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This study aims to explore the effect of innovation ecosystem stability (IES) on innovation performance of enterprises through the mediating role of knowledge acquisition (KA), and to study how these effects are moderated by unabsorbed slack.

This study draws on data from 327 Chinese enterprises and adopts the multiple linear regression method and bootstrapping method to explore the mediating effect of KA and its moderated mediating effect.

The results demonstrate that IES is positively associated with innovation performance of enterprises, and KA plays a partially mediating role. Moreover, unabsorbed slack negatively moderates the relationship between IES and KA as well as the mediating effect of KA.

This study investigates the relationship between IES and innovation performance, and the mechanism of influence, which has not been previously studied in the field of innovation ecosystem. This study also examines the interaction between unabsorbed slack and IES and further clarifies the mechanism and boundary conditions of the impact of IES on innovation performance.

The purpose of this paper is to develop a numerical simulation method based on the transient upstream finite element method (FEM) and Schottky emission theory to reveal the distribution characteristics of space charge in oil-paper insulation.

The main insulation medium of the converter transformer in high voltage direct current transmission is oil-paper insulation. However, the influence of space charge is difficult to be fully considered in the insulation design and simulation of converter transformers. To reveal the influence characteristics of the space charge, this paper proposes a numerical simulation method based on Schottky emission theory and the transient upstream FEM. This method considers the influence of factors, such as carrier mobility, carrier recombination coefficient, trap capture coefficient and diffusion coefficient on the basis of multi-physics field coupling calculation of the electric field and fluid field.

A numerical simulation method considering multiple charge states is proposed for the space charge problem in oil-paper insulation. Meanwhile, a space charge measurement platform based on the electrostatic capacitance probe method for oil-paper insulation structure is built, and the effectiveness and accuracy of the numerical simulation method is verified.

A variety of models are calculated and analyzed by the numerical simulation method in this paper, and the distribution characteristics of the space charge and total electric field in oil-paper insulation medium with single-layer, polarity reversal of plate voltage and double-layer are obtained. The research results of this paper have the guiding significance for the engineering application of oil-paper insulation and the optimal design of converter transformer insulation.

While the growth of emerging technologies like Blockchain has created significant market opportunities and economic incentives for firms, it is valuable for both researchers and practitioners to understand their creation mechanisms. This paper aims to discuss the aforementioned objective.

Based on the knowledge search perspective, this study examines the impact of search boundary on innovation novelty and quality. Additionally, innovation targets, namely R&D innovation and application innovation, are proposed as the moderator of the knowledge search effect. Using a combination of machine learning algorithms such as natural language processing and classification models, the authors propose new methods to measure the identified concepts.

The empirical results of 3,614 Blockchain patents indicate that search boundary enhances both innovation novelty and innovation quality. For R&D innovation, the positive impact of search boundary on innovation quality is enhanced, whereas for application innovation, the positive effect of search boundary on innovation novelty is improved.

This study mainly contributes to the growing literature on emerging technologies by describing their creation mechanisms. Specifically, the exploration of R&D and application taxonomy enriches researchers' understanding of knowledge search in the context of Blockchain invention.

The coupling impact of hybrid uncertain errors on the machine precision is complex, as a result of which the designing method with multiple independent error sources under uncertainties remains a challenge. For the purpose of precision improvement, this paper focuses on the robot design and aims to present an assembly precision design method based on uncertain hybrid tolerance allocation (UHTA), to improve the positioning precision of the mechanized robot, as well as realize high precision positioning within the workspace.

The fundamentals of the parallel mechanism are introduced first to implement concept design of a 3-R(4S) &3-SS parallel robot. The kinematic modeling of the robot is carried out, and the performance indexes of the robot are calculated via Jacobian matrix, on the basis of which, the 3D spatial overall workspace can be quantified and visualized, under the constraints of limited rod, to avoid the singular position. The error of the robot is described, and a probabilistic error model is hereby developed to classify the hybrid error sensitivity of each independent uncertain error source by Monte Carlo stochastic method. Most innovatively, a methodology called UHTA is proposed to optimize the robot precision, and the tolerance allocation approach is conducted to reduce the overall error amplitude and improve the robotized positioning precision, on the premise of not increasing assembly cost.

The proposed approach is validated by digital simulation of medical puncture robot. The experiment highlights the mathematical findings that the horizontal plane positioning error of the parallel robotic mechanism can be effectively reduced after using UHTA, and the average precision can be improved by up to 39.54%.

The originality lies in UHTA-based precision design method for parallel robots. The proposed method has widely expanding application scenarios in industrial robots, biomedical robots and other assembly automation fields.

This paper aims to study a high-temperature (up to 200 °C) data acquisition and processing circuit for logging.

With the decrease in thermal resistance by system-in package technology and exquisite power consumption distribution design, the circuit worked well at high temperatures environment from both theoretical analysis and real experiments evaluation.

In thermal simulation, considering on board chips’ power consumption as additional heat source, the highest temperature point reached by all the chips in the circuit is only 211 °C at work temperature of 200 °C. In addition, the proposed circuit was validated by long time high-temperature experiments. The circuit showed good dynamic performance during a 4-h test in a 200-°C oven, and maintained a signal-to-noise ratio of 92.54 dB, a signal-to-noise and distortion ratio of 91.81 dB, a total harmonic distortion of −99.89 dB and a spurious free dynamic range of 100.28 dB.

The proposed circuit and methodology showed great potential for application in deep-well logging systems and other high-temperature situations.