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Article ; Online: Weighted Signed Networks Reveal Interactions between US Foreign Exchange Rates.

Yang, Leixin / Wang, Haiying / Gu, Changgui / Yang, Huijie

2024 Volume 26, Issue 2

Abstract: Correlations between exchange rates are valuable for illuminating the dynamics of international trade and the financial dynamics of countries. This paper explores the changing interactions of the US foreign exchange market based on detrended cross- ... ...

Abstract	Correlations between exchange rates are valuable for illuminating the dynamics of international trade and the financial dynamics of countries. This paper explores the changing interactions of the US foreign exchange market based on detrended cross-correlation analysis. First, we propose an objective way to choose a time scale parameter appropriate for comparing different samples by maximizing the summed magnitude of all DCCA coefficients. We then build weighted signed networks under this optimized time scale, which can clearly display the complex relationships between different exchange rates. Our study shows negative cross-correlations have become pyramidally rare in the past three decades. Both the number and strength of positive cross-correlations have grown, paralleling the increase in global interconnectivity. The balanced strong triads are identified subsequently after the network centrality analysis. Generally, while the strong development links revealed by foreign exchange have begun to spread to Asia since 2010, Europe is still the center of world finance, with the euro and Danish krone consistently maintaining the closest balanced development relationship. Finally, we propose a fluctuation propagation algorithm to investigate the propagation pattern of fluctuations in the inferred exchange rate networks. The results show that, over time, fluctuation propagation patterns have become simpler and more predictable.
Language	English
Publishing date	2024-02-12
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2014734-X
ISSN	1099-4300 ; 1099-4300
ISSN (online)	1099-4300
ISSN	1099-4300
DOI	10.3390/e26020161
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Do Chinese Farmers Misuse Pesticide Intentionally or Not?

Li Zhao / Changwei Wang / Haiying Gu / Chengyan Yue

Agriculture, Vol 13, Iss 1749, p

2023 Volume 1749

Abstract: Nonstandard pesticide-application behavior leads to excessive pesticide residue and even affects the quality and safety of agricultural products and agricultural sustainability. Based on 968 valid samples randomly selected in Jiangsu Province of China, ... ...

Abstract	Nonstandard pesticide-application behavior leads to excessive pesticide residue and even affects the quality and safety of agricultural products and agricultural sustainability. Based on 968 valid samples randomly selected in Jiangsu Province of China, it focuses on the impact of incident shock and yield fluctuation avoidance on the pesticide-application behavior of farmers. Then, it investigated the impact of intentional factors, such as insufficient cognition and lack of knowledge, on their improper pesticide-application behavior. This study shows that, besides the pursuit of improper income, inadequate awareness and preventive actions to avoid operational risks are also important factors in farmers’ nonstandard pesticide application. In addition, the study also shows that farmers who understand the responsibility unit of agricultural product quality and safety supervision are more inclined to choose standardized application of pesticides. The higher the education level of farmers, the higher the probability of standardized application of pesticides. Therefore, farmers’ nonstandard pesticide-application behavior is largely due to the farmers’ insufficient awareness of the harm of pesticide residues or the lack of trust in the efficacy of pesticides. Moreover, the study also shows that adverse selection phenomenon exists in pesticide-application training.
Keywords	quality and safety ; pesticide application ; risk aversion ; incidents shock ; Agriculture (General) ; S1-972
Subject code	910
Language	English
Publishing date	2023-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Role of Flagella in the Pathogenesis of Helicobacter pylori.

Gu, Haiying

Current microbiology

2017 Volume 74, Issue 7, Page(s) 863–869

Abstract: This review aimed to investigate the role of Helicobacter pylori flagella on the pathogenicity of this bacterium in humans. Helicobacter pylori is a flagellated pathogen that colonizes the human gastroduodenal mucosa and produces inflammation, and is ... ...

Abstract	This review aimed to investigate the role of Helicobacter pylori flagella on the pathogenicity of this bacterium in humans. Helicobacter pylori is a flagellated pathogen that colonizes the human gastroduodenal mucosa and produces inflammation, and is responsible for gastrointestinal disease. Its pathogenesis is attributed to colonization and virulence factors. The primary function of H. pylori flagella is to provide motility. We believe that H. pylori flagella play an important role in the colonization of the gastrointestinal mucosa. Therefore, we reviewed previous studies on flagellar morphology and motility in order to explore the relationship between H. pylori flagella and pathogenicity. Further investigation is required to confirm the association between flagella and pathogenicity in H. pylori.
Language	English
Publishing date	2017-07
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	134238-1
ISSN	1432-0991 ; 0343-8651
ISSN (online)	1432-0991
ISSN	0343-8651
DOI	10.1007/s00284-017-1256-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Generating Paired Seismic Training Data with Cycle-Consistent Adversarial Networks

Zheng Zhang / Zhe Yan / Jiankun Jing / Hanming Gu / Haiying Li

Remote Sensing, Vol 15, Iss 1, p

2023 Volume 265

Abstract: Deep-learning-based seismic data interpretation has received extensive attention and focus in recent years. Research has shown that training data play a key role in the process of intelligent seismic interpretation. At present, the main methods used to ... ...

Abstract	Deep-learning-based seismic data interpretation has received extensive attention and focus in recent years. Research has shown that training data play a key role in the process of intelligent seismic interpretation. At present, the main methods used to obtain training data are synthesizing seismic data and manually labeling the real data. However, synthetic data have certain feature differences from real data, and the manual labeling of data is time-consuming and subjective. These factors limit the application of deep learning algorithms in seismic data interpretation. To obtain realistic seismic training data, we propose label-to-data networks based on cycle-consistent adversarial networks in this work. These networks take random labels and unlabeled real seismic data as input and generate synthetic seismic data that match the random labels and have similar features to the real seismic data. Quantitative analysis of the generated data demonstrate the effectiveness of the proposed methods. Meanwhile, test results on different data indicate that the generated data are reliable and can be applied for seismic fault detection.
Keywords	generating paired seismic data ; generative adversarial networks ; seismic fault detection ; Science ; Q
Subject code	550
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Towards building a firm metaverse security base

Li Anmin / Yao Xiaohui / Gu Haiying / Zhang Yungeng / Chang Yuan

Security and Safety, Vol 2, p

2023 Volume 2023005

Abstract: The Metaverse is a significant field that is currently receiving considerable attention from both the industry and academia. The transformation of the Metaverse from science fiction to reality is being actively promoted by technology, industry, and ... ...

Abstract	The Metaverse is a significant field that is currently receiving considerable attention from both the industry and academia. The transformation of the Metaverse from science fiction to reality is being actively promoted by technology, industry, and capital. However, the development of the Metaverse is still in its early stages, and the system architecture and theoretical technology of the Metaverse are not yet mature. This paper provides a comprehensive analysis of the Metaverse and summarizes its holographic, omnipotent, multidimensional, and multifaceted characteristics. The development of the Metaverse is founded on the relevant infrastructure, and we elaborate on the primary components of the Metaverse infrastructure. Furthermore, we systematically summarize the security risks inherent in the Metaverse infrastructure. Based on this, we propose utilizing the system security technology concept to guide the construction of a Metaverse security protection system from various perspectives at each level of computing, cloud, network, digital assets, and terminals, in order to construct a secure foundation for addressing the Metaverse’s security risks and challenges.
Keywords	metaverse ; new infrastructure ; security base ; highly trusted network ; trusted identiry ; trusted circulation of data ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	303
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	EDP Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Do Chinese Farmers Misuse Pesticide Intentionally or Not?

Zhao, Li / Wang, Changwei / Gu, Haiying / Yue, Chengyan

Agriculture. 2023 Sept. 03, v. 13, no. 9

2023

Abstract	Nonstandard pesticide-application behavior leads to excessive pesticide residue and even affects the quality and safety of agricultural products and agricultural sustainability. Based on 968 valid samples randomly selected in Jiangsu Province of China, it focuses on the impact of incident shock and yield fluctuation avoidance on the pesticide-application behavior of farmers. Then, it investigated the impact of intentional factors, such as insufficient cognition and lack of knowledge, on their improper pesticide-application behavior. This study shows that, besides the pursuit of improper income, inadequate awareness and preventive actions to avoid operational risks are also important factors in farmers’ nonstandard pesticide application. In addition, the study also shows that farmers who understand the responsibility unit of agricultural product quality and safety supervision are more inclined to choose standardized application of pesticides. The higher the education level of farmers, the higher the probability of standardized application of pesticides. Therefore, farmers’ nonstandard pesticide-application behavior is largely due to the farmers’ insufficient awareness of the harm of pesticide residues or the lack of trust in the efficacy of pesticides. Moreover, the study also shows that adverse selection phenomenon exists in pesticide-application training.
Keywords	agriculture ; cognition ; educational status ; income ; pesticide application ; pesticide residues ; pesticides ; probability ; product quality ; sustainable agriculture ; China
Language	English
Dates of publication	2023-0903
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ZDB-ID	2651678-0
ISSN	2077-0472
ISSN	2077-0472
DOI	10.3390/agriculture13091749
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Risk Amplification, Risk Preference and Acceptance of Transgenic Technology

Zhao, Li / Liu, Shumin / Gu, Haiying / Ahlstrom, David

Agriculture. 2023 Sept. 25, v. 13, no. 10

2023

Abstract: Consumer preferences and attitudes toward genetically modified (GM) food have been widely studied, yet there is little research on the aspects of farmers and risk amplification. Based on both a field survey and an experiment conducted in villages in ... ...

Abstract	Consumer preferences and attitudes toward genetically modified (GM) food have been widely studied, yet there is little research on the aspects of farmers and risk amplification. Based on both a field survey and an experiment conducted in villages in China’s eastern provinces of Shandong, Shanxi and Henan in 2021, we explore the impact of producers’ risk amplification and risk preferences on the acceptance of transgenic technology. Results show that only 37.3% of participants from the whole sample did not amplify the risk associated with GM products. In terms of regions, the percentages of participants in Henan, Shanxi and Shandong who amplified the risk associated with GM products were 65.3%, 62.4% and 60%, respectively. Moreover, the results of the economic experiment on risk preference indicate that over two-thirds of farmers proved to be risk-averse. Finally, full sample estimation results using ordered logit and Poisson models showed that risk amplification, relative risk aversion and risk perception all have negative impacts on producers’ response to GM plant seeds, including participants’ acceptance intention, purchasing intention and recommendation intention.
Keywords	agriculture ; genetic engineering ; genetically modified plants ; relative risk ; risk perception ; surveys ; China
Language	English
Dates of publication	2023-0925
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ZDB-ID	2651678-0
ISSN	2077-0472
ISSN	2077-0472
DOI	10.3390/agriculture13101871
Database	NAL-Catalogue (AGRICOLA)

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Article: How Does the Change of Information Source Affect Residents' Risk Attitudes?

Zhang, Shihu / Zhang, Guangcai / Li, Jinpei / Gu, Haiying

Frontiers in psychology

2022 Volume 13, Page(s) 918427

Abstract: Using data from the China Family Panel Studies (CFPS), this paper investigates the effects of Internet use on residents' risk attitudes. Both Generalized Ordered Logit Model and Logit model are used to identify the effects of Internet use. The results ... ...

Abstract	Using data from the China Family Panel Studies (CFPS), this paper investigates the effects of Internet use on residents' risk attitudes. Both Generalized Ordered Logit Model and Logit model are used to identify the effects of Internet use. The results reveal an association between Internet use and increases in both subjective and objective risk preferences that remains even after we adjust for possible endogeneity. The heterogeneity analysis also reveals that these impacts are different among groups with different reasons for Internet use and different personal characteristics. Our study expands the research on the effects of Internet on people's concepts from the micro perspective and suggests that while promoting the application of information technology we should also pay attention to the individual characteristics of residents so that we can better share the "digital dividend" brought by the popularization of information technology in the whole society.
Language	English
Publishing date	2022-06-17
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2563826-9
ISSN	1664-1078
ISSN	1664-1078
DOI	10.3389/fpsyg.2022.918427
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A lightweight YOLOv3 algorithm used for safety helmet detection.

Deng, Lixia / Li, Hongquan / Liu, Haiying / Gu, Jason

Scientific reports

2022 Volume 12, Issue 1, Page(s) 10981

Abstract: YOLOv3 is a popular and effective object detection algorithm. However, YOLOv3 has a complex network, and floating point operations (FLOPs) and parameter sizes are large. Based on this, the paper designs a new YOLOv3 network and proposes a lightweight ... ...

Abstract	YOLOv3 is a popular and effective object detection algorithm. However, YOLOv3 has a complex network, and floating point operations (FLOPs) and parameter sizes are large. Based on this, the paper designs a new YOLOv3 network and proposes a lightweight object detection algorithm. First, two excellent networks, the Cross Stage Partial Network (CSPNet) and GhostNet, are integrated to design a more efficient residual network, CSP-Ghost-Resnet. Second, combining CSPNet and Darknet53, this paper designs a new backbone network, the ML-Darknet, to realize the gradient diversion of the backbone network. Finally, we design a lightweight multiscale feature extraction network, the PAN-CSP-Network. The newly designed network is named mini and lightweight YOLOv3 (ML-YOLOv3). Based on the helmet dataset, the FLPSs and parameter sizes of ML-YOLOv3 are only 29.7% and 29.4% of those of YOLOv3. Compared with YOLO5, ML-YOLOv3 also exhibits obvious advantages in calculation cost and detection effect.
MeSH term(s)	Algorithms ; Head Protective Devices
Language	English
Publishing date	2022-06-29
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-022-15272-w
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A lightweight YOLOv3 algorithm used for safety helmet detection

Lixia Deng / Hongquan Li / Haiying Liu / Jason Gu

Scientific Reports, Vol 12, Iss 1, Pp 1-

2022 Volume 15

Abstract: Abstract YOLOv3 is a popular and effective object detection algorithm. However, YOLOv3 has a complex network, and floating point operations (FLOPs) and parameter sizes are large. Based on this, the paper designs a new YOLOv3 network and proposes a ... ...

Abstract	Abstract YOLOv3 is a popular and effective object detection algorithm. However, YOLOv3 has a complex network, and floating point operations (FLOPs) and parameter sizes are large. Based on this, the paper designs a new YOLOv3 network and proposes a lightweight object detection algorithm. First, two excellent networks, the Cross Stage Partial Network (CSPNet) and GhostNet, are integrated to design a more efficient residual network, CSP-Ghost-Resnet. Second, combining CSPNet and Darknet53, this paper designs a new backbone network, the ML-Darknet, to realize the gradient diversion of the backbone network. Finally, we design a lightweight multiscale feature extraction network, the PAN-CSP-Network. The newly designed network is named mini and lightweight YOLOv3 (ML-YOLOv3). Based on the helmet dataset, the FLPSs and parameter sizes of ML-YOLOv3 are only 29.7% and 29.4% of those of YOLOv3. Compared with YOLO5, ML-YOLOv3 also exhibits obvious advantages in calculation cost and detection effect.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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