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The purpose of this paper is to provoke discussion on the choice of initial public offering (IPO) timing and issues that entrepreneurs need to think about when making such decision.

This case explores issues surrounding IPOs and in particular, the potential conflict of interest between company founder and external investors. H‐Solution, founded in 2002, was an entrepreneurial company in China's medical device industry. It started as an importer and distributor of advanced medical equipment and subsequently transformed its business model to providing integrated outsourcing solutions for hospitals. While Beta Venture, H‐Solution's venture capital (VC) investor, was eager to take the company public early, Xia Chen, H‐Solution's founder, was concerned that the increased disclosure requirement would force H‐Solution to disclose the details of its new business model to rivals, endangering H‐Solution's future market position and growth.

The paper finds that it is important to focus on a company's fundamentals and long‐term value creation. Senior managers should avoid decisions that may sacrifice the long‐term well‐being of the company for short‐term gains.

This case provides insight into the founder‐VC relationship and potential conflicts of interest between them. Students are encouraged to think about issues surrounding H‐Solution's IPO and decide whether or not the company should pursue a public offering given the circumstances. This case can be used in entrepreneurship and/or venture capital and private equity courses.

The purpose of this paper is to provide a summarization and review of the present author's main investigations on failure modes of reticular metal foams under different loadings in engineering applications.

With the octahedral structure model proposed by the present authors themselves, the fundamentally mechanical relations have been systematically studied for reticular metal foams with open cells in their previous works. On this basis, such model theory is continually used to investigate the failure mode of this kind of porous materials under compression, bending, torsion and shearing, which are common loading forms in engineering applications.

The pore-strut of metal foams under different compressive loadings will fail in the tensile breaking mode when it is brittle. While it is ductile, it will tend to the shearing failure mode when the shearing strength is half or nearly half of the tensile strength for the corresponding dense material and to the tensile breaking mode when the shearing strength is higher than half of the tensile strength to a certain value. The failure modes of such porous materials under bending, torsional and shearing loads are also similarly related to their material species.

This paper presents a distinctive method to conveniently analyze and estimate the failure mode of metal foams under different loadings in engineering applications.

The purpose of this paper is to focus on applications related to the hyperthermia treatment of cancer, with heating imposed either by a laser in the near-infrared range or by radiofrequency waves. The particle filter algorithms are compared in terms of computational time and solution accuracy.

The authors extend the analyses performed in their previous works to compare three different algorithms of the particle filter, as applied to the hyperthermia treatment of cancer. The particle filters examined here are the sampling importance resampling (SIR) algorithm, the auxiliary sampling importance resampling (ASIR) algorithm and Liu & West’s algorithm.

Liu & West’s algorithm resulted in the largest computational times. On the other hand, this filter was shown to be capable of dealing with very large uncertainties. In fact, besides the uncertainties in the model parameters, Gaussian noises, similar to those used for the SIR and ASIR filters, were added to the evolution models for the application of Liu & West’s filter. For the three filters, the estimated temperatures were in excellent agreement with the exact ones.

This work may help medical doctors in the future to prescribe treatment protocols and also opens the possibility of devising control strategies for the hyperthermia treatment of cancer.

The natural solution to couple the uncertain results from numerical simulations with the measurements that contain uncertainties, aiming at the better prediction of the temperature field of the tissues inside the body, is to formulate the problem in terms of state estimation, as performed in this work.

The purpose of this paper is to evaluate the impact of the International Financial Reporting Standards (IFRS) and eXtensible Business Reporting Language (XBRL) on audit fees based on evidence from listed companies operating in an emerging economy. Whilst IFRS constitute high-quality accounting standards, XBRL represents a technology standard that can enhance the usability of IFRS and overall financial reporting transparency.

Multivariate analyses are used on a sample of 1,798 firm-year observations between 2000 and 2011 from companies listed in the Shanghai Stock Exchange that were subject to XBRL and IFRS adoption mandates.

The main results suggest that XBRL has a main negative effect on audit fees which is weaker for larger firms. Additionally, the authors find that IFRS increases audit fees for all companies. Whilst this effect is positive for firms of different sizes, it is weaker for larger firms.

Whilst the findings are applicable to the selected sample and may or may not be generaliseable to other economies, they can provide important implications for both regulators and companies that are undertaking IFRS convergence and XBRL implementation projects in developing economies around the world.

This study offers a timely assessment of the economic consequences of IFRS and XBRL on listed companies operating in an emerging economy, in addition to providing an important basis upon which further research can be designed in order to extend the analysis.

An automatic text annotation system (ATAS) that can collect resources from different databases through Linked Data (LD) for automatically annotating ancient texts was developed in this study to support digital humanities research. It allows the humanists referring to resources from diverse databases when interpreting ancient texts as well as provides a friendly text annotation reader for humanists interpreting ancient text through reading. The paper aims to discuss whether the ATAS is helpful to support digital humanities research or not.

Based on the quasi-experimental design, the ATAS developed in this study and MARKUS semi-ATAS were compared whether the significant differences in the reading effectiveness and technology acceptance for supporting humanists interpreting ancient text of the Ming dynasty’s collections existed or not. Additionally, lag sequential analysis was also used to analyze users’ operation behaviors on the ATAS. A semi-structured in-depth interview was also applied to understand users’ opinions and perception of using the ATAS to interpret ancient texts through reading.

The experimental results reveal that the ATAS has higher reading effectiveness than MARKUS semi-ATAS, but not reaching the statistically significant difference. The technology acceptance of the ATAS is significantly higher than that of MARKUS semi-ATAS. Particularly, the function comparison of the two systems shows that the ATAS presents more perceived ease of use on the functions of term search, connection to source websites and adding annotation than MARKUS semi-ATAS. Furthermore, the reading interface of ATAS is simple and understandable and is more suitable for reading than MARKUS semi-ATAS. Among all the considered LD sources, Moedict, which is an online Chinese dictionary, was confirmed as the most helpful one.

This study adopted Jieba Chinese parser to perform the word segmentation process based on a parser lexicon for the Chinese ancient texts of the Ming dynasty’s collections. The accuracy of word segmentation to a lexicon-based Chinese parser is limited due to ignoring the grammar and semantics of ancient texts. Moreover, the original parser lexicon used in Jieba Chinese parser only contains the modern words. This will reduce the accuracy of word segmentation for Chinese ancient texts. The two limitations that affect Jieba Chinese parser to correctly perform the word segmentation process for Chinese ancient texts will significantly affect the effectiveness of using ATAS to support digital humanities research. This study thus proposed a practicable scheme by adding new terms into the parser lexicon based on humanists’ self-judgment to improve the accuracy of word segmentation of Jieba Chinese parser.

Although some digital humanities platforms have been successfully developed to support digital humanities research for humanists, most of them have still not provided a friendly digital reading environment to support humanists on interpreting texts. For this reason, this study developed an ATAS that can automatically retrieve LD sources from different databases on the Internet to supply rich annotation information on reading texts to help humanists interpret texts. This study brings digital humanities research to a new ground.

This study proposed a novel ATAS that can automatically annotate useful information on an ancient text to increase the readability of the ancient text based on LD sources from different databases, thus helping humanists obtain a deeper and broader understanding in the ancient text. Currently, there is no this kind of tool developed for humanists to support digital humanities research.

The purpose of this paper is mainly to know: (1) the sound absorption coefficient of porous composite structures constituted by a new kind of lightweight ceramic foam and perforated plate; (2) the availability of an equivalent porous material model, recently proposed by the present author, to these composite structures in sound absorption.

A kind of lightweight ceramic foam with bulk density of 0.38–0.56 g·cm-3 was produced by means of molding, drying and sintering. The effect of stainless steel perforated plate on sound absorption performance of the ceramic foam was investigated by means of JTZB absorption tester.

The results indicate that the sound absorption performance could be obviously changed by adding the stainless steel perforated plate in front of the porous samples and the air gap in back of the porous samples. Adding the perforated plate to the porous sample with a relatively large pore size, the sound absorption performance could be evidently improved for the composite structure. When the air gap is added to the composite structure, the first absorption peak shifts to the lower frequency, and the sound absorption coefficient could increase in the low frequency range.

Based on the equivalent porous material model and the “perforated plate with air gap” model, the sound absorption performance of the composite structures can be simulated conveniently to a great extent by using Johnson-Champoux-Allard model.

In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.

With the nickel foam made by the technique of electrodeposition on polymer foam, the purpose of this paper is to investigate the influence of several deferent processes on the surface morphology and the specific surface area of this porous product.

The surface morphologies of the nickel foam were examined by SEM. The specific surface area of the porous product was measured by gas (N₂) permeability method and also calculated by the reported formula.

The nickel foam from sintering in NH₃ decomposition atmosphere at 850°C will achieve the same specific surface area as that at 980°C, whether this porous structure after electrodeposition comes through direct sintering in NH₃ decomposition atmosphere, or through burning in air at 600°C for 4 min beforehand then the same reductive sintering.

There have been some studies on the preparation and application of nickel foam, but few works focus on the processing influence on the specific surface of this porous product. The present work provides the investigations on the difference of the product made under different producing conditions, and the influence of several deferent processes on the specific surface area of the product.

Prosocial lending in online crowdfunding has flourished in recent years, and it has become a new way to fundraise for philanthropy. However, there is almost a 70% user attrition rate in crowdfunding. The purpose of this study is to understand what the lender’s lending experience and social connection influence lender retention of online prosocial lending from a self-determination perspective.

Drawing on self-determination theory (SDT), this research utilizes a quantifiable method for factors of the lender's lending experience and social connection. Additionally, the research constructs economic models to explore the impacts of these factors acting as the necessary conditions for basic psychological needs on lender retention, using a large-scale sample of over 380,000 lenders from Kiva.

The results indicate that, from the lender's lending experience aspect, the loan narratives with more profit language in the last lending and the failure of past participation are negatively related to lender retention. Regarding the lender's social connection aspect, their friends or small lending teams are positively related to lender retention, while whether they are invited and lending team size show negative influence. Furthermore, results indicate the moderating effects of the disclosure of lending motivation.

This research explores the mechanism of lender retention of online prosocial lending, providing a self-determination perspective about how previous experience influences long-term lending behavior. The study offers significant implications for the literature on online philanthropy, SDT and user retention of online platforms. At the same time, the study provides an understanding of the effects of different aspects of SDT.