Source author record

Jin Li

Jin Li appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

ResearcherUnclaimed source record

Catalog footprint

What is connected

122works

39topics

4close collaborators

Actions

Connect this record

Open graph Browse works

Inspect adjacent papers, topics, institutions and collaborators without losing the researcher page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

preprint2026arXiv

AnyECG: Evolved ECG Foundation Model for Holistic Health Profiling

Background: Artificial intelligence enabled electrocardiography (AI-ECG) has demonstrated the ability to detect diverse pathologies, but most existing models focus on single disease identification, neglecting comorbidities and future risk prediction. Although ECGFounder expanded cardiac disease coverage, a holistic health profiling model remains needed. Methods: We constructed a large multicenter dataset comprising 13.3 million ECGs from 2.98 million patients. Using transfer learning, ECGFounder was fine-tuned to develop AnyECG, a foundation model for holistic health profiling. Performance was evaluated using external validation cohorts and a 10-year longitudinal cohort for current diagnosis, future risk prediction, and comorbidity identification. Results: AnyECG demonstrated systemic predictive capability across 1172 conditions, achieving an AUROC greater than 0.7 for 306 diseases. The model revealed novel disease associations, robust comorbidity patterns, and future disease risks. Representative examples included high diagnostic performance for hyperparathyroidism (AUROC 0.941), type 2 diabetes (0.803), Crohn disease (0.817), lymphoid leukemia (0.856), and chronic obstructive pulmonary disease (0.773). Conclusion: The AnyECG foundation model provides substantial evidence that AI-ECG can serve as a systemic tool for concurrent disease detection and long-term risk prediction.

preprint2026arXiv

Gaussian Relational Graph Transformer

Relational graph learning models relational databases as graphs and has demonstrated superior performance on a wide range of relational predictive tasks. However, existing methods struggle to capture long-range dependencies due to information decay in their message-passing mechanisms, and recent relational graph transformers remain limited in jointly modeling structural, semantic, and temporal information. In this paper, we propose GelGT, a Gaussian relational graph transformer that explicitly addresses these challenges. GelGT introduces a structure-semantic collaborative sampling strategy to preserve structural connectivity while filtering irrelevant semantic information, and incorporates a Gaussian graph attention mechanism with a learnable Gaussian bias on the sampled subgraphs to dynamically encode temporal dependencies. Extensive experiments on various real-world datasets demonstrate that GelGT achieves state-of-the-art downstream task performance, with up to a 13.8% improvement in predictive performance.

preprint2023arXiv

A Framework for Mutual Information-based MIMO Integrated Sensing and Communication Beamforming Design

Integrated sensing and communication (ISAC) unifies sensing and communication, and improves the efficiency of the spectrum, energy, and hardware. In this work, we investigate the ISAC beamforming design to maximize the mutual information between the target response matrix of a point radar target and the echo signals, while ensuring the data rate requirements of the communication users. In order to study the impact of the echo interference caused by communication users on sensing performance, we study two scenarios: a single communication user and multiple communication users. For the case of a single communication user, we consider three types of echo interference, no interference, a point interference, and an extended interference. For the case of multiple communication users, the interference is also an extended one, and furthermore, each user's communication rate requirement needs to be satisfied. To find the optimal beamforming design in these problems, we provide a closed-form solution with low complexiy, a semidefinite relaxation (SDR) method, a low-complexity algorithm based on the Majorization-Minimization (MM) method and the successive convex approximation (SCA) method, and an algorithm based on MM method and SCA method, respectively. Numerical results demonstrate that, compared to the ISAC beamforming schemes based on the Cramér-Rao bound (CRB) metric and the beampattern metric, the proposed mutual information metric can bring better beampattern and root mean square error (RMSE) of angle estimation. Furthermore, our proposed schemes designed based on the mutual information metric can suppress the echo interference from the communication users effectively.

preprint2022arXiv

A Multi-level Acoustic Feature Extraction Framework for Transformer Based End-to-End Speech Recognition

Transformer based end-to-end modelling approaches with multiple stream inputs have been achieved great success in various automatic speech recognition (ASR) tasks. An important issue associated with such approaches is that the intermediate features derived from each stream might have similar representations and thus it is lacking of feature diversity, such as the descriptions related to speaker characteristics. To address this issue, this paper proposed a novel multi-level acoustic feature extraction framework that can be easily combined with Transformer based ASR models. The framework consists of two input streams: a shallow stream with high-resolution spectrograms and a deep stream with low-resolution spectrograms. The shallow stream is used to acquire traditional shallow features that is beneficial for the classification of phones or words while the deep stream is used to obtain utterance-level speaker-invariant deep features for improving the feature diversity. A feature correlation based fusion strategy is used to aggregate both features across the frequency and time domains and then fed into the Transformer encoder-decoder module. By using the proposed multi-level acoustic feature extraction framework, state-of-the-art word error rate of 21.7% and 2.5% were obtained on the HKUST Mandarin telephone and Librispeech speech recognition tasks respectively.

preprint2022arXiv

Adaptive Domain Interest Network for Multi-domain Recommendation

Industrial recommender systems usually hold data from multiple business scenarios and are expected to provide recommendation services for these scenarios simultaneously. In the retrieval step, the topK high-quality items selected from a large number of corpus usually need to be various for multiple scenarios. Take Alibaba display advertising system for example, not only because the behavior patterns of Taobao users are diverse, but also differentiated scenarios' bid prices assigned by advertisers vary significantly. Traditional methods either train models for each scenario separately, ignoring the cross-domain overlapping of user groups and items, or simply mix all samples and maintain a shared model which makes it difficult to capture significant diversities between scenarios. In this paper, we present Adaptive Domain Interest network that adaptively handles the commonalities and diversities across scenarios, making full use of multi-scenarios data during training. Then the proposed method is able to improve the performance of each business domain by giving various topK candidates for different scenarios during online inference. Specifically, our proposed ADI models the commonalities and diversities for different domains by shared networks and domain-specific networks, respectively. In addition, we apply the domain-specific batch normalization and design the domain interest adaptation layer for feature-level domain adaptation. A self training strategy is also incorporated to capture label-level connections across domains.ADI has been deployed in the display advertising system of Alibaba, and obtains 1.8% improvement on advertising revenue.

preprint2022arXiv

AI-enabled Automatic Multimodal Fusion of Cone-Beam CT and Intraoral Scans for Intelligent 3D Tooth-Bone Reconstruction and Clinical Applications

A critical step in virtual dental treatment planning is to accurately delineate all tooth-bone structures from CBCT with high fidelity and accurate anatomical information. Previous studies have established several methods for CBCT segmentation using deep learning. However, the inherent resolution discrepancy of CBCT and the loss of occlusal and dentition information largely limited its clinical applicability. Here, we present a Deep Dental Multimodal Analysis (DDMA) framework consisting of a CBCT segmentation model, an intraoral scan (IOS) segmentation model (the most accurate digital dental model), and a fusion model to generate 3D fused crown-root-bone structures with high fidelity and accurate occlusal and dentition information. Our model was trained with a large-scale dataset with 503 CBCT and 28,559 IOS meshes manually annotated by experienced human experts. For CBCT segmentation, we use a five-fold cross validation test, each with 50 CBCT, and our model achieves an average Dice coefficient and IoU of 93.99% and 88.68%, respectively, significantly outperforming the baselines. For IOS segmentations, our model achieves an mIoU of 93.07% and 95.70% on the maxillary and mandible on a test set of 200 IOS meshes, which are 1.77% and 3.52% higher than the state-of-art method. Our DDMA framework takes about 20 to 25 minutes to generate the fused 3D mesh model following the sequential processing order, compared to over 5 hours by human experts. Notably, our framework has been incorporated into a software by a clear aligner manufacturer, and real-world clinical cases demonstrate that our model can visualize crown-root-bone structures during the entire orthodontic treatment and can predict risks like dehiscence and fenestration. These findings demonstrate the potential of multi-modal deep learning to improve the quality of digital dental models and help dentists make better clinical decisions.

preprint2022arXiv

An efficient real-time target tracking algorithm using adaptive feature fusion

Visual-based target tracking is easily influenced by multiple factors, such as background clutter, targets fast-moving, illumination variation, object shape change, occlusion, etc. These factors influence the tracking accuracy of a target tracking task. To address this issue, an efficient real-time target tracking method based on a low-dimension adaptive feature fusion is proposed to allow us the simultaneous implementation of the high-accuracy and real-time target tracking. First, the adaptive fusion of a histogram of oriented gradient (HOG) feature and color feature is utilized to improve the tracking accuracy. Second, a convolution dimension reduction method applies to the fusion between the HOG feature and color feature to reduce the over-fitting caused by their high-dimension fusions. Third, an average correlation energy estimation method is used to extract the relative confidence adaptive coefficients to ensure tracking accuracy. We experimentally confirm the proposed method on an OTB100 data set. Compared with nine popular target tracking algorithms, the proposed algorithm gains the highest tracking accuracy and success tracking rate. Compared with the traditional Sum of Template and Pixel-wise LEarners (STAPLE) algorithm, the proposed algorithm can obtain a higher success rate and accuracy, improving by 0.023 and 0.019, respectively. The experimental results also demonstrate that the proposed algorithm can reach the real-time target tracking with 50 fps. The proposed method paves a more promising way for real-time target tracking tasks under a complex environment, such as appearance deformation, illumination change, motion blur, background, similarity, scale change, and occlusion.

preprint2022arXiv

ApolloRL: a Reinforcement Learning Platform for Autonomous Driving

We introduce ApolloRL, an open platform for research in reinforcement learning for autonomous driving. The platform provides a complete closed-loop pipeline with training, simulation, and evaluation components. It comes with 300 hours of real-world data in driving scenarios and popular baselines such as Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC) agents. We elaborate in this paper on the architecture and the environment defined in the platform. In addition, we discuss the performance of the baseline agents in the ApolloRL environment.

preprint2022arXiv

CaTT-KWS: A Multi-stage Customized Keyword Spotting Framework based on Cascaded Transducer-Transformer

Customized keyword spotting (KWS) has great potential to be deployed on edge devices to achieve hands-free user experience. However, in real applications, false alarm (FA) would be a serious problem for spotting dozens or even hundreds of keywords, which drastically affects user experience. To solve this problem, in this paper, we leverage the recent advances in transducer and transformer based acoustic models and propose a new multi-stage customized KWS framework named Cascaded Transducer-Transformer KWS (CaTT-KWS), which includes a transducer based keyword detector, a frame-level phone predictor based force alignment module and a transformer based decoder. Specifically, the streaming transducer module is used to spot keyword candidates in audio stream. Then force alignment is implemented using the phone posteriors predicted by the phone predictor to finish the first stage keyword verification and refine the time boundaries of keyword. Finally, the transformer decoder further verifies the triggered keyword. Our proposed CaTT-KWS framework reduces FA rate effectively without obviously hurting keyword recognition accuracy. Specifically, we can get impressively 0.13 FA per hour on a challenging dataset, with over 90% relative reduction on FA comparing to the transducer based detection model, while keyword recognition accuracy only drops less than 2%.

preprint2022arXiv

Coarse-to-Fine Sparse Sequential Recommendation

Sequential recommendation aims to model dynamic user behavior from historical interactions. Self-attentive methods have proven effective at capturing short-term dynamics and long-term preferences. Despite their success, these approaches still struggle to model sparse data, on which they struggle to learn high-quality item representations. We propose to model user dynamics from shopping intents and interacted items simultaneously. The learned intents are coarse-grained and work as prior knowledge for item recommendation. To this end, we present a coarse-to-fine self-attention framework, namely CaFe, which explicitly learns coarse-grained and fine-grained sequential dynamics. Specifically, CaFe first learns intents from coarse-grained sequences which are dense and hence provide high-quality user intent representations. Then, CaFe fuses intent representations into item encoder outputs to obtain improved item representations. Finally, we infer recommended items based on representations of items and corresponding intents. Experiments on sparse datasets show that CaFe outperforms state-of-the-art self-attentive recommenders by 44.03% NDCG@5 on average.

preprint2022arXiv

Complementary Calibration: Boosting General Continual Learning with Collaborative Distillation and Self-Supervision

General Continual Learning (GCL) aims at learning from non independent and identically distributed stream data without catastrophic forgetting of the old tasks that don't rely on task boundaries during both training and testing stages. We reveal that the relation and feature deviations are crucial problems for catastrophic forgetting, in which relation deviation refers to the deficiency of the relationship among all classes in knowledge distillation, and feature deviation refers to indiscriminative feature representations. To this end, we propose a Complementary Calibration (CoCa) framework by mining the complementary model's outputs and features to alleviate the two deviations in the process of GCL. Specifically, we propose a new collaborative distillation approach for addressing the relation deviation. It distills model's outputs by utilizing ensemble dark knowledge of new model's outputs and reserved outputs, which maintains the performance of old tasks as well as balancing the relationship among all classes. Furthermore, we explore a collaborative self-supervision idea to leverage pretext tasks and supervised contrastive learning for addressing the feature deviation problem by learning complete and discriminative features for all classes. Extensive experiments on four popular datasets show that our CoCa framework achieves superior performance against state-of-the-art methods. Code is available at https://github.com/lijincm/CoCa.

preprint2022arXiv

Construction of MDS self-dual codes from generalized Reed-Solomon codes

MDS codes and self-dual codes are important families of classical codes in coding theory. It is of interest to investigate MDS self-dual codes. The existence of MDS self-dual codes over finite field $F_q$ is completely solved for $q$ is even. In this paper, for finite field with odd characteristic, we construct some new classes of MDS self-dual codes by (extended) generalized Reed-Solomon codes.

preprint2022arXiv

GraphEye: A Novel Solution for Detecting Vulnerable Functions Based on Graph Attention Network

With the continuous extension of the Industrial Internet, cyber incidents caused by software vulnerabilities have been increasing in recent years. However, software vulnerabilities detection is still heavily relying on code review done by experts, and how to automatedly detect software vulnerabilities is an open problem so far. In this paper, we propose a novel solution named GraphEye to identify whether a function of C/C++ code has vulnerabilities, which can greatly alleviate the burden of code auditors. GraphEye is originated from the observation that the code property graph of a non-vulnerable function naturally differs from the code property graph of a vulnerable function with the same functionality. Hence, detecting vulnerable functions is attributed to the graph classification problem.GraphEye is comprised of VecCPG and GcGAT. VecCPG is a vectorization for the code property graph, which is proposed to characterize the key syntax and semantic features of the corresponding source code. GcGAT is a deep learning model based on the graph attention graph, which is proposed to solve the graph classification problem according to VecCPG. Finally, GraphEye is verified by the SARD Stack-based Buffer Overflow, Divide-Zero, Null Pointer Deference, Buffer Error, and Resource Error datasets, the corresponding F1 scores are 95.6%, 95.6%,96.1%,92.6%, and 96.1% respectively, which validate the effectiveness of the proposed solution.

preprint2022arXiv

High precision measurement of cosmic curvature: from gravitational waves and cosmic chronometer

Although the spatial curvature has been measured with very high precision, it still suffers from the well known cosmic curvature tension. In this paper, we propose an improved method to determine the cosmic curvature, by using the simulated data of binary neutron star mergers observed by the second generation space-based DECi-hertz Interferometer Gravitational-wave Observatory (DECIGO). By applying the Hubble parameter observations of cosmic chronometers to the DECIGO standard sirens, we explore different possibilities of making measurements of the cosmic curvature referring to a distant past: one is to reconstruct the Hubble parameters through the Gaussian process without the influence of hypothetical models, and the other is deriving constraints on $Ω_K$ in the framework of non-flat $Λ$ cold dark matter model. It is shown that in the improved method DECIGO could provide a reliable and stringent constraint on the cosmic curvature ($Ω_{K} = -0.007\pm0.016$), while we could only expect the zero cosmic curvature to be established at the precision of $ΔΩ_K=0.12$ in the second model-dependent method. Therefore, our results indicate that in the framework of methodology proposed in this paper, the increasing number of well-measured standard sirens in DECIGO could significantly reduce the bias of estimations for cosmic curvature. Such constraint is also comparable to the precision of Planck 2018 results with the newest cosmic microwave background (CMB) observations ($ΔΩ_{K} \approx 0.018$), based on the concordance $Λ$CDM model.

preprint2022arXiv

Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback

This paper studies the item-to-item recommendation problem in recommender systems from a new perspective of metric learning via implicit feedback. We develop and investigate a personalizable deep metric model that captures both the internal contents of items and how they were interacted with by users. There are two key challenges in learning such model. First, there is no explicit similarity annotation, which deviates from the assumption of most metric learning methods. Second, these approaches ignore the fact that items are often represented by multiple sources of meta data and different users use different combinations of these sources to form their own notion of similarity. To address these challenges, we develop a new metric representation embedded as kernel parameters of a probabilistic model. This helps express the correlation between items that a user has interacted with, which can be used to predict user interaction with new items. Our approach hinges on the intuition that similar items induce similar interactions from the same user, thus fitting a metric-parameterized model to predict an implicit feedback signal could indirectly guide it towards finding the most suitable metric for each user. To this end, we also analyze how and when the proposed method is effective from a theoretical lens. Its empirical effectiveness is also demonstrated on several real-world datasets.

preprint2022arXiv

Multiple Targets Directed Greybox Fuzzing

Directed greybox fuzzing (DGF) can quickly discover or reproduce bugs in programs by seeking to reach a program location or explore some locations in order. However, due to their static stage division and coarse-grained energy scheduling, prior DGF tools perform poorly when facing multiple target locations (targets for short). In this paper, we present multiple targets directed greybox fuzzing which aims to reach multiple programs locations in a fuzzing campaign. Specifically, we propose a novel strategy to adaptively coordinate exploration and exploitation stages, and a novel energy scheduling strategy by considering more relations between seeds and target locations. We implement our approaches in a tool called LeoFuzz and evaluate it on crash reproduction, true positives verification, and vulnerability exposure in real-world programs. Experimental results show that LeoFuzz outperforms six state-of-the-art fuzzers, i.e., QYSM, AFLGo, Lolly, Berry, Beacon and WindRanger in terms of effectiveness and efficiency. Moreover, LeoFuzz has detected 23 new vulnerabilities in real-world programs, and 11 of them have been assigned CVE IDs.

preprint2022arXiv

Neural Points: Point Cloud Representation with Neural Fields for Arbitrary Upsampling

In this paper, we propose Neural Points, a novel point cloud representation and apply it to the arbitrary-factored upsampling task. Different from traditional point cloud representation where each point only represents a position or a local plane in the 3D space, each point in Neural Points represents a local continuous geometric shape via neural fields. Therefore, Neural Points contain more shape information and thus have a stronger representation ability. Neural Points is trained with surface containing rich geometric details, such that the trained model has enough expression ability for various shapes. Specifically, we extract deep local features on the points and construct neural fields through the local isomorphism between the 2D parametric domain and the 3D local patch. In the final, local neural fields are integrated together to form the global surface. Experimental results show that Neural Points has powerful representation ability and demonstrate excellent robustness and generalization ability. With Neural Points, we can resample point cloud with arbitrary resolutions, and it outperforms the state-of-the-art point cloud upsampling methods. Code is available at https://github.com/WanquanF/NeuralPoints.

preprint2022arXiv

Simulation of a Xe-based X-ray Polarimeter at 10-30 keV

Polarization detection of X-rays is a non-negligible topic to astrophysical observation. Many polarization detection methods have been well developed for X-rays in the energy range below 10~keV, while the detection at 10-30~keV is rarely discussed. This paper presents a simulation study of a Xe-based gas pixel detector, which can achieve the polarization detection of X-rays at 10-30~keV. To verify the emission angle distribution of photoelectrons, different electromagnetic models in Geant4 were investigated. After a necessary modification by considering the missing factor when sampling the emission angle, a good agreement can be achieved. Moreover, the detection capability of 20~keV polarized photons was discussed and the modulation factor could be 43\%.

preprint2022arXiv

Wavelet Transform-assisted Adaptive Generative Modeling for Colorization

Unsupervised deep learning has recently demonstrated the promise of producing high-quality samples. While it has tremendous potential to promote the image colorization task, the performance is limited owing to the high-dimension of data manifold and model capability. This study presents a novel scheme that exploits the score-based generative model in wavelet domain to address the issues. By taking advantage of the multi-scale and multi-channel representation via wavelet transform, the proposed model learns the richer priors from stacked coarse and detailed wavelet coefficient components jointly and effectively. This strategy also reduces the dimension of the original manifold and alleviates the curse of dimensionality, which is beneficial for estimation and sampling. Moreover, dual consistency terms in the wavelet domain, namely data-consistency and structure-consistency are devised to leverage colorization task better. Specifically, in the training phase, a set of multi-channel tensors consisting of wavelet coefficients is used as the input to train the network with denoising score matching. In the inference phase, samples are iteratively generated via annealed Langevin dynamics with data and structure consistencies. Experiments demonstrated remarkable improvements of the proposed method on both generation and colorization quality, particularly in colorization robustness and diversity.

preprint2021arXiv

On the correspondence between energy conservation and energy-momentum tensor conservation in cosmology

The correspondence between the thermodynamic energy equation satisfied by a closed co-moving volume and the conservation equation satisfied by the energy-momentum tensor of the matter inside the co-moving volume is extended to a more general system with an arbitrary cosmological horizon and a heat source. The energy of the system consisting of a cosmological horizon and its internal matter could be conserved by defining a surface energy on the horizons. Therefore, energy conservation and energy-momentum tensor conservation can always be consistent for such a system. On the other hand, from the perspective of classical thermodynamics, one can define an effective pressure at the cosmological horizon to guarantee that the thermodynamic energy equation inside the horizon is consistent with the energy-momentum tensor conservation equation of the matter inside the horizon. These systems can satisfy the generalized second law of thermodynamics under appropriate conditions. The definitions of the surface energy and the effective pressure are extended to the gravity theory with non-minimal coupling between geometry and matter, in which geometry could be regarded as a heat source.

preprint2021arXiv

Simulation on the Transparency of Electrons and Ion Back Flow for a Time Projection Chamber based on Staggered Multiple THGEMs

The IBF and the transparent rate of electrons are two essential indicators of TPC, which affect the energy resolution and counting rate respectively. In this paper, we propose several novel strategies of staggered multi-THGEM to suppress IBF, where the geometry of the first layer THGEM will be optimized to increase the electron transparent rate. By Garfield++ simulation, the electron transparency rate can be more than 90% of single THGEM with a optimized large hole. By simulating these configurations of triple and quadruple THGEM structures, we conclude that the IBF can be reduced to 0.2% level in an optimized configuration denoted as "ACBA". This strategy for staggered THGEM could have potential applications in future TPC projects.

preprint2021arXiv

Truncation-Free Matching System for Display Advertising at Alibaba

Matching module plays a critical role in display advertising systems. Without query from user, it is challenging for system to match user traffic and ads suitably. System packs up a group of users with common properties such as the same gender or similar shopping interests into a crowd. Here term crowd can be viewed as a tag over users. Then advertisers bid for different crowds and deliver their ads to those targeted users. Matching module in most industrial display advertising systems follows a two-stage paradigm. When receiving a user request, matching system (i) finds the crowds that the user belongs to; (ii) retrieves all ads that have targeted those crowds. However, in applications such as display advertising at Alibaba, with very large volumes of crowds and ads, both stages of matching have to truncate the long-tailed parts for online serving, under limited latency. That's to say, not all ads have the chance to participate in online matching. This results in sub-optimal result for both advertising performance and platform revenue. In this paper, we study the truncation problem and propose a Truncation Free Matching System (TFMS). The basic idea is to decouple the matching computation from the online pipeline. Instead of executing the two-stage matching when user visits, TFMS utilizes a near-line truncation-free matching to pre-calculate and store those top valuable ads for each user. Then the online pipeline just needs to fetch the pre-stored ads as matching results. In this way, we can jump out of online system's latency and computation cost limitations, and leverage flexible computation resource to finish the user-ad matching. TFMS has been deployed in our productive system since 2019, bringing (i) more than 50% improvement of impressions for advertisers who encountered truncation before, (ii) 9.4% Revenue Per Mile gain, which is significant enough for the business.

preprint2020arXiv

A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction

For e-commerce platforms such as Taobao and Amazon, advertisers play an important role in the entire digital ecosystem: their behaviors explicitly influence users' browsing and shopping experience; more importantly, advertiser's expenditure on advertising constitutes a primary source of platform revenue. Therefore, providing better services for advertisers is essential for the long-term prosperity for e-commerce platforms. To achieve this goal, the ad platform needs to have an in-depth understanding of advertisers in terms of both their marketing intents and satisfaction over the advertising performance, based on which further optimization could be carried out to service the advertisers in the correct direction. In this paper, we propose a novel Deep Satisfaction Prediction Network (DSPN), which models advertiser intent and satisfaction simultaneously. It employs a two-stage network structure where advertiser intent vector and satisfaction are jointly learned by considering the features of advertiser's action information and advertising performance indicators. Experiments on an Alibaba advertisement dataset and online evaluations show that our proposed DSPN outperforms state-of-the-art baselines and has stable performance in terms of AUC in the online environment. Further analyses show that DSPN not only predicts advertisers' satisfaction accurately but also learns an explainable advertiser intent, revealing the opportunities to optimize the advertising performance further.

preprint2020arXiv

Controllable List-wise Ranking for Universal No-reference Image Quality Assessment

No-reference image quality assessment (NR-IQA) has received increasing attention in the IQA community since reference image is not always available. Real-world images generally suffer from various types of distortion. Unfortunately, existing NR-IQA methods do not work with all types of distortion. It is a challenging task to develop universal NR-IQA that has the ability of evaluating all types of distorted images. In this paper, we propose a universal NR-IQA method based on controllable list-wise ranking (CLRIQA). First, to extend the authentically distorted image dataset, we present an imaging-heuristic approach, in which the over-underexposure is formulated as an inverse of Weber-Fechner law, and fusion strategy and probabilistic compression are adopted, to generate the degraded real-world images. These degraded images are label-free yet associated with quality ranking information. We then design a controllable list-wise ranking function by limiting rank range and introducing an adaptive margin to tune rank interval. Finally, the extended dataset and controllable list-wise ranking function are used to pre-train a CNN. Moreover, in order to obtain an accurate prediction model, we take advantage of the original dataset to further fine-tune the pre-trained network. Experiments evaluated on four benchmark datasets (i.e. LIVE, CSIQ, TID2013, and LIVE-C) show that the proposed CLRIQA improves the state of the art by over 9% in terms of overall performance. The code and model are publicly available at https://github.com/GZHU-Image-Lab/CLRIQA.

preprint2020arXiv

Fast Reinforcement Learning for Anti-jamming Communications

This letter presents a fast reinforcement learning algorithm for anti-jamming communications which chooses previous action with probability $τ$ and applies $ε$-greedy with probability $(1-τ)$. A dynamic threshold based on the average value of previous several actions is designed and probability $τ$ is formulated as a Gaussian-like function to guide the wireless devices. As a concrete example, the proposed algorithm is implemented in a wireless communication system against multiple jammers. Experimental results demonstrate that the proposed algorithm exceeds Q-learing, deep Q-networks (DQN), double DQN (DDQN), and prioritized experience reply based DDQN (PDDQN), in terms of signal-to-interference-plus-noise ratio and convergence rate.

preprint2020arXiv

Feasibility and physics potential of detecting $^8$B solar neutrinos at JUNO

The Jiangmen Underground Neutrino Observatory~(JUNO) features a 20~kt multi-purpose underground liquid scintillator sphere as its main detector. Some of JUNO's features make it an excellent experiment for $^8$B solar neutrino measurements, such as its low-energy threshold, its high energy resolution compared to water Cherenkov detectors, and its much large target mass compared to previous liquid scintillator detectors. In this paper we present a comprehensive assessment of JUNO's potential for detecting $^8$B solar neutrinos via the neutrino-electron elastic scattering process. A reduced 2~MeV threshold on the recoil electron energy is found to be achievable assuming the intrinsic radioactive background $^{238}$U and $^{232}$Th in the liquid scintillator can be controlled to 10$^{-17}$~g/g. With ten years of data taking, about 60,000 signal and 30,000 background events are expected. This large sample will enable an examination of the distortion of the recoil electron spectrum that is dominated by the neutrino flavor transformation in the dense solar matter, which will shed new light on the tension between the measured electron spectra and the predictions of the standard three-flavor neutrino oscillation framework. If $Δm^{2}_{21}=4.8\times10^{-5}~(7.5\times10^{-5})$~eV$^{2}$, JUNO can provide evidence of neutrino oscillation in the Earth at the about 3$σ$~(2$σ$) level by measuring the non-zero signal rate variation with respect to the solar zenith angle. Moveover, JUNO can simultaneously measure $Δm^2_{21}$ using $^8$B solar neutrinos to a precision of 20\% or better depending on the central value and to sub-percent precision using reactor antineutrinos. A comparison of these two measurements from the same detector will help elucidate the current tension between the value of $Δm^2_{21}$ reported by solar neutrino experiments and the KamLAND experiment.

preprint2020arXiv

Frequency stabilization and tuning of breathing soliton in SiN microresonators

Dissipative Kerr soliton offers broadband coherent and low-noise frequency comb and stable temporal pulse train, having shown great potential applications in spectroscopy, communications, and metrology. Breathing soliton is a particular dissipative Kerr soliton that the pulse duration and peak intensity show periodic oscillation. However, the noise and stability of the breathing soliton is still remaining unexplored, which would be the main obstacle for future applications. Here, we have investigated the breathing dissipative Kerr solitons in the silicon nitride (SiN) microrings, while the breather period shows uncertainties around MHz in both simulation and experiments. By applying a modulated pump, the breathing frequency can be injectively locked to the modulation and tuned over tens of MHz with frequency noise significantly suppressed. Our demonstration offers an alternative knob for the controlling of soliton dynamics in microresonator and paves a new avenue towards practical applications of breathing soliton.

preprint2020arXiv

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising

Bipartite b-matching is fundamental in algorithm design, and has been widely applied into economic markets, labor markets, etc. These practical problems usually exhibit two distinct features: large-scale and dynamic, which requires the matching algorithm to be repeatedly executed at regular intervals. However, existing exact and approximate algorithms usually fail in such settings due to either requiring intolerable running time or too much computation resource. To address this issue, we propose \texttt{NeuSearcher} which leverages the knowledge learned from previously instances to solve new problem instances. Specifically, we design a multichannel graph neural network to predict the threshold of the matched edges weights, by which the search region could be significantly reduced. We further propose a parallel heuristic search algorithm to iteratively improve the solution quality until convergence. Experiments on both open and industrial datasets demonstrate that \texttt{NeuSearcher} can speed up 2 to 3 times while achieving exactly the same matching solution compared with the state-of-the-art approximation approaches.

preprint2020arXiv

Measuring the viscosity of dark matter with strongly lensed gravitational waves

Based on the strongly lensed gravitational waves (GWs) from compact binary coalescence, we propose a new strategy to examine the fluid shear viscosity of dark matter (DM) in the gravitational wave domain, i.e., whether a GW experiences the damping effect when it propagates in DM fluid with nonzero shear viscosity. By assuming that the dark matter self-scatterings are efficient enough for the hydrodynamic description to be valid, our results demonstrate that future ground-based Einstein Telescope (ET) and satellite GW observatory (Big Bang Observer; BBO) may succeed in detecting any dark matter self-interactions at the scales of galaxies and clusters.

preprint2020arXiv

New structure canditates for the experimentally synthesized heptazine-based and triazine-based two dimensional graphitic carbon nitride

The widely used crystal structures for both heptazine-based and triazine-based two-dimensional (2D) graphitic carbon nitride (g-C$_3$N$_4$) are the flat P-6m2 configurations. However, the experimentally synthesized 2D g-C$_3$N$_4$ possess thickness ranging in 0.2-0.5 nm, indicating that the theoretically used flat P-6m2 configurations are not the correct ground states. In this work, we propose three new corrugated structures P321, P3m1 and Pca21 with energies of 66 (86), 77 (87) and 78 (89) meV/atom lower than that of the corresponding heptazine-based (triazine-based) g-C$_3$N$_4$ in flat P-6m2 configuration, respectively. These corrugated structures have very similar periodic patterns to the flat P-6m2 ones and they are difficult to be distinguished from each other according to their top-views. The optimized thicknesses of the three corrugated structures ranging in 1.347-3.142 Å are in good agreement with the experimental results. The first-principles results show that these corrugated structural candidates are also semiconductors with band gaps slightly larger than those of the correspondingly flat P-6m2 ones. Furthermore, they possess also suitable band edge positions for sun-light-driven water-splitting at both $pH=0$ and $pH=7$ environments. Our results show that these three new structures are more promising candidates for the experimentally synthesized g-C$_3$N$_4$.

preprint2020arXiv

Observation of a cross-section enhancement near mass threshold in $e^{+}e^{-}\rightarrowΛ\barΛ$

The process $e^{+}e^{-}\rightarrowΛ\barΛ$ is studied using data samples at $\sqrt{s}=2.2324$, 2.400, 2.800 and 3.080 GeV collected with the BESIII detector operating at the BEPCII collider. The Born cross section is measured at $\sqrt{s}$=2.2324 GeV, which is 1.0 MeV above the $Λ\barΛ$ mass threshold, to be $305\pm45^{+66}_{-36}$ pb, where the first uncertainty is statistical and the second systematic. The substantial cross section near threshold is significantly larger than that expected from theory, which predicts the cross section to vanish at threshold. The Born cross sections at $\sqrt{s}$=2.400, 2.800 and 3.080 GeV are measured and found to be consistent with previous experimental results, but with improved precision. Finally, the corresponding effective electromagnetic form factors of $Λ$ are deduced.

preprint2020arXiv

PrivacyGuard: Enforcing Private Data Usage Control with Blockchain and Attested Off-chain Contract Execution

The abundance and rich varieties of data are enabling many transformative applications of big data analytics that have profound societal impacts. However, there are also increasing concerns regarding the improper use of individual data owner's private data. In this paper, we propose PrivacyGuard, a system that leverages blockchain smart contract and trusted execution environment (TEE) to enable individual's control over the access and usage of their private data. Smart contracts are used to specify data usage policy, i.e., who can use what data under which conditions and what analytics to perform, while the distributed blockchain ledger is used to keep an irreversible and non-repudiable data usage record. To address the efficiency problem of on-chain contract execution and to prevent exposing private data on the publicly viewable blockchain, PrivacyGuard incorporates a novel TEE-based off-chain contract execution engine along with a protocol to securely commit the execution result onto blockchain. We have built and deployed a prototype of PrivacyGuard with Ethereum and Intel SGX. Our experiment result demonstrates that PrivacyGuard fulfills the promised privacy goal and supports analytics on data from a considerable number of data owners.

preprint2020arXiv

TAO Conceptual Design Report: A Precision Measurement of the Reactor Antineutrino Spectrum with Sub-percent Energy Resolution

The Taishan Antineutrino Observatory (TAO, also known as JUNO-TAO) is a satellite experiment of the Jiangmen Underground Neutrino Observatory (JUNO). A ton-level liquid scintillator detector will be placed at about 30 m from a core of the Taishan Nuclear Power Plant. The reactor antineutrino spectrum will be measured with sub-percent energy resolution, to provide a reference spectrum for future reactor neutrino experiments, and to provide a benchmark measurement to test nuclear databases. A spherical acrylic vessel containing 2.8 ton gadolinium-doped liquid scintillator will be viewed by 10 m^2 Silicon Photomultipliers (SiPMs) of >50% photon detection efficiency with almost full coverage. The photoelectron yield is about 4500 per MeV, an order higher than any existing large-scale liquid scintillator detectors. The detector operates at -50 degree C to lower the dark noise of SiPMs to an acceptable level. The detector will measure about 2000 reactor antineutrinos per day, and is designed to be well shielded from cosmogenic backgrounds and ambient radioactivities to have about 10% background-to-signal ratio. The experiment is expected to start operation in 2022.

preprint2020arXiv

Theoretical prediction of a low-energy Stone-Wales graphene with intrinsic type-III Dirac-cone

Based on first-principles method we predict a new low-energy Stone-Wales graphene SW40, which has an orthorhombic lattice with Pbam symmetry and 40 carbon atoms in its crystalline cell forming well-arranged Stone-Wales patterns. The calculated total energy of SW40 is just about 133 meV higher than that of graphene, indicating its excellent stability exceeds all the previously proposed graphene allotropes. We find that SW40 processes intrinsic Type-III Dirac-cone (Phys. Rev. Lett., 120, 237403, 2018) formed by band-crossing of a local linear-band and a local flat-band, which can result in highly anisotropic Fermions in the system. Interestingly, such intrinsic type-III Dirac-cone can be effectively tuned by inner-layer strains and it will be transferred into Type-II and Type-I Dirac-cones under tensile and compressed strains, respectively. Finally, a general tight-binding model was constructed to understand the electronic properties nearby the Fermi-level in SW40. The results show that type-III Dirac-cone feature can be well understood by the $π$-electron interactions between adjacent Stone-Wales defects.

preprint2019arXiv

Cosmic opacity: cosmological-model-independent tests from gravitational waves and Type Ia Supernova

In this paper, we present a scheme to investigate the opacity of the Universe in a cosmological-model-independent way, with the combination of current and future available data in gravitational wave (GW) and electromagnetic (EM) domain. In the FLRW metric, GWs propagate freely through a perfect fluid without any absorption and dissipation, which provides a distance measurement unaffected by the cosmic opacity. Focusing on the simulated data of gravitational waves from the third-generation gravitational wave detector (the Einstein Telescope, ET), as well as the newly-compiled SNe Ia data (JLA and Pantheon sample), we find an almost transparent universe is strongly favored at much higher redshifts ($z\sim 2.26$). Our results suggest that, although the tests of cosmic opacity are not significantly sensitive to its parametrization, a strong degeneracy between the cosmic opacity parameter and the absolute \textit{B}-band magnitude of SNe Ia is revealed in this analysis. More importantly, we obtain that future measurements of the luminosity distances of gravitational waves sources will be much more competitive than the current analyses, which makes it expectable more vigorous and convincing constraints on the cosmic opacity (and consequently on background physical mechanisms) and a deeper understanding of the intrinsic properties of type Ia supernovae in a cosmological-model-independent way.

preprint2019arXiv

On the boundary condition and related instability in the Smoothed Particle Hydrodynamics

In this work, we explore various relevant aspects of the Smoothed Particle Hydrodynamics regarding Burger's equation. The stability, precision, and efficiency of the algorithm are investigated in terms of different implementations. In particular, we argue that the boundary condition plays an essential role in the stability of numerical implementation. Besides, the issue is shown to be closely associated with the initial particle distribution and the interpolation scheme. Among others, we introduce an interpolation scheme termed symmetrized finite particle method. The main advantage of the scheme is that its implementation does not involve any derivative of the kernel function. Concerning the equation of motion, the calculations are carried out using two distinct scenarios where the particles are chosen to be either stationary or dynamically evolved. The obtained results are compared with those obtained by using the standard finite difference method for spatial derivatives. Our numerical results indicate subtle differences between different schemes regarding the choice of boundary condition. In particular, a novel type of instability is observed where the regular distribution is compromised as the particles start to traverse each other. Implications and further discussions of the present study are also addressed.

preprint2019arXiv

Tip enhanced IR imaging with sub-10 nm resolution and hypersensitivity

IR spectroscopy has been widely used for chemical identification and quantitative analysis of reactions occurring in a specific time and space domains by measuring an average signal of the entire system1. Achieving IR measurements with nanometer-scale spatial resolution is highly desirable to obtain a detailed understanding of the composition, structure and function of interfaces2-5. The challenges in IR nanoscopy yet exist owing to the small molecular cross section and pristine optical diffraction limit. Although atomic force microscopy (AFM) based techniques, such as scattering-type scanning near-field optical microscopy and photothermal-induced resonance microscopy (PTIR), can acquire IR spectroscopy in a few tens of nanometer scale resolution6-9, IR measurements with monolayer level sensitivity remains elusive and can only be realized under critical conditions10,11. Herein, we demonstrate sub-10 nm spatial resolution sampling a volume of ~360 molecules with a strong field enhancement at the sample-tip junction by implementing noble metal substrates (Au, Ag, Pt) in photo-induced force microscopy (PiFM). This technique shows versatility and robustness of PiFM, and is promising for application in interfacial studies with hypersensitivity and super spatial resolution.

preprint2017arXiv

Observation of the decay $Λ_c^+\rightarrow Σ^- π^+π^+π^0$

We report the first observation of the decay $Λ^+_{c}\rightarrow Σ^- π^+π^+π^0$, based on data obtained in $e^+e^-$ annihilations with an integrated luminosity of 567~pb$^{-1}$ at $\sqrt{s}=4.6$~GeV. The data were collected with the BESIII detector at the BEPCII storage rings. The absolute branching fraction $\mathcal{B}(Λ^+_{c}\rightarrowΣ^-π^+π^+π^0)$ is determined to be $(2.11\pm0.33({\rm stat.})\pm0.14({\rm syst.}))\%$. In addition, an improved measurement of $\mathcal{B}(Λ^+_{c}\rightarrowΣ^-π^+π^+)$ is determined as $(1.81\pm0.17({\rm stat.})\pm0.09({\rm syst.}))\%$.

preprint2016arXiv

Construction of Cyclic and Constacyclic Codes for b-symbol Read Channels Meeting the Plotkin-like Bound

The symbol-pair codes over finite fields have been raised for symbol-pair read channels and motivated by application of high-density data storage technologies [1, 2]. Their generalization is the code for b-symbol read channels (b > 2). Many MDS codes for b-symbol read channels have been constructed which meet the Singleton-like bound ([3, 4, 10] for b = 2 and [11] for b > 2). In this paper we show the Plotkin-like bound and present a construction on irreducible cyclic codes and constacyclic codes meeting the Plotkin-like bound.

preprint2016arXiv

Improved measurement of the absolute branching fraction of $D^{+}\rightarrow \bar K^0 μ^{+}ν_μ$

By analyzing 2.93 fb$^{-1}$ of data collected at $\sqrt s=3.773$ GeV with the BESIII detector, we measure the absolute branching fraction ${\mathcal B}(D^{+}\rightarrow\bar K^0μ^{+}ν_μ)=(8.72 \pm 0.07_{\rm stat.} \pm 0.18_{\rm sys.})\%$, which is consistent with previous measurements within uncertainties but with significantly improved precision. Combining the Particle Data Group values of ${\mathcal B}(D^0\to K^-μ^+ν_μ)$, ${\mathcal B}(D^{+}\rightarrow\bar K^0 e^{+}ν_{e})$, and the lifetimes of the $D^0$ and $D^+$ mesons with the value of ${\mathcal B}(D^{+}\rightarrow\bar K^0 μ^{+}ν_μ)$ measured in this work, we determine the following ratios of partial widths: $Γ(D^0\to K^-μ^+ν_μ)/Γ(D^{+}\rightarrow\bar K^0μ^{+}ν_μ)=0.963\pm0.044$ and $Γ(D^{+}\rightarrow\bar K^0 μ^{+}ν_μ)/Γ(D^{+}\rightarrow\bar K^0 e^{+}ν_{e})=0.988\pm0.033$.

preprint2016arXiv

Linear Codes over $\mathbb{F}_{q}[x]/(x^2)$ and $GR(p^2,m)$ Reaching the Griesmer Bound

We construct two series of linear codes over finite ring $\mathbb{F}_{q}[x]/(x^2)$ and Galois ring $GR(p^2,m)$ respectively reaching the Griesmer bound. They derive two series of codes over finite field $\mathbb{F}_{q}$ by Gray map. The first series of codes over $\mathbb{F}_{q}$ derived from $\mathbb{F}_{q}[x]/(x^2)$ are linear and also reach the Griesmer bound in some cases. Many of linear codes over finite field we constructed have two Hamming (non-zero) weights.

preprint2016arXiv

Linear Codes over Galois Ring $GR(p^2,r)$ Related to Gauss sums

Linear codes over finite rings become one of hot topics in coding theory after Hommons et al.([4], 1994) discovered that several remarkable nonlinear binary codes with some linear-like properties are the images of Gray map of linear codes over $Z_4$. In this paper we consider two series of linear codes $C(G)$ and $\widetilde{C}(G)$ over Galois ring $R=GR(p^2,r)$, where $G$ is a subgroup of $R^{(s)^*}$ and $R^{(s)}=GR(p^2,rs)$. We present a general formula on $N_β(a)$ in terms of Gauss sums on $R^{(s)}$ for each $a\in R$, where $N_β(a)$ is the number of a-component of the codeword $c_β\in C(G) (β\in R^{(s)})$ (Theorem 3.1). We have determined the complete Hamming weight distribution of $C(G)$ and the minimum Hamming distance of $\widetilde{C}(G)$ for some special G (Theorem 3.3 and 3.4). We show a general formula on homogeneous weight of codewords in $C(G)$ and $\widetilde{C}(G)$ (Theorem 4.5) for the special $G$ given in Theorem 3.4. Finally we obtained series of nonlinear codes over $\mathbb{F}_{q} \ (q=p^r)$ with two Hamming distance by using Gray map (Corollary 4.6).

preprint2016arXiv

Measurement of azimuthal asymmetries in inclusive charged dipion production in $e^+e^-$ annihilations at $\sqrt{s}$ = 3.65 GeV

We present a measurement of the azimuthal asymmetries of two charged pions in the inclusive process $e^+e^-\rightarrow ππX$ based on a data set of 62 $\rm{pb}^{-1}$ at the center-of-mass energy $\sqrt{s}=3.65$ GeV collected with the BESIII detector. These asymmetries can be attributed to the Collins fragmentation function. We observe a nonzero asymmetry, which increases with increasing pion momentum. As our energy scale is close to that of the existing semi-inclusive deep inelastic scattering experimental data, the measured asymmetries are important inputs for the global analysis of extracting the quark transversity distribution inside the nucleon and are valuable to explore the energy evolution of the spin-dependent fragmentation function.

preprint2016arXiv

Measurement of the $D_s^+ \to \ell^+ν_\ell$ branching fractions and the decay constant $f_{D_s^+}$

Using 482~pb$^{-1}$ of $e^+e^-$ collision data collected at a center-of-mass energy of $\sqrt{s} = 4.009$ GeV with the BESIII detector, we measure the branching fractions of the decays $D_s^+\toμ^+ν_μ$ and $D_s^+\toτ^+ν_τ$. By constraining the ratio of decay rates of $D_s^+$ to $τ^+ν_τ$ and to $μ^+ν_μ$ to the Standard Model prediction, the branching fractions are determined to be $\mathcal{B}(D_s^+ \to μ^+ν_μ) = (0.495 \pm 0.067 \pm 0.026)\%$ and $\mathcal{B}(D_s^+ \to τ^+ν_τ) = (4.83 \pm 0.65 \pm 0.26)\%$. Using these branching fractions, we obtain a value for the decay constant $f_{D_s^+}$ of $(241.0 \pm 16.3 \pm 6.5)~\text{MeV}$, where the first error is statistical and the second systematic.

preprint2016arXiv

Measurement of the absolute branching fraction of $D^{+}\rightarrow\bar K^0 e^{+}ν_{e}$ via $\bar K^0\toπ^0π^0$

By analyzing 2.93 fb$^{-1}$ data collected at the center-of-mass energy $\sqrt s=3.773$ GeV with the BESIII detector, we measure the absolute branching fraction of the semileptonic decay $D^+\rightarrow\bar K^0 e^{+}ν_{e}$ to be ${\mathcal B}(D^{+}\rightarrow\bar K^0 e^{+}ν_{e})=(8.59 \pm 0.14 \pm 0.21)\%$ using $\bar K^0\to K^0_S\to π^0π^0$, where the first uncertainty is statistical and the second systematic. Our result is consistent with previous measurements within uncertainties.

preprint2016arXiv

Measurement of the leptonic decay width of $J/ψ$ using initial state radiation

Using a data set of 2.93 fb$^{-1}$ taken at a center-of-mass energy of $\sqrt{s}$ = 3.773 GeV with the BESIII detector at the BEPCII collider, we measure the process $e^+e^-\rightarrow J/ψγ\rightarrow μ^+μ^-γ$ and determine the product of the branching fraction and the electronic width $\mathcal B_{μμ}\cdot Γ_{ee} = (333.4 \pm 2.5_{\rm stat} \pm 4.4_{\rm sys})$~eV. Using the earlier-published BESIII result for $\mathcal B_{μμ}$ = (5.973 $\pm$ 0.007$_{\rm stat}$ $\pm$ 0.037$_{\rm sys}$)\%, we derive the $J/ψ$ electronic width $Γ_{ee}$~= (5.58 $\pm$ 0.05$_{\rm stat}$ $\pm$ 0.08$_{\rm sys}$) keV.

preprint2016arXiv

Measurements of absolute hadronic branching fractions of $Λ_{c}^{+}$ baryon

Using $567\rm{pb}^{-1}$ of $e^+e^-$ collisions recorded at $\sqrt{s}=4.599\rm{GeV}$ with the BESIII detector, we report first measurements of absolute hadronic branching fractions of Cabibbo-favored decays of the $Λ_{c}^{+}$ baryon with a double-tag technique. A global least-square fitter is utilized to improve the measured precision. Among the measurements for twelve $Λ_{c}^{+}$ decay modes, the branching fraction for $Λ_{c}^{+} \rightarrow pK^-π^+$ is determined to be $(5.84\pm0.27\pm0.23)\%$, where the first uncertainty is statistical and the second is systematic. In addition, the measurements of the branching fractions of the other eleven Cabbibo-favored hadronic decay modes are significantly improved.

preprint2016arXiv

New Boys and Girls in Phosphorene Family from Gene Recombination: Different from Parents, Excellent than Parents

Based on the crystal structures of the previously proposed low energy phosphorene allotropes η-P and θ-P (Nano. Lett. 2015, 15, 3557), we propose five new structural stable phosphorene boys (XX-XY or XY-XY) and girls (XX-XX) through gene (XY from η-P and XX from θ-P) recombination methods. All of these five new phosphorene allotropes are obviously different from their parents, showing very different and fascinating two-dimensional patterns between each other. The dynamical stabilities of these phosphorene allotropes are confirmed positive and some of them are confirmed energetically more favorable than their parents (η-P and θ-P). Especially, the XX-XX type girl G1-P is confirmed energetically more favorable than all the previously proposed phosphorene allotropes, including black phosphorene (α-P, ACS Nano, 2014, 8, 4033) and blue phosphorene (β-P, Phys. Rev. Lett. 2014, 112, 176802), which is expected to be synthesized in future experiment through vapor deposition. Our results show that such a new promising phosphorene allotrope G1-P is an excellent candidate for potential applications in nano-electronics according to its middle band gap about 1.58 eV from DFT-HSE06 calculation.

preprint2016arXiv

Observation of $e^{+}e^{-} \to η^{\prime} J/ψ$ at center-of-mass energies between 4.189 and 4.600 GeV

The process $e^{+}e^{-}\to η^{\prime} J/ψ$ is observed for the first time with a statistical significance of $8.6σ$ at center-of-mass energy $\sqrt{s} = 4.226$ GeV and $7.3σ$ at $\sqrt{s} = 4.258$ GeV using data samples collected with the BESIII detector. The Born cross sections are measured to be $(3.7 \pm 0.7 \pm 0.3)$ and $(3.9 \pm 0.8 \pm 0.3)$ pb at $\sqrt{s} = 4.226$ and $4.258$ GeV, respectively, where the first errors are statistical and the second systematic. Upper limits at the 90% confidence level of the Born cross sections are also reported at other 12 energy points.

preprint2016arXiv

Observation of $e^+e^- \rightarrow ωχ_{c1,2}$ near $\sqrt{s}$ = 4.42 and 4.6 GeV

Based on data samples collected with the BESIII detector operating at the BEPCII storage ring at center-of-mass energies $\sqrt{s} >$ 4.4 GeV, the processes $e^+e^- \rightarrow ωχ_{c1,2}$ are observed for the first time. With an integrated luminosity of $1074 pb^{-1}$ near $\sqrt{s} =$ 4.42 GeV, a significant $ωχ_{c2}$ signal is found, and the cross section is measured to be $(20.9 \pm 3.2 \pm 2.5)\pb$. With $567 pb^{-1}$ near $\sqrt{s} =$ 4.6 GeV, a clear $ωχ_{c1}$ signal is seen, and the cross section is measured to be $(9.5 \pm 2.1 \pm 1.3) \pb$, while evidence is found for an $ωχ_{c2}$ signal. The first errors are statistical and the second are systematic. Due to low luminosity or low cross section at other energies, no significant signals are observed. In the $ωχ_{c2}$ cross section, an enhancement is seen around $\sqrt{s} =$ 4.42 GeV. Fitting the cross section with a coherent sum of the $ψ(4415)$ Breit-Wigner function and a phase space term, the branching fraction $\mathcal{B}(ψ(4415)\toωχ_{c2})$ is obtained to be of the order of $10^{-3}$.

preprint2016arXiv

Observation of $h_{c}$ radiative decay $h_{c} \rightarrow γη'$ and evidence for $h_{c} \rightarrow γη$

A search for radiative decays of the $P$-wave spin singlet charmonium resonance $h_c$ is performed based on $4.48 \times 10^{8}$ $ψ'$ events collected with the BESIII detector operating at the BEPCII storage ring. Events of the reaction channels $h_{c} \rightarrow γη'$ and $γη$ are observed with a statistical significance of $8.4 σ$ and $4.0 σ$, respectively, for the first time. The branching fractions of $h_{c} \rightarrow γη'$ and $h_{c} \rightarrow γη$ are measured to be $\mathcal{B}(h_{c} \rightarrow γη')=(1.52 \pm 0.27 \pm 0.29)\times10^{-3}$ and $\mathcal{B}(h_{c} \rightarrow γη)=(4.7 \pm 1.5 \pm 1.4)\times10^{-4}$, respectively, where the first errors are statistical and the second are systematic uncertainties.

preprint2016arXiv

Observation of an anomalous line shape of the $η^{\prime}π^{+}π^{-}$ mass spectrum near the $p\bar{p}$ mass threshold in $J/ψ\rightarrowγη^{\prime}π^{+}π^{-}$

Using $1.09\times10^{9}$ $J/ψ$ events collected by the BESIII experiment in 2012, we study the $J/ψ\rightarrowγη^{\prime}π^{+}π^{-}$ process and observe a significant abrupt change in the slope of the $η^{\prime}π^{+}π^{-}$ invariant mass distribution at the proton-antiproton ($p\bar{p}$) mass threshold. We use two models to characterize the $η^{\prime}π^{+}π^{-}$ line shape around $1.85~\text{GeV}/c^{2}$: one which explicitly incorporates the opening of a decay threshold in the mass spectrum (Flatté formula), and another which is the coherent sum of two resonant amplitudes. Both fits show almost equally good agreement with data, and suggest the existence of either a broad state around $1.85~\text{GeV}/c^{2}$ with strong couplings to $p\bar{p}$ final states or a narrow state just below the $p\bar{p}$ mass threshold. Although we cannot distinguish between the fits, either one supports the existence of a $p\bar{p}$ molecule-like state or bound state with greater than $7σ$ significance.

preprint2016arXiv

Observation of pseudoscalar and tensor resonances in $J/ψ\rightarrow γϕϕ$

Based on a sample of $(1310.6 \pm 10.5) \times 10^{6}$ $J/ψ$ events collected with the BESIII detector operating at the BEPCII storage ring, a partial wave analysis of the decay $J/ψ\rightarrow γϕϕ$ is performed in order to study the intermediate states. Results of the partial wave analysis show that the structures are predominantly $0^{-+}$ states. The existence of the $η(2225)$ is confirmed, and its resonance parameters are measured. Two additional pseudoscalar states, the $η(2100)$ with a mass of $2050_{-24}^{+30}{}_{-26}^{+75}$~MeV/$c^{2}$ and a width of $250_{-30}^{+36}{}_{-164}^{+181}$~MeV/$c^{2}$ and the $X(2500)$ with a mass of $2470_{-19}^{+15}{}_{-23}^{+101}$~MeV/$c^{2}$ and a width of $230_{-35}^{+64}{}_{-33}^{+56}$~MeV/$c^{2}$, are observed. In addition to these three pseudoscalar states, the scalar state $f_0(2100)$, and three tensor states, the $f_2(2010)$, $f_2(2300)$ and $f_2(2340)$, are observed in the process $J/ψ\rightarrow γϕϕ$. The product branching fractions ${\cal B}$($J/ψ\rightarrow γX)\times{\cal B}(X\rightarrow ϕϕ)$ are reported.

preprint2016arXiv

Resonance of Gaussian electromagnetic field to the high frequency gravitational waves

We consider a Gaussian Beam (GB) resonant system for high frequency gravitational waves (HFGWs) detection. At present, we find the optimal signal strength in theory through setting the magnetic component of GB in a standard gaussian form. Under the synchro-resonance condition, we study the signal strength (i.e., transverse perturbative photon fluxes) from the relic HFGWs (predicted by ordinary inflationary model) and the braneworld HFGWs (from braneworld scenarios). Both of them would generate potentially detectable transverse perturbative photon fluxes (PPFs). Furthermore we find optimal system parameters and the relationship between frequency and effective width of energy fluxes accumulation.

preprint2016arXiv

Search for the weak decay $η^{\prime}\to K^{\pm}π^{\mp}$ and precise measurement of the branching fraction ${\cal B}(J/ψ\toϕη^{\prime})$

We present the first search for the rare decay of $η^\prime$ into $K^{\pm}π^{\mp}$ in $J/ψ\toϕη^{\prime}$, using a sample of $1.3\times10^{9}$ $J/ψ$ events collected with the BESIII detector. No significant signal is observed, and the upper limit at the 90\% confidence level for the ratio $\frac{{\cal B}(η^{\prime}\to K^{\pm}π^{\mp})}{{\cal B}(η^{\prime}\toγπ^{+}π^{-})}$ is determined to be $1.3\times10^{-4}$. In addition, we report the measurement of the branching fraction of $J/ψ\toϕη^{\prime}$ to be $(5.10\pm0.03(\text{stat.})\pm0.32(\text{syst.}))\times10^{-4}$, which agrees with previous results from BESII.

preprint2016arXiv

Study of $D^{+} \to K^{-} π^+ e^+ ν_e$

We present an analysis of the decay $D^{+} \to K^{-} π^+ e^+ ν_e$ based on data collected by the BESIII experiment at the $ψ(3770)$ resonance. Using a nearly background-free sample of 18262 events, we measure the branching fraction $\mathcal{B}(D^{+} \to K^{-} π^+ e^+ ν_e) = (3.71 \pm 0.03 \pm 0.08)\%$. For $0.8<m_{Kπ}<1.0$ GeV/$c^{2}$ the partial branching fraction is $\mathcal{B}(D^{+} \to K^{-} π^+ e^+ ν_e)_{[0.8,1]} = (3.33 \pm 0.03 \pm 0.07)\%$. A partial wave analysis shows that the dominant $\bar K^{*}(892)^{0}$ component is accompanied by an \emph{S}-wave contribution accounting for $(6.05\pm0.22\pm0.18)\%$ of the total rate and that other components are negligible. The parameters of the $\bar K^{*}(892)^{0}$ resonance and of the form factors based on the spectroscopic pole dominance predictions are also measured. We also present a measurement of the $\bar K^{*}(892)^{0}$ helicity basis form factors in a model-independent way.

preprint2016arXiv

Study of $J/ψ\to p\bar{p}ϕ$ at BESIII

Using a data sample of $1.31 \times 10^{9}$ $J/ψ$ events accumulated with the BESIII detector, the decay $J/ψ\to p\bar{p}ϕ$ is studied via two decay modes, $ϕ\to K^{0}_{S}K^{0}_{L}$ and $ϕ\to K^{+}K^{-}$. The branching fraction of $J/ψ\to p\bar{p}ϕ$ is measured to be $\mathcal{B}(J/ψ\to p\bar{p}ϕ)=[5.23\pm0.06(\mbox{stat})\pm0.33(\mbox{syst})]\times10^{-5}$, which agrees well with a previously published measurement, but with a significantly improved precision. No evident enhancement near the $p\bar{p}$ mass threshold, denoted as $X(p\bar{p})$, is observed, and the upper limit on the branching fraction of $J/ψ\to X(p\bar{p})ϕ\to p\bar{p}ϕ$ is determined to be $\mathcal{B}(J/ψ\to X(p\bar{p})ϕ\to p\bar{p}ϕ)<2.1\times10^{-7}$ at the 90\% confidence level.

preprint2016arXiv

Study of $ψ$ decays to the $Ξ^{-}\barΞ^{+}$ and $Σ(1385)^{\mp}\barΣ(1385)^{\pm}$ final states

We study the decays of the charmonium resonances $J/ψ$ and $ψ(3686)$ to the final states $Ξ^{-}\barΞ^{+}$, $Σ(1385)^{\mp}\barΣ(1385)^{\pm}$ based on a single baryon tag method using data samples of $(223.7 \pm 1.4) \times 10^{6}$ $J/ψ$ and $(106.4 \pm 0.9) \times 10^{6}$ $ψ(3686)$ events collected with the BESIII detector at the BEPCII collider. The decay $ψ(3686)\rightarrowΣ(1385)^{\mp}\barΣ(1385)^{\pm}$ is observed for the first time, and the measurements of the other processes, including the branching fractions and angular distributions, are in good agreement with and much more precise than the previously published results. Additionally, the ratios $\frac{\cal{B}(ψ(3686)\rightarrowΞ^{-}\barΞ^{+})}{\cal{B}(J/ψ\rightarrowΞ^{-}\barΞ^{+})}$, $\frac{\cal{B}(ψ(3686)\rightarrowΣ(1385)^{-}\barΣ(1385)^{+})}{\cal{B}(J/ψ\rightarrowΣ(1385)^{-}\barΣ(1385)^{+})}$ and $\frac{\cal{B}(ψ(3686)\rightarrowΣ(1385)^{+}\barΣ(1385)^{-})}{\cal{B}(J/ψ\rightarrowΣ(1385)^{+}\barΣ(1385)^{-})}$ are determined.

Jin Li

What is connected

Connect this record

See the researcher in context

Building this map preview

122 published item(s)

AnyECG: Evolved ECG Foundation Model for Holistic Health Profiling

Gaussian Relational Graph Transformer

A Framework for Mutual Information-based MIMO Integrated Sensing and Communication Beamforming Design

A Multi-level Acoustic Feature Extraction Framework for Transformer Based End-to-End Speech Recognition

Adaptive Domain Interest Network for Multi-domain Recommendation

AI-enabled Automatic Multimodal Fusion of Cone-Beam CT and Intraoral Scans for Intelligent 3D Tooth-Bone Reconstruction and Clinical Applications

An efficient real-time target tracking algorithm using adaptive feature fusion

ApolloRL: a Reinforcement Learning Platform for Autonomous Driving

CaTT-KWS: A Multi-stage Customized Keyword Spotting Framework based on Cascaded Transducer-Transformer

Coarse-to-Fine Sparse Sequential Recommendation

Complementary Calibration: Boosting General Continual Learning with Collaborative Distillation and Self-Supervision

Construction of MDS self-dual codes from generalized Reed-Solomon codes

GraphEye: A Novel Solution for Detecting Vulnerable Functions Based on Graph Attention Network

High precision measurement of cosmic curvature: from gravitational waves and cosmic chronometer

Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback

Multiple Targets Directed Greybox Fuzzing

Neural Points: Point Cloud Representation with Neural Fields for Arbitrary Upsampling

Simulation of a Xe-based X-ray Polarimeter at 10-30 keV

Wavelet Transform-assisted Adaptive Generative Modeling for Colorization

On the correspondence between energy conservation and energy-momentum tensor conservation in cosmology

Simulation on the Transparency of Electrons and Ion Back Flow for a Time Projection Chamber based on Staggered Multiple THGEMs

Truncation-Free Matching System for Display Advertising at Alibaba

A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction

Controllable List-wise Ranking for Universal No-reference Image Quality Assessment

Fast Reinforcement Learning for Anti-jamming Communications

Feasibility and physics potential of detecting $^8$B solar neutrinos at JUNO

Frequency stabilization and tuning of breathing soliton in SiN microresonators

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising

Measuring the viscosity of dark matter with strongly lensed gravitational waves

New structure canditates for the experimentally synthesized heptazine-based and triazine-based two dimensional graphitic carbon nitride

Observation of a cross-section enhancement near mass threshold in $e^{+}e^{-}\rightarrowΛ\barΛ$

PrivacyGuard: Enforcing Private Data Usage Control with Blockchain and Attested Off-chain Contract Execution

TAO Conceptual Design Report: A Precision Measurement of the Reactor Antineutrino Spectrum with Sub-percent Energy Resolution

Theoretical prediction of a low-energy Stone-Wales graphene with intrinsic type-III Dirac-cone

Cosmic opacity: cosmological-model-independent tests from gravitational waves and Type Ia Supernova

On the boundary condition and related instability in the Smoothed Particle Hydrodynamics

Tip enhanced IR imaging with sub-10 nm resolution and hypersensitivity

Observation of the decay $Λ_c^+\rightarrow Σ^- π^+π^+π^0$

Construction of Cyclic and Constacyclic Codes for b-symbol Read Channels Meeting the Plotkin-like Bound

Improved measurement of the absolute branching fraction of $D^{+}\rightarrow \bar K^0 μ^{+}ν_μ$

Linear Codes over $\mathbb{F}_{q}[x]/(x^2)$ and $GR(p^2,m)$ Reaching the Griesmer Bound

Linear Codes over Galois Ring $GR(p^2,r)$ Related to Gauss sums

Measurement of azimuthal asymmetries in inclusive charged dipion production in $e^+e^-$ annihilations at $\sqrt{s}$ = 3.65 GeV

Measurement of the $D_s^+ \to \ell^+ν_\ell$ branching fractions and the decay constant $f_{D_s^+}$

Measurement of the absolute branching fraction of $D^{+}\rightarrow\bar K^0 e^{+}ν_{e}$ via $\bar K^0\toπ^0π^0$

Measurement of the leptonic decay width of $J/ψ$ using initial state radiation

Measurements of absolute hadronic branching fractions of $Λ_{c}^{+}$ baryon

New Boys and Girls in Phosphorene Family from Gene Recombination: Different from Parents, Excellent than Parents

Observation of $e^{+}e^{-} \to η^{\prime} J/ψ$ at center-of-mass energies between 4.189 and 4.600 GeV

Observation of $e^+e^- \rightarrow ωχ_{c1,2}$ near $\sqrt{s}$ = 4.42 and 4.6 GeV

Observation of $h_{c}$ radiative decay $h_{c} \rightarrow γη'$ and evidence for $h_{c} \rightarrow γη$

Observation of an anomalous line shape of the $η^{\prime}π^{+}π^{-}$ mass spectrum near the $p\bar{p}$ mass threshold in $J/ψ\rightarrowγη^{\prime}π^{+}π^{-}$

Observation of pseudoscalar and tensor resonances in $J/ψ\rightarrow γϕϕ$

Resonance of Gaussian electromagnetic field to the high frequency gravitational waves

Search for the weak decay $η^{\prime}\to K^{\pm}π^{\mp}$ and precise measurement of the branching fraction ${\cal B}(J/ψ\toϕη^{\prime})$

Study of $D^{+} \to K^{-} π^+ e^+ ν_e$

Study of $J/ψ\to p\bar{p}ϕ$ at BESIII

Study of $ψ$ decays to the $Ξ^{-}\barΞ^{+}$ and $Σ(1385)^{\mp}\barΣ(1385)^{\pm}$ final states

An amplitude analysis of the $π^{0}π^{0}$ system produced in radiative $J/ψ$ decays

Compound Poisson Processes, Latent Shrinkage Priors and Bayesian Nonconvex Penalization

Confirmation of a charged charmoniumlike state $Z_c(3885)^{\mp}$ in $e^+e^-\toπ^{\pm}(D\bar{D}^*)^\mp$ with double $D$ tag

Dark Matter Directionality Revisited with a High Pressure Xenon Gas Detector

Directional dark matter by polar angle direct detection and application of columnar recombination

Exothermic isospin-violating dark matter after SuperCDMS and CDEX

Measurement of $\mathcal B(ψ(3770)\toγχ_{c1})$ and search for $ψ(3770)\toγχ_{c2}$

Measurement of $y_{CP}$ in $D^0-\overline{D}^0$ oscillation using quantum correlations in $e^+e^-\to D^0\overline{D}^0$ at $\sqrt{s}$ = 3.773\,GeV

Measurement of the $\mathrm e^+\mathrm e^-\rightarrow\mathrmπ^+\mathrmπ^-$ Cross Section between 600 and 900 MeV Using Initial State Radiation

Measurement of the $e^{+}e^{-} \to ηJ/ψ$ cross section and search for $e^{+}e^{-} \to π^{0} J/ψ$ at center-of-mass energies between 3.810 and 4.600~GeV

Measurement of the branching fraction for $ψ(3770) \to γχ_{c0}$

Measurement of the branching fractions of $D_{s}^{+}\rightarrow η'X$ and $D_{s}^{+}\rightarrow η'ρ^{+}$ in $e^+e^-\to D^+_{s}D^-_{s}$

Measurement of the form factors in the decay $D^+ \to ωe^+ ν_{e}$ and search for the decay $D^+ \to ϕe^+ ν_{e}$

Measurement of the Matrix Elements for the Decays $η\rightarrow π^{+}π^{-}π^0$ and $η/η^{\prime}\rightarrowπ^0π^0π^0$

Measurement of the proton form factor by studying $e^{+} e^{-}\rightarrow p\bar{p}$

Measurements of $ψ(3686) \to K^{-} Λ\barΞ^{+} +c.c.$ and $ψ(3686) \to γK^{-} Λ\barΞ^{+} +c.c$

Observation of a neutral charmoniumlike state $Z_c(4025)^0$ in $e^{+} e^{-} \to (D^{} \bar{D}^{})^{0} π^0$

Observation of a Neutral Structure near the $D\bar{D}^{}$ Mass Threshold in $e^{+}e^{-}\to (D \bar{D}^)^0π^0$ at $\sqrt{s}$ = 4.226 and 4.257 GeV