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This paper aims to prepare Poly(Styrene-Butyl acrylate-Methacrylic acid) @Poly Gallic acid-Fe³⁺ photonic crystal composite inks [P(St-BA-MAA)@PGA-Fe³⁺ PCCI, @ means the PGA-Fe³⁺ is loaded on the microspheres] and construct noniridescent structural colors on fabric substrates, with the goal of improving the visibility of structural colors.

P(St-BA-MAA)@PGA-Fe³⁺ PCCI were prepared by coating P(St-BA-MAA) microspheres with a metal-polyphenol network formed by gallic acid (GA, C₇H₆O₅) and Fe³⁺. The assembly effects of the inks were explored under different conditions, including pH, temperature, concentration and surface tension. The optimal self-assembly conditions of the inks were determined using the controlled variable method.

The results demonstrated the successful preparation of P(St-BA-MAA)@PGA-Fe³⁺ PCCI. The metal polyphenol network film composed of GA and Fe³⁺ was successfully coated on the surface of P(St-BA-MAA) seed microspheres. The assembly mechanism of the inks was investigated, indicating that at a diethylene glycol (DEG, C₄H₁₀O₃) concentration of 0.3 wt% and pH of 7, bright noniridescent structural colors could be formed on fabric surfaces after self-assembly by PCCI at 60 °C for 10 min. Furthermore, the mechanical fastness of the structural colors was enhanced due to the adherence of the soft shell composed of P(St-BA-MAA) and GA.

Utilizing a cost-effective approach and a diverse array of readily available raw materials, we have successfully prepared P(St-BA-MAA)@PGA-Fe³⁺ PCCI, which boasts superior performance and offers fabrics a range of unique coloring styles. This innovation paves the way for potential applications of structural colors in practical production, thereby broadening their realm of utility.

The purpose of this study is to investigate the effects of uncertainty, namely, macroeconomic uncertainty (MU) and financial uncertainty (FU) on foreign exchange market stability, specifically on foreign exchange market pressure (EMP) and jump risk (RJV).

The latent threshold time-varying parameter VAR (LT-TVP-VAR) econometric approach is used in estimations to solve structural breaks.

The relationship of uncertainties and China's foreign exchange market stability is latent threshold nonlinear dynamic time-varying. In China's renminbi (RMB) appreciation stage, both MU and FU weaken the appreciation pressure of RMB. Moreover, MU and FU significantly increase the RJV, while MU significantly affects the RJV of the foreign exchange market. In the RMB depreciation stage, both MU and FU strengthen the EMP.

Findings based on data in China's foreign exchange market can be considered for other global markets in future research.

An increase in MU and FU has a negative effect on foreign exchange stability. Regulators can prevent the economic system uncertainty shocks on foreign exchange market stability through observation and judgment of MU and FU, which helps prevent and relieve financial risks. Investors can reduce foreign exchange risk as the exchange rate rebounds after hedging behavior during high uncertainty periods.

The effect of MU on the foreign exchange market stability is greater than that of FU, regardless of whether EMP or RJV occurs in the foreign exchange market.

It is well known that the selection of initial cluster centers can significantly affect K-means clustering results. The purpose of this paper is to propose an improved, efficient methodology to handle such a challenge.

According to the fact that the inner-class distance among samples within the same cluster is supposed to be smaller than the inter-class distance among clusters, the algorithm will dynamically adjust initial cluster centers that are randomly selected. Consequently, such adjusted initial cluster centers will be highly representative in the sense that they are distributed among as many samples as possible. As a result, local optima that are common in K-means clustering can then be effectively reduced. In addition, the algorithm is able to obtain all initial cluster centers simultaneously (instead of one center at a time) during the dynamic adjustment.

Experimental results demonstrate that the proposed algorithm greatly improves the accuracy of traditional K-means clustering results and, in a more efficient manner.

The authors presented in this paper an efficient algorithm, which is able to dynamically adjust initial cluster centers that are randomly selected. The adjusted centers are highly representative, i.e. they are distributed among as many samples as possible. As a result, local optima that are common in K-means clustering can be effectively reduced so that the authors can achieve an improved clustering accuracy. In addition, the algorithm is a cost-efficient one and the enhanced clustering accuracy can be obtained in a more efficient manner compared with traditional K-means algorithm.

Tourists’ destination image is crucial for visiting intentions. An ancient capital with diverse characteristics is an important component of China’s urban tourism. The purpose of this paper is to address the following questions: what are the differences and commonalities of the perceived destination image of ancient capitals? What makes the difference of the perceived destination image in these cities? Aside from the exterior factors, are there internal factors of cities that influence tourists’ cognition and perception of destination image?

The comment text data of Baidu tourism website were used to determine the differences in the destination images of China’s four great ancient capitals: Beijing, Xi’an, Nanjing and Luoyang. ROST content mining and semantic network analysis were for differences and commonalities of the perceived destination image, and correlation analysis was used to explore the internal factors of cities that influence tourists’ cognition and perception of destination image.

Though the same as ancient capital, the four ancient capitals’ images are far apart; historical interests are the core of tourism experience in ancient capital city; image perception is from physical carrier, history and culture, and human cognition; tourist’ destination affect of ancient capital is most from its history and culture; protecting identity and maintaining daily life are crucial for ancient city tourism.

Previous studies on ancient capitals have focused on the invariable identity of ancient capitals’ destination images, and left a gap on determining from where the invariable identity comes in general and how much it influences destination image. This gap was addressed in this study, by analyzing the destination images of four ancient capitals in China as cases. In this way, this study provided reference to the other ancient cities worldwide.

This study aims to conduct an empirical investigation of differing perceptions of nine types of urban space and nine visual elements among tourists in destination using a computer vision (CV) approach.

The data for this study was extracted from YFCC 100 M dataset. Nine types of urban space in Beijing were initially identified using a scene recognition model. Subsequently, a semantic segmentation model was applied, which yielded substantial evidence relating to nine visual elements that were used to elicit differing perceptions among tourists from different continents.

Tourists from three continents had different perceptions about corridors, old buildings, overlooks and traffic spaces, reflecting their cultural convention. Asians, Europeans and North Americans diversely gazed at the landscape element of buildings, foliage, sky and people in urban space. All those provided evidence to contribute to the tourist gaze theory's construction.

This study firstly depicted how tourists perceive the tourism symbol of urban space. The novel approach of employing two CV models offer methodological insights to tourism research relevant to visual perception.

游客对城市空间的感知:计算机视觉途径

本研究采用计算机视觉方法, 探究游客对旅游目的地九种城市空间类型及九种视觉元素的感知差异。

本研究数据提取自YFCC 100M图片数据集。首先, 利用场景识别模型识别了游客图片中的九种城市空间类型。其次, 应用语义分割模型识别了游客图片的九个视觉元素。这些分析结果被用于探究不同大洲游客的视觉感知差异。

来自不同大洲的游客对城市空间有不同的感知偏好。亚洲人更喜欢拍摄自己与著名的城市建筑, 欧洲人和北美人更喜欢自然元素, 如水、树叶和天空。不同大洲游客对视觉元素的偏好佐证了旅游凝视理论。

本研究选取了独特的城市空间为研究对象, 来验证游客凝视理论。此外, 两种计算机视觉模型为旅游研究提供了新的方法论视角。

La percepción de los turistas del espacio urbano: Un enfoque de vision artificial

Resumen

Los datos para este estudio se extrajeron del conjunto de datos YFCC 100 M. Inicialmente se identificaron nueve tipos de espacio urbano en Pekín mediante un modelo de reconocimiento de escenas. Posteriormente, se aplicó un modelo de segmentación semántica, que aportó pruebas sustanciales en relación con nueve elementos visuales que se utilizaron para suscitar percepciones diferentes entre turistas de distintos continentes.

El objetivo de este estudio es llevar a cabo una investigación empírica sobre las diferentes percepciones de nueve tipos de espacio urbano y nueve elementos visuales entre los turistas en destino, utilizando un enfoque de visión artificial (CV).

Los turistas de tres continentes tenían percepciones diferentes sobre los pasillos, los edificios antiguos, los miradores y los espacios de tráfico, lo que refleja su convención cultural. Los asiáticos, los europeos y los norteamericanos observaron de forma diversa el elemento paisajístico de los edificios, el follaje, el cielo y las personas en el espacio urbano. Todos ellos aportaron pruebas para contribuir a la construcción de la teoría de la mirada turística.

Este estudio describe por primera vez cómo los turistas perciben el símbolo turístico del espacio urbano. El novedoso enfoque de emplear dos modelos de vision artificial ofrece conocimientos metodológicos para la investigación del turismo relacionados con la percepción visual.

The purpose of this paper is first, to find out store image attributes valued by Chinese consumers in Beijing; second, to understand Chinese consumers' preference by comparing an international retailer with a domestic retailer; and third, to provide both international and domestic retailers with suggestions for store image improvement.

This study used a three‐stage approach to collect the data. First, two waves of semi‐structured interviews were carried out, followed by a survey, concluding with another wave of interviews. The survey data were analyzed using SPSS.

The paper finds that there are 18 important attributes in building a hypermarket retailer's store image in China. Beijing consumers are more concerned with a retailer's reputation and services than with the price. In terms of store image dimensions, the paper concludes that store atmosphere is the most important, followed by service personnel and merchandise.

The research scope is limited to Beijing.

The practical implications of the findings are that: store atmosphere is the most important store image dimension for Beijing consumers; Chinese consumers no longer look only for low prices; international hypermarket retailers hold better store image than domestic retailers; and corporate reputation is important for hypermarket retailers in China, followed by quality of goods and staff's service attitude.

This paper is the first to investigate Chinese consumers' perception of store image and top concerns when shopping at a hypermarket.

The main purpose of this study is to examine the impact of agricultural internet information (AII) acquisition on climate-resilient variety adoption among rice farmers in the Jianghan Plain region of China. Additionally, it explores the influencing channels involved in this process.

Based on survey data for 877 rice farmers from 10 counties in the Jianghan Plain, China, this paper used an econometric approach to estimate the impact of AII acquisition on farmers’ adoption of climate-resilient varieties. A recursive bivariate Probit model was used to address endogeneity issues and obtain accurate estimates. Furthermore, three main influencing mechanisms were proposed and tested, which are broadening information channels, enhancing social interactions and improving agricultural skills.

The results show that acquiring AII can overall enhance the likelihood of farmers adopting climate-resilient varieties by 36.8%. The three influencing channels are empirically confirmed. Besides, educational attainment, income and peer effects can facilitate farmers’ acquisition of AII, while climate conditions and age significantly influence the adoption of climate-resilient varieties.

Practical recommendations are put forward to help farmers build climate resilience, including investing in rural internet infrastructures, enhancing farmers’ digital literacy and promoting the dissemination of climate-resilient information through diverse internet platforms.

Strengthening climate resilience is essential for sustaining the livelihoods of farmers and ensuring national food security; however, the role of internet information has received limited attention. To the best of the authors’ knowledge, this study is the first to examine the casual relationship between internet information and climate resilience, which fills the research gap.

Academic contention occurs when research evidence is amenable to more than one interpretation. China has a long tradition of Shang Que (商榷), in which authors argue for their preferred interpretation. The modern form of this tradition is the Shang Que article, which often takes the form of research papers in Chinese-language journals and which tends to be question-oriented. Shang Que articles usually take the views of a particular author or article as the focus of independent and complete criticism by another, independent, academic. This paper explains the role of Shang Que articles in Chinese scholarship and their influence on international academia.

A bibliometric analysis was used to explore the characteristics and evolution of Chinese Shang Que articles using 30,577 articles published between 1979 and 2018. Microsoft Excel and Gephi were used for data analysis and visualization.

Findings suggest a decline in the number of Shang Que articles and an increase in the number of co-authors. Shang Que articles remained particularly prominent in Philosophy and Humanities and Social Sciences, where they focused on local issues such as classical Chinese, the Sinicization of Marxism and Chinese literature. This suggests that the number of Shang Que articles is related to the degree of internationalization of a research field.

Shang Que articles, which have been influenced by academic paradigms in English, are a fusion of China's Shang Que tradition and of the modern academic system. Through considering Shang Que articles, this paper explores the benefits of local academic traditions in non-English-speaking cultures.

The banking industry plays a key role in China's financial industry. In the past decade, the speed of the development of China's commercial banks has gradually declined. Commercial banks with different ownership structures also have certain differences in terms of operating efficiency, and their monetary policies are often different. Therefore, the authors study the impact of ownership structure on the efficiency of commercial banks under different monetary policies. This study also provides relevant reference opinions with regard to the healthy, sustainable and stable development of China's banking industry.

This paper mainly uses the two-stage data envelope analysis (DEA) model under meta-frontier and group frontier to study the deposit and loan efficiency changes of 16 banks from 2007 to 2014 under ownership structure heterogeneity. Furthermore, the model introduces the balance parameters between deposits and loans, in order to realize the mathematical abstraction description of macro-monetary policy.

First, based on bank efficiency analysis, the paper finds that most banks' loan efficiency is higher than their deposits. Second, the paper concludes that different monetary policies have little effect on bank deposit and loan efficiency, while ownership heterogeneity has a significant impact on bank performance. Finally, through the decomposition of the sources of inefficiency in bank performance, this paper finds that management and technology are two factors that affect the inefficiency of banks.

The authors work contributes to the existing literature in the following ways: First, to the best of the authors’ knowledge, this is the first attempt to use the DEA model to study the relationship between monetary policies and bank supply chain efficiency. The results may provide additional managerial implications for the banking industry from the perspective of monetary policies. The result is helpful in terms of explaining how and why banks should strengthen risk management, as well as how to deal with non-performing loans in management terms and finally, why banks should make financial technology innovations in technology terms.