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This article intends to explore the sustainability accounting practices that emerge from the business of artificial forestry in the Qingshui River society of southwest China in the 18th-19th centuries.

Using a historical approach, we set out to discuss the systematic use of “folk contract” as a tool of tracing accountability in timber trading and in the collective management of community forests in this region, based on the archives of Qingshui River Manuscripts.

The findings indicate that active transactions of small forest plots facilitated by the prevalent use of folk contracts allow both the landlords and the tenants to easily acquire cashflow needed any time before the harvest, and in turn prevent premature logging and deforestation for crop farming. An “open ledger” bookkeeping system emerged from the extensive contracting practices guarantees the functioning of a dualistic accountability system, where both market value of timbers and “face” value of community members' reputation are preserved for long-term sustainability of local economy, society and ecological environment.

From the perspective of economic anthropology, this study forms the link between the folk contract practice in sustainable forestry of the Qingshui River society and the emancipatory accounting literature.

Network orchestration has received widespread attention from scholars engaged in network-relationship governance research. This study aims to explore progress in network orchestration research and future prospects.

In this study, 105 articles related to network orchestration from the Web of Science Core Collection Database for the period 2006–2022 are collected as sample data, and bibliometric relationship maps of network orchestration research are visually presented using the CiteSpace software.

First, this study presents distributions of articles, methods, journals, authors, institutions and countries/regions in network orchestration research. Second, based on a reference co-citation analysis, three articles are identified as the key literature in network orchestration research. Based on a keyword co-occurrence analysis, the hotspots are found to include studies related to overall network and individual levels. A cluster analysis reveals six themes: innovation ecosystem, sustainable development, product development, sourcing, hub firm and innovation network. From a burst detection analysis, three frontiers emerge: organisation, collaboration and governance. Finally, some future research directions are proposed and important issues are raised.

This study is the first to reveal the progress of network orchestration research using quantitative bibliometric methods, and it provides insights to scholars and offers practitioners with a better understanding of network orchestration.

The purpose of this paper is to examine the key factors affecting Mainland Chinese students pursuing a Master of Education degree in Hong Kong on their study abroad decision and return intentions.

The current study employed a mixed-methods approach to investigate factors that affect Mainland Chinese students pursuing MEd degrees in Hong Kong. Participants were first invited to fill out a questionnaire. After collecting and analyzing the survey data, in-depth interviews with a selected group of students were carried out by the research team to obtain useful qualitative data to triangulate the survey findings. A purposeful and convenience sampling method, carried out through the personal network of the research team, was used to recruit MEd Mainland Chinese students in Hong Kong to participate in the current study.

The findings provided compelling evidence that Hong Kong was an attractive study destination to this particular group of MEd Chinese students. The findings also indicated that academic factors were more important than social, cultural and economic factors when it came to choosing their study destination. In contrast to previous studies, participants expressed a much stronger desire to return home upon graduation. The three most influential predictors of their decision to return were the lack of a Hong Kong teaching certificate (r=+0.36), the opportunity to contribute to their hometown (r=+0.31) and the inclination to be closer to family and friends (r=+0.20).

While a number of studies have been carried out to study why Mainland Chinese students chose Hong Kong as their study destination to pursue their teacher training degree, none of these studies focused exclusively on fee-paying MEd Chinese students. Hong Kong is facing keen competition from both traditional host countries and emerging host countries to recruit students from Mainland China. It is therefore crucial to understand the needs of these Mainland Chinese students in a competitive, globalized, tertiary education market, as the satisfaction of students, in the form of positive discussion among alumni, promotes a university’s reputation and sustains its advantage in attracting students.

The purpose of this paper is to identify corrosion types and corrosion transitions by a novel electrochemical noise analysis method based on Adaboost.

The corrosion behavior of Q235 steel was investigated in typical passivation, uniform corrosion and pitting solution by electrochemical noise. Nine feature parameters were extracted from the electrochemical noise data based on statistical analysis and shot noise theory. The feature parameters were analysis by Adaboost to train model and identify corrosion types. The trained Adaboost model was used to identify corrosion type transitions.

Adaboost algorithm can accurately identify the corrosion type, and the accuracy rate is 99.25%. The identification results of Adaboost for the corrosion type are consistent with corroded morphology analysis. Compared with other machine learning, Adaboost can identify corrosion types more accurately. For corrosion type transition, Adaboost can effectively identify the transition from passivation to uniform corrosion and from passivation to pitting corrosion consistent with corroded morphology analysis.

Adaboost is a suitable method for prediction of corrosion type and transitions. Adaboost can establish the classification model of metal corrosion, which can more conveniently and accurately explore the corrosion types. Adaboost provides important reference for corrosion prediction and protection.

The aim of this study is to present a novel approach based on semantic fingerprinting and a clustering algorithm called density-based spatial clustering of applications with noise (DBSCAN), which can be used to convert investor records into 128-bit semantic fingerprints. Inventor disambiguation is a method used to discover a unique set of underlying inventors and map a set of patents to their corresponding inventors. Resolving the ambiguities between inventors is necessary to improve the quality of the patent database and to ensure accurate entity-level analysis. Most existing methods are based on machine learning and, while they often show good performance, this comes at the cost of time, computational power and storage space.

Using DBSCAN, the meta and textual data in inventor records are converted into 128-bit semantic fingerprints. However, rather than using a string comparison or cosine similarity to calculate the distance between pair-wise fingerprint records, a binary number comparison function was used in DBSCAN. DBSCAN then clusters the inventor records based on this distance to disambiguate inventor names.

Experiments conducted on the PatentsView campaign database of the United States Patent and Trademark Office show that this method disambiguates inventor names with recall greater than 99 per cent in less time and with substantially smaller storage requirement.

A better semantic fingerprint algorithm and a better distance function may improve precision. Setting of different clustering parameters for each block or other clustering algorithms will be considered to improve the accuracy of the disambiguation results even further.

Compared with the existing methods, the proposed method does not rely on feature selection and complex feature comparison computation. Most importantly, running time and storage requirements are drastically reduced.

Epoxy resin (EP) is a kind of thermosetting resin, and its application is usually limited by poor toughness. In this case, a type of new flexible chain blocking hyperbranched polyester (HBP) was designed and synthesized. The purpose of this study is to enhance the toughness and dielectric properties of EP.

P-toluene sulfonic acid was used as the catalyst, with dimethy propionic acid as the branch unit and pentaerythritol as the core in the experiment. Then, n-hexanoic acid and n-caprylic acid were, respectively, put to gain HBP with a n-hexanoic acid and n-caprylic acid capped structure. The microstructure, mechanical properties, insulation properties and dielectric properties of the composite were characterized for the purpose of finding the appropriate proportion of HBP.

HBP enhanced the toughness of epoxy-cured products by interpenetrating polymer network structure between the flexible chain of HBP and the EP molecular chain. Meanwhile, HBP reduced the ε and tgδ of the epoxy anhydride-cured product by reducing the number of polar groups per unit volume of the EP through free volumes.

Yet EP is a kind of thermosetting resin, which is widely used in coating, aerospace, electronics, polymer composites and military fields, but it is usually limited by poor toughness. In a word, it is an urgent priority to develop new EP with better toughness and mechanical properties.

At present, HBP has been applied as a new kind of toughening strategy and as a modifier for EP. According to the toughening mechanism of HBP modified EP, the free volume of HBP creates a space for the EP molecule to move around when loaded. Moreover, the free volume could cause the dielectric constant of EP to diminish by reducing the content of polarizable groups. Meanwhile, the addition of HBP with flexible chains grafted to the EP could develop an interpenetrating network structure, thus further enhancing the toughness of EP

This paper aims to explore question and answer (Q&A) participation and behavioral patterns on academic social networking sites (ASNSs) from the perspective of multiple subjects such as academic, corporate and government institutions.

Focused on the Q&A service of ASNSs, this study chooses ResearchGate (RG) as the target ASNS and collects a large-scale data set from it, involving a sample of users and a Q&A sample about academic, corporate and government institutions. First, it studies the law of Q&A participation and the distribution of the type of user according to the sample of users. Second, it compares question-asking behavior and question-answering behavior stimulated by questions among the three types of institutions based on the Q&A sample. Finally, it discusses the Q&A participation and behavioral patterns of the three types of institutions in academic Q&A exchanges with full consideration of institutional attributes, and provides some suggestions for institutions and ASNSs.

The results show that these three types of institutions generally have a low level of participation in the Q&A service of RG, and the numbers of questions and answers proposed by institutional users conform to the power-law distribution. There are differences in Q&A participation and Q&A behavioral patterns among academic, corporate and government institutions. Government and academic institutions have more users participating in the Q&A service and their users are more willing to ask questions, while corporate institutions have fewer users who participate in the Q&A service and their users are inclined to provide answers. Questions from corporate institutions attract much more attention than those from the other two types of institutions.

This study reveals and compares the Q&A participation and the behavioral patterns of the three types of institutions in academic Q&A, thus deepening the understanding of the attributes of institutions in the academic information exchange context. In practice, the results can help guide different institutions to use the Q&A service of ASNSs more effectively and help ASNSs to better optimize their Q&A service.

In this paper, microbial transglutaminase (MTG) was applied to process silk fabric for improving its crease resistance under the prerequisite of maintaining other performances. Not only was the effect of MTG on silk fabric investigated through the Fourier transform infrared spectroscopy (FR), but analysis was also undertaken in the microcosmic structure of fibroin through the scanning electron microscope (SEM). Solo MTG treatment as well as compound treatments of MTG followed by hydrogen peroxide, protease and ultrasonic, all showed that MTG can improve the crease resistance of silk fabric. It also enhanced its tensile breaking strength or amended damage in the tensile breaking strength caused by pretreatments.

Simultaneously, comparison with other treatments showed that compound treatment of MTG followed by ultrasonic exerted a better coordinated effect and conferred better performances, which made the wrinkle recovery angle (WRA) increase by 17.4% and tensile breaking strength improve by 11.2% respectively. At the same time, other performances were still maintained well.

Based on the dynamic capability theory, our study tries to explore the mediator mechanism of service supply chain dynamic capability between market orientation and service innovation performance, as well as the boundary conditions in which service supply chain dynamic capability plays a role, in order to reveal the key elements and their mechanisms for manufacturing enterprises to improve service performance.

With a total of 317 valid questionnaires, structural equation modeling (SEM) was used to test the research model and hypotheses.

The empirical results confirm that the three types of service supply chain dynamic capability (environment insight capability, resource integration capability and resource reconfiguration capability) can partially mediate the relationship between firm market orientation (responsive and proactive market orientations) and service innovation performance. In addition, supply chain collaboration has different types of moderator effects on the relationship between the three types of service supply chain dynamic capability and service innovation performance.

This research discovers that market orientation and dynamic capability are the key factors leading to high service performance and reveals the mediating role of service supply chain dynamic capability between market orientation and service innovation performance. Moreover, this research explores the moderating role of supply chain collaboration in service supply chain resource reconfiguration capability and service innovation performance.

The dispersity of graphene oxide (GO) has an important effect on the properties of epoxy resin (EP) composites. Many modification and dispersion methods require the use of inert solvents which do not participate in the modification reaction, although GO can be uniformly dispersed in water and alcohol solvents. Based on this requirement, several inert solvents were selected as dispersion solvents to find out the suitable inert solvent for GO dispersion into EP matrix.

Several inert solvents with different solubility parameters were selected as dispersion solvents to prepare GO/EP composite. The microstructure, mechanical properties, insulation properties, dielectric properties and thermal property of the composite were characterized, which was due to find suitable inert solvent for GO dispersion into EP matrix.

The dispersity of N, N-dimethylformamide (DMF) was the best stable suspension state when it was used as solvent instead of occurring sedimentation and agglomeration. Moreover, DMF was further confirmed as a suitable inert solvent for the dispersion of GO into EP according to the mechanical properties, insulation properties and thermal conductivity characterization.

The dispersion of GO in solvents has already been researched, but the traditional solvents, such as alcohols and water, has shown their limitations with the increase of modification methods, which were not suitable for the modification environment such as cyanate graft modification. Therefore, it was very important to choose a kind of inert solvent for dissolving EP matrix and dispersing GO better.

Several inert solvents were used to disperse GO into EP, and the influence of different dispersing solvents on the adhesive was discussed through the analysis of the mechanical properties, insulation properties and thermal conductivity, which was due to explore the inert solvent suitable for GO dispersion.