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Paediatric congenital esophageal atresia surgery typically requires delicate and dexterous operations in a narrow and confined workspace. This study aims to develop a novel robot assisted surgical system to address these challenges.

The proposed surgical robot consists of two symmetrical slave arms with nine degree of freedoms each. Each slave arm uses a rigid-dexterous configuration and consists of a coarse positioning manipulator and a distal fine operation manipulator. A small Selective Compliance Assembly Robot Arm (SCARA) mechanism was designed to form the main component of the coarse positioning unit, ensuring to endure large forces along the vertical direction and meet the operational demands. The fine positioning manipulator applied the novel design using flexible shafts and universal joints to achieve delicate operations while possessing a high rigidity. The corresponding kinematics has been derived and then was validated by a co-simulation that was performed based on the combined use of Adams and MATLAB with considering the real robot mass information. Experimental evaluations for the tip positioning accuracy and the ring transfer tasks have been performed.

The simulation was performed to verify the correctness of the derived inverse kinematics and demonstrated the robot’s flexibility. The experimental results illustrated that the end-effector can achieve a positioning accuracy within 1.5 mm in a confined 30 × 30 × 30 mm workspace. The ring transfer task demonstrated that the surgical robot is capable of providing a solution for dexterous tissue intervention in a narrow workspace for paediatric surgery.

A novel and compact surgical assist robot is developed to support delicate operations by using the dexterous slave arm. The slave arm consists of a SCARA mechanism to avoid experiencing overload in the vertical direction and a tool manipulator driven by flexible shafts and universal joints to provide high dexterity for operating in a narrow workspace.

Proper topic selection is an essential prerequisite for the success of research. To study this, this article proposes an important concerned factor of topic selection-topic popularity, to examine the relationship between topic selection and team performance.

The authors adopt extracted entities on the type of gene/protein, which are used as proxies as topics, to keep track of the development of topic popularity. The decision tree model is used to classify the ascending phase and descending phase of entity popularity based on the temporal trend of entity occurrence frequency. Through comparing various dimensions of team performance – academic performance, research funding, relationship between performance and funding and corresponding author's influence at different phases of topic popularity – the relationship between the selected phase of topic popularity and academic performance of research teams can be explored.

First, topic popularity can impact team performance in the academic productivity and their research work's academic influence. Second, topic popularity can affect the quantity and amount of research funding received by teams. Third, topic popularity can impact the promotion effect of funding on team performance. Fourth, topic popularity can impact the influence of the corresponding author on team performance.

This is a new attempt to conduct team-oriented analysis on the relationship between topic selection and academic performance. Through understanding relationships amongst topic popularity, team performance and research funding, the study would be valuable for researchers and policy makers to conduct reasonable decision making on topic selection.

A more accurate comprehension of data elements and the exploration of new laws governing contemporary data in both theoretical and practical domains constitute a significant research topic.

Based on the perspective of evolutionary economics, this paper re-examines economic history and existing literature to study the following: changes in the “connotation of production factors” in economics caused by the evolution of production factors; the economic paradoxes formed by data in the context of social production processes and business models, which traditional theoretical frameworks fail to solve; the disruptive innovation of classical theory of value by multiple theories of value determination and the conflicts between the data market monopoly as well as the resulting distribution of value and the real economic society. The research indicates that contemporary advancements in data have catalyzed transformative innovation within the field of economics.

The research indicates that contemporary advancements in data have catalyzed disruptive innovation in the field of economics.

This paper, grounded in academic research, identifies four novel issues arising from contemporary data that cannot be adequately addressed within the confines of the classical economic theoretical framework.

The purpose of this study is to present a new integrated structure for a fault tolerant aircraft control system because fault diagnosis of flight control systems is extremely important in obtaining healthy flight. An approach to detect and isolate aircraft sensor faults is proposed, and a new integrated structure for a fault tolerant aircraft control system is presented.

As disturbance and sensor faults are mixed together in a flight control system, it is difficult to isolate any fault from the disturbance. This paper proposes a robust unknown input observer for state estimation and fault detection as well as isolation using fuzzy logic.

The dedicated observer scheme (DOS) and generalized observer scheme (GOS) are used for fault detection and isolation in an observer-based approach. Using the DOS, it has been shown through simulation that sensor fault detection and isolation can be made, but here the threshold value must be well chosen; if not, the faulty sensor cannot be correctly isolated. On the other hand, the GOS is more usable and flexible than the DOS and allows isolation of faults more correctly and for a fuzzy logic-based controller to be used to realize fault isolation completely.

The fuzzy logic approach applied to the flight control system adds an important key for sensor fault isolation because it reduces the effect of false alarms and allows the identification of different kinds of sensor faults. The proposed approach can be used for similar systems.