arXiv subjects

Jiang Li

Publications and source records attributed to Jiang Li.

At least 73 records · Page 4Linked to original sources

arXiv2022

Duration of and time to response in oncology clinical trials from the perspective of the estimand framework

Duration of response (DOR) and time to response (TTR) are typically evaluated as secondary endpoints in early-stage clinical studies in oncology when efficacy is assessed by the best overall response (BOR) and presented as the overall response rate (ORR). Despite common use of DOR and TTR in particular in single-arm studies, the definition of these endpoints and the questions they are intended to answer remain unclear. Motivated by the estimand framework, we present relevant scientific questions of interest for DOR and TTR and propose corresponding estimand definitions. We elaborate on how to deal with relevant intercurrent events which should follow the same considerations as implemented for the primary response estimand. A case study in mantle cell lymphoma illustrates the implementation of relevant estimands of DOR and TTR. We close the paper with practical recommendations to implement DOR and TTR in clinical study protocols.

stat.ME↗

arXiv2022

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results. In this challenge, the new Large-scale Diverse Video (LDV) dataset is employed. The challenge has three tracks. Tracks 1 and 2 aim at enhancing the videos compressed by HEVC at a fixed QP, while Track 3 is designed for enhancing the videos compressed by x265 at a fixed bit-rate. Besides, the quality enhancement of Tracks 1 and 3 targets at improving the fidelity (PSNR), and Track 2 targets at enhancing the perceptual quality. The three tracks totally attract 482 registrations. In the test phase, 12 teams, 8 teams and 11 teams submitted the final results of Tracks 1, 2 and 3, respectively. The proposed methods and solutions gauge the state-of-the-art of video quality enhancement. The homepage of the challenge: https://github.com/RenYang-home/NTIRE21_VEnh

eess.IV↗

arXiv2022

SciEv: Finding Scientific Evidence Papers for Scientific News

In the past decade, many scientific news media that report scientific breakthroughs and discoveries emerged, bringing science and technology closer to the general public. However, not all scientific news article cites proper sources, such as original scientific papers. A portion of scientific news articles contain misinterpreted, exaggerated, or distorted information that deviates from facts asserted in the original papers. Manually identifying proper citations is laborious and costly. Therefore, it is necessary to automatically search for pertinent scientific papers that could be used as evidence for a given piece of scientific news. We propose a system called SciEv that searches for scientific evidence papers given a scientific news article. The system employs a 2-stage query paradigm with the first stage retrieving candidate papers and the second stage reranking them. The key feature of SciEv is it uses domain knowledge entities (DKEs) to find candidates in the first stage, which proved to be more effective than regular keyphrases. In the reranking stage, we explore different document representations for news articles and candidate papers. To evaluate our system, we compiled a pilot dataset consisting of 100 manually curated (news,paper) pairs from ScienceAlert and similar websites. To our best knowledge, this is the first dataset of this kind. Our experiments indicate that the transformer model performs the best for DKE extraction. The system achieves a P@1=50%, P@5=71%, and P@10=74% when it uses a TFIDF-based text representation. The transformer-based re-ranker achieves a comparable performance but costs twice as much time. We will collect more data and test the system for user experience.

cs.IR↗

arXiv2021

Optical Kerr nonlinearity and multi-photon absorption of DSTMS measured by Z-scan method

We investigate the optical Kerr nonlinearity and multi-photon absorption (MPA) properties of DSTMS excited by femtosecond pulses at a wavelengths of 1.43 μm, which is optimal for terahertz generation via difference frequency mixing. The MPA and the optical Kerr coefficients of DSTMS at 1.43 μm are strongly anisotropic indicating a dominating contribution from cascaded 2nd-order nonlinearity. These results suggest that the saturation of the THz generation efficiency is mainly related to the MPA process and to a spectral broadening caused by cascaded 2nd-order frequency mixing within DSTMS

physics.optics↗

arXiv2021

JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu

In modern internet industries, deep learning based recommender systems have became an indispensable building block for a wide spectrum of applications, such as search engine, news feed, and short video clips. However, it remains challenging to carry the well-trained deep models for online real-time inference serving, with respect to the time-varying web-scale traffics from billions of users, in a cost-effective manner. In this work, we present JIZHI - a Model-as-a-Service system - that per second handles hundreds of millions of online inference requests to huge deep models with more than trillions of sparse parameters, for over twenty real-time recommendation services at Baidu, Inc. In JIZHI, the inference workflow of every recommendation request is transformed to a Staged Event-Driven Pipeline (SEDP), where each node in the pipeline refers to a staged computation or I/O intensive task processor. With traffics of real-time inference requests arrived, each modularized processor can be run in a fully asynchronized way and managed separately. Besides, JIZHI introduces heterogeneous and hierarchical storage to further accelerate the online inference process by reducing unnecessary computations and potential data access latency induced by ultra-sparse model parameters. Moreover, an intelligent resource manager has been deployed to maximize the throughput of JIZHI over the shared infrastructure by searching the optimal resource allocation plan from historical logs and fine-tuning the load shedding policies over intermediate system feedback. Extensive experiments have been done to demonstrate the advantages of JIZHI from the perspectives of end-to-end service latency, system-wide throughput, and resource consumption. JIZHI has helped Baidu saved more than ten million US dollars in hardware and utility costs while handling 200% more traffics without sacrificing inference efficiency.

cs.IR↗

arXiv2021

High-entropy van der Waals materials formed from mixed metal dichalcogenides, halides and phosphorus trisulfides

The charge, spin, and composition degrees of freedom in high-entropy alloy endow it with tunable valence and spin states, infinite combinations and excellent mechanical performance. Meanwhile, the stacking, interlayer, and angle degrees of freedom in van der Waals material bring it with exceptional features and technological applications. Integration of these two distinct material categories while keeping their merits would be tempting. Based on this heuristic thinking, we design and explore a new range of materials (i.e., dichalcogenides, halides and phosphorus trisulfides) with multiple metallic constitutions and intrinsic layered structure, which are coined as high-entropy van der Waals materials. Millimeter-scale single crystals with homogeneous element distribution can be efficiently acquired and easily exfoliated or intercalated in this materials category. Multifarious physical properties like superconductivity, magnetic ordering, metal-insulator transition and corrosion resistance have been exploited. Further research based on the concept of high-entropy van der Waals materials will enrich the high-throughput design of new systems with intriguing properties and practical applications.

cond-mat.mtrl-sci↗

arXiv2021

DNA origami

Biological materials are self-assembled with near-atomic precision in living cells, whereas synthetic 3D structures generally lack such precision and controllability. Recently, DNA nanotechnology, especially DNA origami technology, has been useful in the bottom-up fabrication of well-defined nanostructures ranging from tens of nanometres to sub-micrometres. In this Primer, we summarize the methodologies of DNA origami technology, including origami design, synthesis, functionalization and characterization. We highlight applications of origami structures in nanofabrication, nanophotonics and nanoelectronics, catalysis, computation, molecular machines, bioimaging, drug delivery and biophysics. We identify challenges for the field, including size limits, stability issues and the scale of production, and discuss their possible solutions. We further provide an outlook on next-generation DNA origami techniques that will allow in vivo synthesis and multiscale manufacturing.

physics.bio-ph↗

arXiv2020

AUSN: Approximately Uniform Quantization by Adaptively Superimposing Non-uniform Distribution for Deep Neural Networks

Quantization is essential to simplify DNN inference in edge applications. Existing uniform and non-uniform quantization methods, however, exhibit an inherent conflict between the representing range and representing resolution, and thereby result in either underutilized bit-width or significant accuracy drop. Moreover, these methods encounter three drawbacks: i) the absence of a quantitative metric for in-depth analysis of the source of the quantization errors; ii) the limited focus on the image classification tasks based on CNNs; iii) the unawareness of the real hardware and energy consumption reduced by lowering the bit-width. In this paper, we first define two quantitative metrics, i.e., the Clipping Error and rounding error, to analyze the quantization error distribution. We observe that the boundary- and rounding- errors vary significantly across layers, models and tasks. Consequently, we propose a novel quantization method to quantize the weight and activation. The key idea is to Approximate the Uniform quantization by Adaptively Superposing multiple Non-uniform quantized values, namely AUSN. AUSN is consist of a decoder-free coding scheme that efficiently exploits the bit-width to its extreme, a superposition quantization algorithm that can adapt the coding scheme to different DNN layers, models and tasks without extra hardware design effort, and a rounding scheme that can eliminate the well-known bit-width overflow and re-quantization issues. Theoretical analysis~(see Appendix A) and accuracy evaluation on various DNN models of different tasks show the effectiveness and generalization of AUSN. The synthesis~(see Appendix B) results on FPGA show $2\times$ reduction of the energy consumption, and $2\times$ to $4\times$ reduction of the hardware resource.

eess.SP↗

arXiv2020

Ghost spintronic THz-emitter-array microscope

Terahertz (THz) wave shows great potential in non-destructive testing, bio detection and cancer imaging. Recent progresses on THz wave near-field probes/apertures enable mechanically raster scanning of an object's surface in the near-field region, while an efficient, non-scanning, non-invasive, deeply sub-diffraction-limited imaging still remains challenging. Here, we demonstrate a THz near-field microscopy using a reconfigurable spintronic THz emitter array (STEA) with computational ghost imaging. By illuminating an object with the reconfigurable STEA in near field and computing the correlation measurements, we reconstruct its image with deeply sub-diffraction resolution. By circulating an external magnetic field, the in-line polarization rotation of THz waves is realized, making the fused image contrast polarization-free. The time-of-flight (TOF) measurements of coherent THz pulses further enables to resolve objects at different distances or depths. The demonstrated ghost spintronic THz-emitter-array microscope (GHOSTEAM) is a new imaging tool for THz near-field real-time imaging (with potential of video framerate), especially opening up paradigm-shift opportunities in non-intrusive label-free bioimaging in a broadband frequency range from 0.1 THz to 30 THz (namely 3.3-1000 cm-1).

physics.optics↗

arXiv2019

High-performance silicon-graphene hybrid plasmonic waveguide photodetectors beyond 1.55 μm

A fast silicon-graphene hybrid plasmonic waveguide photodetectors beyond 1.55 μm is proposed and realized by introducing an ultra-thin wide silicon-on-insulator ridge core region with a narrow metal cap. With this novel design, the light absorption in graphene is enhanced while the metal absorption loss is reduced simultaneously, which helps greatly improve the responsivity as well as shorten the absorption region for achieving fast responses. Furthermore, metal-graphene-metal sandwiched electrodes are introduced to reduce the metal-graphene contact resistance, which is also helpful for improving the response speed. When the photodetector operates at 2 μm, the measured 3dB-bandwidth is >20 GHz (which is limited by the experimental setup) while the 3dB-bandwith calculated from the equivalent circuit with the parameters extracted from the measured S11 is as high as ~100 GHz. To the best of our knowledge, it is the first time to report the waveguide photodetector at 2 μm with a 3dB-bandwidth over 20 GHz. Besides, the present photodetectors also work very well at 1.55 μm. The measured responsivity is about 0.4 A/W under a bias voltage of -0.3 V for an optical power of 0.16 mW, while the measured 3dB-bandwidth is over 40 GHz (limited by the test setup) and the 3 dB-bandwidth estimated from the equivalent circuit is also as high as ~100 GHz, which is one of the best results reported for silicon-graphene photodetectors at 1.55 μm.

physics.app-ph↗

arXiv2018

High-speed and high-responsivity hybrid silicon/black-phosphorus waveguide photodetectors at 2 μm

Silicon photonics is being extended from the near-infrared (near-IR) window of 1.3-1.5 μm for optical fiber communications to the mid-infrared (mid-IR) wavelength-band of 2 μm or longer for satisfying the increasing demands in many applications. Mid-IR waveguide photodetectors on silicon have attracted intensive attention as one of the indispensable elements for various photonic systems. Previously high-performance waveguide photodetectors on silicon were realized for the near-IR window of 1.3-1.5 μm by introducing another semiconductor material (e.g., Ge, and III-V compounds) in the active region. Unfortunately, these traditional semiconductor materials do not work well for the wavelength of ~2 μm or longer because the light absorption becomes very weak. As an alternative, two-dimensional materials provide a new and promising option for enabling active photonic devices on silicon. Here black-phosphorus (BP) thin films with optimized medium thicknesses (~40 nm) are introduced as the active material for light absorption and silicon/BP hybrid ridge waveguide photodetectors are demonstrated with a high responsivity at a low bias voltage. And up to 4.0Gbps data transmission is achieved at 2μm.

physics.app-ph↗

arXiv2016

Deep Models for Engagement Assessment With Scarce Label Information

Task engagement is defined as loadings on energetic arousal (affect), task motivation, and concentration (cognition). It is usually challenging and expensive to label cognitive state data, and traditional computational models trained with limited label information for engagement assessment do not perform well because of overfitting. In this paper, we proposed two deep models (i.e., a deep classifier and a deep autoencoder) for engagement assessment with scarce label information. We recruited 15 pilots to conduct a 4-h flight simulation from Seattle to Chicago and recorded their electroencephalograph (EEG) signals during the simulation. Experts carefully examined the EEG signals and labeled 20 min of the EEG data for each pilot. The EEG signals were preprocessed and power spectral features were extracted. The deep models were pretrained by the unlabeled data and were fine-tuned by a different proportion of the labeled data (top 1%, 3%, 5%, 10%, 15%, and 20%) to learn new representations for engagement assessment. The models were then tested on the remaining labeled data. We compared performances of the new data representations with the original EEG features for engagement assessment. Experimental results show that the representations learned by the deep models yielded better accuracies for the six scenarios (77.09%, 80.45%, 83.32%, 85.74%, 85.78%, and 86.52%), based on different proportions of the labeled data for training, as compared with the corresponding accuracies (62.73%, 67.19%, 73.38%, 79.18%, 81.47%, and 84.92%) achieved by the original EEG features. Deep models are effective for engagement assessment especially when less label information was used for training.

cs.CV↗

arXiv2015

Broadband dispersion engineered microresonator on-a-chip

Control of dispersion in fibre optical waveguides is of critical importance to optical fibre communications systems and more recently for continuum generation from the ultraviolet to the mid-infrared. The wavelength at which the group velocity dispersion crosses zero can be set by varying fibre core diameter or index step. Moreover, sophisticated methods to manipulate higher-order dispersion so as shape and even flatten dispersion over wide bandwidths are possible using multi-cladding fibre. Here we introduce design and fabrication techniques that allow analogous dispersion control in chip-integrated optical microresonators, and thereby demonstrate higher-order, wide-bandwidth dispersion control over an octave of spectrum. Importantly, the fabrication method we employ for dispersion control simultaneously permits optical Q factors above 100 million, which is critical for efficient operation of nonlinear optical oscillators. Dispersion control in high Q systems has taken on greater importance in recent years with increased interest in chip-integrable optical frequency combs.

physics.optics↗

arXiv2015

Conjugate adaptive optics in widefield microscopy with an extended-source wavefront sensor

Adaptive optics is a strategy to compensate for sample-induced aberrations in microscopy applications. Generally, it requires the presence of "guide stars" in the sample to serve as localized reference targets. We describe an implementation of conjugate adaptive optics that is amenable to widefield (i.e. non-scanning) microscopy, and can provide aberration corrections over potentially large fields of view without the use of guide stars. A unique feature of our implementation is that it is based on wavefront sensing with a single-shot partitioned-aperture sensor that provides large dynamic range compatible with extended samples. Combined information provided by this sensor and the imaging camera enable robust image de-blurring based on a rapid estimation of sample and aberrations obtained by closed-loop feedback. We present the theoretical principle of our technique and proof of concept experimental demonstrations.

physics.optics↗

arXiv2013

Measurement and Analysis of Fission Rates in a Spherical Mockup of Uranium and Polyethylene

Measurements of the reaction rate distribution were carried out using two kinds of Plate Micro Fission Chamber(PMFC). The first is a depleted uranium chamber and the second an enriched uranium chamber. The material in the depleted uranium chamber is strictly the same as the material in the uranium assembly. With the equation solution to conduct the isotope contribution correction, the fission rate of 238U and 235U were obtained from the fission rate of depleted uranium and enriched uranium. And then, the fission count of 238U and 235U in an individual uranium shell was obtained. In this work, MCNP5 and continuous energy cross sections ENDF/BV.0 were used for the analysis of fission rate distribution and fission count. The calculated results were compared with the experimental ones. The calculation of fission rate of DU and EU were found to agree with the measured ones within 10% except at the positions in polyethylene region and the two positions near the outer surface. Beacause the fission chamber was not considered in the calculation of the fission counts of 238U and 235U, the calculated results did not agree well with the experimental ones.

physics.ins-det↗

arXiv2012

Low-Pump-Power, Low-Phase-Noise, and Microwave to Millimeter-wave Repetition Rate Operation in Microcombs

Microresonator-based frequency combs (microcombs or Kerr-combs) can potentially miniaturize the numerous applications of conventional frequency combs. A priority is the realization of broad-band (ideally octave spanning) spectra at detectable repetition rates for comb self referencing. However, access to these rates involves pumping larger mode volumes and hence higher threshold powers. Moreover, threshold power sets both the scale for power per comb tooth and also the optical pump. Along these lines, it is shown that a class of resonators having surface-loss-limited Q factors can operate over a wide range of repetition rates with minimal variation in threshold power. A new, surface-loss-limited resonator illustrates the idea. Comb generation on mode spacings ranging from 2.6 GHz to 220 GHz with overall low threshold power (as low as 1 mW) is demonstrated. A record number of comb lines for a microcomb (around 1900) is also observed with pump power of 200 mW. The ability to engineer a wide range of repetition rates with these devices is also used to investigate a recently observed mechanism in microcombs associated with dispersion of subcomb offset frequencies. We observe high-coherence, phase-locking in cases where these offset frequencies are small enough so as to be tuned into coincidence. In these cases, a record-low microcomb phase noise is reported at a level comparable to an open-loop, high-performance microwave oscillator.

physics.optics↗

arXiv2012

Chip-based Brillouin lasers as spectral purifiers for photonic systems

High coherence lasers are essential in a wide range of applications, however, such performance is normally associated with large laser cavities, because increasing energy storage reduces quantum phase noise and also renders the laser frequency less sensitive to cavity vibration. This basic scaling rule is at odds with an emerging set of optical systems that place focus on compact (optimally integrable) sources of high coherence light. These include phase-coherent optical communication using quadrature-amplitude-modulation, and also record-low phase noise microwave sources based upon optical comb techniques. In this work, the first, chip-based Brillouin laser is demonstrated. It features high-efficiency and single-line operation with the smallest recorded Schawlow-Townes frequency noise for any chip-based laser. Because the frequency offset between the laser's emission and the input pump is relatively small, the device provides a new function: spectral purification of compact, low coherence sources such as semiconductor lasers.

physics.optics↗

arXiv2011

Ultra-high-Q wedge-resonator on a silicon chip

Ultra-high-Q optical resonators are being studied across a wide range of research subjects including quantum information, nonlinear optics, cavity optomechanics, and telecommunications. Here, we demonstrate a new, resonator on-a-chip with a record Q factor of 875 million, surpassing even microtoroids. Significantly, these devices avoid a highly specialized processing step that has made it difficult to integrate microtoroids with other photonic devices and to also precisely control their size. Thus, these devices not only set a new benchmark for Q factor on a chip, but also provide, for the first time, full compatibility of this important device class with conventional semiconductor processing. This feature will greatly expand the possible kinds of system on a chip functions enabled by ultra-high-Q devices.

physics.optics↗