Information Scrambling in Quantum Neural Networks

The quantum neural network is one of the promising applications for near-term noisy intermediate-scale quantum computers. A quantum neural network distills the information from the input wave function into the output qubits. In this Letter, we show that this process can also be viewed from the opposite direction: the quantum information in the output qubits is scrambled into the input. This observation motivates us to use the tripartite information—a quantity recently developed to characterize information scrambling—to diagnose the training dynamics of quantum neural networks. We empirically find strong correlation between the dynamical behavior of the tripartite information and the loss function in the training process, from which we identify that the training process has two stages for randomly initialized networks. In the early stage, the network performance improves rapidly and the tripartite information increases linearly with a universal slope, meaning that the neural network becomes less scrambled than the random unitary. In the latter stage, the network performance improves slowly while the tripartite information decreases. We present evidences that the network constructs local correlations in the early stage and learns large-scale structures in the latter stage. We believe this two-stage training dynamics is universal and is applicable to a wide range of problems. Our work builds bridges between two research subjects of quantum neural networks and information scrambling, which opens up a new perspective to understand quantum neural networks

Project - To Serve the People 为人民服务

The artwork is a series of artistic acts that lasted 36 days in Luo yang 洛阳, China. On August 20,1992, the author inscribed the slogan “To Serve the People” with lime on a dam wall. On the next day, towels were distributed to the farmers at the kiln. At 8:00 P.M on the same day, he rented a film and played for the villages in Luoyang. On September 18, 1992, Hui wrote the slogan “To Serve the People \u27\u27 on a red paper and stuck it on Dongfanghong Square 东方红广场( the square was about 200 meters long). On September 20, 1992, Hui hung and posted “To Serve the People” ( printed on a fabric) in a factory. Later the participants of the event received repeated police investigations. These acts that respond to the question ‘Does today’s art still have the power of criticism in real life?’, which Hui asked in his proposal (written in Chinese). (Hao Yang’25)https://digital.kenyon.edu/zhoudocs/1243/thumbnail.jp

Analgesic, anti-inflammatory and immuno-modulatory effects of dezocine-propofol anesthesia combination following colonoscopy

Purpose: To study and compare the analgesic, anti-inflammatory and immuno-modulatory effects of dezocine-propofol, and fentanyl-propofol combinations in colonoscopy.Methods: One hundred and thirty-four patients who received painless colonoscopy in Eastern Medical District of Linyi People's Hospital, Linyi City, Shandong Province, China, from June 2013 to December 2016 were randomly divided into two groups. Patients in the observation group (aged 42 - 65 years) received dezocine-propofol combination as anesthesia, while those in the control group (aged 41 - 67 years) were anesthetized with fentanyl-propofol. Serum levels of pain and inflammatory mediators, as well as contents of immune response molecules were determined prior to, during and after colonoscopy using either enzyme-linked immunosorbent assay (ELISA) or electro-chemiluminescence kits.Results: There were no statistically significant differences in the serum levels of 5-hydroxytryptophan (5-HTP), 5-hydroxy indole acetic acid (5-HIAA), substance P (SP), prostaglandin E2 (PGE2), C-reactive protein (CRP), heat shock protein 70 (HSP70), Interleukin-1 β(IL-1β), adrenocorticotropic hormone (ACTH), Cortisol (Cor), Inositol (Ins), c-peptide (C-P), immunoglobulin G (IgG) and immunoglobulin A (IgA), complement 3 (C3) and complement 4 (C4) before and during colonoscopy between the two groups of patients. However, after the examination, serum levels of 5-HTP, 5-HIAA, SP, PGE2, CRP, HSP70, IL-1 beta, ACTH, Cor, Ins and C-P in the observation group were significantly lower than those in control group (p < 0.05), while IgG, IgA, C3 and C4 contents were significantly higher than those of the control group (p < 0.05).Conclusion: These results suggest that the analgesic effect of dezocine-propofol combination after colonoscopy examination is superior to that of fentanyl-propofol combination, due to its effectiveness in inhibiting inflammatory reactions and improving immune response.Keywords: Colonoscopy, Dezocine, Propofol Fentanyl, Pain mediators, Analgesic, Inflammatory reaction, Immune respons

Development of online education and its applicationin Shanghai Maritime University

Online teaching is becoming an important alternative approach to maritime education, which traditionally relies on face-to-face instruction, particularly during the period when the COVID-19 has had a devastating impact on the educational system worldwide. On the base of the conceptualization of online education through a literature review, this study demonstrates the case of an innovative online teaching system developed and implemented by Shanghai Maritime University (SMU) that successfully allowed some 20,000 students to resume learning despite the COVID-19 disruption. To realize large-scale online teaching, four phases of development the SMU underwent are introduced. The whole process of planning, preparation, implementation as well as evaluation is elaborated. In addition to class teaching, other major activities delivered remotely are also introduced, including short-term training programs, graduation ceremony, online career fairs, online interviews for postgraduate admission. Difficulties and challenges in shifting to the new teaching method and how SMU developed effective strategies to solve these issues are addressed. This study provides a valuable example of an online teaching system realized in a maritime institution. Furthermore, it may serve as an inspirational reference to peer maritime institutions to adopt or improve their competence of online learning systems

A Comprehensive Survey on Database Management System Fuzzing: Techniques, Taxonomy and Experimental Comparison

Database Management System (DBMS) fuzzing is an automated testing technique aimed at detecting errors and vulnerabilities in DBMSs by generating, mutating, and executing test cases. It not only reduces the time and cost of manual testing but also enhances detection coverage, providing valuable assistance in developing commercial DBMSs. Existing fuzzing surveys mainly focus on general-purpose software. However, DBMSs are different from them in terms of internal structure, input/output, and test objectives, requiring specialized fuzzing strategies. Therefore, this paper focuses on DBMS fuzzing and provides a comprehensive review and comparison of the methods in this field. We first introduce the fundamental concepts. Then, we systematically define a general fuzzing procedure and decompose and categorize existing methods. Furthermore, we classify existing methods from the testing objective perspective, covering various components in DBMSs. For representative works, more detailed descriptions are provided to analyze their strengths and limitations. To objectively evaluate the performance of each method, we present an open-source DBMS fuzzing toolkit, OpenDBFuzz. Based on this toolkit, we conduct a detailed experimental comparative analysis of existing methods and finally discuss future research directions.Comment: 34 pages, 22 figure

Information Scrambling in Quantum Neural Networks

The quantum neural network is one of the promising applications for near-term noisy intermediate-scale quantum computers. A quantum neural network distills the information from the input wave function into the output qubits. In this Letter, we show that this process can also be viewed from the opposite direction: the quantum information in the output qubits is scrambled into the input. This observation motivates us to use the tripartite information—a quantity recently developed to characterize information scrambling—to diagnose the training dynamics of quantum neural networks. We empirically find strong correlation between the dynamical behavior of the tripartite information and the loss function in the training process, from which we identify that the training process has two stages for randomly initialized networks. In the early stage, the network performance improves rapidly and the tripartite information increases linearly with a universal slope, meaning that the neural network becomes less scrambled than the random unitary. In the latter stage, the network performance improves slowly while the tripartite information decreases. We present evidences that the network constructs local correlations in the early stage and learns large-scale structures in the latter stage. We believe this two-stage training dynamics is universal and is applicable to a wide range of problems. Our work builds bridges between two research subjects of quantum neural networks and information scrambling, which opens up a new perspective to understand quantum neural networks