Search results

The purpose of this study was to explore the differences in the corrosion behavior of carbon steel in simulated reverse osmosis (RO) product water, and in seawater.

The wire beam electrodes (WBE) and coupons made from Type Q235 carbon steel and were immersed in simulated reverse osmosis product water, and in seawater, for fifteen days. The corrosion potential distribution on the WBE at different times was measured. The corrosion rates of the carbon steel in different solutions were obtained using weight loss determinations. The different corrosion behavior of carbon steel in the two kinds of solution was analyzed.

The results showed that the average corrosion potential, micro-cathode potential and micro-anode potential of the WBE decreased with time in simulated RO product water. During this period, the maximum potential difference between micro-cathodes and micro-anodes on the WBE surface also decreased with time. The potential difference was more than 260mV at the beginning of the test and was still greater than 110mV after fifteen days of immersion. The positions of cathodes and anodes remained basically unchanged and corrosion took place on the localized anode during the experiments. The average corrosion potential, micro-cathode potential and micro-anode potential on the WBE surface also decreased with time in the simulated seawater. However, the maximum potential difference between micro-cathode and micro-anode on the WBE surface in the simulated seawater was much smaller than was the case in simulated RO product water. It was 37.8 mV at the beginning of the test and was no more than 12mV after two days immersion. The positions of cathode region and anode kept changing, leading to overall uniform corrosion. The actual corrosion rate on the corroded anode region in simulated RO product water was greater than was the case in simulated seawater.

The corrosion behavior differences of carbon steel between in RO product water and in seawater were revealed by using wire beam electrodes (WBE). From the micro point of view, it explained the reason why the actual corrosion rate of carbon steel in RO product water was greater than that in sea water. The results can be helpful to explore future corrosion control methods for carbon steel in RO product water.

Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that incorporating online review data can enhance the performance of tourism demand forecasting models, the reliability of online review data and consumers’ decision-making process have not been given adequate attention. To address the aforementioned problem, the purpose of this study is to forecast tourism demand using online review data derived from the analysis of review helpfulness.

The authors propose a novel “identification-first, forecasting-second” framework. This framework prioritizes the identification of helpful reviews through a comprehensive analysis of review helpfulness, followed by the integration of helpful online review data into the forecasting system. Using the SARIMAX model with helpful online review data sourced from TripAdvisor, this study forecasts tourist arrivals in Hong Kong during the period from August 2012 to June 2019. The SNAÏVE/SARIMA model was used as the benchmark model. Additionally, artificial intelligence models including long short-term memory, back propagation neural network, extreme learning machine and random forest models were used to assess the robustness of the results.

The results demonstrate that online review data are subject to noise and bias, which can adversely affect the accuracy of predictions when used directly. However, by identifying helpful online reviews beforehand and incorporating them into the forecasting process, a notable enhancement in predictive performance can be realized.

First, to the best of the authors’ knowledge, this study is one of the first to focus on the data issue of online reviews on tourism arrivals forecasting. Second, this study pioneers the integration of the consumer decision-making process into the domain of tourism demand forecasting, marking one of the earliest endeavors in this area. Third, this study makes a novel attempt to identify helpful online reviews based on reviews helpfulness analysis.

How to extract useful information from a very large volume of literature is a great challenge for librarians. Topic modeling technique, which is a machine learning algorithm to uncover latent thematic structures from large collections of documents, is a widespread approach in literature analysis, especially with the rapid growth of academic literature. In this paper, a comparison of topic modeling based literature analysis has been done using full texts and abstracts of articles.

The authors conduct a comparison study of topic modeling on full-text paper and corresponding abstract to assess the influence of the different types of documents been used as input for topic modeling. In particular, the authors use the large volumes of COVID-19 research literature as a case study for topic modeling based literature analysis. The authors illustrate the research topics, research trends and topic similarity of COVID-19 research by using Latent Dirichlet allocation (LDA) and topic visualization method.

The authors found 14 research topics for COVID-19 research. The authors also found that the topic similarity between using full-text paper and corresponding abstract is higher when more documents are analyzed.

First, this study contributes to the literature analysis approach. The comparison study can help us understand the influence of the different types of documents on the results of topic modeling analysis. Second, the authors present an overview of COVID-19 research by summarizing 14 research topics for it. This automated literature analysis can help specialists in the health and medical domain or other people to quickly grasp the structured morphology of the current studies for COVID-19.

The purpose of this paper is to investigate the mechanism how the platform obtains and uses undisclosed information to determine individual borrowers’ credit score and to examine the effectiveness of credit scoring in predicting default. The motivation stems from the fact that there is little evidence about the role of P2P platform, which has been positioned as a kind of information intermediary.

Using a sample of 5,176 unsecured P2P loans having expired before December 31, 2015 on Renrendai.com and an approach of two-stage regression, the paper first estimates the undisclosed information embedded in credit score by regressing credit score on four types of public information about a borrower’s creditworthiness. Then, the authors use a Logit regression to examine the role of the excess information in predicting the default probability.

The certification information provided by the platform is the most important determinant for a borrower’s credit score and the undisclosed information embedded in credit score can predict the loan performance better than the public information of posted listings. Moreover, the predictive ability of the undisclosed information is better for high-risk borrowers than for low-risk ones.

Providing a credit score for each individual is a way for P2P platforms to play an information intermediary role. More evidence about whether or how a platform plays its role are worthy to be exploited by investigating a platform’s operating policies in detail and doing cross-platform comparative studies.

The results about the effect of various types of information on loan performance can provide an insightful guidance for P2P platforms to optimize their mechanism on information disclosure and credit scoring.

The existing literature mainly focuses on the effects of information voluntarily disclosed by borrowers and the behaviors of investors on P2P lending outcomes. The paper highlights the information intermediary role played by the platform and presents empirical evidence that credit scoring for individual borrowers is a way for P2P platforms to promote the direct lending for individual.

Hydro-viscous drive (HVD) clutches are widely used in equipment requiring soft start, such as fans and pumps, to transmit torque and adjust speed by changing the gap distance between friction pairs. This paper aims to propose a novel two-parameter evaluation method for HVD during the mixed lubrication stage. The objective is to develop an effective model that establishes the relationship between these parameters and the actual surface topography.

In the presented methods, the fractal features of the real manufacturing surface are calculated based on the power spectrum function by the ultra-depth three-dimensional microscope. After that, the hybrid friction model of the friction plate is established based on mixed elasto-hydrodynamic lubrication theory, boundary friction model and fractal theory. Then the torque and load bearing characteristics of the clutch are obtained, and the influences of the surface fractal features are investigated and discussed. Finally, the Weierstrass–Mandelbrot function is adopted for the surface topography characterization and evaluation.

The results indicate that the proposed method exhibits good accuracy, while the speed difference between the friction pair exceeds 2,500 rpm. It is concluded that this paper proposed a way to evaluate the torque and loading capacity of HVD considering the real manufacturing surface topography and is helpful for surface optimization.

The originality and value of this study lie in its development of a novel torque and load bearing capacity evaluation method for HVD in mixed lubrication stage, considering manufacturing surface topography and describing the real manufacturing surface.

This paper aims to investigate the influence of the contact status between the seal ring and its support on the seal performance in hydrostatic mechanical face seal.

A thermal fluid-solid interaction (TFSI) model of hydrostatic mechanical face seal is further developed, in which the multi-body contacts between components are particularly given more attention. The numerical models of the flow field and complete seal assemblies are developed. A specific energy equation is obtained to simplify the calculation of film temperature. Based on the mechanism for the continuity condition of the physical quantities at the fluid–solid interface, the TFSI model uses an on-line iterative coupling method.

The contact status between seal ring and its support affects the seal performance significantly. The rotating ring and the stationary ring contribute differently because of the contact status difference.

The contact status between the seal ring and the ring seat is key to gain an insight into the performance of the hydrostatic mechanical face seal thus provides guidance for mechanical seal design.

Wealth Management Products (WMPs) are the largest and most crucial component of China's Shadow banking, which are off the balance sheet and considered as a substitute for deposits. Commercial banks in China are involved in the issuance of WMPs mainly to; evade the regulatory restrictions, move non-performing loans away from the balance sheet, chase the profits and take advantage of yield spread (the difference between WMPs yield and deposit rate).

In this study, the authors investigate what bank related characteristics and needs; influenced and prompted the issuance of WMPs. By using a quarterly panel data from 2010 to 2019, this study performed the fixed effects approach favored by the Hausman specification test, and a feasible generalized least square (FGLS) estimation method is employed to deal with any issues of heteroscedasticity and auto-correlation.

This study found that there is a positive and significant association between the non-performing loan ratio and the issuance of WMPs. Moreover, profitability and spread were found to play an essential role in the issuance of WMPs. The findings of this study suggest that WMPs are issued for multi-purpose, and off the balance sheet status of these products makes them very lucrative for regulated Chinese commercial banks.

Non-guaranteed WMPs are considered as an item of shadow banking in China, as banks do not consolidate this type of WMPs into their balance sheet; due to that reason, there is no individual bank data available for the amount of WMPs. The authors use the number of WMPs issued by banks as a proxy for the bank's exposure to the WMPs business.

From a regulatory perspective, this study helps regulators to understand the risk associated with the issuance of WMPs; by providing empirical evidence that Chinese banks issue WMPs to hide the actual risk of non-performing loans, and this practice could mislead the regulators to evaluate the bank credit risk and loan quality. This study also identifies that Chinese banks issue WMPs for multi-purpose; this can help potential investors to understand the dynamics of WMPs issuance.

This research is innovative in its orientation because it is designed to investigate the less explored wealth management products (WMPs) issued by Chinese banks. This study's content includes not only innovation but also contributes to the existing literature on the shadow banking sector in terms of regulatory arbitrage. Moreover, the inclusion of FGLS estimation models, ten years of quarterly data, and the top 30 Chinese banks (covers 70% of the total Chinese commercial banking system's assets) make this research more comprehensive and significant.

Leveraging the benefits of supply chain digitalization is a big challenge for many firms. To address this issue, this study aims to use information processing theory to explore the mechanisms between supply chain digitalization and supply chain performance.

Based on survey data from 223 Chinese companies, the authors tested the moderated mediation model using the Process program in SPSS.

The empirical results reveal that supply chain traceability and supply chain agility partially mediate the supply chain digitalization–supply chain performance relationship. More interestingly, the above significant mediation effects show differences across industries. In particular, manufacturing firms rely more on supply chain traceability, whereas supply chain agility contributes more to service firms. Lastly, supply chain dynamism is a significant moderator that enhances the mediation effect of supply chain traceability in the supply chain digitalization–supply chain performance relationship.

This study offers new insights into the growing literature on supply chain digitalization by proposing a new moderated mediation model that demonstrates the relative importance of different mediators. The findings also help managers boost their supply chain performance in the digital era.

The aim of this study is to undertake a systematic analysis of the supply chain literature to uncover the changes and patterns of international cooperation in the context of the COVID-19 pandemic.

In this study, the information on supply chain-related publications in the Web of Science (WOS) database is analyzed using statistical techniques and visual approaches. The focus is on the five countries with the highest number of supply chain publications, accounting for approximately 70% of global publications. This in-depth analysis aims to provide a clearer understanding of the cooperation patterns and their impact on the supply chain during the COVID-19 pandemic.

The results of the study reveal that the growth rate of international cooperation in supply chain research during the COVID-19 pandemic is higher compared to the 5-year and 10-year periods before the pandemic. This suggests that the pandemic has not hindered international cooperation in the field, but instead has increased collaboration. In terms of international cooperation patterns, the findings indicate that China and the USA have a strong partnership, with China being the largest partner for the USA and vice versa. The UK's largest partner is China, India's largest partner is the UK and Italy's largest partner is also the UK. This implies that trade, rather than the pandemic, is a determining factor in supply chain research.

This study examines the patterns of international cooperation in supply chain research during the COVID-19 pandemic, providing insights into the changes and mechanisms of international cooperation in this field. Moreover, the results of this study may offer practical benefits for supply chain operators and managers. By providing a deeper understanding of the international cooperation patterns in the field, this research could contribute to the recovery and growth of the global supply chain.

This study's analysis of the impact of crisis events, such as the COVID-19 pandemic, on international cooperation in supply chain research contributes to the theoretical development of the field. Additionally, by examining how academia responds to emergencies, it provides valuable insights for operations and supply chain managers in their pursuit of more effective supply chain management.

This study provides a preliminary examination of the international cooperation patterns of supply chain research in the context of the COVID-19 pandemic, representing a novel and early contribution to the existing literature, helping to expand upon current understanding in the field and provide a more comprehensive perspective. Furthermore, this study offers a practical analysis strategy for future supply chain research, fostering progress and growth in the field.

The car body stiffness of express freight sliding side covered wagon decreased for the sliding and the resonance vibration based on the flexible car body has affected the dynamics performances. Dynamic loading will cause fatigue cracks and eventually lead to fatigue failure of the car body. This paper aims to investigate the influence of car body flexibility on the evaluation of the failure.

In this paper, the railway vehicles random analysis procedure (RVRAP) is employed to study the fatigue failure of the rigid-flexibility model. Following the analysis process, the rigid-flexibility model is established and four contrastive schemes for simulation analysis are designed. To verify the results, an experimental test using the real car body structure on the vibration test plant is carried out; the RMS of dynamic stress is obtained and compared with the simulation results.

The results show that the flexibility of the car body has a crucial influence on the fatigue life.

The reliability is verified regarding the use of RVRAP at an appropriate stage on the antifatigue design of the vehicle.