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The purpose of this paper is to establish an accurate model to quantify the effect of conductor roughness on insertion loss (IL) and provide improved measurements and suggestions for manufacturing good conductive copper lines of printed circuit board.

To practically investigates the modified model of conductor roughness, three different kinds of alternate oxidation treatments were used to provide transmission lines with different roughness. The IL results were measured by a vector net analyzer for comparisons with the modified model results.

An accurate model, with only a 1.8% deviation on average from the measured values, is established. Compared with other models, the modified model is more reliable in industrial manufacturing.

This paper introduces the influence of tiny roughness structures on IL. Besides, this paper discusses the effect of current distribution on IL.

This paper seeks to answer two questions: (1) where do a country's entrepreneurship policies come from? (2) How do they evolve and shape entrepreneurial activities?

Drawing upon the comparative political economy literature and the institutional perspective, this paper proposes a theoretical model of the origin and evolution of entrepreneurship policies. We use China as a case study to apply the theoretical model and demonstrate the evolution of entrepreneurship policies in three stages during the period 1978 to 2012.

The case analysis of China provides evidence and support for our theoretical model and unpacks the process by which entrepreneurship policies originate and evolve as the result of the interplay among constantly changing policymaking, production, and knowledge regimes.

Because of the research context, findings may lack generalisability. Additional studies on policymaking and production regimes of different kinds and their respective roles in shaping entrepreneurship policies are encouraged to further advance this line of research.

This paper offers important implications concerning entrepreneurship policy and activities for policymakers, practitioners and other stakeholders in emerging economies.

Our study fills a gap in the entrepreneurship literature by expanding scholarly understanding of the origin and evolution of entrepreneurship policies.

Social enterprise plays a pivotal role in helping people and communities. Since the global financial crisis of 2008, there has been an upsurge of social enterprise within a local, national and global context. The purpose of this paper is to explore the debates and issues presented by social enterprise in a very complex globalized world.

In this paper, the authors apply two geographical case studies: China and India. The purpose for selecting both China and India is their increasing economic super power on the global stage. It is argued that the concept of social enterprise within the geographical context of China and India is significant to their individual economies.

The concept of social enterprise within the geographical context of China and India is significant to their individual economies and as explored within the notion of “think global, act local” the conceptual debates of place, space and time enables people to take positive action and enable the development of healthy communities.

This paper contributes to the discussion around the definition of the nature of social enterprise and gives concrete examples of the contextually specific nature of the term.

Globalisation is generally defined as the “denationalisation of clusters of political, economic, and social activities” that destabilize the ability of the sovereign State to control activities on its territory, due to the rising need to find solutions for universal problems, like the pollution of the environment, on an international level. Globalisation is a complex, forceful legal and social process that take place within an integrated whole with out regard to geographical boundaries. Globalisation thus differs from international activities, which arise between and among States, and it differs from multinational activities that occur in more than one nation‐State. This does not mean that countries are not involved in the sociolegal dynamics that those transboundary process trigger. In a sense, the movements triggered by global processes promote greater economic interdependence among countries. Globalisation can be traced back to the depression preceding World War II and globalisation at that time included spreading of the capitalist economic system as a means of getting access to extended markets. The first step was to create sufficient export surplus to maintain full employment in the capitalist world and secondly establishing a globalized economy where the planet would be united in peace and wealth. The idea of interdependence among quite separate and distinct countries is a very important part of talks on globalisation and a significant side of today’s global political economy.

This study aims to explore the role of trust and effect of age in the process of technology acceptance.

Using data collected from an online survey, this study conducts structural equation modeling to assess the relationship between technology adoption and users’ trust in that technology.

Findings of this study indicate that the formation of trust in technology is based on user experiences (i.e. the perception of usefulness and ease of use), while the perception of trust in technology is similar to human-like trust (i.e. competence and benevolence). This study clarifies that trust has a mediating effect on the relationship between perceived technology ease of use and behavioral intention to use. Trust belief of competence is found to be more effective on adoption behavior than trust belief of benevolence. In exploring the moderating effect of age, results find that easy use of an app is crucial for elderly people to create trust belief in technical competence and develop behavioral control over such technologies. Trust in technology is an essential factor that should be widely applied when analyzing technology adoption behaviors.

This study contributes in three ways. First, it reveals both how trust in technology is formed and the effect of that trust on technology adoption. Second, it extends the discussion of age as a variable in tourism app usage. Third, it shows how the experience of usage influences intentions towards the adoption of tourism apps.

重新认识旅游APP的技术信任：年龄的调节作用

本研究旨在探索技术信任和年龄对技术采用行为的作用。

本研究通过发放网络问卷收集数据，并构建结构方程模型验证并分析技术信任感知对技术采用行为的影响方式。

研究发现，技术信任是基于用户体验而形成的（如，对技术有用性和易用性的感知），用户对技术信任的感知与人际信任相似（如，对其能力信任和善意信任的感知）。研究结果表明，技术信任对感知技术易用性与使用意向之间的关系具有显著的中介作用，在这个过程中，用户更关注技术的能力信任而非其善意信任。此外，年龄对实现技术信任有一定调节作用，如，对于老年人用户而言，易用性更容易建立技术的能力信任，并有效帮助增强其对技术的控制感知。因此，技术信任应作为技术采用行为研究的重要考量因素。

首先，研究揭示了技术信任的实现路径，并解释了用户的技术信任感知对技术采用行为的影响方式。 其次，本文将年龄作为调节变量检验了其对用户技术采用行为的作用。 最后，本文讨论了旅游APP使用体验是如何影响用户采用意向的。

Human–robot collaboration (HRC) is on the rise in a bid for improved flexibility in production cells. In the context of overlapping workspace between a human operator and an industrial robot, the major cause for concern rests on the safety of the former.

In light of recent advances and trends, this paper proposes to implement a monitoring system for the shared workspace HRC, which supplements the robot, to locate the human operator and to ensure that at all times a minimum safe distance is respected by the robot with respect to its human partner. The monitoring system consists of four neural networks, namely, an object detector, two neural networks responsible for assessing the detections and a simple, custom speech recognizer.

It was observed that with due consideration of the production cell, it is possible to create excellent data sets which result in promising performances of the neural networks. Each neural network can be further improved by using its mistakes as examples thrown back in the data set. Thus, the whole monitoring system can achieve a reliable performance.

Success of the proposed framework may lead to any industrial robot being suitable for use in HRC.

This paper proposes a system comprising neural networks in most part, and it looks at a digital representation of the workspace from a different angle. The exclusive use of neural networks is seen as an attempt to propose a system which can be relatively easily deployed in industrial settings as neural networks can be fine-tuned for adjustments.

Six-axis force sensors play an important role in civilian and military fields because of their multifunctionality. In the context of sensor structure design, sensitivity and sensitivity isotropy are often considered. This paper aims to study the possible relationship between the sensitivity/sensitivity isotropy and structural parameters of an 8/4–4 parallel six-axis force sensor. A comprehensive evaluation index and structural optimization design scheme are suggested in the end.

Based on the conditional number of the Jacobian matrix spectral norm, the sensitivity and sensitivity isotropy of the sensor are derived. Orthogonal experiments are used to determine the degree of primary and secondary factors that have a substantial effect on the sensor characteristics. The relationship between the performance indices and the structural parameters is analyzed by the performance atlas method. The comprehensive evaluation index lays the foundation for the structural optimization design of an 8/4–4 parallel six-axis force sensor.

The variation in each performance index of the sensor for each of the structural parameters is analyzed, and the structural parameters of the sensor with the desired performance indices can be easily selected from the performance atlases. A comprehensive performance evaluation index with a target value of 1 is proposed, and the overall influence of the structural parameters on the sensor performance index is investigated. A simulation example shows the feasibility of the proposed evaluation index.

The importance of each structural parameter of the 8/4–4 parallel six-axis force sensor is determined through orthogonal experiments in this paper. Relations among the structural parameters meeting the performance indices are derived and shown in the performance atlases. A comprehensive evaluation index is proposed to analyze the overall sensor performance.

The screw extruder is applied in cement-three-dimensional (3D) printing. The cement paste flow in 3D printing is the typical Herschel–Bulkley fluid. To understand the flow in the channel, the improved lattice Boltzmann method (LBM) is proposed.

For Herschel–Bulkley flow, an improved LBM is presented to avoid the poor stability and accuracy. The non-Newtonian effect is regard as a special forcing term. The Poiseuille flow is taken to discuss the detailed process of the method. With the method, the analytical solution and numerical solution are obtained and compared. Then, the effect of the initial yield stress on the numerical solution is both explored by the shear-thickening fluid and the shear-thinning fluid. Moreover, the variations of the relative errors under different lattice nodes and different power-law indexes are analyzed. Finally, the method is applied into the simulation of the flow in the extruder of cement-3D printing.

The results show that the improved method is effective for Herschel–Bulkley fluids, which can simulate the flow in the extruder stably and accurately.

The simulation can contribute to understand the cement paste flow in the screw extruder, which helps to optimize the structure of the extruder in the following periods.

The improve method provide a new way to analyze the flow in the extruder of cement-3D printing. Also, in the past research, LBM for Herschel–Bulkley fluid is ignored, whereas the study can provide the reference for the numerical simulation.

The purpose of this paper is to identify smaller wear particles and improve the calculation speed, identify more abrasive particles and promote industrial applications.

This paper studies a new intelligent recognition method for equipment wear debris based on the YOLO V5S model released in June 2020. Nearly 800 ferrography pictures, 23 types of wear debris, about 5,000 wear debris were used to train and test the model. The new lightweight approach of wear debris recognition can be implemented in rapidly and automatically and also provide for the recognition of wear debris in the field of online wear monitoring.

An intelligent recognition method of wear debris in ferrography image based on the YOLO V5S model was designed. After the training, the GIoU values of the model converged steadily at about 0.02. The overall precision rate and recall rate reached 0.4 and 0.5, respectively. The overall MAP value of each type of wear debris was 40.5, which was close to the official recognition level of YOLO V5S in the MS COCO competition. The practicality of the model was approved. The intelligent recognition method of wear debris based on the YOLO V5S model can effectively reduce the sensitivity of wear debris size. It also has a good recognition effect on wear debris in different sizes and different scales. Compared with YOLOV. YOLOV, Mask R-CNN and other algorithms%2C, the intelligent recognition method based on the YOLO V5S model, have shown their own advantages in terms of the recognition effect of wear debris%2C the operation speed and the size of weight files. It also provides a new function for implementing accurate recognition of wear debris images collected by online and independent ferrography analysis devices.

To the best of the authors’ knowledge, the intelligent identification of wear debris based on the YOLO V5S network is proposed for the first time, and a large number of wear debris images are verified and applied.

Globally, India ranks third in greenhouse gas (GHGs) emissions. Decarbonizing India's economy would necessitate significant changes in how the country generates energy, manufactures things, delivers services and manages natural resources. Recently, scholars from different parts of the world have used various indicators like carbon and methane emissions to investigate potential solutions to the global warming problem that has resulted in climate change. Therefore, this study aims to investigate the impact of foreign direct investment, renewable and non-renewable energy consumption, in addition to economic growth, trade openness, and natural resources on ecological footprint.

Using India's yearly data from 1990 to 2016, this research investigates the impact of direct foreign investment (FDI), trade (TA) and natural resources (NR) on the ecological footprint (EF) within the framework of economic growth (GDP), renewable (RE) and non-renewable (NRE) energy consumption. The Zivot–Andrews unit root approach was used to examine the structural breaks in data series and the presence of stationary. An auto regressive distributive lag model was used to investigate the presence of long-run and short-run dynamic relationships among the variables.

The empirical findings demonstrate that FDI, RE and GDP have a negative and substantial impact on EF in the long term; in contrast, NRE and TA are significant and positive. The Granger causality test indicates that feedback transmission was observed between NR and EF and TA and EF. One-way causation passed from GDP to FDI and NR; TA to FDI and RE.

Indian Government and authorities should push for an eco-friendly manufacturing process and technology adaptation to improve environmental quality.