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arXiv 2024年

作者： Wang, Ping Chen, Chong Liao, Hao Vorobyov, Vadim V. Wrachtrup, Jörg Liu, Ren-Bao College of Education for the Future Beijing Normal University Zhuhai519087 China Department of Physics The Chinese University of Hong Kong New Territories Shatin Hong Kong Centre for Quantum Coherence The Chinese University of Hong Kong New Territories Shatin Hong Kong The Hong Kong Institute of Quantum Information Science and Technology The Chinese University of Hong Kong New Territories Shatin Hong Kong National Engineering Laboratory on Big Data System Computing Technology Guangdong Province Engineering Center of China-made High Performance Data Computing System College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China 3rd Institute of Physics Research Center SCoPE and IQST University of Stuttgart Stuttgart70569 Germany New Cornerstone Science Laboratory The Chinese University of Hong Kong New Territories Shatin Hong Kong

Test of macroscopic realism (MR) is key to understanding the foundation of quantum mechanics. Due to the existence of the non-invasive measurability loophole and other interpretation loopholes, however, such test remains an open question. Here we propose a general inequality based on high-order correlations of measurements for a loophole-free test of MR at the weak signal limit. Importantly, the inequality is established using the statistics of raw data recorded by classical devices, without requiring a specific model for the measurement process, so its violation would falsify MR without the interpretation loophole. The non-invasive measurability loophole is also closed, since the weak signal limit can be verified solely by measurement data (using the relative scaling behaviors of different orders of correlations). We demonstrate that the inequality can be broken by a quantum spin model. The inequality proposed here provides an unambiguous test of the MR principle and is also useful to characterizing quantum coherence. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum theory

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Adaptive Surrogate Model for Failure Probability Estimation 21

Adaptive Surrogate Model for Failure Probability Estimation

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5th International Conference on Computer Science and Application Engineering, CSAE 2021

作者： Qin, Yi Zhang, Yue Liu, Zexin Zhu, Xueyu Wang, Peng School of Mathematical Sciences Beihang University Haidian District Beijing China School of Integrated Circuit Science and Engineering Beihang University Haidian District Beijing China Department of Mathematics University of Utah Salt Lake CityUtah United States Scientific Computing and Imaging Institute University of Utah Salt Lake CityUtah United States Department of Mathematics University of Iowa Iowa City United States Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Haidian District Beijing China

ISBN: (纸本)9781450389853

Estimating failure probability becomes a fundamental task in many complex engineering designs and optimizations. Yet, evaluation of failure probability via direct sampling from a given system can be computationally expensive and sometimes impossible. Although the construction of a response surface/surrogate could reduce such computational cost, reliance on its sampling alone may still yield an erroneous estimate of the failure probability. In this paper, we employ generalized polynomial chaos and develop an adaptive method whose surrogate model evolves with the additional data sampled from the underlying system as the iteration proceeds. It is more flexible by not requiring an accurate surrogate model in priori. Via three distinct numerical examples and one practical problem on a spintronic device, we demonstrate that our novel scheme provides an efficient tool to estimate system failure probability.. © 2021 Association for computing Machinery. All rights reserved.

关键词： Iterative methods

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Z16b,a natural compound from Ganoderma cochlear is a novel RyR2 stabilizer preventing catecholaminergic polymorphic ventricular tachycardia

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中国药理学报（英文版） 2022年第9期43卷 2340-2350页

作者： Jiang-fan Wan Gang Wang Fu-ying Qin Dan-ling Huang Yan Wang Ai-ling Su Hai-ping Zhang Yang Liu Shao-yin Zeng Chao-liang Wei Yong-xian Cheng Jie Liu Guangdong Key Laboratory of Genome Stability and Human Disease Prevention Department of PathophysiologySchool of MedicineShenzhen UniversityShenzhen 518000China College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060China Guangdong Key Laboratory of Genome Stability and Human Disease Prevention Department of PathophysiologySchool of MedicineShenzhen UniversityShenzhen 518000China School of Pharmaceutical Sciences Shenzhen University Health Science CenterShenzhen 518000China Center for Translation Medicine Research and Development Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518000China Center for High Performance Computing Joint Engineering Research Center for Health Big Data Intelligent Analysis TechnologyShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518000China Guangdong Cardiovascular Institute Guangdong Provincial People's HospitalGuangdong Academy of Medical SciencesGuangzhou 510000China Guangdong Provincial key laboratory of South China Structure Heart Disease Department of Pediatric CardiologyGuangdong Cardiovascular InstituteGuangdong Provincial People's HospitalGuangdong Academy of Medical SciencesGuangzhou 510000China

Catecholaminergic polymorphic ventricular tachycardia(CPVT)is an inherited,lethal ventricular arrhythmia triggered by *** in genes that encode cardiac ryanodine receptor(RyR2)and proteins that regulate RyR2 activity cause enhanced diastolic Ca2+release(leak)through the RyR2 channels,resulting in *** therapies for CPVT are *** found that Z16b,a meroterpenoid isolated from Ganoderma cochlear,inhibited Ca2+spark frequency(CaSF)in R2474S/+cardiomyocytes in a dose-dependent manner,with an IC50 of 3.2 μM.Z16b also dose-dependently suppressed abnormal post-pacing Ca2+release *** injection(i.p.)of epinephrine and caffeine stimulated sustained ventricular tachycardia in all R2474S/+mice,while pretreatment with Z16b(0.5 mg/kg,i.p.)prevented ventricular arrhythmia in 9 of 10 mice,and Z16b administration immediately after the onset of VT abolished sVT in 9 of 12 *** translational significance,Z16b significantly inhibited CaSF and abnormal Ca2+release events in human CPVT ***,Z16b interacts with RyR2,enhancing the"zipping"state of the N-terminal and central domains of RyR2.A molecular docking simulation and point mutation and pulldown assays identified Z16b forms hydrogen bonds with Arg626,His1670,and Gln2126 in RyR2 as a triangle shape that anchors the NTD and CD interaction and thus stabilizes RyR2 in a tight"zipping"*** findings support that Z16b is a novel RyR2 stabilizer that can prevent *** may also serve as a lead compound with a new scaffold for the design of safer and more efficient drugs for treating CPVT.

关键词： arrhythmia catecholaminergic polymorphic ventricular tachycardia natural product ryanodine receptor induced pluripotent stem cell-derived cardiomyocytes

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High-Frequency Stereo Matching Network

High-Frequency Stereo Matching Network

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Haoliang Zhao Huizhou Zhou Yongjun Zhang Jie Chen Yitong Yang Yong Zhao Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry State Key Laboratory of Public Big Data College of Computer Science and Technology Institute of Artificial Intelligence Guizhou University Guiyang Guizhou China Ghost-Valley AI Technology Shenzhen Guangdong China School of Physics and Optoelectronic Engineering Guangdong University of Technology Guangzhou China The Key Laboratory of Integrated Microsystems Shenzhen Graduate School Peking University China

In the field of binocular stereo matching, remarkable progress has been made by iterative methods like RAFT-Stereo and CREStereo. However, most of these methods lose information during the iterative process, making it difficult to generate more detailed difference maps that take full advantage of high-frequency information. We propose the Decouple module to alleviate the problem of data coupling and allow features containing subtle details to transfer across the iterations which proves to alleviate the problem significantly in the ablations. To further capture high-frequency details, we propose a Normalization Refinement module that unifies the disparities as a proportion of the disparities over the width of the image, which address the problem of module failure in cross-domain scenarios. Further, with the above improvements, the ResNet-like feature extractor that has not been changed for years becomes a bottleneck. Towards this end, we proposed a multi-scale and multi-stage feature extractor that introduces the channel-wise self-attention mechanism which greatly addresses this bottleneck. Our method (DLNR) ranks 1st on the Middlebury leaderboard, significantly outperforming the next best method by 13.04%. Our method also achieves SOTA performance on the KITTI-2015 benchmark for D1-fg. Code and demos are available at: https://***/David-Zhao-1997/High-frequency-Stereo-Matching-Network.

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Grammars and a random generator for deterministic chain regular expressions 46

Grammars and a random generator for deterministic chain regu...

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46th International Conference on Current Trends in Theory and Practice of Computer Science Doctoral Student Research Forum, SOFSEM-SRF 2020

作者： Chu, Xinyu Lu, Ping Chen, Haiming State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

Deterministic regular expressions (DREs) are a core part of XML Schema and widely used in other applications. There are context-free grammars for DREs, which are not efficient for being used and also lead to the problem of being unable to generate expressions of the given length in an efficient manner. Deterministic chain regular expressions (dCHAREs) are a very practical subclass of DREs. In many practical situations, dCHAREs are more suitable than standard or deterministic regular expressions. But dCHAREs do not have a simple syntax, which puts a burden on the applications of these expressions. In this paper, we propose derivation rules and give regular grammars for dCHAREs which are more succinct than the grammars of DREs. Based on the grammars, we further design an algorithm to randomly generate dCHAREs of the given length, which fills the gap in the generation of DREs. Experimental results demonstrate that our generator is efficient in terms of running time and complexity. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Pattern matching

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A novel in-memory computing scheme based on toggle spin torque MRAM 20

A novel in-memory computing scheme based on toggle spin torq...

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30th Great Lakes Symposium on VLSI, GLSVLSI 2020

作者： Bai, Yining Zhang, Yue Wang, Jinkai Wang, Guanda Zhang, Zhizhong Zheng, Zhenyi Zhang, Kun Zhao, Weisheng Fert Beijing Institute School of Microelectronics Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University China Nanoelectronics Science and Technology Center Hefei Innovation Research Institute Beihang University Hefei China School of Electronics Engineering Beihang University Beijing China

ISBN: (纸本)9781450379441

This paper proposes a novel in-memory computing (IMC) scheme based on toggle spin torque magnetic random access memory (TST-MRAM), called TST-IMC, which makes full use of the unique TST writing mechanism. In this scheme, all of the computing results are directly written in bit-cells without transferring data out of the memory array. Varied Boolean logic operations, such as, NAND, NOR and XOR, can be achieved by specially configuring decision cells. We can also implement three-input majority logic through replacing a decision cell with a datum cell, which can further be used to realize the carry of full-adder. By using 28 nm CMOS technology node and 50 nmdiameter TST-MRAM, we perform mixed simulations to validate the functionality of the proposed TST-IMC scheme. Simulation results show that XOR logic operation can be carried out within 4 ns at 1.8 V supply voltage while the other basic logic operations can be faster, i.e. within 2 ns. In addition, TST-IMC 33% less time and 44% energy saved comparing with existing IMC schemes. © 2020 Association for computing Machinery.

关键词： Cells

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Federated Learning for Medical Image Classification: Advances, Challenges and Opportunities

SSRN

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SSRN 2023年

作者： Zhang, Xiaobo Zhao, Xiaole Wu, Yunyang Zheng, Hailong Li, Yang School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu611756 China Artificial Intelligence Research Institute Southwest Jiaotong University Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu611756 China Engineering Research Center of Sustainable Urban Intelligent Transportation Ministry of Education China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China

Medical images are private integrations comprising private patient information owned by various hospitals and relevant research institutes, and the generated image data can be utilized to infer physical health conditions. In recent years, more and more AI researchers have used medical images as datasets for their analysis purposes, which will cause relevant personnel to worry about their privacy. As a distributed machine learning framework, federated learning can effectively solve the problem of data privacy. It participates in and completes model training without sharing personal data, with strong universality and good results. In this work, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Wilhelm Conrad Röntgen (X-Ray) as well as other typical medical imaging modes are used as research objects to summarize, analyze and look forward to the previous work related to federal learning in the field of medical image analysis. On the one hand, this survey classifies and compares the existing federal learning framework and algorithm for different medical image datasets;on the other hand, it discusses the relevant federal studies that are widely used in medical images, analyses the problems that need to be solved in the field of medical images, and looks forward to future studies. © 2023, The Authors. All rights reserved.

关键词： Medical imaging

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The 3D projection function on NetPad 15

The 3D projection function on NetPad

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15th International Conference on Computer Science and Education, ICCSE 2020

作者： Zhou, Qixin Li, Chuanzhong Cai, Ruiqi Li, Miaoxuan Zhang, Chuanjun Guan, Hao Guangzhou University Institute of Computing Science and Technology Guangzhou China Guangzhou University School of Computer Science and Cyber Engineering Guangzhou China Guizhou Education University School of Mathematics and Big Data Guiyang China Chinese Academy of Science Chengdu Institute of Computer Application Chengdu China

ISBN: (纸本)9781728172675

Projection of 3D geometric graphics is an introduction to solid geometry, which has indispensable functional requirements for 3D Dynamic Geometry Software. To optimize the 3D dynamic geometry software in the construction of projection steps and support more types of projected objects, this paper presents a method of construction of 3D projection. The key steps as follows: Firstly, discretize the projection object. Secondly, transform the set of the discrete point according to the projection type selected by the user. Thirdly, construct a new geometric object as the projection using the set of transformed point. The experimental results show that using the method can support the projection of various geometric objects, dynamically show the projection process, and reduce the construction burden of the user. © 2020 IEEE.

关键词： Geometry

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Cryptomania v.s. Minicrypt in a Quantum World

arXiv

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arXiv 2025年

作者： Li, Longcheng Li, Qian Li, Xingjian Liu, Qipeng State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences China Shenzhen International Center For Industrial And Applied Mathematics Shenzhen Research Institute of Big Data China Tsinghua University China University of California San Diego United States

We prove that it is impossible to construct perfect-complete quantum public-key encryption (QPKE) with classical keys from quantumly secure one-way functions (OWFs) in a black-box manner, resolving a long-standing open question in quantum cryptography. Specifically, in the quantum random oracle model (QROM), no perfect-complete QPKE scheme with classical keys, and classical/quantum ciphertext can be secure. This improves the previous works which require either unproven conjectures or imposed restrictions on key generation algorithms. This impossibility even extends to QPKE with quantum public key if the public key can be uniquely determined by the secret key, and thus is tight to all existing QPKE constructions. © 2025, CC BY.

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A Large-scale Multiple-objective Method for Black-box Attack against Object Detection

arXiv

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arXiv 2022年

作者： Liang, Siyuan Li, Longkang Fan, Yanbo Jia, Xiaojun Li, Jingzhi Wu, Baoyuan Cao, Xiaochun State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China School of Data Science Secure Computing Lab of Big Data The Chinese University of Hong Kong Shenzhen China Tencent AI Lab Shenzhen China School of Cyber Science and Technology Shenzhen Campus Sun Yat-sen University Shenzhen China

Recent studies have shown that detectors based on deep models are vulnerable to adversarial examples, even in the black-box scenario where the attacker cannot access the model information. Most existing attack methods aim to minimize the true positive rate, which often shows poor attack performance, as another sub-optimal bounding box may be detected around the attacked bounding box to be the new true positive one. To settle this challenge, we propose to minimize the true positive rate and maximize the false positive rate, which can encourage more false positive objects to block the generation of new true positive bounding boxes. It is modeled as a multi-objective optimization (MOP) problem, of which the generic algorithm can search the Pareto-optimal. However, our task has more than two million decision variables, leading to low searching efficiency. Thus, we extend the standard Genetic Algorithm with Random Subset selection and Divide-and-Conquer, called GARSDC, which significantly improves the efficiency. Moreover, to alleviate the sensitivity to population quality in generic algorithms, we generate a gradient-prior initial population, utilizing the transferability between different detectors with similar backbones. Compared with the state-of-art attack methods, GARSDC decreases by an average 12.0 in the mAP and queries by about 1000 times in extensive experiments. Our codes can be found at https://***/LiangSiyuan21/ GARSDC. © 2022, CC BY.

关键词： Object detection

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