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The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

As foreign direct investment (FDI) plays an important role in economic globalization. This paper examines the structural features of the global FDI network based on FDI flows data and changes in the position of countries within the network.

In order to study the structural characteristics of the global FDI network and the status and changes of countries in the global FDI network, the authors build the investment network and apply the QAP (Quadratic Assignment Procedure) analysis to examine the evolutionary characteristics of the network and its influencing factors.

The global FDI network becomes more interconnected and has a clear “core-periphery” structure. The network connections and volumes have increased dramatically and most countries spread their assets across multiple countries, while only a handful of countries have concentrated investments. The topological structure of the global FDI network has changed noticeably, although this process has been slow and stable and countries in the core position have remained largely intact. The authors find that trade relations between countries, geographic distance and differences in economic size, income levels and institutional environments all have a significant impact on the global FDI network.

Although we find some valuable results, some aspects need further investigation. For example, how a country uses the investment network to boost its economy and how the different industries in the investment network change over time. It is important to get the industry-level details to understand the impact of the global investment network from a government's perspective.

FDI affects the distribution of international capital and contributes to the development of the global economy. Therefore, it is important to study the characteristics of the global FDI network and its development patterns. With more understanding about the network as well as its evolutionary pattern, the government can possibly carry out some policies to promote direct investments as well as economic development.

All countries should actively engage in international direct investments and strengthen their economic ties. At the same time, they can put more emphasis on inward or outward FDI based on their own level of economic development to better establish the circulation channel for domestic and international capital.

This paper examines foreign direct investments through the lens of a global network. In contrast to traditional bilateral studies, this paper focuses on the network structure and evolution, reflecting the dynamics of the entire direct investment system as well as the changing positions of participating countries.

The purpose of this study is to designed a robot odometry based on three dimensional (3D) laser point cloud data, inertial measurement unit (IMU) data and real-time kinematic (RTK) data in underground spatial features and gravity fluctuations environment. This method improves the mapping accuracy in two types of underground space: multi-layer space and large-scale scenarios.

An IMU–Laser–RTK fusion mapping algorithm based on Iterative Kalman Filter was proposed, and the observation equation and Jacobian matrix were derived. Aiming at the problem of inaccurate gravity estimation, the optimization of gravity is transformed into the optimization of SO(3), which avoids the problem of gravity over-parameterization.

Compared with the optimization method, the computational cost is reduced. Without relying on the wheel speed odometer, the robot synchronization localization and 3D environment modeling for multi-layer space are realized. The performance of the proposed algorithm is tested and compared in two types of underground space, and the robustness and accuracy in multi-layer space and large-scale scenarios are verified. The results show that the root mean square error of the proposed algorithm is 0.061 m, which achieves higher accuracy than other algorithms.

Based on the problem of large loop and low feature scale, this algorithm can better complete the map loop and self-positioning, and its root mean square error is more than double compared with other methods. The method proposed in this paper can better complete the autonomous positioning of the robot in the underground space with hierarchical feature degradation, and at the same time, an accurate 3D map can be constructed for subsequent research.

As Chinese stock market develops and grows, mutual fund plays an increasingly important role for strong financial strength and good social resources. This paper aims to present an overview of fund investment effect, identify the investment preference of institutional investors and explore the socially responsible investment value of mutual fund, especially green fund.

In order to test the green effects in the fund market, especially from the perspective of institutional shareholding, the authors build three panel data models to examine the attention, promotion and network effect respectively.

In general terms, the authors obtain a positive relationship between mutual funds and green firms (attention effect). This positive relationship is conducted by the comparison of institutional shareholding level between green firms and non-green firms by using two-sample t-test. The authors find that although all the coefficients of mutual funds' shareholding variables are positively related to social performance, only the number of mutual fund shareholders shows slight significance. The authors observe a stronger promotion effect of green funds on social performance than the other mutual funds (promotion effect). From a network perspective as well as previous social capital research, the mutual funds shareholding network shows a significant and positive effect on the firm's social performance in the firm–fund network (CFClose) as well as in the firm–firm network (CCClose), while the coefficients of closeness in the firm and green fund network are positive but non-significant (network effect).

Although some valuable findings have been documented, there is a great potential to be further explored. For example, how to guide more green funds to solve the finance problem of middle and small-sized firms may be another crucial task for the point of view of government or industry level. While at the mutual fund level, it is essential to positively participate in and fulfill the environment duty of listed firms which can not only satisfy the expectation of environment value investment.

The fund market has witnessed unprecedented growth in China and plays an important role in promoting the development of green industries. This indicates the practice of mutual funds as socially responsible investment in China. Some effective measures should be taken to incentive the mutual funds to continually invest in environment-friendly firms, which would benefit to the promotion of social performance driven by financing innovation.

The ESG issue is a global one that needs the participation of the countries worldwide. As one of the most important emerging markets, regulators in China should consider taking more action in promoting ESG concerns. To some extent, institutional investments can actually reflect how the responsible investments are going in this market.

This paper provides a systematic empirical analysis of Chinese fund market in the view of institutional investor preference. Three green effects, namely attention, promotion and network effects, are put forward, which have not been employed in previous studies. Our work is useful for understanding sustainable finance which has been elevating into national strategy.

According to unearthed materials of braids, hand braiding originate in the last stage of the Old Stone Age China and has a history of over 7000 years, which remains a unique handicraft in our society. In terms of the arrangement of yarns, braiding can be categorized into two kinds of techniques: double system braiding and single system. In ancient China, most braids were made by double system braiding. The technique of single system braiding was at its peak of development in the Zhou dynasty. Around the Han dynasty, diagonal braiding and twist braiding were in fashion, and a complex braiding technique of the combining of the two types of braiding was invented. Since the Shang dynasty, the application of braiding has been limited to narrow fabrics, shaped products, and some special trimmings, such as knots.

Double system braiding was directly responsible for the development of machine weaving. Loop braiding and crook braiding are similar to modern knitting and crocheting in many aspects. The scope of braiding application has now diminished, but its technical and cultural significance remains.

With the increasing interest in public private partnership (PPP), there is a need to investigate the factors contributing to successful delivery of PPP projects. The purpose of this paper is to analyze the perceptions of respondents from Hong Kong, Australia and the UK on the importance of 18 such factors.

An empirical questionnaire survey was conducted in Hong Kong and Australia. The survey respondents were asked to rate 18 factors which contribute to delivering successful PPP projects.

The findings from this survey were further compared with the results achieved by a previous researcher in a similar survey conducted in the UK. The comparison showed that amongst the top five success factors ranked by Hong Kong respondents, three were also ranked highly by the Australians and British. These success factors included: “Commitment and responsibility of public and private sectors”; “Strong and good private consortium”; and “Appropriate risk allocation and risk sharing”. Therefore, it can be concluded that there are certain common critical success factors for conducting PPP projects, irrespective of the geographical locations.

The findings presented in this paper have highlighted the most significant critical success factors which may be applicable to all jurisdictions, and also those which are specifically for Hong Kong and Australia. It is believed that the participants of future PPP projects can use these findings to maximize the success of conducting similar projects.

This paper aims to explore the critical success factors (CSFs) necessary for adopting public private partnerships (PPPs) in both Mainland China and Hong Kong.

An empirical questionnaire survey was conducted with relevant experienced practitioners in Mainland China and Hong Kong.

Both Mainland China and Hong Kong have been keen to deliver more infrastructure service projects through PPP mode, with the former aiming to meet its rapidly growing infrastructure demand and the latter uplifting its efficiency further. The results indicate that Hong Kong does not regard multi‐benefit objectives as importantly as Mainland China. Mainland China on the contrary felt more concerned with an equitable risk sharing mechanism, which is understandable given the problems affecting the financial market in Mainland China.

It is anticipated that the results presented in this paper will assist both the public and private sectors to deliver PPP projects more successfully.

Reconfigurability of the assembly fixtures, which enables a set of sheet metal automotive parts to be produced on a single production line, is becoming crucial to maintaining competitiveness in the rapidly changing market. One of the key issues in reconfigurable fixture design is to identify the fixture configuration and make sure there is enough workspace for a family of parts. The purpose of this paper is to address this issue, through the design and analysis of two novel reconfigurable fixturing robots.

Following an introduction, the application of the reconfigurable fixturing robot addressed in this paper is described; it is characterized by using parallel manipulator as programmable fixture elements. Kinematic design and reconfigurable design of the fixturing robot is presented based on screw theory and modularized design, respectively.

The proposed reconfigurable fixturing robots can transform their configurations with 4 DoF (degrees‐of‐freedom), and have a continuous workspace for their application.

Reconfigurability of the assembly fixtures is an important issue for automotive manufacturing, due to the highly competitive nature of this industry. The proposed reconfigurable fixturing robots can greatly facilitate the development of new models of vehicles.

This paper aims to present the main factors affecting the mechanical drilling of the printed circuit board (PCB for short) micro-holes and method of micro-ultrasonic powder molding (micro-UPM for short) by utilizing PCB micro-hole array.

To optimize the drilling process, the paper proposes the on-line monitoring methods for the drilling process including drilling force, drilling temperature, high-speed photography and vibration signals. Taking 0.10 and 0.15 mm micro-drilling as examples, the paper analyzes the drilling process of ultra-small micro-holes. Finally, by taking the PCBs with 0.10 and 0.15 mm micro-hole arrays as the micro-cavity inserts, utilizing ultra-high-molecule weight polyethylene powder with the average particle size of about 150 μm as raw material, two sizes of micro-cylinder array polymer parts are fabricated through micro-UPM process.

PCB micro-cavity inserts with micro-hole arrays fabricated by mechanical drilling has the advantages of low costs, high efficiency and good consistency. Taking 0.10 and 0.15 mm micro-drilling as examples, it is found that the both measured apertures are about 10.0 μm more than the diameter of the micro-drill bits on average. The average diameter of the micro-cylinders by micro-UPM process is smaller than that of the micro-hole with the same specification, while the value of the roughness of the cylinder surface is more than that of the hole-wall surface with the same specification.

This paper describes the challenges and the developments of mechanical drilling and by using PCB micro-cavity inserts with micro-hole arrays fabricated by mechanical drilling, two different micro-cylinder array polymer parts are successfully made and thus the application area of PCB micro-drilling is broadened.