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In order to extend the application of the original octagonal Goodman–Smith fatigue limit diagram, which is commonly used for the evaluation of structure fatigue stress in engineering, a modification of it is proposed for the structure made of S355 steel (commonly used in high-speed electric multiple units (EMUs) bogie frame).

The modification is made based on Deutscher Verband für Schweißen und verwandte Verfahren e. V. (DVS) 1612 standard and the γ-P-S-N curve, with consideration of the fatigue evaluation requirements of different survival rates and confidence levels. The verification of the modification is performed for three welded joints and for the comparison with the experimental data.

The results indicate that the design survival rate, the design safety margin and the fatigue stress evaluation of welded joint types are all improved by using the modified diagram.

There are relatively few studies on modifying octagonal Goodman–Smith fatigue limit diagram. In this paper, a modified diagram is proposed and applied in order to ensure the safety and durability of key welded structures of rail vehicles.

This study aims to test the link between enterprise digital transformation and technological innovation and the mechanisms and channels behind this link.

This study systematically examines whether and how enterprise digital transformation affects technological innovation in China.

Enterprise digital transformation effectively improves technological innovation. This result remains stable in robustness and endogeneity checks. The channel mechanisms of this promoting effect are internal (improvement of internal control quality and alleviation of agency costs) and external (increased attention of analysts and reduction of customer concentration). Moreover, this promoting effect is more significant for state-owned enterprises, small and medium-sized enterprises, enterprises in areas with low marketization and enterprises that do not enjoy digital subsidies from the government.

Enterprises need to attend to the mechanisms behind the link between digital transformation and technological innovation and to the unique effects of different enterprise attributes and capital markets, such as size, the ownership nature, the degree of regional marketization and government subsidies. Doing so will effectively promote digital transformation and technological innovation and strengthen core competitiveness.

This study provides systemic evidence of the link between enterprise digital transformation and technological innovation. The findings enrich the research literature on enterprise digitization and the factors of influencing enterprises’ technological innovation and provide a reasonable explanation for how enterprise digital transformation affects technological innovation.

In China, libraries can be grouped into three major categories: (1) the public libraries, headed by the National Library of China and including the provincial, municipal, prefectural, and county libraries; (2) the academic libraries under the control of the Ministry of Education, including the university and college libraries and middle and elementary school libraries; and (3) the libraries of the Chinese Academy of Sciences (Academic Sinica), including the science and research libraries. Academic libraries play a very special role in the country among these groups of libraries and are becoming increasingly important, as they are at the centre of information and education on each campus (Ma 1989).

The purpose of this paper is to propose a data prediction framework for scenarios which require forecasting demand for large-scale data sources, e.g., sensor networks, securities exchange, electric power secondary system, etc. Concretely, the proposed framework should handle several difficult requirements including the management of gigantic data sources, the need for a fast self-adaptive algorithm, the relatively accurate prediction of multiple time series, and the real-time demand.

First, the autoregressive integrated moving average-based prediction algorithm is introduced. Second, the processing framework is designed, which includes a time-series data storage model based on the HBase, and a real-time distributed prediction platform based on Storm. Then, the work principle of this platform is described. Finally, a proof-of-concept testbed is illustrated to verify the proposed framework.

Several tests based on Power Grid monitoring data are provided for the proposed framework. The experimental results indicate that prediction data are basically consistent with actual data, processing efficiency is relatively high, and resources consumption is reasonable.

This paper provides a distributed real-time data prediction framework for large-scale time-series data, which can exactly achieve the requirement of the effective management, prediction efficiency, accuracy, and high concurrency for massive data sources.

Oppositional loyalty toward rival brands is prevalent. Although its antecedents have increasingly received scholarly attention, the literature is rather disparate. Based on identity theory, this study aims to propose that oppositional loyalty is a brand identity-driven outcome and provides a unified framework for understanding the formation and activation of brand identity in influencing oppositional loyalty.

Structural equation modeling was used to test the theoretical framework based on an online survey of 329 brand community members. Multigroup analysis was used to test the moderating effect of inter-consumer brand rivalry and brand community engagement.

The results show that self-brand similarity, brand prestige and brand uniqueness lead to consumers’ brand identity (i.e. consumer-brand identification), which, in turn, facilitates oppositional loyalty. Furthermore, the results indicate that inter-consumer brand rivalry and brand community engagement are identity-salient situations that strengthen the relationship between consumer-brand identification and oppositional loyalty.

Identity has great power in shaping consumer behaviors. Fostering consumer-brand identification is critical for firms to prevent consumers from switching to competing brands. Inter-consumer brand rivalry and brand community engagement can help firms consolidate their customer base by evoking consumers’ brand identity.

This investigation makes theoretical contributions by providing a unified theoretical framework to model the development of oppositional loyalty based on identity theory.

The highly uncertain and turbulent environments nowadays intensify the paradoxical effects of supply base concentration (SBC) on improving cost efficiency while increasing idiosyncratic risk (IR). Digitalization is regarded as a remedy for this paradox, yet digitization's potentially curative effect has not been empirically tested. Leveraging the lenses of paradox theory and information processing theory (IPT), this study explores how two distinct dimensions of digitalization, i.e. digitalization intensity (DI) and digitalization breadth (DB), reconcile the paradoxical effects of SBC.

Using a panel dataset of 1,238 Chinese manufacturing firms in the period of 2012–2020, this study utilizes fixed-effects regression models to test the proposed hypotheses.

The authors discover that SBC enhances a firm's cost efficiency but induces greater IR. More importantly, there is evidence that DI restrains the amplifying effect of SBC on IR. However, DB weakens the enhancing effect of SBC on cost efficiency and aggravates the SBC's exacerbating effect on IR.

This study advances the understanding of the paradoxical effects of SBC on cost efficiency and IR from a paradox theory perspective. More importantly, to the best of the authors' knowledge, the authors' study is the first to untangle the differential roles of DI and DB in reconciling the paradox of SBC. This study also provides practitioners with nuanced insights into how the practitioners should use appropriate tactics to deploy digital technologies effectively.

The purpose of this paper is to empirically examine the impact of closing mechanism changes on market quality, investor trading behavior and market manipulation in the Shanghai stock market.

A dummy variable is constructed indicating whether the closing mechanism is call auction or continuous auction. Market quality is measured from aspects of liquidity, volatility and price continuity; investor trading behavior is scaled by order timing and order aggressiveness, and a price deviation indicator is the proxy of manipulation. Using panel regression, this study examines the impact of closing mechanism changes based on intraday transaction data from the Shanghai stock market.

The conclusions are as follows: First, market quality improves after the closing mechanism is reformed in terms of liquidity, volatility and price continuity. Second, order strategy changes significantly in the closing call market, and investors trade more aggressively in the continuous trading period before closing. Third, the closing call mechanism restrains the closing price manipulation and thus prompts an efficient closing price.

This paper examines the policy effects of closing mechanism changes from aspects of market quality, trading behavior and price manipulation, providing pieces of evidence for trading mechanism design and market supervision in emerging markets.

This paper aims to evaluate and compare the performance of different computer vision algorithms in the context of visual servoing for augmented robot perception and autonomy.

The authors evaluated and compared three different approaches: a feature-based approach, a hybrid approach and a machine-learning-based approach. To evaluate the performance of the approaches, experiments were conducted in a simulated environment using the PyBullet physics simulator. The experiments included different levels of complexity, including different numbers of distractors, varying lighting conditions and highly varied object geometry.

The experimental results showed that the machine-learning-based approach outperformed the other two approaches in terms of accuracy and robustness. The approach could detect and locate objects in complex scenes with high accuracy, even in the presence of distractors and varying lighting conditions. The hybrid approach showed promising results but was less robust to changes in lighting and object appearance. The feature-based approach performed well in simple scenes but struggled in more complex ones.

This paper sheds light on the superiority of a hybrid algorithm that incorporates a deep neural network in a feature detector for image-based visual servoing, which demonstrates stronger robustness in object detection and location against distractors and lighting conditions.

The purpose of this paper is to provide a micro historical account of the work of a key Chinese educational reformer, Tao Xingzhi (1891–1946), who transformed educational ideas from John Dewey to effect social and cultural change in 1920s–1940s China.

This paper examines English and Chinese language sources, including Tao’s poetry, to present a fresh analysis of Tao’s epistemological life history. It draws upon transnational historical approaches to chart the multidirectional circulation of progressive education philosophies around the globe. It also explores some conceptual dimensions of Chinese historical thinking and historiographical strategies.

Tao Xingzhi engaged in critical intercultural knowledge exchange in implementing educational reforms in China. He blended and critiqued Chinese and Deweyian educational philosophies to create unique educational reform, which involved reversing some of Dewey’s approaches as well as adapting others.

This paper foregrounds Tao Xingzhi’s agency in transforming some of Dewey’s ideas in the Chinese context and challenges studies that adopt an “impact-response” approach to Tao’s contribution, which suggest a one-way flow of knowledge from a “modern” West to a “traditional” China. It brings hitherto unexplored Chinese language sources to an English-speaking audience, particularly Tao’s poetry, to gain new historical insights into Tao’s educational reforms. It contributes to transnational understandings of the multidirectional flows of knowledge about Progressive educational philosophies around the world.