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Straightness measurement of rail weld joint is of essential importance to railway maintenance. Due to the lack of efficient measurement equipment, there has been limited in-depth research on rail weld joint with a 5-m wavelength range, leaving a significant knowledge gap in this field.

In this study, the authors used the well-established inertial reference method (IR-method), and the state-of-the-art multi-point chord reference method (MCR-method). Two methods have been applied in different types of rail straightness measurement trollies, respectively. These instruments were tested in a high-speed rail section within a certain region of China. The test results were ultimately validated through using traditional straightedge and feeler gauge methods as reference data to evaluate the rail weld joint straightness within the 5-m wavelength range.

The research reveals that IR-method and MCR-method produce reasonably similar measurement results for wavelengths below 1 m. However, MCR-method outperforms IR-method in terms of accuracy for wavelengths exceeding 3 m. Furthermore, it was observed that IR-method, while operating at a slower speed, carries the risk of derailing and is incapable of detecting rail weld joints and low joints within the track.

The research compare two methods’ measurement effects in a longer wavelength range and demonstrate the superiority of MCR-method.

Social media networks like Twitter, Facebook, WhatsApp etc. are most commonly used medium for sharing news, opinions and to stay in touch with peers. Messages on twitter are limited to 140 characters. This led users to create their own novel syntax in tweets to express more in lesser words. Free writing style, use of URLs, markup syntax, inappropriate punctuations, ungrammatical structures, abbreviations etc. makes it harder to mine useful information from them. For each tweet, we can get an explicit time stamp, the name of the user, the social network the user belongs to, or even the GPS coordinates if the tweet is created with a GPS-enabled mobile device. With these features, Twitter is, in nature, a good resource for detecting and analyzing the real time events happening around the world. By using the speed and coverage of Twitter, we can detect events, a sequence of important keywords being talked, in a timely manner which can be used in different applications like natural calamity relief support, earthquake relief support, product launches, suspicious activity detection etc. The keyword detection process from Twitter can be seen as a two step process: detection of keyword in the raw text form (words as posted by the users) and keyword normalization process (reforming the users’ unstructured words in the complete meaningful English language words). In this paper a keyword detection technique based upon the graph, spanning tree and Page Rank algorithm is proposed. A text normalization technique based upon hybrid approach using Levenshtein distance, demetaphone algorithm and dictionary mapping is proposed to work upon the unstructured keywords as produced by the proposed keyword detector. The proposed normalization technique is validated using the standard lexnorm 1.2 dataset. The proposed system is used to detect the keywords from Twiter text being posted at real time. The detected and normalized keywords are further validated from the search engine results at later time for detection of events.

The purpose of this paper is to develop a statistical-based model to forecast future domestic water demand in the context of climate change, population growth and technological development in Yellow River.

The model is developed through the analysis of the effects of climate variables and population on domestic water use in eight sub-basins of the Yellow River. The model is then used to forecast water demand under different environment change scenarios.

The model projected an increase in domestic water demand in the Yellow River basin in the range of 67.85 × 10⁸ to 62.20 × 10⁸ m³ in year 2020 and between 73.32 × 10⁸ and 89.27 × 10⁸ m³ in year 2030. The general circulation model Beijing Normal University-Earth System Model (BNU-ESM) predicted the highest increase in water demand in both 2020 and 2030, while Centre National de Recherches Meteorologiques Climate Model v.5 (CNRM-CM5) and Model for Interdisciplinary Research on Climate- Earth System (MIROC-ESM) projected the lowest increase in demand in 2020 and 2030, respectively. The fastest growth in water demand is found in the region where water demand is already very high, which may cause serious water shortage and conflicts among water users.

The simple regression-based domestic water demand model proposed in the study can be used for rapid evaluation of possible changes in domestic water demand due to environmental changes to aid in adaptation and mitigation planning.

Web-based course assessment is a new thing at China's Open University – China Radio and Television Universities (China RTVUs). This article reports an innovative pilot study in this research area. The experimental course for integrated web-based assessment in this study is Advanced English Writing, which is a compulsory course in the B.A. English programme at China Central Radio and Television University (CCRTVU). The study started in March 2005 and it is still in progress at the moment. This article first describes the webbased assessment design of the course and the implementation procedures. Then it moves on to report some initial feedback from the student participants on the pilot study. The article ends with a tentative plan for further actions based on the current study.

The study performs an empirical test to assess the impact of the Pakistan-China Free trade agreement (FTA) on Pakistan, China, and the World's exports under homogenous and differentiated products. This study employs the modeling with Poisson specification with Poisson Pseudo-Maximum Likelihood method for the estimations. The results of empirical test show that the effect of FTA on the FTA and Non-FTA countries is greater in the differentiated product as compared to the homogenous product. Therefore, one of the most important policy implications provided by this study is that export enterprises need to concentrate on differentiated products as compare to the homogenous products after the implementation of the Pakistan-China FTA. Moreover, the previous literature concluded that Pakistan-China FTA was more beneficial for China as compared to Pakistan. However, according to this study, if Pakistani enterprises focus more on differentiated products as compared to homogenous products, then it will be equally beneficial for both Chinese and Pakistani enterprises. This study will contribute to the literature by considering the Bertrand competition between asymmetric countries and find out the effect of the FTA on these three countries. It considers China, Pakistan, and the Rest of the World as first, second, and third countries.

In this chapter, rephrasing Spivak's question into ‘can subaltern children speak?’, I reorient the research on China's gigantic population of children and youths in rural migrant families towards a critical interpretative approach. Based on life history and longitudinal ethnographic interview gathered with three cases, I unpack the multiple meanings migrants' children attach to mobility in their childhood experiences. First, despite emotional difficulties, children see their parents' out-migration more as a ‘mobility imperative’ than their abandonment of parental responsibilities, which should be contextualized in China's long-term urban-biased social policies and the resultant development gaps in rural and urban societies. Second, the seemingly ‘unstable’ and ‘flexible’ mobility patterns observed in migrant families should be understood in relation to a long-term family social mobility strategy to promote children's educational achievement and future attainment. The combination of absent class politics in an illiberal society with an enduring ideology of education-based meritocracy in Confucianism makes this strategy a culturally legitimate channel of social struggle for recognition and respect for the subaltern. Last, children in migrant families are active contributors to their families' everyday organization amidst mobilities through sharing care and household responsibilities, and developing temporal and mobility strategies to keep alive intergenerational exchanges and family togetherness. The study uncovers coexisting resilience and vulnerabilities of migrants' children in their ‘doing class’ in contemporary China. It also contributes insights into our understanding of the diversity of childhoods in Asian societies at the intersection of familyhood, class dynamics and cultural politics.

This paper aims that mobile health (mHealth) applications have emerged as a key tool to support public health. However, there are only a few studies examining the influences of health-related ascribes on continuance intention to use mHealth apps and how these influences are contingent on gender in the mHealth app using context.

This study takes the protection motivation theory as a theoretical framework to examine the ordered relationship between threat and coping appraisals and their impacts on continuance intention to use mHealth apps. In addition, this study further extends the literature on gender differences into the mHealth app's context to investigate the moderating role of gender. The suggested hypotheses are confirmed by a structural equation modeling approach and multigroup investigation employing survey data of 345 users of Spring Rain Doctor in China, a typical mHealth app.

The findings suggest that the impact of perceived disease threat on user's continuance intention is mediated entirely by coping appraisals. Furthermore, the three coping appraisals' impacts are contingent upon gender. Specifically, response efficacy is more crucial for male users in forecasting continuance intention, whereas self-efficacy and response cost have a more salient influence on continuance intention for female users.

This study examines the ordered influences of threat and coping appraisal, moderated by gender, on continuance intention on use mHealth apps. These findings could contribute to relevant theoretical and practical implications.

The purpose of this study is to investigate the transport phenomena of smoke flow in a semi-open vertical shaft.

The large eddy simulation (LES) method was used to model the movement of fire-induced thermal flow in a full-scale vertical shaft. With this model, different fire locations and heat release rates (HRRs) were considered simultaneously.

It was determined that the burning intensity of the fire is enhanced when the fire attaches to the sidewall, resulting in a larger continuous flame region in the compartment and higher temperatures of the spill plume in the shaft compared to a center fire. In the initial stage of the fire with a small HRR, the buoyancy-driven spill plumes incline toward the side of the shaft opposite the window. Meanwhile, the thermal plumes are also directed away from the center of the shaft by the entrained airflow, but the inclination diminishes as HRR increases. This is because a greater HRR produces higher temperatures, resulting in a stronger buoyancy to drive smoke movement evenly in the shaft. In addition, a dimensionless equation was proposed to predict the rise-time of the smoke plume front in the shaft.

The results need to be verified with experiments.

The results could be applied for design and assessment of semi-open shafts.

This study shows the transport phenomena of smoke flow in a vertical shaft with one open side.

Nowadays businesses tend to compete with rivals by improving capability to meet customer demands. One of the key to improve logistics efficiency of a firm is to select appropriate supplier. In the past, to select the most suitable supplier, most people evaluated performance by using average performance or variance from historical data but did not mentioned skewness. In other words, skewness impact on supplier performance is ignored by researchers and buyers. In fact, supplier with greatest average performance does not confirm to be the most suitable one because of uncertainties which make its performance skew either to the left or right, i.e., lower or higher than expectation. Therefore, this empirical study aims to discover and determine the important role of skewness on supplier selection problem. After identifying influential criteria on supplier selection, we analyze skewness effect on suppliers’ performance in each criterion by surveying real data of suppliers’ performances. Skewness effect can be rated in 3 levels; no effect, moderately effect, and highly effect. The results show that, there is only one criterion with no skewness effect, which is price. Criteria which have high skewed performance, for both of medium-sized and large-sized buyers, are lead time, product quality and reliability, and on-time delivery. Also, skewness has higher effect on suppliers’ performance of medium-sized buyers than large-sized buyers. The conclusion surprisingly shows that, skewness is the best index to distinguish between good and bad suppliers, while mean is the worst index.

This study aims to take advantage of the unprecedented anti-corruption campaign launched in China in December 2012 and examine the effect of improved public governance on tunneling.

This study uses a sample of Shanghai and Shenzhen Stock Exchange listed companies from 2010 to 2014 and conduct regression analyses to investigate the effect of improved public governance attributed to the anti-corruption campaign on tunneling.

This study finds that the level of tunneling decreased significantly after the anti-corruption campaign, suggesting that increased public governance effectively curbs tunneling. Cross-sectional results show that this mitigating effect is more pronounced for non-SOE firms, especially non-SOE firms with political connections, firms audited by non-Big 8 auditors, firms with a large divergence between control rights and cash flow rights and firms located in areas with lower marketization.

This study highlights the importance of anti-corruption initiatives in improving public governance and in turn reducing tunneling. This study provides important implications for many other emerging economies to improve public governance.

This study contributes to the literature on the role of public governance in constraining corporate agency problems and advances the understanding of the economic consequences of China's anti-corruption campaign in the context of tunneling.