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The purpose of this paper is to promote the corrosion resistance of the 5083-111H aluminum alloy by laser cleaning.

Laser with 2 ns pulse width was adopted in this project and the corrosion resistance of cleaned samples was tested by copper-accelerated salt spray (CASS). The surface morphology, elemental composition and distribution were then characterized by SEM. Moreover, surface morphology, elemental composition and distribution were also tested.

Results suggested a higher corrosion resistance was successfully obtained by laser cleaning. Compared with samples cleaned by 2000 grit sandpaper, mechanical cleaning resulted in a 53% larger height difference between the peak and valley. The content of the oxygen is 8.85% on the surface cleaned mechanically and the distribution is dependent on the distribution of aluminum whereas that of the laser cleaning sample is 24.41% and the distribution existed even in the Al-poor area.

In this project, the 2-ns laser cleaning was proved to have the capability to remove the oxide layer on the aluminum alloy surface while retaining an excellent corrosion resistance and smooth surface. Meanwhile, a thorough elemental distribution and smaller grain size lead to a smaller difference in elemental concentration. This retards the diffusion of oxygen into the substrate and hence increases the corrosion resistance of the surface.

The proportional distribution of social labor is a general law governing human social and economic activities, also a law discovered by Marxist political economy that governs socialist economic operations and development based on public ownership.

This law draws on Marx's vision of future society, but how it is adopted is not only subject to the way a country's economy interacts but also to the influence of a country's historical and cultural traditions. Generations of the CPC and state leaders since Mao Zedong have made unremitting explorations for its application.

As socialism with Chinese characteristics enters a new era, the Party Central Committee with Comrade Xi Jinping at the core adheres to the standpoints, viewpoints and methods of Marxist political economy, draws from the splendid Chinese traditional culture that values integrity, peace and harmony of all, builds on the reality of China's socialist market economy development, has summed up the features of socialist economy development with Chinese characteristics, and has proposed the five-sphere integrated plan, the four-pronged comprehensive strategy.

The new development concept of “innovation, coordination, green development, openness, and sharing” for socialism with Chinese characteristics, all reflecting the Party's deepening understanding of coordinated development, the gradual formation of the general thought and policy methods of the country's economic regulations based on the coordination and balance of economic structure, the continuous explorations to open a new chapter of contemporary Marxist political economy, China's experience and wisdom, and the Party's confidence in the theories it applies, the road it takes, its system and its culture. The coordination and balance of economic structure are a major theoretical innovation of socialist political economy with Chinese characteristics in the new era.

Early turnover is a worldwide problem that occurs frequently during the first three years of employment. From a multidisciplinary perspective, this study attempts to find the economic, organizational and psychological factors that account for turnover at the early stage of employment.

The authors used turnover records provided by the human resources division of a US pharmaceutical company operating in China of 222 Medical Representatives (MR). The method of Firth's logistic regression for analyzing was employed.

As an economic factor, the favorable labor conditions (i.e. high ratio of job vacancies) at the time of recruitment were inversely associated with MR subsequent retention. For organizational factors, unsatisfactory supervision and disappointment of intra-organizational career were the major predictors, and job ranks showed a U-shaped relationship to early resignation. Moreover, working pressure was a psychological factor of early exit.

This study provides organizations with empirical implications to devise retention plans for newcomers at risk of attrition, which prevent them from early turnover in the industry facing a talent shortage. Studies based on the company exit records have little been done in turnover literature.

Laser cleaning, as a new type of cleaning technology, has the advantages of environment-friendliness, better selectivity, better controllability and higher efficiency compared to traditional chemical cleaning or grinding. This paper aims to use ultra-fast surface laser cleaning equipment built in laboratory to study the influence of different energy density (7.6, 11.5 and 15.3 J/cm²) on corrosion resistance of the aluminum alloy A7N01P-T4, a high-speed train body material.

SEM, white light interferometer, EDS and XPS were used to analyze the surface morphology, roughness, element content and oxide layer composition of aluminum alloy before and after cleaning. The corrosion resistance was studied by electrochemical experiments and exfoliation corrosion experiments.

The results showed that new oxide scale was formed on the surface after laser cleaning. The changes of surface roughness and chemical composition of oxide scale made a significant influence on corrosion behaviors. Better corrosion resistance was obtained with the energy density increased, and at the energy density of 11.5 J/cm², aluminum alloy exhibited the best corrosion resistance.

The paper only studies specific aluminum alloys and is not universal. Laser cleaning equipment is set up for the laboratory and has not yet been put into industrial production.

This paper indicated that ultra-fast laser processing was a new direction for the development of industrial equipment surface cleaning and carried out ultra-fast laser of aluminum alloy surface cleaning had certain research significance for its corrosion resistance.

Compared with the conventional cleaning methods such as air abrasives grinding or chemical cleaning, laser cleaning has advantages of environment-friendliness, better selectivity, better controllability and higher efficiency. Laser cleaning can not only protect the environment, but also improve cleaning efficiency.

Changes in the surface of aluminum alloys after ultra-fast surface laser treatment were found, and the mechanism of changes in aluminum alloy corrosion properties was clarified.

The COVID-19 pandemic has profoundly impacted small and medium-sized enterprises (SMEs), inherently vulnerable entities, prompting a pivotal question of how to enhance SMEs’ organizational resilience (OR) to withstand discontinuous crises. Although digital innovation (DI) is widely acknowledged as a critical antecedent to OR, limited studies have analyzed the configurational effects of DI on OR, particularly stage-based analysis.

Underpinned by the dynamic capabilities view, this study introduces a multi-stage dynamic capabilities framework for OR. Employing Latent Dirichlet Allocation (LDA), digital product innovation (DPI), digital services innovation (DSI) and digital process innovation (DCI) are further deconstructed into six dimensions. Furthermore, we utilized fuzzy-set qualitative comparative analysis (fsQCA) to explore the configuration effects of six DI on OR at different stages, using data from 94 Chinese SMEs.

First, OR improvement hinges not on a singular DI but on the interactions among various DIs. Second, multiple equivalent configurations emerge at different stages. Before the crisis, absorptive capability primarily advanced through iterative DPI and predictive DSI. During the crisis, response capability is principally augmented by the iterative DPI, distributed DCI, and integrated DCI. After the crisis, recovery capability is predominantly fortified by the iterative DPI, expanded DPI and experiential DSI. Third, iterative DPI consistently assumes a supportive role in fortifying OR.

This study contributes to the extant literature on DI and OR, offering practical guidance for SMEs to systematically enhance OR by configuring DI across distinct stages.

The purpose of this paper is to understand the factors that enable and inhibit WhatsApp users' discontinuance intention (DI) following the change in WhatsApp's privacy policy.

Using the enabler-inhibitor model as a framework, a research model consisting of discontinuation enabler distrust (DT) and the DT's antecedents [(negative electronic word of mouth (NEWOM), negative offline word of mouth (NOWOM) and privacy invasion (PI)], discontinuation inhibitor inertia (INR) and INR's antecedents (affective commitment, switching cost and use habit) and moderator structural assurance was proposed and tested with data from 624 WhatsApp users using partial least square structure equational modeling (PLS-SEM).

The results show that DT created due to NEWOM and a sense of PI significantly impact DI. However, INR has no significant impact on DI. Structural assurance significantly moderates the relationship between DT and DI.

The paper collected data when many WhatsApp users switched to other platforms due to the change in WhatsApp's terms of service. The timing of data collection allowed for collecting the real impact of the sense of PI compared to other studies where the effect is hypothetically induced. Further, the authors acknowledge social media providers' efforts to address privacy criticism and regain users’ trust, an area that has received little attention in prior literature.

The skin and skeleton of aircraft are connected by adhesives or rivets to bear and transfer aerodynamic load. It is easy for crack and fracture damage to occur under the action of cyclic load, thus reducing aircraft bearing capacity/integrity and causing serious security risks. Therefore, it is particularly important that passive wireless radio frequency identification (RFID) sensors be used for the health monitoring of aircraft skin in its whole life cycle. This paper aims to investigate the influence of miniaturization on the coupling effect between RFID tag sensors.

Two groups of crack sensing systems based on RFID tags were designed. Gain and mutual impedance of sensor tags were analyzed via mode analysis. The reliability of crack detection of both sensing systems was compared using a preset experimental scheme.

Miniaturized antennas can reduce edge influence and the coupling effect. Gain and mutual impedance decrease with the increase in distance between dual tags. Backscatter power shows a decreasing trend and threshold power to activate tags in reader antenna increases. Results show that the miniaturization of size is more suitable for the application of multiple sensors.

By comparing two groups of sensing systems, the consistency of crack detection sensitivity is better when small tags are placed in parallel, which provides a theoretical basis for the application of small, passive and densely distributed crack sensors in the future.

Text mining has been used for various knowledge discovery based applications, and thus, a lot of research has been contributed towards it. Latest trending research in the text mining is adopting the incremental learning data, as it is economical while dealing with large volume of information.

The primary intention of this research is to design and develop a technique for incremental text categorization using optimized Support Vector Neural Network (SVNN). The proposed technique involves four major steps, such as pre-processing, feature selection, classification and feature extraction. Initially, the data is pre-processed based on stop word removal and stemming. Then, the feature extraction is done by extracting semantic word-based features and Term Frequency and Inverse Document Frequency (TF-IDF). From the extracted features, the important features are selected using Bhattacharya distance measure and the features are subjected as the input to the proposed classifier. The proposed classifier performs incremental learning using SVNN, wherein the weights are bounded in a limit using rough set theory. Moreover, for the optimal selection of weights in SVNN, Moth Search (MS) algorithm is used. Thus, the proposed classifier, named Rough set MS-SVNN, performs the text categorization for the incremental data, given as the input.

For the experimentation, the 20 News group dataset, and the Reuters dataset are used. Simulation results indicate that the proposed Rough set based MS-SVNN has achieved 0.7743, 0.7774 and 0.7745 for the precision, recall and F-measure, respectively.

In this paper, an online incremental learner is developed for the text categorization. The text categorization is done by developing the Rough set MS-SVNN classifier, which classifies the incoming texts based on the boundary condition evaluated by the Rough set theory, and the optimal weights from the MS. The proposed online text categorization scheme has the basic steps, like pre-processing, feature extraction, feature selection and classification. The pre-processing is carried out to identify the unique words from the dataset, and the features like semantic word-based features and TF-IDF are obtained from the keyword set. Feature selection is done by setting a minimum Bhattacharya distance measure, and the selected features are provided to the proposed Rough set MS-SVNN for the classification.

The principal aim of the present study was to identify and model the subject structure of the research area on collaborative information behaviour (CIB).

A qualitative, inductive and exploratory approach was adopted, and the method of thematic analysis was used. This study was based on the analysis of 79 publications selected from the Library, Information Science and Technology Abstracts (LISTA) database in April 2019.

Collaborative and collective information behaviours were differentiated, and the subject structure of the CIB research area was identified to contain collaborative activities oriented to both information access and content, their various conditions, means of conducting, experiences of selected communities and metascientific research on the area itself.

The limitations result primarily from relying on the research material selected from the database (LISTA) focussed mainly on the issues of library and information science.

This study contributes by proposing an original model of the CIB research area representing its subject structure and providing a coherent list of subjects of interest to CIB researchers. Hopefully, it will also contribute to the harmonisation of terminology related to this research area and thus facilitate communication between CIB researchers and accelerate the cumulative development of scientific knowledge on CIB.

Considering the current importance of leadership, digital transformation and performance in the changes state higher education institutions (HEIs) have been subject to, this study aims to present an analysis of how these three concepts have been related in the literature.

This study proposes to study the state-of-the-art of research on leadership styles, digital transformation and performance in a single study, through a systematic literature review using two major databases, ISI Web of Science and Scopus.

The results reveal that the most common leadership style in the articles analysed is transformational; the most studied dimension of performance is the one representing teaching and learning activities; and the most discussed aspects of digital transformation are those concerning online learning systems and various types of technology. Identifying gaps in the literature, a future research agenda is formulated.

Amongst the theoretical implications of this study are the importance of understanding leadership styles and digital transformation for better understanding of state HEIs' performance as well as its dimensions, considering the relations found between these constructs. Therefore, there is greater theoretical advancement in the study of transformational leadership, diverse educational technologies, online teaching systems, global performance and teaching/learning.