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In view of the difficulty in determining the key parameters d in the Corten-Dolan model, based on the introduction of small loads, damage degrees and stress states to the Corten-Dolan model and the existing improved model, the sequential effects of the adjacent two-stage load were further considered.

Two improved Corten-Dolan models were established on the basis of modifying the parameter d by two different methods, namely, increasing stress ratio coefficient as well as considering the effects of loading sequence and damage degree as independent influencing factors respectively. According to the test data of the welded joints of common materials (standard 45 steel), alloy materials (standard 16Mn steel) and Q235B steel, the validity and feasibility of the above two improved models for fatigue life prediction were verified.

Results show that, compared with the traditional Miner model and the existing Corten-Dolan improved model, the two improved models have higher prediction accuracy in the fatigue life prediction of welding materials whether under two-stage load or multi-stage load.

Because the mathematical expressions of the models are relatively simple and need no multi-layer iterative calculation, it is convenient to predict the fatigue life of welded structure in practical engineering.

Since the declaration of reform and market opening from China in 1990, China has drawn much attention from the world thanks to its rapid economic growth and its emergence as the world's major consumer market and the center of the global economy. Moreover, it established the new trade order, making East Asia the center of the new trade trend as it becomes a manufactural and sales stronghold of multinational companies. The Chinese distribution market is expected to show a high growth rate by 2010 and it draws attention as a new business sector which can bring huge profits. However, advancement of the Chinese distribution industry now faces systemic problems and research on such problems is insufficient. Therefore, in this study we will conduct SWOT analysis based on previous studies on the Chinese distribution industry and use it as a ground to propose strategic solutions for development.

This paper aims to study the FinTech enterprises and the management theories related to this subject in a scientific way.

This study is a bibliometric study on FinTech enterprises. Its origin is a survey of 1,749 papers in 6 traditional peer-reviewed academic databases (e.g. Science Direct and Scopus) and in the “gray” literature, published by other agents and not subject to double-blind peer review. In this analysis we use three approaches: academic paper or not; journal main interest, and main purpose of the paper.

The first approach shows 45% of papers without blind review. The second approach shows no concentration on any journal. It represents no concentration on any kind of specific journal. And the third approach shows four kinds of contents in all researched papers: FinTech categorizations; FinTech related to theory of disruptive innovation; FinTech and theories of administration or economy; and finally, FinTech and regulatory and legislative aspects.

The findings identified the emergence of new research strands, precedence of studies of “gray” literature to explain the phenomenon, distribution of studies in different fields of knowledge (e.g. information technology, business and law) and lack of consensus in theories to explain the matter.

The proliferation of technological advancements has facilitated unrestricted access to and customizable consumption of content for viewers. Over-the-top (OTT) services are becoming more and more popular as the number of people using video streaming services grows around the world. In this context, this study aims to identify the antecedents and outcomes of Customer over-the-top Experience (COTTE) by synthesizing the existing research.

This research used the systematic literature review approach to identify the antecedents and outcomes of COTTE, along with the publication schedule, theories, analytical techniques, research methodology, and geographic scope of the 47 studies identified from the Scopus and Web of Science database.

The findings elucidate various antecedents of COTTE, including user-related, social, content-related, and website/platform-related factors. Additionally, diverse outcomes, encompassing behavioural/attitudinal and company-related factors have been discussed. Furthermore, an integrated framework is presented herein, synthesizing extant research and guiding future researchers in this domain.

The study’s findings offer a novel perspective for service providers aiming to enhance the OTT experience for their customers. This study stands out as one of the first to comprehensively present the antecedents and consequences of COTTE.

The type 120 emergency valve is an essential braking component of railway freight trains, but corresponding diaphragms consisting of natural rubber (NR) and chloroprene rubber (CR) exhibit insufficient aging resistance and low-temperature resistance, respectively. In order to develop type 120 emergency valve rubber diaphragms with long-life and high-performance, low-temperatureresistant CR and NR were processed.

The physical properties of the low-temperature-resistant CR and NR were tested by low-temperature stretching, dynamic mechanical analysis, differential scanning calorimetry and thermogravimetric analysis. Single-valve and single-vehicle tests of type 120 emergency valves were carried out for emergency diaphragms consisting of NR and CR.

The low-temperature-resistant CR and NR exhibited excellent physical properties. The elasticity and low-temperature resistance of NR were superior to those of CR, whereas the mechanical properties of the two rubbers were similar in the temperature range of 0 °C–150 °C. The NR and CR emergency diaphragms met the requirements of the single-valve test. In the low-temperature single-vehicle test, only the low-temperature sensitivity test of the NR emergency diaphragm met the requirements.

The innovation of this study is that it provides valuable data and experience for future development of type 120 valve rubber diaphragms.

Informal street vending is traditionally widespread and studied concerning developing countries. Nevertheless, recently, interest in the study of this practice has also increased regarding specific developed countries. The aim of the article is to contribute to overcoming the tendency to investigate this informal economy sector with different analytical lenses between the global South and global North and to highlight the usefulness of analyzing the phenomenon from a comparative perspective.

Therefore, the article represents a comparative review of the existing literature on informal street vending considering both the global South and global North.

The analysis revealed similarities and differences in the characteristics the phenomenon assumes in the two areas of the world while at the same time, showing how there are aspects mainly explored in the literature of southern countries and little explored in the literature of northern countries and vice-versa.

This analytical attempt allows us to highlight any gaps present in the literature, which may represent the basis for future comparative research on the topic. Comparative research will improve both theoretical and empirical knowledge of the phenomenon.

On the one hand, the article represents an innovative literature review attempt, as it explicitly compares the street vending between developing and developed countries. On the other hand, it represents the first academic contribution to review street vending in the global North.

This study aims to examine the effectiveness of an integrated intervention program for alcoholism (IIPA) for improving verbal encoding and memory, visuospatial construction, visual memory and quality of life (QoL) in persons with alcohol dependence.

The sample comprised treatment-seeking alcohol-dependent persons (n = 50), allotted into two groups: (1) the treatment as usual (TAU) group (n = 25) and (2) the treatment group (n = 25)]. The groups were matched on age (±1 year) and education (±1 year). The TAU group received standard pharmacological treatment, psychotherapeutic sessions on relapse prevention and yoga for 18 days, while the treatment group received IIPA sessions in addition to the usual treatment. Auditory verbal learning test, complex figure test and QoL scale were administered at pre- and post-treatment along with screening measures.

The two groups were comparable on demographic variables, clinical characteristics and outcome measures at baseline. Pre- to post-treatment changes (gain scores) comparison between the treatment and TAU groups revealed a significant difference in verbal encoding, verbal and visual memory, verbal recognition, visuospatial construction and QoL.

This study suggests that IIPA is effective for improving learning and memory in both modality (verbal and visual) and QoL in persons with alcoholism. The IIPA may help in better treatment recovery.

The IIPA may help in treatment for alcoholism and may enhance treatment efficacy.

IIPA is effective for improving learning and memory in both modalities and QoL in persons with alcohol dependence. The IIPA may help in better treatment recovery.

Carbon trading mechanism has been adopted to foster the green transformation of the economy on a global scale, but its effectiveness for the power industry remains controversial. Given that energy-related greenhouse gas emissions account for most of all anthropogenic emissions, this paper aims to evaluate the effectiveness of this trading mechanism at the plant level to support relevant decision-making and mechanism design.

This paper constructs a novel spatiotemporal data set by matching satellite-based high-resolution (1 × 1 km) CO₂ and PM_2.5 emission data with accurate geolocation of power plants. It then applies a difference-in-differences model to analyse the impact of carbon trading mechanism on emission reduction for the power industry in China from 2007 to 2016.

Results suggest that the carbon trading mechanism induces 2.7% of CO₂ emission reduction and 6.7% of PM_2.5 emission reduction in power plants in pilot areas on average. However, the reduction effect is significant only in coal-fired power plants but not in gas-fired power plants. Besides, the reduction effect is significant for power plants operated with different technologies and is more pronounced for those with outdated production technology, indicating the strong potential for green development of backward power plants. The reduction effect is also more intense for power plants without affiliation relationships than those affiliated with particular manufacturers.

This paper identifies the causal relationship between the carbon trading mechanism and emission reduction in the power industry by providing an innovative methodology for identifying plant-level emissions based on high-resolution satellite data, which has been practically absent in previous studies. It serves as a reference for stakeholders involved in detailed policy formulation and execution, including policymakers, power plant managers and green investors.

Current models of transaction credit in the e-commerce network face many problems, such as the one-sided measurement, low accuracy and insufficient anti-aggression solutions. This paper aims to address these problems by studying the transaction credit problem in the crowd transaction network.

This study divides the transaction credit into two parts, direct transaction credit and recommended transaction credit, and it proposes a model based on the crowd transaction network. The direct transaction credit comprehensively includes various factors influencing the transaction credit, including transaction evaluation, transaction time, transaction status, transaction amount and transaction times. The recommendation transaction credit introduces two types of recommendation nodes and constructs the recommendation credibility for each type. This paper also proposes a “buyer + circle of friends” method to store and update the transaction credit data.

The simulation results show that this model is superior with high accuracy and anti-aggression.

The direct transaction credit improves the accuracy of the transaction credit data. The recommendation transaction credit strengthens the anti-aggression of the transaction credit data. In addition, the “buyer + circle of friends” method fully uses the computing of the storage ability of the internet, and it also solves the failure problem of using a single node.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.