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The purpose of this study is to develop a robotic hand–arm system for on-orbit servicing missions at the Tiangong-2 (TG-2) Space Laboratory.

The hand–arm system is mainly composed of a lightweight arm, a dexterous hand, an electrical cabinet, a global camera, a hand–eye camera and some human–machine interfaces. The 6-DOF lightweight arm and the 15-DOF dexterous hand adopt the modular design philosophy that greatly reduces the design cycle and cost. To reduce the computational burden on the central controller and simplify system maintenance, an electrical system which has a hierarchical structure is introduced.

The prototypical operating experiments completed in TG-2 space laboratory demonstrate the performance of the hand–arm system and lay foundations for the future applications of space manipulators.

The main contributions of this paper are as follows a robotic hand–arm system which can perform on-orbit servicing missions such as grasping the electric drill, screwing the bolt, unscrewing J599 electrical connector has been developed; a variable time step motion plan method is proposed to adjust the trajectories of the lightweight arm to reduce or eliminate the collision force; and a dexterous hand uses the coordinated grasp control based on the object Cartesian stiffness to realize stable grasp. To solve the kinematic mapping from the cyber glove commands to the dexterous hand, a fingertip-position-based method is proposed to acquire precise solutions.

The purpose of this paper is to build cyber-physical-psychological ternary fusion crowd intelligence network and realize comprehensive, real, correct and synchronous projection in cyber–physical–psychological ternary fusion system. Since the network of crowd intelligence is the future interconnected network system that takes on the features of large scale, openness and self-organization. The Digital-selfs in the network of crowd intelligence interact and cooperate with each other to finish transactions and achieve co-evolution eventually.

To realize comprehensive, real, correct and synchronous projection between cyber–physical–psychological ternary fusion system, the authors propose the rules and methods of projection from real world to the CrowdIntell Network. They build the mental model of the Digital-self including structure model and behavior model in four aspects: identity, provision, demand and connection, thus forming a theoretical mental model framework of Digital-self.

The mental model is excepted to lay a foundation for the theory of modeling and simulation in the research of crowd science and engineering.

This paper is the first one to propose the mental model framework and projection rules and methods of Digital-selfs in network of crowd intelligence, which lays a solid foundation for the theory of modeling, simulation, intelligent transactions, evolution and stability of CrowdIntell Network system, thus promoting the development of crowd science and engineering.

The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.

In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.

The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.

In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.

The purpose of this paper is to detect abnormal data of complex and sophisticated industrial equipment with sensors quickly and accurately. Due to the rapid development of the Internet of Things, more and more equipment is equipped with sensors, especially more complex and sophisticated industrial equipment is installed with a large number of sensors. A large amount of monitoring data is quickly collected to monitor the operation of the equipment. How to detect abnormal data quickly and accurately has become a challenge.

In this paper, the authors propose an approach called Multiple Group Correlation-based Anomaly Detection (MGCAD), which can detect equipment anomaly quickly and accurately. The single-point anomaly degree of equipment and the correlation of each kind of data sequence are modeled by using multi-group correlation probability model (a probability distribution model which is helpful to the anomaly detection of equipment), and the anomaly detection of equipment is realized.

The simulation data set experiments based on real data show that MGCAD has better performance than existing methods in processing multiple monitoring data sequences.

The MGCAD method can detect abnormal data quickly and accurately, promote the intelligent level of smart articles and ultimately help to project the real world into cyber space in CrowdIntell Network.

This study aims to address the unanswered question of whether corporate sustainability has an impact on auditors’ overall judgment and to provide incremental evidence that corporate sustainability reporting has significant effect on financial auditors’ judgment.

Following prior research, the authors, respectively, apply auditors’ decisions on going-concern opinions and three discretionary accrual measures as proxies for auditor conservatism over financial risk and financial reporting risk. The authors collect corporate sustainability reporting and sustainability assurance data of U.S. firms from the global reporting initiative (GRI) database to construct and measure firms’ sustainability reporting activities.

The authors find that nonreporting firms are more likely to receive going-concern opinions than the reporting firms. In addition, reporting firms have a larger scale of discretionary accruals than their nonreporting counterparts. The authors also obtain consistent findings that sustainability assurance or accounting assurance providers strengthen the effect of sustainability reporting on auditors’ judgment.

First, using discretionary accruals as measures of auditor conservatism is controversial, as accruals are the joint product by auditors and clients. Second, binary variables as a measure of sustainability reporting activities limit the inference. Lastly, the findings based on limited samples may weaken the external validity.

The findings imply that firms engaging in sustainability activities are lower in financial or financial reporting risk. Firms can influence audit practitioners’ overall judgment through sustainability reports. Sustainability commitments and reporting have become a part of firms’ risk management.

The findings imply that sustainability reporting could become an integrated part of regulated corporate disclosure. Sustainability assurance reduces social costs by lending credibility to sustainability reports.

This paper provides incremental evidence that sustainability reports provide useful information and signals that influence auditors’ professional judgment. The findings also suggest that sustainability assurance strengthens auditors’ confidence in using sustainability information, thus amplifying the effect of sustainability reporting on auditors’ judgment.

The purpose of this paper is to determine the effect of flash fire exposure on the mechanical properties of single-layer thermal protective clothing.

The full-scale flame manikin tests were performed to simulate flash fire exposure. Two typical fire-resistant fabrics were investigated. The manikin was divided into seven body parts and the specimens meeting the requirements of tensile and tear strength standards were sampled. Fabric thickness, mass per unit area, tensile strength and tear strength were measured and analyzed.

The results revealed the significant influence of heat flux on both of tensile and tear strength. However, the regression analysis indicated the low R² of the liner models. When the tensile and tear strength retention were reorganized based on the body parts, both of the multiple linear regression models for tensile and tear strength showed higher R² than the one-variable linear regressions. Furthermore, the R² of the multiple linear regression model for tear strength retention was remarkably higher than that of the tensile strength.

The findings suggested that greater attention should be paid to the local part of human body and more factors such as the air gap should be considered in the future thermal aging of firefighters’ clothing studies.

The outcomes provided useful information to evaluate the mechanical properties of thermal protective clothing and predict its service life.

The purpose of this paper is to study friction and wear properties of three types of steels against paper-based friction disc, including 65Mn, 20#steel and 30CrAl, so as to obtain the appropriate working conditions for different friction materials in the transmission system.

Based on actual working conditions, pin-on-disc tests are conducted on a universal material tester. The two evaluation indexes, including average friction coefficient and variation coefficient, are introduced to analyze the different friction properties among three types of steel. Furthermore, the temperature-dependent wear pattern and wear depth are subsequently studied.

The results show that 65Mn is more suitable for working under heavy load and low velocity, but 30CrAl and 20#steel are suitable for working under light load and high velocity. Moreover, wear primarily occurs on paper-based material and peaks at about 325.

This research of different materials and friction property for friction pairs is helpful to improve the performance and prolong the service life of transmission systems.

Suitable working conditions of different friction materials are obtained, and the correlation between wear and decomposition in high temperature is verified.