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Min Wang

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preprint2026arXiv

A Multimodal Pre-trained Network for Integrated EEG-Video Seizure Detection

Reliable seizure detection in mouse models is essential for preclinical epilepsy research, yet manual review of synchronized video-EEG recordings is labor-intensive and single-modality systems fail for complementary reasons: video-based methods are easily confounded by benign behaviors, whereas EEG-based methods are vulnerable to ictal motion artifacts. We present EEGVFusion, a multimodal framework that combines self-supervised EEG representation learning, spatio-temporal video encoding, optimal-transport alignment, and bidirectional cross-attention to integrate neural and behavioral evidence. We also curate an expert-annotated dataset of synchronized EEG and video recordings comprising 93 sessions from 15 mice for training and evaluation. In the random-session split, EEGVFusion achieved a Balanced Accuracy of 0.9957 with perfect event sensitivity and an Event FAR of 0.6250 FP/h, indicating strong seizure detection performance with a low false-alarm burden. In a single held-out-subject evaluation with Subject 110 reserved for testing, EEGVFusion achieved a Balanced Accuracy of 0.9718 and reduced Event FAR from 2.7250 FP/h for the EEG-only counterpart to 0.4833 FP/h while preserving perfect event sensitivity. Targeted ablations further showed that EEG pre-training and OT alignment help reduce false alarms while preserving event sensitivity.

preprint2023arXiv

Self-distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach

Text recognition methods are gaining rapid development. Some advanced techniques, e.g., powerful modules, language models, and un- and semi-supervised learning schemes, consecutively push the performance on public benchmarks forward. However, the problem of how to better optimize a text recognition model from the perspective of loss functions is largely overlooked. CTC-based methods, widely used in practice due to their good balance between performance and inference speed, still grapple with accuracy degradation. This is because CTC loss emphasizes the optimization of the entire sequence target while neglecting to learn individual characters. We propose a self-distillation scheme for CTC-based model to address this issue. It incorporates a framewise regularization term in CTC loss to emphasize individual supervision, and leverages the maximizing-a-posteriori of latent alignment to solve the inconsistency problem that arises in distillation between CTC-based models. We refer to the regularized CTC loss as Distillation Connectionist Temporal Classification (DCTC) loss. DCTC loss is module-free, requiring no extra parameters, longer inference lag, or additional training data or phases. Extensive experiments on public benchmarks demonstrate that DCTC can boost text recognition model accuracy by up to 2.6%, without any of these drawbacks.

preprint2022arXiv

A Feature Weighted Mixed Naive Bayes Model for Monitoring Anomalies in the Fan System of a Thermal Power Plant

With the increasing intelligence and integration, a great number of two-valued variables (generally stored in the form of 0 or 1 value) often exist in large-scale industrial processes. However, these variables cannot be effectively handled by traditional monitoring methods such as LDA, PCA and PLS. Recently, a mixed hidden naive Bayesian model (MHNBM) is developed for the first time to utilize both two-valued and continuous variables for abnormality monitoring. Although MHNBM is effective, it still has some shortcomings that need to be improved. For MHNBM, the variables with greater correlation to other variables have greater weights, which cannot guarantee greater weights are assigned to the more discriminating variables. In addition, the conditional probability must be computed based on the historical data. When the training data is scarce, the conditional probability between continuous variables tends to be uniformly distributed, which affects the performance of MHNBM. Here a novel feature weighted mixed naive Bayes model (FWMNBM) is developed to overcome the above shortcomings. For FWMNBM, the variables that are more correlated to the class have greater weights, which makes the more discriminating variables contribute more to the model. At the same time, FWMNBM does not have to calculate the conditional probability between variables, thus it is less restricted by the number of training data samples. Compared with MHNBM, FWMNBM has better performance, and its effectiveness is validated through the numerical cases of a simulation example and a practical case of Zhoushan thermal power plant (ZTPP), China.

preprint2022arXiv

A learning-based projection method for model order reduction of transport problems

The Kolmogorov $n$-width of the solution manifolds of transport-dominated problems can decay slowly. As a result, it can be challenging to design efficient and accurate reduced order models (ROMs) for such problems. To address this issue, we propose a new learning-based projection method to construct nonlinear adaptive ROMs for transport problems. The construction follows the offline-online decomposition. In the offline stage, we train a neural network to construct adaptive reduced basis dependent on time and model parameters. In the online stage, we project the solution to the learned reduced manifold. Inheriting the merits from both deep learning and the projection method, the proposed method is more efficient than the conventional linear projection-based methods, and may reduce the generalization error of a solely learning-based ROM. Unlike some learning-based projection methods, the proposed method does not need to take derivatives of the neural network in the online stage.

preprint2022arXiv

A simple consistent Bayes factor for testing the Kendall rank correlation coefficient

In this paper, we propose a simple and easy-to-implement Bayesian hypothesis test for the presence of an association, described by Kendall's τcoefficient, between two variables measured on at least an ordinal scale. Owing to the absence of the likelihood functions for the data, we employ the asymptotic sampling distributions of the test statistic as the working likelihoods and then specify a truncated normal prior distribution on the noncentrality parameter of the alternative hypothesis, which results in the Bayes factor available in closed form in terms of the cumulative distribution function of the standard normal distribution. Investigating the asymptotic behavior of the Bayes factor we find the conditions of the priors so that it is consistent to whichever the hypothesis is true. Simulation studies and a real-data application are used to illustrate the effectiveness of the proposed Bayes factor. It deserves mentioning that the proposed method can be easily covered in undergraduate and graduate courses in nonparametric statistics with an emphasis on students' Bayesian thinking for data analysis.

preprint2022arXiv

A Study on the Power Parameter in Power Prior Bayesian Analysis

The power prior and its variations have been proven to be a useful class of informative priors in Bayesian inference due to their flexibility in incorporating the historical information by raising the likelihood of the historical data to a fractional power δ. The derivation of the marginal likelihood based on the original power prior,and its variation, the normalized power prior, introduces a scaling factor C(δ) in the form of a prior predictive distribution with powered likelihood. In this paper, we show that the scaling factor might be infinite for some positive δ with conventionally used initial priors, which would change the admissible set of the power parameter. This result seems to have been almost completely ignored in the literature. We then illustrate that such a phenomenon may jeopardize the posterior inference under the power priors when the initial prior of the model parameters is improper. The main findings of this paper suggest that special attention should be paid when the suggested level of borrowing is close to 0, while the actual optimum might be below the suggested value. We use a normal linear model as an example for illustrative purposes.

preprint2022arXiv

An expectation-maximization algorithm for estimating the parameters of the correlated binomial distribution

The correlated binomial (CB) distribution was proposed by Luceño (Computational Statistics $\&$ Data Analysis, 20, 1995, 511-520) as an alternative to the binomial distribution for the analysis of the data in the presence of correlations among events. Due to the complexity of the mixture likelihood of the model, it may be impossible to derive analytical expressions of the maximum likelihood estimators (MLEs) of the unknown parameters. To overcome this difficulty, we develop an expectation-maximization algorithm for computing the MLEs of the CB parameters. Numerical results from simulation studies and a real-data application showed that the proposed method is very effective by consistently reaching a global maximum. Finally, our results should be of interest to senior undergraduate or first-year graduate students and their lecturers with an emphasis on the interested applications of the EM algorithm for finding the MLEs of the parameters in discrete mixture models.

preprint2022arXiv

Analysis of Age of Information in Dual Updating Systems

We study the average Age of Information (AoI) and peak AoI (PAoI) of a dual-queue status update system that monitors a common stochastic process. Although the double queue parallel transmission is instrumental in reducing AoI, the out of order of data arrivals also imposes a significant challenge to the performance analysis. We consider two settings: the M-M system where the service time of two servers is exponentially distributed; the M-D system in which the service time of one server is exponentially distributed and that of the other is deterministic. For the two dual-queue systems, closed-form expressions of average AoI and PAoI are derived by resorting to the graphic method and state flow graph analysis method. Our analysis reveals that compared with the single-queue system with an exponentially distributed service time, the average PAoI and the average AoI of the M-M system can be reduced by 33.3% and 37.5%, respectively. For the M-D system, the reduction in average PAoI and the average AoI are 27.7% and 39.7%, respectively. Numerical results show that the two dual-queue systems also outperform the M/M/2 single queue dual-server system with optimized arrival rate in terms of average AoI and PAoI.

preprint2022arXiv

Cancellable Template Design for Privacy-Preserving EEG Biometric Authentication Systems

As a promising candidate to complement traditional biometric modalities, brain biometrics using electroencephalography (EEG) data has received a widespread attention in recent years. However, compared with existing biometrics such as fingerprints and face recognition, research on EEG biometrics is still in its infant stage. Most of the studies focus on either designing signal elicitation protocols from the perspective of neuroscience or developing feature extraction and classification algorithms from the viewpoint of machine learning. These studies have laid the ground for the feasibility of using EEG as a biometric authentication modality, but they have also raised security and privacy concerns as EEG data contains sensitive information. Existing research has used hash functions and cryptographic schemes to protect EEG data, but they do not provide functions for revoking compromised templates as in cancellable template design. This paper proposes the first cancellable EEG template design for privacy-preserving EEG-based authentication systems, which can protect raw EEG signals containing sensitive privacy information (e.g., identity, health and cognitive status). A novel cancellable EEG template is developed based on EEG graph features and a non-invertible transform. The proposed transformation provides cancellable templates, while taking advantage of EEG elicitation protocol fusion to enhance biometric performance. The proposed authentication system offers equivalent authentication performance (8.58\% EER on a public database) as in the non-transformed domain, while protecting raw EEG data. Furthermore, we analyze the system's capacity for resisting multiple attacks, and discuss some overlooked but critical issues and possible pitfalls involving hill-climbing attacks, second attacks, and classification-based authentication systems.

preprint2022arXiv

DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Control

Adaptive traffic signal control plays a significant role in the construction of smart cities. This task is challenging because of many essential factors, such as cooperation among neighboring intersections and dynamic traffic scenarios. First, to facilitate cooperation of traffic signals, existing work adopts graph neural networks to incorporate the temporal and spatial influences of the surrounding intersections into the target intersection, where spatial-temporal information is used separately. However, one drawback of these methods is that the spatial-temporal correlations are not adequately exploited to obtain a better control scheme. Second, in a dynamic traffic environment, the historical state of the intersection is also critical for predicting future signal switching. Previous work mainly solves this problem using the current intersection's state, neglecting the fact that traffic flow is continuously changing both spatially and temporally and does not handle the historical state. In this paper, we propose a novel neural network framework named DynSTGAT, which integrates dynamic historical state into a new spatial-temporal graph attention network to address the above two problems. More specifically, our DynSTGAT model employs a novel multi-head graph attention mechanism, which aims to adequately exploit the joint relations of spatial-temporal information. Then, to efficiently utilize the historical state information of the intersection, we design a sequence model with the temporal convolutional network (TCN) to capture the historical information and further merge it with the spatial information to improve its performance. Extensive experiments conducted in the multi-intersection scenario on synthetic data and real-world data confirm that our method can achieve superior performance in travel time and throughput against the state-of-the-art methods.

preprint2022arXiv

Empirical distributions of the robustified $t$-test statistics

Based on the median and the median absolute deviation estimators, and the Hodges-Lehmann and Shamos estimators, robustified analogues of the conventional $t$-test statistic are proposed. The asymptotic distributions of these statistics are recently provided. However, when the sample size is small, it is not appropriate to use the asymptotic distribution of the robustified $t$-test statistics for making a statistical inference including hypothesis testing, confidence interval, p-value, etc. In this article, through extensive Monte Carlo simulations, we obtain the empirical distributions of the robustified $t$-test statistics and their quantile values. Then these quantile values can be used for making a statistical inference.

preprint2022arXiv

Experimental demonstration of phase-matching and Sagnac effect in a millimeter-scale wedged resonator gyroscope

The highly efficient coupling of light from conventional optical components to optical mode volumes lies in the heart of chip-based micro-devices, which is determined by the phase-matching between propagation constants of fiber taper and the whispering-gallery-mode (WGM) of the resonator. Optical gyroscopes, typically realized as fiber-optic gyroscopes and ring-laser gyroscopes, have been the mainstay in diverse applications such as positioning and inertial sensing. Here, the phase-matching is theoretically analyzed and experimentally verified. We observe Sagnac effect in a millimeter-scale wedged resonator gyroscope which has attracted considerable attention and been rapidly promoted in recent years. We demonstrate a bidirectional pump and probe scheme, which directly measures the frequency beat caused by the Sagnac effect. We establish the linear response between the detected beat frequency and the rotation velocity. The clockwise and counterclockwise rotation can also be distinguished according to the value of the frequency beat. The experimental results verify the feasibility of developing gyroscope in WGM resonator system and pave the way for future development.

preprint2022arXiv

FashionVQA: A Domain-Specific Visual Question Answering System

Humans apprehend the world through various sensory modalities, yet language is their predominant communication channel. Machine learning systems need to draw on the same multimodal richness to have informed discourses with humans in natural language; this is particularly true for systems specialized in visually-dense information, such as dialogue, recommendation, and search engines for clothing. To this end, we train a visual question answering (VQA) system to answer complex natural language questions about apparel in fashion photoshoot images. The key to the successful training of our VQA model is the automatic creation of a visual question-answering dataset with 168 million samples from item attributes of 207 thousand images using diverse templates. The sample generation employs a strategy that considers the difficulty of the question-answer pairs to emphasize challenging concepts. Contrary to the recent trends in using several datasets for pretraining the visual question answering models, we focused on keeping the dataset fixed while training various models from scratch to isolate the improvements from model architecture changes. We see that using the same transformer for encoding the question and decoding the answer, as in language models, achieves maximum accuracy, showing that visual language models (VLMs) make the best visual question answering systems for our dataset. The accuracy of the best model surpasses the human expert level, even when answering human-generated questions that are not confined to the template formats. Our approach for generating a large-scale multimodal domain-specific dataset provides a path for training specialized models capable of communicating in natural language. The training of such domain-expert models, e.g., our fashion VLM model, cannot rely solely on the large-scale general-purpose datasets collected from the web.

preprint2022arXiv

High sensitivity air-coupled MHz frequency ultrasound detection using on-chip microcavities

Owing to their dual-resonance enhanced sensitivity, cavity optomechanical systems provide an ideal platform for ultrasound sensing. In this work, we realize high sensitivity air-coupled ultrasound sensing from kilohertz (kHz) to megahertz (MHz) frequency range based on whispering gallery mode microcavities. Using a 57 um-diameter microtoroid with high optical Q factor (~10^7) and mechanical Q factor (~700), we achieve sensitivities of 46 uPa Hz^{-1/2}-10 mPa Hz^{-1/2} in a frequency range of 0.25-3.2 MHz. Thermal-noise-limited sensitivity is realized around the mechanical resonance at 2.56 MHz, in a frequency range of 0.6 MHz. We also observe the second- and third-order mechanical sidebands, and quantitatively study the intensities of each mechanical sideband as a function of the mechanical displacement. Measuring the combination of signal to noise ratios at all sidebands has the potential to extend the dynamic range of ultrasound sensing. In addition, to improve the ultrasound sensitivity in the kHz frequency range, we use a microdisk with a diameter of 200 um, and achieve sensitivities of 1.83 uPa Hz^{-1/2}-10.4 mPa Hz^{-1/2} in 30 kHz-1.65 MHz range.

preprint2022arXiv

High-production-rate fabrication of low-loss lithium niobate electro-optic modulators using photolithography assisted chemo-mechanical etching (PLACE)

Integrated thin-film lithium niobate (LN) electro-optic (EO) modulators of broad bandwidth, low insertion loss, low cost and high production rate are essential elements in contemporary inter-connection industries and disruptive applications. Here, we demonstrated the design and fabri-cation of a high performance thin-film LN EO modulator using photolithography assisted chemo-mechanical etching (PLACE) technology. Our device shows a 3-dB bandwidth over 50 GHz, along with a comparable low half wave voltage-length product of 2.16 Vcm. We obtain a fiber-to-fiber insertion loss of 2.6 dB.

preprint2022arXiv

Hybrid variable monitoring: An unsupervised process monitoring framework with binary and continuous variables

Traditional process monitoring methods, such as PCA, PLS, ICA, MD et al., are strongly dependent on continuous variables because most of them inevitably involve Euclidean or Mahalanobis distance. With industrial processes becoming more and more complex and integrated, binary variables also appear in monitoring variables besides continuous variables, which makes process monitoring more challenging. The aforementioned traditional approaches are incompetent to mine the information of binary variables, so that the useful information contained in them is usually discarded during the data preprocessing. To solve the problem, this paper focuses on the issue of hybrid variable monitoring (HVM) and proposes a novel unsupervised framework of process monitoring with hybrid variables including continuous and binary variables. HVM is addressed in the probabilistic framework, which can effectively exploit the process information implicit in both continuous and binary variables at the same time. In HVM, the statistics and the monitoring strategy suitable for hybrid variables with only healthy state data are defined and the physical explanation behind the framework is elaborated. In addition, the estimation of parameters required in HVM is derived in detail and the detectable condition of the proposed method is analyzed. Finally, the superiority of HVM is fully demonstrated first on a numerical simulation and then on an actual case of a thermal power plant.

preprint2022arXiv

Large discrepancy between observations and simulations: Implications for urban air quality in China

Chemical transport models (CTMs) have been widely used to provide instructions for the control of ozone (O3) pollution. However, we find large discrepancies between observation- and model-based urban O3 chemical regimes: volatile organic compound (VOC)-limited regimes over N. China and weak nitrogen oxides (NOx)-limited regimes over S. China in observations, in contrast to simulations with widespread distributions of strong NOx-limited regimes. The conflicting O3 evolutions are caused by underestimated urban NOx concentrations and the possible overestimation of biogenic VOC emissions. Reductions in NOx emissions, in response to regulations, have thus led to an unintended deterioration of O3 pollution over N. China provinces, for example, an increase in surface O3 by approximately 7 ppb over the Sichuan Basin (SCB) in 2014-2020. The NOx-induced urban O3 changes resulted in an increase in premature mortality by approximately 3000 cases in 2015-2020.

preprint2022arXiv

Minimizing Age-upon-Decisions in Bufferless System: Service Scheduling and Decision Interval

In Internet of Things (IoT), the decision timeliness of time-sensitive applications is jointly affected by the statistics of update process and decision process. This work considers an update-and-decision system with a Poisson-arrival bufferless queue, where updates are delivered and processed for making decisions with exponential or periodic intervals. We use age-upon-decisions (AuD) to characterize timeliness of updates at decision moments, and the missing probability to specify whether updates are useful for decision-making. Our theoretical analyses 1) present the average AuDs and the missing probabilities for bufferless systems with exponential or deterministic decision intervals under different service time distributions; 2) show that for service scheduling, the deterministic service time achieves a lower average AuD and a smaller missing probability than the uniformly distributed and the negative exponentially distributed service time; 3) prove that the average AuD of periodical decision system is larger than and will eventually drop to that of Poisson decision system along with the increase of decision rate; however, the missing probability in periodical decision system is smaller than that of Poisson decision system. The numerical results and simulations verify the correctness of our analyses, and demonstrate that the bufferless systems outperform the systems applying infinite buffer length.

preprint2022arXiv

Monolithically integrated active passive waveguide array fabricated on thin film lithium niobate using a single continuous photolithography process

We demonstrate a robust low-loss optical interface by tiling passive (i.e., without doping of active ions) thin film lithium niobate (TFLN) and active (i.e., doped with rare earth ions) TFLN substrates for monolithic integration of passive/active lithium niobate photonics. The tiled substrates composed of both active and passive areas allow to pattern the mask of the integrated active passive photonic device at once using a single continuous photolithography process. The interface loss of tiled substrate is measured as low as 0.26 dB. Thanks to the stability provided by this approach, a four-channel waveguide amplifier is realized in a straightforward manner, which shows a net gain of ~5 dB at 1550-nm wavelength and that of ~8 dB at 1530-nm wavelength for each channel. The robust low-loss optical interface for passive/active photonic integration will facilitate large-scale high performance photonic devices which require on-chip light sources and amplifiers.

preprint2022arXiv

Monolithically integrated waveguide-coupled single-frequency microlaser on erbium-doped thin film lithium niobate

We overcome the difficulty in realizing a monolithic waveguide-coupled microring laser integrated on erbium-doped thin film lithium niobate (Er: TFLN) using photolithography assisted chemo-mechanical etching (PLACE) technique. We demonstrate an integrated single-frequency microring laser operating around 1531 nm wavelength. The PLACE technique, enabling integrated Er: TFLN photonics with low propagation loss, can thus be used to realize low cost mass production of monolithic on-chip microlasers with applications ranging from optical communication and photonic integrated circuit (PIC) to precision metrology and large-scale sensing.

preprint2022arXiv

Neural Network Based Variational Methods for Solving Quadratic Porous Medium Equations in High Dimensions

In this paper, we propose and study neural network based methods for solutions of high-dimensional quadratic porous medium equation (QPME). Three variational formulations of this nonlinear PDE are presented: a strong formulation and two weak formulations. For the strong formulation, the solution is directly parameterized with a neural network and optimized by minimizing the PDE residual. It can be proved that the convergence of the optimization problem guarantees the convergence of the approximate solution in the $L^1$ sense. The weak formulations are derived following Brenier, Y., 2020, which characterizes the very weak solutions of QPME. Specifically speaking, the solutions are represented with intermediate functions who are parameterized with neural networks and are trained to optimize the weak formulations. Extensive numerical tests are further carried out to investigate the pros and cons of each formulation in low and high dimensions. This is an initial exploration made along the line of solving high-dimensional nonlinear PDEs with neural network based methods, which we hope can provide some useful experience for future investigations.

preprint2022arXiv

Nonlinear Reduced DNN Models for State Estimation

We propose in this paper a data driven state estimation scheme for generating nonlinear reduced models for parametric families of PDEs, directly providing data-to-state maps, represented in terms of Deep Neural Networks. A major constituent is a sensor-induced decomposition of a model-compliant Hilbert space warranting approximation in problem relevant metrics. It plays a similar role as in a Parametric Background Data Weak framework for state estimators based on Reduced Basis concepts. Extensive numerical tests shed light on several optimization strategies that are to improve robustness and performance of such estimators.

preprint2022arXiv

On-chip integrated Yb3+-doped waveguide amplifiers on thin film lithium niobate

We report the fabrication and optical characterization of Yb3+-doped waveguide amplifiers (YDWA) on the thin film lithium niobate fabricated by photolithography assisted chemo-mechanical etching. The fabricated Yb3+-doped lithium niobate waveguides demonstrates low propagation loss of 0.13 dB/cm at 1030 nm and 0.1 dB/cm at 1060 nm. The internal net gain of 5 dB at 1030 nm and 8 dB at 1060 nm are measured on a 4.0 cm long waveguide pumped by 976nm laser diodes, indicating the gain per unit length of 1.25 dB/cm at 1030 nm and 2 dB/cm at 1060 nm, respectively. The integrated Yb3+-doped lithium niobate waveguide amplifiers will benefit the development of a powerful gain platform and are expected to contribute to the high-density integration of thin film lithium niobate based photonic chip.

preprint2022arXiv

PSP: Million-level Protein Sequence Dataset for Protein Structure Prediction

Proteins are essential component of human life and their structures are important for function and mechanism analysis. Recent work has shown the potential of AI-driven methods for protein structure prediction. However, the development of new models is restricted by the lack of dataset and benchmark training procedure. To the best of our knowledge, the existing open source datasets are far less to satisfy the needs of modern protein sequence-structure related research. To solve this problem, we present the first million-level protein structure prediction dataset with high coverage and diversity, named as PSP. This dataset consists of 570k true structure sequences (10TB) and 745k complementary distillation sequences (15TB). We provide in addition the benchmark training procedure for SOTA protein structure prediction model on this dataset. We validate the utility of this dataset for training by participating CAMEO contest in which our model won the first place. We hope our PSP dataset together with the training benchmark can enable a broader community of AI/biology researchers for AI-driven protein related research.

preprint2022arXiv

Rethinking Feature Uncertainty in Stochastic Neural Networks for Adversarial Robustness

It is well-known that deep neural networks (DNNs) have shown remarkable success in many fields. However, when adding an imperceptible magnitude perturbation on the model input, the model performance might get rapid decrease. To address this issue, a randomness technique has been proposed recently, named Stochastic Neural Networks (SNNs). Specifically, SNNs inject randomness into the model to defend against unseen attacks and improve the adversarial robustness. However, existed studies on SNNs mainly focus on injecting fixed or learnable noises to model weights/activations. In this paper, we find that the existed SNNs performances are largely bottlenecked by the feature representation ability. Surprisingly, simply maximizing the variance per dimension of the feature distribution leads to a considerable boost beyond all previous methods, which we named maximize feature distribution variance stochastic neural network (MFDV-SNN). Extensive experiments on well-known white- and black-box attacks show that MFDV-SNN achieves a significant improvement over existing methods, which indicates that it is a simple but effective method to improve model robustness.

preprint2021arXiv

A note on the g and h control charts

In this note, we revisit the $g$ and $h$ control charts that are commonly used for monitoring the number of conforming cases between the two consecutive appearances of nonconformities. It is known that the process parameter of these charts is usually unknown and estimated by using the maximum likelihood estimator and the minimum variance unbiased estimator. However, the minimum variance unbiased estimator in the control charts has been inappropriately used in the quality engineering literature. This observation motivates us to provide the correct minimum variance unbiased estimator and investigate theoretical and empirical biases of these estimators under consideration. Given that these charts are developed based on the underlying assumption that samples from the process should be balanced, which is often not satisfied in many practical applications, we propose a method for constructing these charts with unbalanced samples.

preprint2021arXiv

AsymptoticNG: A regularized natural gradient optimization algorithm with look-ahead strategy

Optimizers that further adjust the scale of gradient, such as Adam, Natural Gradient (NG), etc., despite widely concerned and used by the community, are often found poor generalization performance, compared with Stochastic Gradient Descent (SGD). They tend to converge excellently at the beginning of training but are weak at the end. An immediate idea is to complement the strengths of these algorithms with SGD. However, a truncated replacement of optimizer often leads to a crash of the update pattern, and new algorithms often require many iterations to stabilize their search direction. Driven by this idea and to address this problem, we design and present a regularized natural gradient optimization algorithm with look-ahead strategy, named asymptotic natural gradient (ANG). According to the total iteration step, ANG dynamic assembles NG and Euclidean gradient, and updates parameters along the new direction using the intensity of NG. Validation experiments on CIFAR10 and CIFAR100 data sets show that ANG can update smoothly and stably at the second-order speed, and achieve better generalization performance.

preprint2021arXiv

Broadband highly efficient nonlinear optical processes in on-chip integrated lithium niobate microdisk resonators of Q-factor above 10^8

We demonstrated broadband highly efficient optical nonlinear processes in on-chip integrated lithium niobate (LN) microdisk resonators. The Q factors of the micro-resonators fabricated by femtosecond laser writing and chemo-mechanical polishing are reliably above 10^8, approaching the intrinsic material absorption limit of LN. Broadband nonlinear processes, including optical parametric oscillation (OPO), second harmonic generation (SHG), third harmonic generation, and fourth harmonic generation, were observed with ultrahigh efficiencies in the same LN microdisk without introducing domain inversion, thanks to the natural quasi phase-matching and the dense spectral modes of the X-cut LN microdisk with millimeter diameter. The threshold of OPO and the absolute conversion efficiency of SHG are 19.6 microwatt and 66%, both surpass the state-of-the-art values among on-chip LN micro-resonators demonstrated so far. The broadband and highly efficient nonlinear frequency conversions achieved with the ultrahigh-Q LN microdisk resonators promise high-density integration of nonlinear photonic devices such as frequency convertors and entangled photon sources.

preprint2021arXiv

Decimetric type U solar radio bursts and associated EUV phenomena on 2011 February 9

A GOES M1.9 flare took place in active region AR 11153 on February 9,2011. With the resolution of 200 kHz and a time cadence of 80 ms, the reverse-drifting (RS) type III bursts, intermittent sequence of type U bursts, drifting pulsation structure (DPS), and fine structures were observed by the Yunnan Observatories Solar Radio Spectrometer(YNSRS). Combined information revealed by the multi-wavelength data indicated that after the DPS which observed by YNSRS, the generation rate of type U bursts suddenly increased 5 times than before. In this event, the generation rate of type U bursts may depend on the magnetic reconnection rate. Our observations are consistent with previous numerical simulations results. After the first plasmoid produced (plasma instability occurred), the magnetic reconnection rate increased suddenly 5-8 times than before. Furthermore, after the DPS, the frequency range of turnover frequency of type U bursts is obviously broadened 3 times than before, which indicates the fluctuation amplitude of the density in the loop-top. Our observations also support the numerical simulations during the flare impulsive phase. The turbulence occurs at the top of the flare loop, the plasmoids can trap the non-thermal particles and cause the density fluctuation at the loop-top. The observations are generally consistent with the results of numerical simulations, helping us to better understand the characteristics of the whole physical process of eruption.

preprint2021arXiv

Monocular Human Pose and Shape Reconstruction using Part Differentiable Rendering

Superior human pose and shape reconstruction from monocular images depends on removing the ambiguities caused by occlusions and shape variance. Recent works succeed in regression-based methods which estimate parametric models directly through a deep neural network supervised by 3D ground truth. However, 3D ground truth is neither in abundance nor can efficiently be obtained. In this paper, we introduce body part segmentation as critical supervision. Part segmentation not only indicates the shape of each body part but helps to infer the occlusions among parts as well. To improve the reconstruction with part segmentation, we propose a part-level differentiable renderer that enables part-based models to be supervised by part segmentation in neural networks or optimization loops. We also introduce a general parametric model engaged in the rendering pipeline as an intermediate representation between skeletons and detailed shapes, which consists of primitive geometries for better interpretability. The proposed approach combines parameter regression, body model optimization, and detailed model registration altogether. Experimental results demonstrate that the proposed method achieves balanced evaluation on pose and shape, and outperforms the state-of-the-art approaches on Human3.6M, UP-3D and LSP datasets.

preprint2021arXiv

On-chip integrated waveguide amplifiers on Erbium-doped thin film lithium niobate on insulator

We demonstrate on-chip light amplification with integrated optical waveguide fabricated on erbium-doped thin film lithium niobate on insulator (TFLNOI) using the photolithography assisted chemo-mechanical etching (PLACE) technique. A maximum internal net gain of 18 dB in the small-signal-gain regime is measured at the peak emission wavelength of 1530 nm for a waveguide length of 3.6 cm, indicating a differential gain per unit length of 5 dB/cm. This work paves the way to the monolithic integration of diverse active and passive photonic components on the TFLNOI platform.

preprint2021arXiv

Protein corona critically affects the bio-behaviors of SARS-CoV-2

The outbreak of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a worldwide public health crisis. When the SARS-CoV-2 enters the biological fluids in the human body, different types of biomolecules (in particular proteins) may adsorb on its surface and alter its infection ability. Although great efforts have recently been devoted to the interaction of the specific antibodies with the SARS-CoV-2, it still remains largely unknown how the other serum proteins affect the infection of the SARS-CoV-2. In this work, we systematically investigate the interaction of serum proteins with the SARS-CoV-2 RBD by the molecular docking and the all-atom molecular dynamics simulations. It is found that the non-specific immunoglobulin (Ig) indeed cannot effectively bind to the SARS-CoV-2 RBD while the human serum albumin (HSA) may have some potential of blocking its infection (to ACE2). More importantly, we find that the RBD can cause the significant structural change of the Apolipoprotein E (ApoE), by which SARS-CoV-2 may hijack the metabolic pathway of the ApoE to facilitate its cell entry. The present study enhances the understanding of the role of protein corona in the bio-behaviors of SARS-CoV-2, which may aid the more precise and personalized treatment for COVID-19 infection in the clinic.

preprint2021arXiv

Tunable partial polarization beam splitter and optomechanically induced Faraday effect

Polarization beam splitter (PBS) is a crucial photonic element to separately extract transverse-electric (TE) and transverse-magnetic (TM) polarizations from the propagating light fields. Here, we propose a concise, continuously tunable and all-optical partial PBS in the vector optomechanical system which contains two orthogonal polarized cavity modes with degenerate frequency. The results show that one can manipulate the polarization states of different output fields by tuning the polarization angle of the pumping field and the system function as partial PBS when the pump laser polarizes vertically or horizontally. As a significant application of the tunable PBS, we propose a scheme of implementing quantum walks in resonator arrays without the aid of other auxiliary systems. Furthermore, we investigate the optomechanically induced Faraday effect in the vector optomechanical system which enables arbitrary tailoring of the input lights and the behaviors of polarization angles of the output fields in the under couple, critical couple, and over couple regimes. Our findings prove the optomechanical system is a potential platform to manipulate the polarization states in multimode resonators and boost the process of applications related to polarization modulation.

preprint2020arXiv

A second order accurate scalar auxiliary variable (SAV) numerical method for the square phase field crystal equation

In this paper we propose and analyze a second order accurate (in time) numerical scheme for the square phase field crystal (SPFC) equation, a gradient flow modeling crystal dynamics at the atomic scale in space but on diffusive scales in time. Its primary difference with the standard phase field crystal model is an introduction of the 4-Laplacian term in the free energy potential, which in turn leads to a much higher degree of nonlinearity. To make the numerical scheme linear while preserving the nonlinear energy stability, we make use of the scalar auxiliary variable (SAV) approach, in which a second order backward differentiation formula (BDF) is applied in the temporal stencil. Meanwhile, a direct application of the SAV method faces certain difficulties, due to the involvement of the 4-Laplacian term, combined with a derivation of the lower bound of the nonlinear energy functional. In the proposed numerical method, an appropriate decomposition for the physical energy functional is formulated, so that the nonlinear energy part has a well-established global lower bound, and the rest terms lead to constant-coefficient diffusion terms with positive eigenvalues. In turn, the numerical scheme could be very efficiently implemented by constant-coefficient Poisson-like type solvers (via FFT), and energy stability is established by introducing an auxiliary variable, and an optimal rate convergence analysis is provided for the proposed SAV method. A few numerical experiments are also presented, which confirm the efficiency and accuracy of the proposed scheme.

preprint2020arXiv

Efficient light coupling between an ultra-low loss lithium niobate waveguide and an adiabatically tapered single mode optical fiber

A lithium niobate on insulator ridge waveguide allows constructing high-density photonic integrated circuits thanks to its small bending radius offered by the high index contrast. Meanwhile, the significant mode-field mismatch between an optical fiber and the single-mode lithium niobate waveguide leads to low coupling efficiencies. Here, we demonstrate, both numerically and experimentally, that the problem can be solved with a tapered single mode fiber of an optimized mode field profile. Numerical simulation shows that the minimum coupling losses for the TE and TM mode are 0.32 dB and 0.86 dB, respectively. Experimentally, though without anti-reflection coating, the measured coupling losses for TE and TM mode are 1.32 dB and 1.88 dB, respectively. Our technique paves a way for a broad range of on-chip lithium niobate applications.

preprint2020arXiv

Field-free Deterministic Magnetization Switching Induced by Interlaced Spin-Orbit Torques

Spin-orbit torque (SOT) based magnetic random access memory (MRAM) is envisioned as an emerging non-volatile memory due to its ultra-high speed and low power consumption. The field-free switching schema in SOT devices is of great interest to both academia and industry. Here we propose a novel field-free deterministic magnetization switching in a regular magnetic tunnel junction (MTJ) by using two currents sequentially passing interlaced paths, with less requirements of manufacturing process or additional physical effects. The switching is bipolar since the final magnetization state depends on the combination of current paths. The functionality and robustness of the proposed schema is validated through both macrospin and micromagnetic simulation. The influences of field-like torque and Dzyaloshinskii-Moriya interaction (DMI) effect are further researched. Our proposed schema shows good scalability and is expected to realize novel digital logic and even computing-in-memory platform.

preprint2020arXiv

Health Assessment and Prognostics Based on Higher Order Hidden Semi-Markov Models

This paper presents a new and flexible prognostics framework based on a higher order hidden semi-Markov model (HOHSMM) for systems or components with unobservable health states and complex transition dynamics. The HOHSMM extends the basic hidden Markov model (HMM) by allowing the hidden state to depend on its more distant history and assuming generally distributed state duration. An effective Gibbs sampling algorithm is designed for statistical inference of an HOHSMM. The performance of the proposed HOHSMM sampler is evaluated by conducting a simulation experiment. We further design a decoding algorithm to estimate the hidden health states using the learned model. Remaining useful life (RUL) is predicted using a simulation approach given the decoded hidden states. The practical utility of the proposed prognostics framework is demonstrated by a case study on NASA turbofan engines. The results show that the HOHSMM-based prognostics framework provides good hidden health state assessment and RUL estimation for complex systems.

preprint2020arXiv

High-index-contrast single-mode optical waveguides fabricated on lithium niobate by photolithography assisted chemo-mechanical etching (PLACE)

We report fabrication of low loss single mode waveguides on lithium niobate on insulator (LNOI) cladded by a layer of SiO2. Our technique, termed photolithography assisted chemo-mechanical etching (PLACE), relies on patterning of a chromium film into the mask shape by femtosecond laser micromachining and subsequent chemo-mechanical etching of the lithium niobate thin film. The high-index-contrast single mode waveguide is measured to have a propagation loss of 0.13 dB/cm. Furthermore, waveguide tapers are fabricated for boosting the coupling efficiency.

preprint2020arXiv

Investigation of finite-sample properties of robust location and scale estimators

When the experimental data set is contaminated, we usually employ robust alternatives to common location and scale estimators such as the sample median and Hodges-Lehmann estimators for location and the sample median absolute deviation and Shamos estimators for scale. It is well known that these estimators have high positive asymptotic breakdown points and are Fisher-consistent as the sample size tends to infinity. To the best of our knowledge, the finite-sample properties of these estimators, depending on the sample size, have not well been studied in the literature. In this paper, we fill this gap by providing their closed-form finite-sample breakdown points and calculating the unbiasing factors and relative efficiencies of the robust estimators through the extensive Monte Carlo simulations up to the sample size 100. The numerical study shows that the unbiasing factor improves the finite-sample performance significantly. In addition, we provide the predicted values for the unbiasing factors obtained by using the least squares method which can be used for the case of sample size more than 100.

preprint2020arXiv

Local Molecular Gas toward the Aquila Rift Region

We present the results of a ~250 square degrees CO mapping (+26d<l<+50d and -5d<b<+5d) toward the Aquila Rift region at a spatial resolution of ~50" and a grid spacing of 30". The high dynamic range CO maps with a spectral resolution of ~0.2km/s display highly structured molecular cloud (MC) morphologies with valuable velocity information, revealing complex spatial and dynamical features of the local molecular gas. In combination with the MWISP CO data and the Gaia DR2, distances of the main MC structures in the local ISM are well determined toward the Aquila Rift. We find that the total MC mass within 1 kpc is about >4.1x10^5 Msun in the whole region. In fact, the mass of the molecular gas is dominated by the W40 giant molecular cloud (GMC) at ~474 pc (~1.4x10^5 Msun) and the GMC complex G036.0+01.0 at ~560-670 pc (~2.0x10^5 Msun), while the MCs at ~220-260pc have gas masses of 10^2-10^3 Msun. Interestingly, an ~80pc long filamentary MC G044.0-02.5 at a distance of ~404 pc shows a systematic velocity gradient along and perpendicular to the major axis of the filament. The HI gas with the enhanced emission has the similar spatial morphologies and velocity features compared to the corresponding CO structure, indicating that the large-scale converging HI flows are probably responsible for the formation of the MC. Meanwhile, the long filamentary MC consists of many sub-filaments with the lengths ranging from ~0.5 pc to several pc, as well as prevalent networks of filaments in other large-scale local MCs.

preprint2020arXiv

Theoretical Conditions for Field-free Magnetization Switching Induced by Spin-orbit Torque and Dzyaloshinskii-Moriya Interaction

Recently, it was demonstrated that field-free switching could be achieved by combining spin-orbit torque (SOT) and Dzyaloshinskii-Moriya interaction (DMI). However, this mechanism only occurs under certain conditions which have not been well discussed. In this letter, it is found that the ratio of domain wall width to diameter of nanodots could be utilized as a criteria for judging this mechanism. Influences of different magnetic parameters are studied, including exchange constant, DMI magnitude and field-like toque, etc. Besides, we reveal the importance of the shrinkage of magnetic domain wall surface energy for metastable states. Our work provides guidelines to the experiments on the DMI-induced field-free magnetization switching, and also offers a new way for the design of SOT-based memory or logic circuits.

preprint2019arXiv

A compact and efficient three-dimensional microfluidic mixer

Microfluidic mixing is a fundamental functionality in most lab on a chip (LOC) systems,whereas realization of efficient mixing is challenging in microfluidic channels due to the small Reynolds numbers. Here, we design and fabricate a compact three-dimensional (3D) micromixer to enable efficient mixing at various flow rates. The performance of the fabricated micromixer was examined using blue and red inks. The extreme flexibility in fabricating microfluidic structures of arbitrary 3D geometries using femtosecond laser micromachining allows us to tackle the major disadvantageous effects for optimizing the mixing efficiency.

preprint2019arXiv

Efficient Electro-optical Tuning of Optical Frequency Microcomb on a Monolithically Integrated High-Q Lithium Niobate Microdisk

We demonstrate efficient tuning of a monolithically integrated lithium niobate microdisk (LN) optical frequency microcomb. Utilizing the high optical quality (Q) factor (i.e., Q~7.1*10^6) of the microdisk, the microcomb spans over a spectral bandwidth of ~200 nm at a pump power as low as 20.4 mW. Combining the large eletro-optic coefficient of LN and optimum design of the geometry of microelectrodes, we demonstrate electro-optical tuning of the comb with a spectral range of 400 pm and a tuning efficiency of ~38 pm/100V.

preprint2019arXiv

Manipulation of optomechanically induced transparency and absorption by indirectly coupling to an auxiliary cavity mode

We theoretically study the optomechanically induced transparency (OMIT) and absorption(OMIA) phenomena in a single microcavity optomechanical system, assisted by an indirectly-coupledauxiliary cavity mode. We show that the interference effect between the two optical modes playsan important role and can be used to control the multiple-pathway induced destructive or construc-tive interference effect. The three-pathway interference could induce an absorption dip within thetransparent window in the red sideband driving regime, while we can switch back and forth betweenOMIT and OMIA with the four-pathway interference. The conversion between the transparencypeak and absorption dip can be achieved by tuning the relative amplitude and phase of the multiplelight paths interference. Our system proposes a new platform to realize multiple pathways inducedtransparency and absorption in a single microcavity and a feasible way for realizing all-opticalinformation processing.

preprint2016arXiv

Broadband angle- and permittivity-insensitive nondispersive optical activity based on chiral metamaterials

Because of the strong inherent resonances, the giant optical activity obtained via chiral metamaterials generally suffers from high dispersion, which has been a big stumbling block to broadband applications. In this paper, we propose a type of chiral metamaterial consisting of interconnected metal helix structures with four-fold symmetry, which exhibits nonresonant Drude-like response and can therefore avoid the highly dispersive optical activity resulting from resonances. It shows that the well-designed chiral metamaterial can achieve nondispersive and pure optical activity with high transmittance in a broadband frequency range. And the optical activity of multi-layer chiral metamaterials is proportional to the layer numbers of single-layer chiral metamaterial. Most remarkably, the broadband behaviors of nondispersive optical activity and high transmission are insensitive to the incident angles of electromagnetic waves and permittivity of dielectric substrate, thereby enabling more flexibility in polarization manipulation.

preprint2016arXiv

Consistency of Bayes factor for nonnested model selection when the model dimension grows

Zellner's $g$-prior is a popular prior choice for the model selection problems in the context of normal regression models. Wang and Sun [J. Statist. Plann. Inference 147 (2014) 95-105] recently adopt this prior and put a special hyper-prior for $g$, which results in a closed-form expression of Bayes factor for nested linear model comparisons. They have shown that under very general conditions, the Bayes factor is consistent when two competing models are of order $O(n^τ)$ for $τ<1$ and for $τ=1$ is almost consistent except a small inconsistency region around the null hypothesis. In this paper, we study Bayes factor consistency for nonnested linear models with a growing number of parameters. Some of the proposed results generalize the ones of the Bayes factor for the case of nested linear models. Specifically, we compare the asymptotic behaviors between the proposed Bayes factor and the intrinsic Bayes factor in the literature.

preprint2016arXiv

Features and stability analysis of non-Schwarzschild black hole in quadratic gravity

Black holes are found to exist in gravitational theories with the presence of quadratic curvature terms and behave differently from the Schwarzschild solution. We present an exhaustive analysis for determining the quasinormal modes of a test scalar field propagating in a new class of black hole backgrounds in the case of pure Einstein-Weyl gravity. Our result shows that the field decay of quasinormal modes in such a non-Schwarzschild black hole behaves similarly to the Schwarzschild one, but the decay slope becomes much smoother due to the appearance of the Weyl tensor square in the background theory. We also analyze the frequencies of the quasinormal modes in order to characterize the properties of new back holes, and thus, if these modes can be the source of gravitational waves, the underlying theories may be testable in future gravitational wave experiments. We briefly comment on the issue of quantum (in)stability in this theory at linear order.

preprint2016arXiv

Multi-frequency Radio Profiles of PSR B1133+16: radiation location and particle energy

The pulse profile of PSR B1133+16 is usually regarded as a conal-double structure. However, its multifrequency profiles cannot simply be fitted with two Gaussian functions, and a third component is always needed to fit the bridge region (between two peaks). This would introduce additional, redundant parameters. In this paper, through a comparison of five fitting functions (Gaussian, von Mises, hyperbolic secant, square hyperbolic secant, and Lorentz), it is found that the square hyperbolic secant function can best reproduce the profile, yielding an improved fit. Moreover, a symmetric 2D radiation beam function, instead of a simple 1D Gaussian function, is used to fit the profile. Each profile with either well-resolved or not-so-well-resolved peaks could be fitted adequately using this beam function, and the bridge emission between the two peaks does not need to be a new component. Adopting inclination and impact angles based on polarization measurements, the opening angle (θ_μ0) of the radiation beam in a certain frequency band is derived from beam-function fitting. The corresponding radiation altitudes are then calculated. Based on multi-frequency profiles, we also computed the Lorentz factors of the particles and their dispersion at those locations in both the curvature-radiation (CR) and inverse-Compton-scattering (ICS) models. We found that the Lorentz factors of the particles decrease rapidly as the radiation altitude increases. Besides, the radiation prefers to be generated in annular region rather than core region, and this needs further validation.

preprint2016arXiv

The Broken Lane of a Type II Radio Burst Caused by Collision of a Coronal Shock with a Flare Current Sheet

We investigated a peculiar metric type II solar radio burst with a broken lane structure, which was observed on November 13, 2012. In addition to the radio data, we also studied the data in the other wavelengths. The bursts were associated with two CMEs and two flares that originated from active region AR 11613. A long current sheet was developed in the first CME, and the second CME collided with the current sheet first and then merged with the first one. Combing information revealed by the multi-wavelength data indicated that a coronal shock accounting for the type II radio burst, and that the collision of this shock with the current sheet resulted in the broken lane of the type II radio burst. The type II burst lane resumed after the shock passed through the current sheet. We further estimated the thickness of the current sheet according to the gap on the lane of the type II burst, and found that the result is consistent with previous ones obtained for various events observed in different wavelengths by different instruments. In addition, the regular type II burst associated with the first CME/flare was also studied, and the magnetic field in each source region of the two type II bursts was further deduced in different way.

preprint2015arXiv

A deep near-infrared survey toward the Aquila molecular cloud - I. Molecular hydrogen outflows

We have performed an unbiased deep near-infrared survey toward the Aquila molecular cloud with a sky coverage of ~1 deg2. We identified 45 molecular hydrogen emission-line objects(MHOs), of which only 11 were previously known. Using the Spitzer archival data we also identified 802 young stellar objects (YSOs) in this region. Based on the morphology and the location of MHOs and YSO candidates, we associate 43 MHOs with 40 YSO candidates. The distribution of jet length shows an exponential decrease in the number of outflows with increasing length and the molecular hydrogen outflows seem to be oriented randomly. Moreover, there is no obvious correlation between jet lengths, jet opening angles, or jet H2 1-0 S(1) luminosities and spectral indices of the possible driving sources in this region. We also suggest that molecular hydrogen outflows in the Aquila molecular cloud are rather weak sources of turbulence, unlikely to generate the observed velocity dispersion in the region of survey.

preprint2015arXiv

A simple two-sample Bayesian t-test for hypothesis testing

In this paper, we propose an explicit closed-form Bayes factor for the problem of two-sample hypothesis testing. The proposed approach can be regarded as a Bayesian version of the pooled-variance t-statistic and has various appealing properties in practical applications. It relies on data only through the t-statistic and can thus be calculated by using an Excel spreadsheet or a pocket calculator. It avoids several undesirable paradoxes, which may be encountered by the previous Bayesian approach of Gonen et al. (2005). Specifically, the proposed approach can be easily taught in an introductory statistics course with an emphasis on Bayesian thinking. Simulated and real data examples are provided for illustrative purposes.

preprint2015arXiv

On the number of representations of n as a linear combination of four triangular numbers

Let $\Bbb Z$ and $\Bbb N$ be the set of integers and the set of positive integers, respectively. For $a,b,c,d,n\in\Bbb N$ let $t(a,b,c,d;n)$ be the number of representations of $n$ by $ax(x-1)/2+by(y-1)/2+cz(z-1)/2 +dw(w-1)/2$ $(x,y,z,w\in\Bbb Z$). In this paper we obtain explicit formulas for $t(a,b,c,d;n)$ in the cases $(a,b,c,d)=(1,2,2,4),\ (1,2,4,4),\ (1,1,4,4),\ (1,4,4,4)$, $(1,3,9,9),\ (1,1,3,9)$, $(1,3,3,9)$, $(1,1,9,9),\ (1,9,9,9)$ and $(1,1,1,9).$

preprint2015arXiv

On the number of representations of n as a linear combination of four triangular numbers II

Let $\Bbb Z$ and $\Bbb N$ be the set of integers and the set of positive integers, respectively. For $a,b,c,d,n\in\Bbb N$ let $N(a,b,c,d;n)$ be the number of representations of $n$ by $ax^2+by^2+cz^2+dw^2$, and let $t(a,b,c,d;n)$ be the number of representations of $n$ by $ax(x-1)/2+by(y-1)/2+cz(z-1)/2 +dw(w-1)/2$ $(x,y,z,w\in\Bbb Z$). In this paper we reveal the connections between $t(a,b,c,d;n)$ and $N(a,b,c,d;n)$. Suppose $a,n\in\Bbb N$ and $2\nmid a$. We show that $$t(a,b,c,d;n)=\frac 23N(a,b,c,d;8n+a+b+c+d)-2N(a,b,c,d;2n+(a+b+c+d)/4)$$ for $(a,b,c,d)= (a,a,2a,8m),\ (a,3a,8k+2,8m+6),\ (a,3a,8m+4,8m+4)\ (n\equiv m+\frac{a-1}2 \pmod 2)$ and $(a,3a,16k+4,16m+4)\ (n\equiv \frac{a-1}2\pmod 2)$. We also obtain explicit formulas for $t(a,b,c,d;n)$ in the cases $(a,b,c,d)=(1,1,2,8),\ (1,1,2,16),(1,2,3,6),\ (1,3,4,12),\ (1,1,$ $3,4),\ (1,1,5,5),\ (1,5,5,5),\ (1,3,3,12),\ (1,1,1,12),\ (1,1,3,12)$ and $(1,3,3,4)$.

preprint2015arXiv

Phase matched second harmonic generation in an on-chip lithium niobate microresonator fabricated by femtosecond laser

Nonlinear optical processes in whispering gallery mode (WGM) microresonators have attracted much attention. Owing to the strong confinement of light in a small volume, a WGM microresonator can dramatically boost the strength of light field, thereby promoting the nonlinear interaction between the light and the resonator material. However, realization of efficient nonlinear parametric process in microresonators is a challenging issue. The major difficulty is to simultaneously ensure the phase matching condition and a coherent multiple resonance condition for all the waves participating in the nonlinear conversion process. Here, we demonstrate highly efficient second harmonic generation (SHG) in an on-chip lithium niobate microresonator fabricated by femtosecond laser direct writing. We overcome the difficulty of double resonance for the phase matched pump and second harmonic waves by selectively exciting high order modes in the fabricated thin-disk microresonator. Our technique opens opportunities for integrated classical and quantum photonic applications.

preprint2015arXiv

The East-Asian VLBI Network

The East-Asian VLBI Network (EAVN) is the international VLBI facility in East Asia and is conducted in collaboration with China, Japan, and Korea. The EAVN consists of VLBI arrays operated in each East Asian country, containing 21 radio telescopes and three correlators. The EAVN will be mainly operated at 6.7 (C-band), 8 (X-band), 22 (K-band), and 43 GHz (Q-band), although the EAVN has an ability to conduct observations at 1.6 - 129 GHz. We have conducted fringe test observations eight times to date at 8 and 22 GHz and fringes have been successfully detected at both frequencies. We have also conducted science commissioning observations of 6.7 GHz methanol masers in massive star-forming regions. The EAVN will be operational from the second half of 2017, providing complementary results with the FAST on AGNs, massive star-forming regions, and evolved stars with high angular resolution at cm- to mm-wavelengths.

preprint2014arXiv

A brief introduction to giant magnetoresistance

Giant magnetoresistance (GMR) is a quantum mechanical magnetoresistance effect observed in thin film structures composed of alternating ferromagnetic and nonmagnetic layers. The effect manifests itself as a significant decrease (typically 10-80%) in electrical resistance in the presence of a magnetic field. The effect is exploited commercially by manufacturers of hard disk drives. The 2007 Nobel Prize in physics was awarded to Albert Fert and Peter Grunberg for the discovery of GMR.

preprint2014arXiv

On Transition Metal Catalyzed Reduction of N-nitrosodimethlamine

This report provides a critical review on "Metal-Catalyzed Reduction of N-Nitrosodimethylamine with Hydrogen in Water", by Davie et al. N-nitrosodimethlamine (NDMA) is a contaminant in drinking and ground water which is difficult to remove by conventional physical methods, such as air stripping. Based on the reported robust capability of metal based powder shaped catalysts in hydrogen reduction, several monometallic and bimetallic catalyst are studied in this paper on the reduction of NDMA with hydrogen. Two kinds of kinetics, metal weight normalized and surface area normalized, are compared between each catalyst in terms of pseudo-first order reaction rate. Palladium, copper enhanced palladium and nickel are found to be very efficient in NDMA reduction, with half-lives on the order of hours per 10 mg/l catalyst metal. Preliminary LC-MS data and carbon balance showed no intermediates. Finally, a simple hydrogen and NMDA surface activated reaction mechanism is proposed by the author for palladium and nickel.

preprint2014arXiv

On-chip tuning of the resonant wavelength in a high-Q microresonator integrated with a microheater

We report on fabrication of a microtoroid resonator of high-quality (high-Q) factor integrated with an on-chip microheater. Both the microresonator and microheater are fabricated using femtosecond laser three-dimensional (3D) micromachining. The microheater, which is located about 200 micron away from the microresonator, has a footprint size of 200 micron by 400 micron. Tuning of the resonant wavelength in the microresonator has been achieved by varying the voltage applied on the microheater. The drifting of the resonant wavelength shows a linear dependence on the square of the voltage applied on the microheater. We found that the response time of the microresonator is less than 10 secs which is significantly shorter than the time required for reaching a thermal equilibrium on conventional heating instruments such as an external electric heater.

preprint2013arXiv

A new three-parameter lifetime distribution and associated inference

In this paper, a new three-parameter lifetime distribution is introduced and many of its standard properties are discussed. These include shape of the probability density function, hazard rate function and its shape, quantile function, limiting distributions of order statistics, and the moments. The unknown parameters are estimated by the maximum likelihood estimation procedure. We develop an EM algorithm to find the maximum likelihood estimates of the parameters, because they are not available in closed form. The Fisher information matrix is also obtained and it can be used for constructing the asymptotic confidence intervals. Finally, a real-data application is given to demonstrate the performance of the new distribution.

preprint2013arXiv

Bayes Factor Consistency for One-way Random Effects Model

In this paper, we consider Bayesian hypothesis testing for the balanced one-way random effects model. A special choice of the prior formulation for the ratio of variance components is shown to yield an explicit closed-form Bayes factor without integral representation. Furthermore, we study the consistency issue of the resulting Bayes factor under three asymptotic scenarios: either the number of units goes to infinity, the number of observations per unit goes to infinity, or both go to infinity. Finally, the behavior of the proposed approach is illustrated by simulation studies.

preprint2012arXiv

Bayes Factor Consistency for Unbalanced ANOVA Models

In practical situations, most experimental designs often yield unbalanced data which have different numbers of observations per unit because of cost constraints, or missing data, etc. In this paper, we consider the Bayesian approach to hypothesis testing or model selection under the one-way unbalanced fixed-effects ANOVA model. We adopt Zellner's g-prior with the beta-prime distribution for g, which results in an explicit closed-form expression of the Bayes factor without integral representation. Furthermore, we investigate the model selection consistency of the Bayes factor under three different asymptotic scenarios: either the number of units goes to infinity, the number of observations per unit goes to infinity, or both go to infinity. The results presented extend some existing ones of the Bayes factor for the balanced ANOVA models in the literature.

preprint2012arXiv

Efficient Multi-way Theta-Join Processing Using MapReduce

Multi-way Theta-join queries are powerful in describing complex relations and therefore widely employed in real practices. However, existing solutions from traditional distributed and parallel databases for multi-way Theta-join queries cannot be easily extended to fit a shared-nothing distributed computing paradigm, which is proven to be able to support OLAP applications over immense data volumes. In this work, we study the problem of efficient processing of multi-way Theta-join queries using MapReduce from a cost-effective perspective. Although there have been some works using the (key,value) pair-based programming model to support join operations, efficient processing of multi-way Theta-join queries has never been fully explored. The substantial challenge lies in, given a number of processing units (that can run Map or Reduce tasks), mapping a multi-way Theta-join query to a number of MapReduce jobs and having them executed in a well scheduled sequence, such that the total processing time span is minimized. Our solution mainly includes two parts: 1) cost metrics for both single MapReduce job and a number of MapReduce jobs executed in a certain order; 2) the efficient execution of a chain-typed Theta-join with only one MapReduce job. Comparing with the query evaluation strategy proposed in [23] and the widely adopted Pig Latin and Hive SQL solutions, our method achieves significant improvement of the join processing efficiency.

preprint2012arXiv

Type IIn Supernova SN 2010jl: Optical Observations for Over 500 Days After Explosion

We present extensive optical observations of a Type IIn supernova (SN) 2010jl for the first 1.5 years after the discovery. The UBVRI light curves demonstrated an interesting two-stage evolution during the nebular phase, which almost flatten out after about 90 days from the optical maximum. SN 2010jl has one of the highest intrinsic H_alpha luminosity ever recorded for a SN IIn, especially at late phase, suggesting a strong interaction of SN ejecta with the dense circumstellar material (CSM) ejected by the progenitor. This is also indicated by the remarkably strong Balmer lines persisting in the optical spectra. One interesting spectral evolution about SN 2010jl is the appearance of asymmetry of the Balmer lines. These lines can be well decomposed into a narrow component and an intermediate-width component. The intermediate-width component showed a steady increase in both strength and blueshift with time until t ~ 400 days after maximum, but it became less blueshifted at t ~ 500 days when the line profile appeared relatively symmetric again. Owing to that a pure reddening effect will lead to a sudden decline of the light curves and a progressive blueshift of the spectral lines, we therefore propose that the asymmetric profiles of H lines seen in SN 2010jl is unlikely due to the extinction by newly formed dust inside the ejecta, contrary to the explanation by some early studies. Based on a simple CSM-interaction model, we speculate that the progenitor of SN 2010jl may suffer a gigantic mass loss (~ 30-50 M_sun) in a few decades before explosion. Considering a slow moving stellar wind (e.g., ~ 28 km/s) inferred for the preexisting, dense CSM shell and the extremely high mass-loss rate (1-2 M_sun per yr), we suggest that the progenitor of SN 2010jl might have experienced a red supergiant stage and explode finally as a post-red supergiant star with an initial mass above 30-40 M_sun.

preprint2011arXiv

gSketch: On Query Estimation in Graph Streams

Many dynamic applications are built upon large network infrastructures, such as social networks, communication networks, biological networks and the Web. Such applications create data that can be naturally modeled as graph streams, in which edges of the underlying graph are received and updated sequentially in a form of a stream. It is often necessary and important to summarize the behavior of graph streams in order to enable effective query processing. However, the sheer size and dynamic nature of graph streams present an enormous challenge to existing graph management techniques. In this paper, we propose a new graph sketch method, gSketch, which combines well studied synopses for traditional data streams with a sketch partitioning technique, to estimate and optimize the responses to basic queries on graph streams. We consider two different scenarios for query estimation: (1) A graph stream sample is available; (2) Both a graph stream sample and a query workload sample are available. Algorithms for different scenarios are designed respectively by partitioning a global sketch to a group of localized sketches in order to optimize the query estimation accuracy. We perform extensive experimental studies on both real and synthetic data sets and demonstrate the power and robustness of gSketch in comparison with the state-of-the-art global sketch method.

preprint2011arXiv

Multiferroic PbFe12O19 Ceramics

PbFe12O19 (PFO) powders in hexagonal structure have been synthesized by sol-gel process using lead acetate, glycerin and ferric acetylacetonate as the precursor. PbFe12O19 ceramics were obtained by sintering the PbFe12O19 powders at 1000\degree C for 1 hour. Distorted flaky hexahedron grains are frequently observed in the SEM images of sintered PbFe12O19 ceramics. Large spontaneous polarization was observed in PbFe12O19 ceramic at room temperature, exhibiting a clear ferroelectric hysteresis loop. The remnant polarization of PbFe12O19 ceramic is estimated to be Pr~21μC/cm2. The distortion of hexahedron grains as well as the Fe oxygen octahedron in its perovskite-like hexagonal unit cell is proposed to be the origin of polarization in PbFe12O19 ceramics. Meanwhile, PbFe12O19 ceramics demonstrate strong ferromagnetism at room temperature. Simultaneous occurrence of large ferroelectricity and strong ferromagnetism in PbFe12O19 ceramics holds promise for its application in new generation of electronic devices as a practical multiferroic candidate in single phase.

preprint2011arXiv

VLBI observations of 10 CSO candidates: expansion velocities of hot spots

Observations of ten Compact Symmetric Objects ({\rm CSO}) candidates have been made with the Very Long Baseline Array at 8.4 GHz in 2005 and with a combined Chinese and European VLBI array at 8.4 GHz in 2009. The 2009 observations incorporate for the first time the two new Chinese telescopes at Miyun and Kunming for international astrophysical observations. The observational data, in combination with archival VLBA data from previous epochs, have been used to derive the proper motions of the VLBI components. Because of the long time baseline of $\sim$16 years of the VLBI data sets, the expansion velocities of the hot spots can be measured at an accuracy as high as $\sim$1.3 $μ$as yr$^{-1}$. Six of the ten sources are identified as CSOs with a typical double or triple morphology on the basis of both spectral index maps and their mirror-symmetry of proper motions of the terminal hot spots. The compact double source J1324+4048 is also identified as a CSO candidate. Among the three remaining sources, J1756+5748 and J2312+3847 are identified as core-jet sources with proper motions of their jet components relating to systemic source expansion. The third source J0017+5312 is likely also a core-jet source, but a robust detection of a core is needed for an unambiguous identification. The kinematic ages of the CSOs derived from proper motions range from 300 to 2500 years. The kinematic age distribution of the CSOs confirm an overabundance of compact young CSOs with ages less than 500 years. CSOs with known kinematic ages may be used to study the dynamical evolution of extragalactic radio sources at early stages.

preprint2009arXiv

Classification of Extremely Red Objects in the COSMOS Field

We present a study of the classification of z ~1 extremely red objects (EROs), using a combination of HST/ACS, Spitzer/IRAC, and ground-based images of the COSMOS field. Our sample includes about 5300 EROs with i-Ks>2.45 (AB, equivalently I-Ks=4 in Vega) and Ks<=21.1 (AB). For EROs in our sample, we compute, using the ACS F814W images, their concentration, asymmetry, as well as their Gini coefficient and the second moment of the brightest 20% of their light. Using those morphology parameters and the Spitzer/IRAC [3.6]-[8.0] color, the spectral energy distribution (SED) fitting method, we classify EROs into two classes: old galaxies (OGs) and young, dusty starburst galaxies (DGs). We found that the fraction of OGs and DGs in our sample is similar, about 48 percentages of EROs in our sample are OGs, and 52 percentages of them are DGs. To reduce the redundancy of these three different classification methods, we performed a principal component analysis on the measurements of EROs, and find that morphology parameters and SEDs are efficient in segregating OGs and DGs. The [3.6]-[8.0] color, which depends on reddening, redshift, and photometric accuracy, is difficult to separate EROs around the discriminating line between starburst and elliptical. We investigate the dependence of the fraction of EROs on their observational properties, and the results suggest that DGs become increasingly important at fainter magnitudes, redder colors, and higher redshifts.

preprint2008arXiv

The Molecular Ridge Close to 30 Doradus in the Large Magellanic Cloud

With the ATNF Mopra telescope we are performing a survey in the 12CO(1-0) line to map the molecular gas in the Large Magellanic Cloud (LMC). For some regions we also obtained interferometric maps of the high density gas tracers HCO+ and HCN with the Australia Telescope Compact Array (ATCA). Here we discuss the properties of the elongated molecular complex that stretches about 2 kpc southward from 30 Doradus. Our data suggests that the complex, which we refer to as the ``molecular ridge,'' is not a coherent feature but consists of many smaller clumps that share the same formation history. Likely molecular cloud formation triggers are shocks and shearing forces that are present in the surrounding south-eastern HI overdensity region, a region influenced by strong ram pressure and tidal forces. The molecular ridge is at the western edge of the the overdensity region where a bifurcated velocity structure transitions into a single disk velocity component. We find that the 12CO(1-0) and HI emission peaks in the molecular ridge are typically near each other but never coincide. A likely explanation is the conversion of warmer, low-opacity HI to colder, high-opacity HI from which H2 subsequently forms. On smaller scales, we find that very dense molecular gas, as traced by interferometric HCO+ and HCN maps, is associated with star formation along shocked filaments and with rims of expanding shell-like structures, both created by feedback from massive stars.

Min Wang

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68 published item(s)

A Multimodal Pre-trained Network for Integrated EEG-Video Seizure Detection

Self-distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach

A Feature Weighted Mixed Naive Bayes Model for Monitoring Anomalies in the Fan System of a Thermal Power Plant

A learning-based projection method for model order reduction of transport problems

A simple consistent Bayes factor for testing the Kendall rank correlation coefficient

A Study on the Power Parameter in Power Prior Bayesian Analysis

An expectation-maximization algorithm for estimating the parameters of the correlated binomial distribution

Analysis of Age of Information in Dual Updating Systems

Cancellable Template Design for Privacy-Preserving EEG Biometric Authentication Systems

DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Control

Empirical distributions of the robustified $t$-test statistics

Experimental demonstration of phase-matching and Sagnac effect in a millimeter-scale wedged resonator gyroscope

FashionVQA: A Domain-Specific Visual Question Answering System

High sensitivity air-coupled MHz frequency ultrasound detection using on-chip microcavities

High-production-rate fabrication of low-loss lithium niobate electro-optic modulators using photolithography assisted chemo-mechanical etching (PLACE)

Hybrid variable monitoring: An unsupervised process monitoring framework with binary and continuous variables

Large discrepancy between observations and simulations: Implications for urban air quality in China

Minimizing Age-upon-Decisions in Bufferless System: Service Scheduling and Decision Interval

Monolithically integrated active passive waveguide array fabricated on thin film lithium niobate using a single continuous photolithography process

Monolithically integrated waveguide-coupled single-frequency microlaser on erbium-doped thin film lithium niobate

Neural Network Based Variational Methods for Solving Quadratic Porous Medium Equations in High Dimensions

Nonlinear Reduced DNN Models for State Estimation

On-chip integrated Yb3+-doped waveguide amplifiers on thin film lithium niobate

PSP: Million-level Protein Sequence Dataset for Protein Structure Prediction

Rethinking Feature Uncertainty in Stochastic Neural Networks for Adversarial Robustness

A note on the g and h control charts

AsymptoticNG: A regularized natural gradient optimization algorithm with look-ahead strategy

Broadband highly efficient nonlinear optical processes in on-chip integrated lithium niobate microdisk resonators of Q-factor above 10^8

Decimetric type U solar radio bursts and associated EUV phenomena on 2011 February 9

Monocular Human Pose and Shape Reconstruction using Part Differentiable Rendering

On-chip integrated waveguide amplifiers on Erbium-doped thin film lithium niobate on insulator

Protein corona critically affects the bio-behaviors of SARS-CoV-2

Tunable partial polarization beam splitter and optomechanically induced Faraday effect

A second order accurate scalar auxiliary variable (SAV) numerical method for the square phase field crystal equation

Efficient light coupling between an ultra-low loss lithium niobate waveguide and an adiabatically tapered single mode optical fiber

Field-free Deterministic Magnetization Switching Induced by Interlaced Spin-Orbit Torques

Health Assessment and Prognostics Based on Higher Order Hidden Semi-Markov Models

High-index-contrast single-mode optical waveguides fabricated on lithium niobate by photolithography assisted chemo-mechanical etching (PLACE)

Investigation of finite-sample properties of robust location and scale estimators

Local Molecular Gas toward the Aquila Rift Region

Theoretical Conditions for Field-free Magnetization Switching Induced by Spin-orbit Torque and Dzyaloshinskii-Moriya Interaction

A compact and efficient three-dimensional microfluidic mixer

Efficient Electro-optical Tuning of Optical Frequency Microcomb on a Monolithically Integrated High-Q Lithium Niobate Microdisk

Manipulation of optomechanically induced transparency and absorption by indirectly coupling to an auxiliary cavity mode

Broadband angle- and permittivity-insensitive nondispersive optical activity based on chiral metamaterials

Consistency of Bayes factor for nonnested model selection when the model dimension grows

Features and stability analysis of non-Schwarzschild black hole in quadratic gravity

Multi-frequency Radio Profiles of PSR B1133+16: radiation location and particle energy

The Broken Lane of a Type II Radio Burst Caused by Collision of a Coronal Shock with a Flare Current Sheet

A deep near-infrared survey toward the Aquila molecular cloud - I. Molecular hydrogen outflows

A simple two-sample Bayesian t-test for hypothesis testing

On the number of representations of n as a linear combination of four triangular numbers

On the number of representations of n as a linear combination of four triangular numbers II

Phase matched second harmonic generation in an on-chip lithium niobate microresonator fabricated by femtosecond laser

The East-Asian VLBI Network

A brief introduction to giant magnetoresistance

On Transition Metal Catalyzed Reduction of N-nitrosodimethlamine

On-chip tuning of the resonant wavelength in a high-Q microresonator integrated with a microheater

A new three-parameter lifetime distribution and associated inference

Bayes Factor Consistency for One-way Random Effects Model

Bayes Factor Consistency for Unbalanced ANOVA Models

Efficient Multi-way Theta-Join Processing Using MapReduce

Type IIn Supernova SN 2010jl: Optical Observations for Over 500 Days After Explosion

gSketch: On Query Estimation in Graph Streams

Multiferroic PbFe12O19 Ceramics

VLBI observations of 10 CSO candidates: expansion velocities of hot spots

Classification of Extremely Red Objects in the COSMOS Field

The Molecular Ridge Close to 30 Doradus in the Large Magellanic Cloud