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This study aims to analyze the differences of electrocardiograph (ECG) characteristics for female drivers in calm and anxious states during driving.

The authors used various materials (e.g. visual materials, auditory materials and olfactory materials) to induce drivers’ mood states (calm and anxious), and then conducted the real driving experiments and driving simulations to collect driver’s ECG signal dynamic data. Physiological changes in ECG during the stimulus process were recorded using PSYLAB software. The paired T-test analysis was conducted to determine if there is a significant difference in driver’s ECG characteristics between calm and anxious states during driving.

The results show significant differences in the characteristic parameters of female driver’s ECG signals, including (average heart rate), (atrioventricular interval), (percentage of NN intervals > 50ms), (R wave average peak), (Root mean square of successive), (Q wave average peak) and ( S wave average peak), in time domain, frequency domain and waveform in emotional states of calmness and anxiety.

Findings of this work show that ECG can be used to identify driver’s anxious and calm states during driving. It can be used for the development of personalized driver assistance system and driver warning system.

Only a few attempts have been made on the influence of human emotions on physiological signals in the transportation field. Hence, there is a need for transport scholars to begin to identify driver’s ECG characteristics under different emotional states. This study will analyze the differences of ECG characteristics for female drivers in calm and anxious states during driving to provide a theoretical basis for developing the intelligent and connected vehicles.

During the industrial design process, a product is usually modified and analyzed repeatedly until reaching the final design. Modifying the model and regenerating a mesh for every update during this process is very time consuming. To improve efficiency, it is necessary to circumvent the computer-aided design modeling stage when possible and directly modify the meshes to save valuable time. The purpose of this paper is to develop a method for mesh modifications.

In contrast to existing studies, which focus on one or a class of modifications, this paper comprehensively studies mesh union, mesh gluing, mesh cutting and mesh partitioning. To improve the efficiency of the method, the paper presents a fast and effective surface mesh remeshing algorithm based on a ball-packing method and controls the remeshing regions with a size field.

Examples and results show that the proposed mesh modification method is efficient and effective. The proposed method can be also applied to meshes with different material properties, which is very different with previous work that is only suitable for the meshes with same material property.

This paper proposes an efficient and comprehensive tetrahedral mesh modification method, through which engineers can directly modify meshes instead of models and save time.

The emission from marine engines has a crucial effect on energy economy and environment pollution. One of the effective emission reduction schemes is to minimize the friction loss of main friction pairs such as cylinder liner-piston ring (CLPR). Micro-groove textures were designed to accomplish this aim.

The authors experimentally investigated the effects of micro-groove textures at different cylinder liner positions. The micro-groove texture was fabricated on samples by chemical etching and cut from the real CLPR pair. Sliding contact tests were conducted by a reciprocation test apparatus.

The average friction coefficient of grooves at 30° inclination were reduced up to 58.22% and produced better tribological behavior at most conditions. The operating condition was the critical factor that determined the optimum texture pattern. The surface morphology indicated that textures could produce smoother surfaces and less scratches as compared with the untextured surface.

Inclined grooves and V-grooves were designed and applied to real CLPR pairs. The knowledge obtained in this study will lead to practical basis for tribological design and manufacturing of CLPR pair in marine diesel engines.

Integrality of surface mesh is requisite for computational engineering. Nonwatertight meshes with holes can bring inconvenience to applications. Unlike simple modeling or visualization, the downstream industrial application scenarios put forward higher requirements for hole-filling, although many related algorithms have been developed. This study aims at the hole-filling issue in industrial application scenarios.

This algorithm overcomes some inherent weakness of general methods and generates a high-level resulting mesh. Initially, the primitive hole boundary is filled with a more appropriate triangulation which introduces fewer geometric errors. And in order for better performances on shape approximation of the background mesh, the algorithm also refines the initial triangulation with topology optimization. When obtaining the background mesh defining the geometry and size field, spheres on it are packed to determine the vertex configuration and then the resulting high-level mesh is generated.

Through emphasizing geometry recovery and mesh quality, the proposed algorithm works well in hole-filling in industrial application scenarios. Many experimental results demonstrate the reliability and the performance of the algorithm. And the processed meshes are capable of being used for industrial simulation computations directly.

This paper makes input meshes more adaptable for solving programs through local modifications on meshes and perfects the preprocessing technology of finite element analysis (FEA).

This paper aims to examine the role of the Chinese People’s Political Consultative Conference (CPPCC), a political advisory body in China, in addressing environmental challenges.

This study uses 457 CPPCC environmental proposals across 160 cities for the period of 2013 to 2015 and a mediation effect model to examine the effect of CPPCC environmental proposals on environmental quality.

This study shows that CPPCC environmental proposals improve environmental quality; and the relationship between CPPCC environmental proposals and environmental quality is partially mediated by enforcement of environmental laws and regulations only although the proposals positively influence both law enforcement and environmental public budget expenditures.

Future research may examine how the interaction between the government and other important stakeholders such as non-governmental organizations can help improve environmental quality. In addition, future research may examine whether other policy tools such as pollution tax and fees, environmental subsidies, and emissions trading can play a role in dealing with environmental issues.

This study provides evidence that supports CPPCC members to take an even more active role in public governance by engaging with both the government and the public.

The CPPCC’s participation in public governance helps the government respond to critical issues more effectively. The government should pay close attention to CPPCC proposals when making public policies. Furthermore, the government probably needs to review its policies in relation to environmental expenditures.

This study is the first to examine the role of the CPPCC, a political advisory body, in addressing environmental challenges through functioning as a bridge between government and the public, whereas the extant literature has predominantly focused on the role of government, market and the public.

Rural credit cooperatives (RCCs) have long dominated China’s rural credit market and met most of agricultural credit demands while the existing literature seldom examines their contribution to agricultural sector. The purpose of this paper is to provide empirical evidence on the contribution of RCCs to agricultural growth, using China’s provincial panel data from 1997 to 2014.

Both static fixed effects models and two-step generalized method of moment dynamic panel data models, which control the endogeneity, are employed to identify the causality from RCC credit to agricultural growth in China.

The results show that the credit from RCCs increases the agricultural output significantly. A 1 percent increase in RCC credit leads to agricultural growth of about 0.08 percent, which is robust to various empirical specifications. Further study shows that the contribution of RCC credit to agricultural growth decreases from the most developed eastern region to the least developed western region and increases over time.

The results imply that RCC credit is critical in financing agricultural activities by relaxing rural credit constraints and intense competition strengthens the contribution of RCCs to agricultural growth by improving managerial efficiency and developing diversified financial products to meet better rural credit demands.

To the authors’ knowledge, this is first empirical study on the effect of RCC credit on agricultural growth despite of many on the role of financial development in agricultural growth.

The purpose of this paper is to provide the historical background of genealogical records and analyze the value of Chinese genealogical research through the study of names and genealogical resources.

The paper examines the historical evolution and value of Chinese genealogical records, with the focus on researching the Islamic Chinese names used by the people living in Guilin. The highlight of this paper includes the analysis and evolution of the Islamic Chinese names commonly adopted by the local people in Guilin. It concludes with the recommendations on emphasizing and making the best use of genealogical records to enhance the research value of Chinese overseas studies.

The paper covers the history of Islam and describes how the religion was introduced into China, as well as Muslims' ethnicity and identity. It also places focus on the importance of building a research collection in Asian history and Chinese genealogy.

This research study has a strong subject focus on Chinese genealogy, Asian history, and Islamic Chinese surnames. It is a narrow field that few researchers have delved into.

The results of this study will assist students, researchers, and the general public in tracing the origin of their surnames and developing their interest in the social and historical value of Chinese local history and genealogies.

The study of Chinese surnames is, by itself, a particular field for researching the social and political implications of contemporary Chinese society during the time the family members lived.

Very little research has been done in the area of Chinese local history and genealogy. The paper would be of value to researchers such as historians, sociologists, ethnologists and archaeologists, as well as students and anyone interested in researching a surname origin, its history and evolution.

The purpose of this paper is to examine the role of education in the labor market and to understand how returns to education change over time in rural China.

Using nationally representative survey data from 2004 to 2015, this study provides insights on wage determination in the labor market and examines how the returns to education in rural China differ with time and educational endowment. This study applies ordinary least squares estimation and the Heckman selection model to estimate the returns to education.

The returns to education decreased during the observed years from more than 6 percent in 2004 to only about 3 percent in 2011, rising to nearly 4 percent in 2015. The overall trend is robust and observed within groups defined by education. Additionally, the returns to education vary greatly with educational endowment. Tertiary education has always maintained a high rate of returns at nearly 10 percent, while returns to senior high school education and below have gradually diminished.

The authors believe that the results will not only enrich studies on the returns to education in rural China, but also provide a basis for diagnosing the changes of rural labor market in the early twenty-first century.

With the development of intelligent technology, deep learning has made significant progress and has been widely used in various fields. Deep learning is data-driven, and its training process requires a large amount of data to improve model performance. However, labeled data is expensive and not readily available.

To address the above problem, researchers have integrated semi-supervised and deep learning, using a limited number of labeled data and many unlabeled data to train models. In this paper, Generative Adversarial Networks (GANs) are analyzed as an entry point. Firstly, we discuss the current research on GANs in image super-resolution applications, including supervised, unsupervised, and semi-supervised learning approaches. Secondly, based on semi-supervised learning, different optimization methods are introduced as an example of image classification. Eventually, experimental comparisons and analyses of existing semi-supervised optimization methods based on GANs will be performed.

Following the analysis of the selected studies, we summarize the problems that existed during the research process and propose future research directions.

This paper reviews and analyzes research on generative adversarial networks for image super-resolution and classification from various learning approaches. The comparative analysis of experimental results on current semi-supervised GAN optimizations is performed to provide a reference for further research.

This paper aims to explore the pathways of carbon transfer in 200 US corporations along with the motivations that drive such transfers. The particular focus is on each firm’s embeddedness in the global value chain (GVC) and the influence of environmental law, operational costs and corporate social responsibility (CSR). The insights gleaned bridge a gap in the literature surrounding GVCs and corporate carbon transfer.

The methodology comprised a two-step research approach. First, the authors used a two-sided fixed regression to analyse the relationship between each firm’s embeddedness in the GVC and its carbon transfers. The sample consisted of 217 US firms. Next, the authors examined the influence of environmental law, operational costs and CSR on carbon transfers using a quantitative comparison analysis. These results were interpreted through the theoretical frameworks of the GVC and legitimacy theory.

The empirical results indicate positive relationships between carbon transfers and GVC embeddedness in terms of both a firm’s position and its degree. From the quantitative comparison, the authors find that the pressure of environmental law and operational costs motivate these transfers through the value chain. Furthermore, CSR does not help to mitigate transfers.

The findings offer insights for policymakers, industry and academia to understand that, with globalised production and greater value creation, transferring carbon to different parts of the GVC – largely to developing countries – will only become more common. The underdeveloped nature of environmental technology in these countries means that global emissions will likely rise instead of fall, further exacerbating global warming. Transferring carbon is not conducive to a sustainable global economy. Hence, firms should be closely regulated and given economic incentives to reduce emissions, not simply shunt them off to the developing world.

Carbon transfer is a major obstacle to effectively reducing carbon emissions. The responsibilities of carbon transfer via GVCs are difficult to define despite firms being a major consideration in such transfers. Understanding how and why corporations engage in carbon transfers can facilitate global cooperation among communities. This knowledge could pave the way to establishing a global carbon transfer monitoring network aimed at preventing corporate carbon transfer and, instead, encouraging emissions reduction.

This study extends the literature by investigating carbon transfers and the GVC at the firm level. The authors used two-step research approach including panel data and quantitative comparison analysis to address this important question. The authors are the primary study to explore the motivation and pathways by which firms transfer carbon through the GVC.