LG↗

arXiv2020

Neural Architecture Search on Acoustic Scene Classification

Convolutional neural networks are widely adopted in Acoustic Scene Classification (ASC) tasks, but they generally carry a heavy computational burden. In this work, we propose a lightweight yet high-performing baseline network inspired by MobileNetV2, which replaces square convolutional kernels with unidirectional ones to extract features alternately in temporal and frequency dimensions. Furthermore, we explore a dynamic architecture space built on the basis of the proposed baseline with the recent Neural Architecture Search (NAS) paradigm, which first trains a supernet that incorporates all candidate networks and then applies a well-known evolutionary algorithm NSGA-II to discover more efficient networks with higher accuracy and lower computational cost. Experimental results demonstrate that our searched network is competent in ASC tasks, which achieves 90.3% F1-score on the DCASE2018 task 5 evaluation set, marking a new state-of-the-art performance while saving 25% of FLOPs compared to our baseline network.

cs.SD↗

arXiv2020

Disk evolution of the M87's nucleus observed in 2008

We report the discovery of year-scale X-ray variation in the nuclear region of the M87 by reanalyzing the 8 Chandra observations from 2007 to 2008. The X-ray spectra are fitted and decomposed into the disk and flaring components. This year-scale X-ray variability can be explained quite well by a simple clumpy accretion model. We conclude that the central super-massive black hole of the M87 was accreting a cloud of $\sim0.5$M$_\odot$ at that time.

astro-ph.HE↗

arXiv2018

Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition

We investigate the use of generative adversarial networks (GANs) in speech dereverberation for robust speech recognition. GANs have been recently studied for speech enhancement to remove additive noises, but there still lacks of a work to examine their ability in speech dereverberation and the advantages of using GANs have not been fully established. In this paper, we provide deep investigations in the use of GAN-based dereverberation front-end in ASR. First, we study the effectiveness of different dereverberation networks (the generator in GAN) and find that LSTM leads a significant improvement as compared with feed-forward DNN and CNN in our dataset. Second, further adding residual connections in the deep LSTMs can boost the performance as well. Finally, we find that, for the success of GAN, it is important to update the generator and the discriminator using the same mini-batch data during training. Moreover, using reverberant spectrogram as a condition to discriminator, as suggested in previous studies, may degrade the performance. In summary, our GAN-based dereverberation front-end achieves 14%-19% relative CER reduction as compared to the baseline DNN dereverberation network when tested on a strong multi-condition training acoustic model.

cs.SD↗

arXiv2012

Deprojected analysis of Abell 1835 observed with Chandra and compared with XMM-Newton

Using a deprojection technique, we study the X-ray properties of the galaxy cluster Abell 1835 observed with Chandra, including temperature, abundance, electron density, gas mass fraction, and total mass. A comparison with the results without deprojection shows that the properties do not change much. When we compare the results with those of XMM-Newton, the difference between the temperature profiles derived from Chandra and XMM-Newton data still exists, even if the point-spread function effect of XMM-Newton is corrected. To investigate the reasons for the difference, we used the spectra to cross-calibrate the temperatures. They show that the Chandra spectra can be fitted well with XMM-Newton temperatures. Furthermore, we derive the electron density profile from Chandra data with XMM-Newton temperatures and calculate the projected mass, which is consistent with the XMM-Newton mass and a little lower than the weak lensing mass at r_500. Thus, it seems that the temperature derived from XMM-Newton may be more reliable.

astro-ph.CO↗

arXiv2009

Evolution of gaseous disk viscosity driven by supernova explosion in star-forming galaxies at high redshift

Motivated by Genzel et al.'s observations of high-redshift star-forming galaxies, containing clumpy and turbulent rings or disks, we build a set of equations describing the dynamical evolution of gaseous disks with inclusion of star formation and its feedback. Transport of angular momentum is due to "turbulent" viscosity induced by supernova explosions in the star formation region. Analytical solutions of the equations are found for the initial cases of a gaseous ring and the integrated form for a gaseous disk, respectively. For a ring with enough low viscosity, it evolves in a slow processes of gaseous diffusion and star formation near the initial radius. For a high viscosity, the ring rapidly diffuses in the early phase. The diffusion drives the ring into a region with a low viscosity and start the second phase undergoing pile-up of gas at a radius following the decreased viscosity torque. The third is a sharply deceasing phase because of star formation consumption of gas and efficient transportation of gas inward forming a stellar disk. We apply the model to two $z\sim 2$ galaxies BX 482 and BzK 6004, and find that they are undergoing a decline in their star formation activity.

astro-ph.CO↗