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The aim of this paper is to enhance the control performance of dexterous hands, enabling them to handle the high data flow from multiple sensors and to meet the deployment requirements of deep learning methods on dexterous hands.

A distributed control architecture was designed, comprising embedded motion control subsystems and a host control subsystem built on ROS. The design of embedded controller state machines and clock synchronization algorithms ensured the stable operation of the entire distributed control system.

Experiments demonstrate that the entire system can operate stably at 1KHz. Additionally, the host can accomplish learning-based estimates of contact position and force.

This distributed architecture provides foundational support for the large-scale application of machine learning algorithms on dexterous hands. Dexterity hands utilizing this architecture can be easily integrated with robotic arms.

The public's trust in the authorities has a great impact on people's perception and cognition on development of different types of urban transport infrastructure projects (UTIPs). Given the importance of public acceptance for the efficient construction and operation of UTIPs, this study aims at investigating the personal and environmental factors that influence public acceptance behavior from the perspective of stakeholder management.

Based on social cognitive theory (SCT), this study explores the multiple dimensions of social trust on public acceptance in the development of UTIPs by a comparative case study. Two types of UTIPs, a metro railway and a bridge in the Wuhan City, China, were selected as cases, with a questionnaire distributed among the public to collect their sense of trust towards the development of these projects. The data were analyzed through structural equation modeling (SEM).

This study reveals that social trust positively influences public acceptance, directly or indirectly through perceived benefit and -risks and self-efficacy. However, the emphasis on social trust about competence and integrity of the authorities varies with the types of projects. Self-efficacy worked as the “mirror of trust” reflecting people's attitude towards social trust in the authorities on their ability and morality.

The value of the paper lies in discussing social trust from multiple dimensions in the field of urban infrastructures, which provides new insights into specific mechanisms for shaping public acceptance in project management towards the development of UTIPs.

The purpose of this paper is to investigate driving factors that improve the project management efficiency (PME) in centralized public procurement systems.

Employees in four public-sector organizations in China were surveyed. The structural equation modeling was employed to examine the relationship amongst those variables.

Organizational culture (OC) is an effective method to improve PME, and employee quality is the most critical factor of OC in this system. Job satisfaction (JS) is another significant contributor to PME and satisfaction with fairness of salary in this system being the key factor of JS. Job analysis (JA) has indirect influence on PME through JS and OC, whereas the job structure in this system is the most critical factor for JA.

An operational way to improve PME is to implement it from the perspectives of employee, organization and technique. At the organizational level, it is imperative to strengthen the OC by a well-structured recruitment system and to improve PME via well-design training. At the person level, both financial (i.e. income and welfare) and career incentives (i.e. promotion opportunities and a sense of belonging) are proposed to achieve employees’ JS to improve PME. At the technique level, JA approach (i.e. job rotation) is recommended to enlarge the positive influence of OC and JS on PME. These can not only ensure the management professionalism in a centralized public procurement system but can also motivate employees and maximize PME.

PME in a centralized public procurement system will be improved by addressing these key factors and their interrelationships. This provides detailed pathways for the centralized public procurement system to achieve better PME via optimal OC and JS and reasonable JA in China. In addition, the institutional and administrative traditions may vary significantly across cities, regions and countries. Therefore, such contextual differences should be taken into consideration for the improvement of PME in a centralized public procurement system.

As it is known, the electrostatic discharge (ESD) protection design of integrated circuit is very important, among which the silicon controlled rectifier (SCR) is one of the most commonly used ESD protection devices. However, the traditional SCR has the disadvantages of too high trigger voltage, too low holding voltage after the snapback and longer turn-on time. The purpose of this paper is to design a high-performance SCR in accordance with the design window under 0.25 µm process, and provide a new scheme for SCR design to reduce the trigger voltage, improve the holding voltage and reduce the turn-on time.

Based on the traditional SCR, an RC-INV trigger circuit is introduced. Through theoretical analysis, TCAD simulation and tape-out verification, it is shown that RC-INV triggering SCR can reduce the trigger voltage, increase the holding voltage and reduce the turn-on time of the device on the premise of maintaining good robustness.

The RC-INV triggering SCR has great performance, and the test shows that the transmission line pulse curve with almost no snapback can be obtained. Compared with the traditional SCR, the trigger voltage decreased from 32.39 to 16.24 V, the holding voltage increased from 3.12 to 14.18 V and the turn-on time decreased from 29.6 to 16.6 ns, decreasing by 43.9% the level of human body model reached 18 kV+.

Under 0.25 µm BCD process, this study propose a high-performance RC-INV triggering SCR ESD protection device. The work presented in this paper has a certain guiding significance for the design of SCR ESD protection devices.