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The unforgettable past: The long-term impact of war on corporate tax avoidance in modern China

Research in International Business and Finance 2025年 77卷

作者： Tan, Xue Yin, Jingwei Lin, Ning Hunan Key Laboratory of Macroeconomic Big Data Mining and Its Application School of Business Hunan Normal University Hunan Changsha 410081 China Business School Central South University Hunan Changsha 410083 China Economics and Management School of Wuhan University Wuhan University Hubei Wuhan China

Prior literature related to war effects usually has a short time horizon between the war event and its outcomes. However, little is known about whether the collective war memories can be transmitted across generations, and then impact later generations' decisions in a long-lasting way. Using a sample of 3244 A-share listed companies in Shanghai and Shenzhen from 2013 to 2019, the study finds that firms hiring CEOs originated from regions that were intensively affected by the war during 1931–1945 (i.e., the Second Sino-Japanese War) exhibit higher level of corporate tax avoidance. Moreover, the positive impact of war on corporate tax avoidance is more pronounced for CEOs who are the first generation born in the post-war period. Our mechanism tests show that firms hiring war-affected CEOs are more likely to make philanthropic giving, and have higher corporate social responsibility ratings, but not hold more risk assets, revealing that war-affected CEOs engaging in greater tax avoidance is due to their prosocial preference rather than risk preference. Our cross-sectional analyses reveal that the positive impact of war on corporate tax avoidance is stronger when CEOs are male, less educated, without political connection, with poor experiences and firms face financing constraints, but weaker when firms are under stricter tax enforcement. Above conclusions are robust to a set of robustness checks and still stand after confronting the endogeneity issue. © 2025

关键词： CEOs' characteristics Corporate tax avoidance Prosocial preference Risk preference War

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Exact Dynamical Correlations of Hard-Core Anyons in One-Dimensional Lattices

arXiv

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arXiv 2022年

作者： Wang, Qing-Wei School of Information Engineering Zhejiang Ocean University Zhejiang Zhoushan316022 China Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhejiang Ocean University Zhejiang Zhoushan316022 China

The dynamical correlations of a strongly correlated system is an essential ingredient to describe its non-equilibrium properties. We present a general method to calculate exactly the dynamical correlations of hard-core anyons in one-dimensional lattices, valid for any type of confining potential and any temperature. We obtain exact explicit expressions of the Green's function, the spectral function, and the out-of-time-ordered correlators (OTOCs). We find that the anyonic spectral function displays three main singularity lines which can be explained as a double spectrum in analogy to the Lieb-Liniger gas. The dispersion relations of these lines can be given explicitly and they cross at a hot point (qm, ωm), which induces a peak in the momentum distribution function at qm and a power-law singularity in the local spectral function at ωm. We also find that the anyonic statistics can induces spatial asymmetry in the Green's function, its spectrum, and the OTOC. Moreover, the information spreading characterized by the OTOCs shows light-cone dynamics, asymmetric for general statistics and low temperatures, but symmetric at infinite temperature. Our results pave the way toward studying the non-equilibrium dynamics of hard-core anyons and experimentally probing anyonic statistics through spectral functions. © 2022, CC BY.

关键词： Correlators

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Exact dynamical correlations of nonlocal operators in quadratic open Fermion systems: a characteristic function approach

arXiv

引用

arXiv 2022年

作者： Wang, Qing-Wei School of Information Engineering Zhejiang Ocean University Zhejiang Zhoushan316022 China Key Laboratory of Oceanographic Big Data Mining Application of Zhejiang Province Zhejiang Ocean University Zhejiang Zhoushan316022 China

The dynamical correlations of nonlocal operators in general quadratic open fermion systems is still a challenging problem. Here we tackle this problem by developing a new formulation of open fermion many-body systems, namely, the characteristic function approach. Illustrating the technique, we analyze a finite Kitaev chain with boundary dissipation and consider anyon-type nonlocal excitations. We give explicit formula for the Green’s functions, demonstrating an asymmetric light cone induced by the anyon statistical parameter and an increasing relaxation rate with this parameter. We also analyze some other types of nonlocal operator correlations such as the full counting statistics of the charge number and the Loschmidt echo in a quench from the vacuum state. The former shows clear signature of a nonequilibrium quantum phase transition, while the later exhibits cusps at some critical times and hence demonstrates dynamical quantum phase transitions. © 2022, CC BY.

关键词： Phase transitions

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ICSDA: a multi-modal deep learning model to predict breast cancer recurrence and metastasis risk by integrating pathological, clinical and gene expression data

引用

BRIEFINGS IN BIOINFORMATICS 2022年第6期23卷 bbac448-bbac448页

作者： Yao, Yuhua Lv, Yaping Tong, Ling Liang, Yuebin Xi, Shuxue Ji, Binbin Zhang, Guanglu Li, Ling Tian, Geng Tang, Min Hu, Xiyue Li, Shijun Yang, Jialiang School of Mathematics and Statistics Hainan Normal University Haikou 570100 China Key Laboratory of Data Science and Intelligence Education Ministry of Education Hainan Normal University Haikou China Key Laboratory of Computational Science and Application of Hainan Province Hainan Normal University Haikou China Genies Beijing Co. Ltd. Beijing 100102 China Chifeng Municipal Hospital Chifeng Inner Mongolia 024000 China Qingdao Geneis Institute of Big Data Mining and Precision Medicine Qingdao 266000 China Basic Courses Department Zhejiang Shuren University Hangzhou 310000 China School of Life Sciences Jiangsu University Zhenjiang 212013 China Dept. of Colorectal Surgery National Cancer Center/ Cancer Hospital Chinese Academy of Medical Science 17 Panjiayuan Nanli Chaoyang District Beijing China 100021

Breast cancer patients often have recurrence and metastasis after surgery. Predicting the risk of recurrence and metastasis for a breast cancer patient is essential for the development of precision treatment. In this study, we proposed a novel multi-modal deep learning prediction model by integrating hematoxylin & eosin (H&E)-stained histopathological images, clinical information and gene expression data. Specifically, we segmented tumor regions in H&E into image blocks (256 x 256 pixels) and encoded each image block into a 1D feature vector using a deep neural network. Then, the attention module scored each area of the H&E-stained images and combined image features with clinical and gene expression data to predict the risk of recurrence and metastasis for each patient. To test the model, we downloaded all 196 breast cancer samples from the Cancer Genome Atlas with clinical, gene expression and H&E information simultaneously available. The samples were then divided into the training and testing sets with a ratio of 7: 3, in which the distributions of the samples were kept between the two datasets by hierarchical sampling. The multi-modal model achieved an area-under-the-curve value of 0.75 on the testing set better than those based solely on H&E image, sequencing data and clinical data, respectively. This study might have clinical significance in identifying high-risk breast cancer patients, who may benefit from postoperative adjuvant treatment.

关键词： breast cancer recurrence and metastasis multi-modality residual network attention module

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Decentralized and Lightweight Cross-Chain Transaction Scheme Based on Proxy Re-signature

Decentralized and Lightweight Cross-Chain Transaction Scheme...

引用

IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Huiying Zou Jia Duan Xi Liu Wei Ren Tao Li Xianghan Zheng Kim-Kwang Raymond Choo School of Computer Science China University of Geosciences Wuhan China The Third Surveying and Mapping Institute of Hunan Province Hunan Engineering Research Center of Geographic Information Security and Application Hunan China Key Laboratory of Data Protection and Intelligent Management Sichuan University Ministry of Education China State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR CASM Beijing China College of Computer and Big Data Fuzhou University School of Information and Intelligent Engineering Sanya College China Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio USA

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

With the widespread application of digital assets and the rapid development of blockchain technology, achieving secure and efficient transactions between different blockchain networks has become an urgent challenge. Existing cross-chain methods impose limitations, e.g., hash lock technology exhibits low scalability, side-chain technology is overly complex, and notary schemes pose centralization risks. In order to address these issues, we propose a cross-chain transaction solution based on proxy re-signature technology. To tackle the centralization concerns, we employ proxy re-signature technology to decentralize the authority of notaries among transaction participants, minimizing the potential for centralization at a low cost. We further present an extended scheme that can guarantee more requirements such as higher transaction amount and shorter transaction time. Furthermore, we analyze and compare the signature technologies used in the proposed solution and provide a systematic proof of our approach’s security.

关键词： Privacy Systematics Costs Scalability Blockchains Security

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Late Mesozoic Tectonic Transfer in the Southern Great Xing'An Range, Ne China: Evidence from Geochronology, Geochemistry and Lu-Hf Isotopes of Magmatic Intrusions in Inner Mongolia

SSRN

引用

SSRN 2023年

作者： Zhao, Zhixiong Dong, Guochen Santosh, M. Bao, Xiangping Ren, Yingwei Xie, Zhuolin School of Earth Science and Mineral Resources China University of Geosciences Beijing100083 China Ulanqab Key Laboratory of Geospatial Big Data Application and Environmental Monitoring Jining Normal University Ulanqab012000 China Department of Earth Science University of Adelaide Adelaide5005 Australia Yonsei Frontier Lab Yonsei University Seoul Korea Republic of

The geodynamic background of the Mesozoic magmatism in the Jarud region of Inner Mongolia remains debated. Here we present zircon U-Pb geochronology, geochemistry and Hf isotope data on the Late Jurassic diorite and Early Cretaceous quartz monzonite porphyry and granite porphyry from the Jarud area to constrain the petrogenesis and tectonic setting. Zircon U-Pb data suggest that the multiphase magmatism extended from the Late Jurassic to Early Cretaceous, i.e., 161.0 ± 1.0 Ma (diorite), 129.9 ± 1.4 Ma (quartz monzonite porphyry), and 125.8 ± 1.1 Ma and 126.8 ± 1.1 Ma (granite porphyry). These rocks are characterized by enrichment of light rare earth and large ion lithophile elements. Based on the geochemistry and Hf isotope data, the diorite with elevated crystallization temperatures (1061 to 1098 ℃), and moderate logfO2 (-22.80 to -7.53) is inferred to have formed by low degree partial melting of depleted mantle wedge metasomatized by fluids at a relatively shallow depth. The quartz monzonite porphyry with moderate crystallization temperatures (755 to 839 °C) and high logfO2 (-18.35 to -9.53) was generated by partial melting of lower crust triggered by depleted mantle-derived basaltic magma underplating, subsequent experienced the fractional crystallization of olivine, pyroxene, Fe-Ti oxides and apatite. The granite porphyry with low crystallization temperatures (643 to 821 °C) and logfO2 (-27.59 to -12.40), is classified as S-type granites, and was sourced from greywacke. The results presented in this study indicate that the Late Jurassic magmatism was related to the southward subduction of the Mongol- Okhotsk Ocean, while the Early Cretaceous magmatic rocks were formed in a post-collision extensional setting. © 2023, The Authors. All rights reserved.

关键词： Quartz

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Perceptive self-supervised learning network for noisy image watermark removal

arXiv

引用

arXiv 2024年

作者： Tian, Chunwei Zheng, Menghua Li, Bo Zhang, Yanning Zhang, Shichao Zhang, David School of Software Northwestern Polytechnical University Xi’an710129 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China School of Electronics and Information Northwestern Polytechnical University Xi’an710129 China School of Computer Science Northwestern Polytechnical University National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology Xi’an710129 China Guangxi Key Lab of Multisource Information Mining & Security College of Computer Science & Engineering Guangxi Normal University Guilin541004 China Shenzhen518172 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518172 China

Popular methods usually use a degradation model in a supervised way to learn a watermark removal model. However, it is true that reference images are difficult to obtain in the real world, as well as collected images by cameras suffer from noise. To overcome these drawbacks, we propose a perceptive self-supervised learning network for noisy image watermark removal (PSLNet) in this paper. PSLNet depends on a parallel network to remove noise and watermarks. The upper network uses task decomposition ideas to remove noise and watermarks in sequence. The lower network utilizes the degradation model idea to simultaneously remove noise and watermarks. Specifically, mentioned paired watermark images are obtained in a self-supervised way, and paired noisy images (i.e., noisy and reference images) are obtained in a supervised way. To enhance the clarity of obtained images, interacting two sub-networks and fusing obtained clean images are used to improve the effects of image watermark removal in terms of structural information and pixel enhancement. Taking into texture information account, a mixed loss uses obtained images and features to achieve a robust model of noisy image watermark removal. Comprehensive experiments show that our proposed method is very effective in comparison with popular convolutional neural networks (CNNs) for noisy image watermark removal. Codes can be obtained at https://***/hellloxiaotian/PSLNet. Copyright © 2024, The Authors. All rights reserved.

关键词： Image denoising

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Cell-average based neural network method for high dimensional parabolic differential equations

arXiv

引用

arXiv 2022年

作者： Zhang, Hong Huang, Hongying Yan, Jue Zhejiang Ocean University Zhejiang Zhoushan316000 China Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhejiang Zhoushan316000 China Department of Mathematics Iowa State University AmesIA50011 United States

In this paper, we introduce cell-average based neural network (CANN) method to solve high-dimensional parabolic partial differential equations. The method is based on the integral or weak formulation of partial differential equations. A feedforward network is considered to train the solution average of cells in neighboring time. Initial values and approximate solution at t = ∆t obtained by high order numerical method are taken as the inputs and outputs of network, respectively. We use supervised training combined with a simple backpropagation algorithm to train the network parameters. We find that the neural network has been trained to optimality for high-dimensional problems, the CFL condition is not strictly limited for CANN method and the trained network is used to solve the same problem with different initial values. For the high-dimensional parabolic equations, the convergence is observed and the errors are shown related to spatial mesh size but independent of time step size. Copyright © 2022, The Authors. All rights reserved.

关键词： Finite volume method

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Multi-Stage Enhanced Rain Image Restoration Network

Multi-Stage Enhanced Rain Image Restoration Network

引用

2021 International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2021

作者： Wang, Quanqing Cheng, Yuanshun Yang, Yueting Wang, Chao Yang, Chuansheng School of Information Engineering Zhejiang Ocean University Zhejiang Zhoushan316022 China Tianfu College of SWUFE Sichuan Mianyang621000 China School of Mathematics and Statistics Beihua University Jilin Jilin132013 China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhejiang Zhoushan316022 China

The restoration task of rain images is beneficial to the further development of computer vision tasks. However, recent rain removal methods have difficulty coping with dense rain streaks. In this paper, we propose a Multi-stage Enhanced Rain Image Restoration Network (MERNet) for the task of rain removal. Our main idea is to design a three-stage network architecture, which makes full use of the enhanced information of the previous stage and complements the information of the next stage through transmission step by step. We give consideration to information enhancement at the same time of information transmission, fully improve the information utilization rate and the overall network effect. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Rain

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Attention-based feature enhanced dehazing network

Attention-based feature enhanced dehazing network

引用

2021 International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2021

作者： Cheng, Yuanshun Tan, Anhui Yang, Chuansheng Yang, Yueting Wang, Chao Tianfu College of SWUFE Sichuan Mianyang621000 China School of Information Engineering Zhejiang Ocean University Zhejiang Zhoushan316022 China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhejiang Zhoushan316022 China School of Mathematics and Statistics Beihua University Jilin Jilin132013 China

Presence of haze in images obscures underlying information, which is undesirable in applications requiring accurate environment information. To recover such an image, a dehazing algorithm should enhance the feature information of the background while weakening the feature information of haze. In this paper, we propose an end-to-end attention-based feature enhanced dehazing network (AEDNet), which integrates enhancement strategy and attention mechanism, to achieve haze removal. The network is based on U-Net, which has the advantages of retaining information, obtaining multi-scale features and so on. In the training of the network, pixel loss and perceptual loss are used to preserve feature information and improve the overall quality of results. The extensive evaluation shows that the proposed model performs significantly better than previous dehazing methods on various benchmarks. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Image enhancement

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