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This paper aims to investigate the effects of low-viscosity and ultralow-viscosity engine oils on the comprehensive friction and fuel economy of turbocharged gasoline direct injection (TGDI) through simulation analysis and experiments.

Numerical analysis models of friction loss for reciprocating, crankshaft and valve train are established. Based on the FAST, the friction loss of 24 specific parts of a TGDI engine was analyzed. Finally, the engine test bench was built, which was used to test the mechanical loss, external characteristics and universal characteristics.

Compared with the baseline oil, lower viscosity lubricating oil can reduce the friction loss of nine components to varying degrees. When the viscosity decreases, the friction distribution ratio of reciprocating, crankshaft and balance shaft will gradually decrease. The proportion of reciprocating when using 0W12 is reduced by 4%. Tests have shown that ultralow viscosity engine oil reduces torque loss by up to 15.74% (2,000 rpm, full throttle), but its fuel consumption rate becomes higher in low-speed and high-torque conditions.

This work helps to understand the effect of lubricating oil characteristics on the comprehensive friction performance of the engine.

This study aims to analyse the geographical distribution of global research activities and to investigate the knowledge diffusion embodied in scientific papers.

The geographical summary of Frontiers articles displays the number of visits and categorizes where the visitors hail from. This study uses the records of 23,798 articles published in 16 Frontiers journals from 2007 to 2015 to analyse the geographical distribution of article visits at both country and city levels. The process of knowledge diffusion is investigated on the basis of the different visiting patterns of new and old papers.

Most article visits are concentrated around major metropolitan areas and some high-tech clusters. The top “visiting countries” include both developed countries and developing countries, and the USA and China are two major players. Publishing cities dominate article visits for new papers; as time passes, there is diffusion from the publishing cities to a broader area.

The data on visiting for open access articles may be generated from various repositories besides the publishers’ websites; these data are ignored, as they are not significant enough to have much influence. There is also a lack of a basic theory in the data processing of outliers in the data set. In addition, only static results are given in this paper, as the data were collected on one day, for one time. A longer time period is necessary to track the dynamic diffusion process of the observations.

Introduction of usage data will propose a novel way to analyse research activities and track knowledge diffusion.

The visiting data of articles offer a new way to investigate research activities at the city level in a detailed and timely manner, for the geographical distribution of research activities and the research resource allocation of a specific country to be explored.

This study measured the research activities of scientific papers by examining the usage data. Compared with previous studies that focused on the geographical distribution of scientific activities using publication data, citation data and even altmetrics data, usage data are at the forefront of this research. Therefore, usage data offer a fresh perspective on methodology, providing more detailed and real-time information.

The purpose of this paper is to find out the anti‐smoking counselling frequency and its correlates in a sample of Chinese physicians.

In this paper, 268 physicians in Baoding, a city near Beijing, filled out a questionnaire asking about their own smoking status, their anti‐smoking behaviors as well as their opinions on how to reduce cigarette smoking in China.

The paper finds that 54 percent of the male and 8.4 percent of the female physicians were current cigarette smokers. When asked whether they had counselled their patients about cigarette smoking in the past year, 43.7 percent answered “always”; 38.1 percent “often”; 13.1 percent “sometimes”; 2.6 percent “occasionally”, and 2.6 percent said: “not much”. However, only 9.0 percent said that they were “very successful”. Physicians' anti‐smoking counselling practices were highly correlated with their own smoking status; whether they perceived their past anti‐smoking activities as successful; whether they thought that they should set examples by not smoking; whether they felt that they had the responsibility to help patients and whether they perceived themselves as influential in persuading patients to quit smoking.

The paper shows that messages aimed at increasing Chinese physicians' anti‐smoking counselling should appeal to their responsibility, exemplary role, and unique influence on patients' health‐related behaviors.

The paper adds to the few studies on Chinese physicians' cigarette smoking behavior and their anti‐smoking activities. In a country where cigarette smoking is a way of life among males, and few people are aware of the health consequences of cigarette smoking, physicians' efforts can be a spearhead to a cessation campaign.

The purpose of this paper was to attempt to confirm the root cause of wafer damage issue by heavy Al wire wedge bonding and propose some permanent solutions for it.

The infra red–optical beam-induced resistance change (IR-OBIRCH) analysis defines the position of an abnormal hotspot. A cross section and an scanning electron microscope (SEM) confirmed the wafer damage issue and its position. Based on the position of wafer damage, the wedge tool with different life and Al buildup was checked found to be on the wedge tool. Finite element analysis (FEA) modeling analysis and simulation experiment guarantee the Al buildup, and low wedge deformation thickness (WDT) can cause the wafer damage issue. Finally, design of experiment (DOE) experiments are designed to optimize wedge tool dimension and wedge-bond parameters to eliminate wafer damage issue.

Wafer damage issue caused the Vpwr-OUTPUT leakage issue by IR-OBIRCH analysis. Al buildup was found on wedge tool with different life and its size gets larger along with the increase in wedge tool life. Low WDT and bigger Al buildup can cause the wafer damage. Designing new wedge tool and parameters optimization can increase WDT.

Because of the limitation of time and resources, finite element method (FEM) modeling and wedge tool dimension could not be studied more deeply.

This paper sets an example on how to find out the root cause of wafer damage by a step-by-step analysis and put forward a quick solution accordingly for the issue.

The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection correction system based on passive light vision sensors was designed using the Halcon software from MVtec Germany as a platform.

This paper proposes an adaptive correction system for welding guns and seams divided into image calibration and feature extraction. In the image calibration method, the field of view distortion because of the position of the camera is resolved using image calibration techniques. In the feature extraction method, clear features of the weld gun and weld seam are accurately extracted after processing using algorithms such as impact filtering, subpixel (XLD), Gaussian Laplacian and sense region for the weld gun and weld seam. The gun and weld seam centers are accurately fitted using least squares. After calculating the deviation values, the error values are monitored, and error correction is achieved by programmable logic controller (PLC) control. Finally, experimental verification and analysis of the tracking errors are carried out.

The results show that the system achieves great results in dealing with camera aberrations. Weld gun features can be effectively and accurately identified. The difference between a scratch and a weld is effectively distinguished. The system accurately detects the center features of the torch and weld and controls the correction error to within 0.3mm.

An adaptive correction system based on a passive light vision sensor is designed which corrects the field-of-view distortion caused by the camera’s position deviation. Differences in features between scratches and welds are distinguished, and image features are effectively extracted. The final system weld error is controlled to 0.3 mm.

Institutional factors play an important and complex role in Chinese outward foreign direct investment (OFDI) location choices that do not seem to be influenced by a host country’s high political risks. Moreover, the location choice for OFDI is key to corporate strategic decision-making on internationalization. Therefore, this study aims to examine the direct investments of Chinese multinational enterprises (MNEs) in Laos.

Combining the purposive sampling strategy and snowball sampling method, the authors interviewed nine market- and resource-seeking Chinese enterprises in Laos. Drawing from the mainstream eclectic paradigm and the theory of new institutional economics, the authors analyzed two key variables – enterprise investment motivation and enterprise heterogeneity.

Chinese MNEs are not insensitive to the regressive institutional quality of host countries; the relationship effect and institutional distance are the location decision pathways along with which institutional factors influence Chinese multinationals’ investments in Laos; political stability is necessary for Chinese-funded enterprises to invest in Laos and the degree of corruption is an overestimated institutional preference factor.

The relationship effect is introduced into the analysis framework as an intermediate variable that influences the decision of MNEs to invest in countries with underdeveloped institutions. It verifies the significant roles of bilateral political relations and network relations in the OFDI location decisions of state-owned and private enterprises, respectively.

Most economic growth is concentrated in the eastern and coastal provinces of China, while the western and central provinces have not yet experienced the expected economic growth. This study aims to address the following crucial research questions: Do the central and western provinces achieved potential efficiency in economic growth? Have China’s provinces used their resources effectively in implementing economic growth strategies?

The research design concerns the use of a panel dataset on province-specific economic growth in China over the years to 2000–2020. The methodology used was a stochastic frontier gross domestic product (GDP) model with time-varying technical efficiency over time. The approach uses the existing literature to identify the important variables influencing economic growth at the provincial level to model the stochastic frontier GDP model for empirical analysis.

This study concludes that the central provinces show the highest rate of efficiency in economic growth, though not 100%, followed by the Eastern and Western provinces. By increasing and improving skilled education institutes and intensifying supply chain opportunities through foreign direct investment (FDI), the central provinces achieving 100% growth efficiency may not be ruled out.

The modes of economic governance and policies to improve GDP growth have been rapidly changing from increasing incentives to improving competition. Thus, more unique avenues and expansion of the horizon for impending research on provincial, national and international macroeconomics would emerge that would make current methodologies of the growth analysis outdated.

The empirical analysis highlights the importance of improving skilled education institutes and intensifying supply chain opportunities through FDI for achieving sustained economic growth.

The empirical analysis facilitates finding ways to reduce income inequality across provinces in China.

To the authors' knowledge empirical analysis examining the Chinese province-specific economic growth efficiency explicitly has not been carried out using the recent Chinese panel dataset.