arXiv subjects

Qing Pan

Publications and source records attributed to Qing Pan.

At least 19 recordsLinked to original sources

arXiv2026

Are Repeaters Prevalent Among the Known Fast Radio Burst Sources?

Fast radio bursts (FRBs) are millisecond radio pulses of unknown origin. Despite extensive follow-up observations, only $\sim3\%$ of FRBs have been confirmed as repeaters. It remains unclear whether the rest are truly one-off bursts, or essentially repeating sources that have only been detected once due to limited monitoring time. Using the second CHIME/FRB catalog, we test this debate by comparing non-repeaters with two repeater-based subsamples: the first-detected bursts of repeaters and their highest-fluence bursts. A non-parametric method that accounts for selection effects is employed to derive the energy functions and event rates of these samples. All samples are well described by broken power-law energy distributions with comparable break energies ($\sim 5\times10^{38}$ erg), but with significantly different slopes between repeating and non-repeating populations. Their event-rate evolution also differs significantly. Assuming $\rho(z) \propto (1+z)^B$, we have $B = -5.57^{+0.15}_{-0.15}$ for non-repeaters and $B = -8.63^{+0.46}_{-0.41}$ and $-9.10^{+0.55}_{-0.56}$ for the two repeater samples. Size-matched resampling shows that the repeater event-rate indices lie far outside the 5$\sigma$ range expected from non-repeater subsamples, ruling out sample size as the reason for the observed difference. These results indicate that at least a subset of one-off FRBs are intrinsically non-repeating, implying that repeating sources may represent a distinct and possibly less common population.

astro-ph.HE↗

arXiv2026

Knowledge-guided Transfer Prediction In Underrepresented Populations: A GRU-D-Static Framework For Maternal And Neonatal Outcomes

Integrating summary-level scientific knowledge into neural network models provides a practical strategy for transferring prediction models trained on adequately sampled source cohorts to underrepresented target populations, where individual-level data in the target domain are often limited or unavailable. In this study, we propose transfer prediction strategies incorporating external summary-level scientific knowledge and illustrate its application on the PRISMA Maternal and Neonatal Health Study, training a neural network model on the source data to predict adverse outcomes in the target cohorts. Besides, we also extend the existing GRU-D framework by incorporating static feature embeddings and attention weights to jointly leverage temporal and static information for improved prediction. Our approach employs soft labels derived from summary-level statistics describing the target population to fine-tune GRU-D-Static models that are initially trained on the source populations. We evaluate six maternal and neonatal outcomes, including stillbirth, preterm birth, low birth weight, small vulnerable newborn, neonatal death, and maternal near miss. Across all tested scenarios, fine-tuning using soft labels from just basic covariates substantially improved predictive performance compared with deep learning models trained on the source sample. Furthermore, the performance slightly improves more when additional covariates were incorporated into the logistic regression model or when partial input features from the target population were available for fine-tuning. These findings demonstrate that integrating existing scientific knowledge in the literature through transfer prediction of source neural network models can enhance prediction performance in underrepresented target populations, reducing reliance on large-scale data collection and supporting risk prediction in global health.

stat.AP↗

arXiv2026

Validation of Smartphone-Based Photogrammetric 3D Body Scanning for Automated Anthropometric Measurements Compared with a Commercial Depth-Sensor-Based Body Scanner

3D body scanning has become an important tool in healthcare applications because of its rapid and non-invasive nature. While smartphone-based photogrammetric reconstruction provide a low-cost and accessible alternative to commercial 3D body scanners, their performance for whole-body scanning remains insufficiently validated. Thus, we designed this study to comprehensively validate the photogrammetric 3D scanning application by evaluating automatically extracted whole-body measurements and longitudinal body-shape monitoring. We evaluated a representative application, PolyCam, against the commercial depth-sensor-based Fit3D ProScanner using 144 pregnant participants scanned longitudinally throughout pregnancy. We designed an automatic circumference extraction pipeline to get measurements at four anatomical landmarks from paired 3D scans. A linear mixed-effects model was used to evaluate scanner effects and longitudinal body-shape changes. Measurement consistency was assessed using repeated PolyCam scans and tape measurements on a rigid mannequin. PolyCam demonstrated strong agreement with Fit3D, with average biases below 16 mm, intraclass correlation coefficients above 0.8, and Pearson correlation coefficients above 0.9 across all landmarks. Both systems captured comparable longitudinal body-shape changes. Mannequin experiments showed mean biases below 3.5 mm and no significant differences from tape measurements. These findings support smartphone photogrammetry as a potential accessible alternative to commercial body scanners and applicable for longitudinal 3D body-shape assessment.

cs.CV↗

arXiv2025

MvBody: Multi-View-Based Hybrid Transformer Using Optical 3D Body Scan for Explainable Cesarean Section Prediction

Accurately assessing the risk of cesarean section (CS) delivery is critical, especially in settings with limited medical resources, where access to healthcare is often restricted. Early and reliable risk prediction allows better-informed prenatal care decisions and can improve maternal and neonatal outcomes. However, most existing predictive models are tailored for in-hospital use during labor and rely on parameters that are often unavailable in resource-limited or home-based settings. In this study, we conduct a pilot investigation to examine the feasibility of using 3D body shape for CS risk assessment for future applications with more affordable general devices. We propose a novel multi-view-based Transformer network, MvBody, which predicts CS risk using only self-reported medical data and 3D optical body scans obtained between the 31st and 38th weeks of gestation. To enhance training efficiency and model generalizability in data-scarce environments, we incorporate a metric learning loss into the network. Compared to widely used machine learning models and the latest advanced 3D analysis methods, our method demonstrates superior performance, achieving an accuracy of 84.62% and an Area Under the Receiver Operating Characteristic Curve (AUC-ROC) of 0.724 on the independent test set. To improve transparency and trust in the model's predictions, we apply the Integrated Gradients algorithm to provide theoretically grounded explanations of the model's decision-making process. Our results indicate that pre-pregnancy weight, maternal age, obstetric history, previous CS history, and body shape, particularly around the head and shoulders, are key contributors to CS risk prediction.

cs.CV↗

arXiv2024

Community Detection with Heterogeneous Block Covariance Model

Community detection is the task of clustering objects based on their pairwise relationships. Most of the model-based community detection methods, such as the stochastic block model and its variants, are designed for networks with binary (yes/no) edges. In many practical scenarios, edges often possess continuous weights, spanning positive and negative values, which reflect varying levels of connectivity. To address this challenge, we introduce the heterogeneous block covariance model (HBCM) that defines a community structure within the covariance matrix, where edges have signed and continuous weights. Furthermore, it takes into account the heterogeneity of objects when forming connections with other objects within a community. A novel variational expectation-maximization algorithm is proposed to estimate the group membership. The HBCM provides provable consistent estimates of memberships, and its promising performance is observed in numerical simulations with different setups. The model is applied to a single-cell RNA-seq dataset of a mouse embryo and a stock price dataset. Supplementary materials for this article are available online.

stat.ML↗

arXiv2021

CycleGAN with Dual Adversarial Loss for Bone-Conducted Speech Enhancement

Compared with air-conducted speech, bone-conducted speech has the unique advantage of shielding background noise. Enhancement of bone-conducted speech helps to improve its quality and intelligibility. In this paper, a novel CycleGAN with dual adversarial loss (CycleGAN-DAL) is proposed for bone-conducted speech enhancement. The proposed method uses an adversarial loss and a cycle-consistent loss simultaneously to learn forward and cyclic mapping, in which the adversarial loss is replaced with the classification adversarial loss and the defect adversarial loss to consolidate the forward mapping. Compared with conventional baseline methods, it can learn feature mapping between bone-conducted speech and target speech without additional air-conducted speech assistance. Moreover, the proposed method also avoids the oversmooth problem which is occurred commonly in conventional statistical based models. Experimental results show that the proposed method outperforms baseline methods such as CycleGAN, GMM, and BLSTM. Keywords: Bone-conducted speech enhancement, dual adversarial loss, Parallel CycleGAN, high frequency speech reconstruction

cs.SD↗

arXiv2019

Time-resolved mid-infrared dual-comb spectroscopy

Dual-comb spectroscopy can provide broad spectral bandwidth and high spectral resolution in a short acquisition time, enabling time-resolved measurements. Specifically, spectroscopy in the mid-infrared wavelength range is of particular interest, since most of the molecules have their strongest rotational-vibrational transitions in this "fingerprint" region. Here we report time-resolved mid-infrared dual-comb spectroscopy for the first time, covering ~300 nm bandwidth around 3.3 {\mu}m with 6 GHz spectral resolution and 20 {\mu}s temporal resolution. As a demonstration, we study a CH4/He gas mixture in an electric discharge, while the discharge is modulated between dark and glow regimes. We simultaneously monitor the production of C2H6 and the vibrational excitation of CH4 molecules, observing the dynamics of both processes. This approach to broadband, high-resolution, and time-resolved mid-infrared spectroscopy provides a new tool for monitoring the kinetics of fast chemical reactions, with potential applications in various fields such as physical chemistry and plasma/combustion analysis.

physics.app-ph↗

arXiv2019

Isogeometric Analysis for Surface PDEs with Extended Loop Subdivision

We investigate the isogeometric analysis for surface PDEs based on the extended Loop subdivision approach. The basis functions consisting of quartic box-splines corresponding to each subdivided control mesh are utilized to represent the geometry exactly, and construct the solution space for dependent variables as well, which is consistent with the concept of isogeometric analysis. The subdivision process is equivalent to the $h$-refinement of NURBS-based isogeometric analysis. The performance of the proposed method is evaluated by solving various surface PDEs, such as surface Laplace-Beltrami harmonic/biharmonic/triharmonic equations, which are defined on different limit surfaces of the extended Loop subdivision for different initial control meshes. Numerical experiments demonstrate that the proposed method has desirable performance in terms of the accuracy, convergence and computational cost for solving the above surface PDEs defined on both open and closed surfaces. The proposed approach is proved to be second-order accuracy in the sense of $L^2$-norm by theoretical and/or numerical results, which is also outperformed over the standard linear finite element by several numerical comparisons.

math.NA↗

arXiv2019

The quantum theory and topological features of photon

In this paper, we have proposed the spinor wave equation of free and non-free photon. On this basis, we given the spin operators and spin wave functions of photon, and calculated the wave function of photon in vacuum and medium. In addition, we have given the quantum Berry phase and Chern number with the photon wave function, which can be used to studied the quantum topological features of photon in one-dimensional period medium.

physics.optics↗

arXiv2018

Logistic Regression Augmented Community Detection for Network Data with Application in Identifying Autism-Related Gene Pathways

When searching for gene pathways leading to specific disease outcomes, additional information on gene characteristics is often available that may facilitate to differentiate genes related to the disease from irrelevant background when connections involving both types of genes are observed and their relationships to the disease are unknown. We propose method to single out irrelevant background genes with the help of auxiliary information through a logistic regression, and cluster relevant genes into cohesive groups using the adjacency matrix. Expectation-maximization algorithm is modified to maximize a joint pseudo-likelihood assuming latent indicators for relevance to the disease and latent group memberships as well as Poisson or multinomial distributed link numbers within and between groups. A robust version allowing arbitrary linkage patterns within the background is further derived. Asymptotic consistency of label assignments under the stochastic blockmodel is proven. Superior performance and robustness in finite samples are observed in simulation studies. The proposed robust method identifies previously missed gene sets underlying autism related neurological diseases using diverse data sources including de novo mutations, gene expressions and protein-protein interactions.

stat.ML↗

arXiv2018

The design of ultra-strong laser with one-dimensional function photonic crystal

With the optical kerr effect, the conventional photonic crystal can be turned into the function photonic crystal under the action of pump light. In the paper, we have designed the ultra-strong light source and laser with one-dimensional function photonic crystal. When the incident light is the ordinary light, the output is ultra-strong light source, and when the incident light is the low power laser, the output is ultra-strong laser, the maximum magnification can be reached $10^{80}$ and even more. Otherwise, we analyzed the effect of period number, medium refractive index and thickness, incident angle, the pump light irradiation way and pump light intensity on the magnification, these results shall help to optimal design ultra-strong light source and laser.

physics.gen-ph↗

arXiv2017

In situ high resolution real-time quantum efficiency imaging for photocathodes

Aspects of the preparation process and performance degradation are two major problems of photocathodes. The lack of a means for dynamic quantum efficiency measurements results in the inability to observe the inhomogeneity of the cathode surface by fine structural analysis and in real time.Here we present a simple and scalable technique for in situ real-time quantum efficiency diagnosis. An incoherent light source provides uniform illumination on the cathode surface, and solenoid magnets are used as lens for focusing and imaging the emitted electron beam on a downstream scintillator screen, which converts the quantum efficiency information into fluorescence intensity distribution. The microscopic discontinuity and the dynamic changes of the quantum efficiency of a gallium arsenide photocathode are observed at a resolution of a few microns. An unexpected uneven decrease of the quantum efficiency is also recorded. The work demonstrates a new observation method for photoemission materials research.

physics.app-ph↗

arXiv2013

Estimating restricted mean job tenures in semi-competing risk data compensating victims of discrimination

When plaintiffs prevail in a discrimination case, a major component of the calculation of economic loss is the length of time they would have been in the higher position had they been treated fairly during the period in which the employer practiced discrimination. This problem is complicated by the fact that one's eligibility for promotion is subject to termination by retirement and both the promotion and retirement processes may be affected by discriminatory practices. This semi-competing risk setup is decomposed into a retirement process and a promotion process among the employees. Predictions for the purpose of compensation are made by utilizing the expected promotion and retirement probabilities of similarly qualified members of the nondiscriminated group. The restricted mean durations of three periods are estimated - the time an employee would be at the lower position, at the higher level and in retirement. The asymptotic properties of the estimators are presented and examined through simulation studies. The proposed restricted mean job duration estimators are shown to be robust in the presence of an independent frailty term. Data from the reverse discrimination case, Alexander v. Milwaukee, where White-male lieutenants were discriminated in promotion to captain are reanalyzed. While the appellate court upheld liability, it reversed the original damage calculations, which heavily depended on the time a plaintiff would have been in each position. The results obtained by the proposed method are compared to those made at the first trial. Substantial differences in both directions are observed.

stat.AP↗

arXiv2008

RubberEdge: Reducing Clutching by Combining Position and Rate Control with Elastic Feedback

Position control devices enable precise selection, but significant clutching degrades performance. Clutching can be reduced with high control-display gain or pointer acceleration, but there are human and device limits. Elastic rate control eliminates clutching completely, but can make precise selection difficult. We show that hybrid position-rate control can outperform position control by 20% when there is significant clutching, even when using pointer acceleration. Unlike previous work, our RubberEdge technique eliminates trajectory and velocity discontinuities. We derive predictive models for position control with clutching and hybrid control, and present a prototype RubberEdge position-rate control device including initial user feedback.

cs.HC↗

arXiv2006

Dense-coding quantum key distribution based on continuous-variable entanglement

We proposed a scheme of continuous-variable quantum key distribution, in which the bright Einstein-Podolsky-Rosen entangled optical beams are utilized. The source of the entangled beams is placed inside the receiving station, where half of the entangled beams are transmitted with round trip and the other half are retained by the receiver. The amplitude and phase signals modulated on the signal beam by the sender are simultaneously extracted by the authorized receiver with the scheme of the dense-coding correlation measurement for continuous quantum variables, thus the channel capacity is significantly improved. Two kinds of possible eavesdropping are discussed. The mutual information and the secret key rates are calculated and compared with those of unidirectional transmission schemes.

quant-ph↗

arXiv2005

Quantum Key Ditribution Based on Quantum Intensity Correlation of Twin Beams

A new and simple quantum key distribution scheme based on the quantum intensity correlation of optical twin beams and the directly local measurements of intensity noise of single optical beam is presented and experimentally demonstrated. Using the twin beams with the quantum intensity correlation of 5dB the effective bit rate of $2\times 10^7bits/s$ is completed. The noncloning of quantum systems and the sensitivity of the existing correlations to losses provide the physical mechamism for the security against eavesdropping. In the presented scheme the signal modulation and homodyne detection are not needed.

quant-ph↗

arXiv2004

Experimental Demonstration of Unconditional Entanglement Swapping for Continuous Variables

The unconditional entanglement swapping for continuous variables is experimentally demonstrated. Two initial entangled states are produced from two nondegenerate optical parametric amplifiers operating at deamplification. Through implementing the direct measurement of Bell-state between two optical beams from each amplifier the remaining two optical beams, which have never directly interacted with each other, are entangled. The quantum correlation degrees of 1.23dB and 1.12dB below the shot noise limit for the amplitude and phase quadratures resulting from the entanglement swapping are straightly measured.

quant-ph↗

arXiv2003

Experiment towards continuous-variable entanglement swapping: Highly correlated four-partite quantum state

We present a protocol for performing entanglement swapping with intense pulsed beams. In a first step, the generation of amplitude correlations between two systems that have never interacted directly is demonstrated. This is verified in direct detection with electronic modulation of the detected photocurrents. The measured correlations are better than expected from a classical reconstruction scheme. In the entanglement swapping process, a four--partite entangled state is generated. We prove experimentally that the amplitudes of the four optical modes are quantum correlated 3 dB below shot noise, which is due to the potential four--party entanglement.

quant-ph↗