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This paper aims to design a new bandgap reference circuit with complementary metal–oxide–semiconductor (CMOS) technology.

Different from the conventional bandgap reference circuit with operational amplifiers, this design directly connects the two bases of the transistors with both the ends of the resistor. The transistor acts as an amplifier to amplify the change of voltage, which is convenient for the feedback regulation of low dropout regulator (LDO) regulator circuit, at last to realize the temperature control. In addition, introducing the depletion-type metal–oxide–semiconductor transistor and the transistor operating in the saturation region through the connection of the novel circuit structure makes a further improvement on the performance of the whole circuit.

This design is base on the 0.18?m process of BCD, and the new bandgap reference circuit is verified. The results show that the circuit design not only is simple and novel but also can effectively improve the performance of the circuit. Bandgap voltage reference is an important module in integrated circuits and electronic systems. To improve the stability and performance of the whole circuit, simple structure of the bandgap reference voltage source is essential for a chip.

This paper adopts a new circuit structure, which directly connects the two base voltages of the transistors with the resistor. And the transistor acts as an amplifier to amplify the change of voltage, which is convenient for the feedback regulation of LDO regulator circuit, at last to realize the temperature control.

The hands of intelligent robots perceive external stimuli and respond effectively according to tactile or pressure sensors. However, the traditional tactile and pressure sensors cannot perform human-skin-like intelligent properties of high sensitivity, large measurement range, multi-function and flexibility simultaneously. The purpose of this paper is to present a flexible tactile-pressure sensor based on hyper-elastics polydimethylsiloxane and plate capacitance.

With regard to this problem, this paper presents a flexible tactile-pressure sensor based on hyper-elastics PDMS and plate capacitance. The sensor has a size of 10 mm × 10 mm × 1.3 mm and is composed of four upper electrodes, one middle driving electrode and one lower electrode. The authors first analyzed the structure and the tactile-pressure sensing principle of human skin to obtain the design parameters of the sensor. Then they presented the working principle, material selection and mechanical structure design and fabrication process of the sensor. The authors also fabricated several sample devices of the sensor and carried out experiments to establish the relationship between the sensor output and the pressure.

The results show that the tactile part of the sensor can measure a range of 0.05-1N/mm² micro pressure with a sensitivity of 2.93 per cent/N and a linearity of 0.03 per cent. The pressure part of the sensor can measure a range of 1-30N/mm² pressure with a sensitivity of 0.08 per cent/N and a linearity of 0.07 per cent.

This paper analyzes the tactile and pressure sensing principles of human skin and develop an intelligent sensitive human-skin-like tactile-pressure sensor for intelligent robot perception systems. The sensor can achieve to imitate the tactile and pressure function simultaneously with a measurement resolution of 0.01 N and a spatial resolution of 2 mm.

The purpose of this study is to analyze the speed characteristics of the water hydraulic axial piston motor. The speed performance of water hydraulic piston motor which uses water as medium is different from that mineral oil one.

To analyze the speed characteristics of the water hydraulic motor, the speed model of a swash plate water hydraulic piston motor is developed theoretically and a simulation model with AMESim is built.

The effects of clearance between friction pairs and input pressure on the speed are analyzed and compared between the theoretical and numerical models.

The results of the theoretical and simulation models both verify that the clearance of friction pairs is the key factor in the hydraulic piston motor’s speed.

The high specific strength makes magnesium alloys have a wide range of applications in aerospace, military, automotive, marine and construction industries. However, its poor corrosion resistance and weldability have limited its development and application. Friction stir welding (FSW) can effectively avoid the defects of fusion welding. However, the microstructure, mechanical properties and corrosion behavior of FSW joints in magnesium alloys vary among different regions. The purpose of this paper is to review the corrosion of magnesium alloy FSW joints, and to summarize the protection technology of welded joints.

The corrosion of magnesium alloy FSW joints includes electrochemical corrosion and stress corrosion. This paper summarizes corrosion protection techniques for magnesium alloys FSW joints, focusing on composition, microstructure changes and surface treatment methods.

Currently, this research is mainly focused on enhancing the corrosion resistance of magnesium alloy FSW joints by changing compositions, structural modifications and surface coating technologies. Refinement of the grains can be achieved by adjusting welding process parameters, which in turn minimizes the effects of the second phase on the alloy’s corrosion resistance.

This paper presents a comprehensive review on the corrosion and protection of magnesium alloys FSW joints, covering the latest research advancements and practical applications. It aims to equip researchers with a better insight into the field and inspire new studies on this topic.

The purpose of this paper is to propose a three-dimensional (3D) assembly model retrieval method based on assembling semantic information to address semantic mismatches, poor accuracy and low efficiency in existing 3D assembly model retrieval methods.

The paper proposes an assembly model retrieval method. First, assembly information retrieval is performed, and 3D models that conform to the design intention of the assembly are found by retrieving the code. On this basis, because there are conjugate subgraphs between attributed adjacency graphs (AAG) that have an assembly relationship, the assembly model geometric retrieval is translated into a problem of finding AAGs with a conjugate subgraph. Finally, the frequent subgraph mining method is used to retrieve AAGs with conjugate subgraphs.

The method improved the efficiency and accuracy of assembly model retrieval.

The examples illustrate the specific retrieval process and verify the feasibility and reasonability of the assembly model retrieval method in practical applications.

The assembly model retrieval method in the paper is an original method. Compared with other methods, good results were obtained.

In the era of big data, various industries are generating large amounts of text data every day. Simplifying and summarizing these data can effectively serve users and improve efficiency. Recently, zero-shot prompting in large language models (LLMs) has demonstrated remarkable performance on various language tasks. However, generating a very “concise” multi-document summary is a difficult task for it. When conciseness is specified in the zero-shot prompting, the generated multi-document summary still contains some unimportant information, even with the few-shot prompting. This paper aims to propose a LLMs prompting for multi-document summarization task.

To overcome this challenge, the authors propose chain-of-event (CoE) prompting for multi-document summarization (MDS) task. In this prompting, the authors take events as the center and propose a four-step summary reasoning process: specific event extraction; event abstraction and generalization; common event statistics; and summary generation. To further improve the performance of LLMs, the authors extend CoE prompting with the example of summary reasoning.

Summaries generated by CoE prompting are more abstractive, concise and accurate. The authors evaluate the authors’ proposed prompting on two data sets. The experimental results over ChatGLM2-6b show that the authors’ proposed CoE prompting consistently outperforms other typical promptings across all data sets.

This paper proposes CoE prompting to solve MDS tasks by the LLMs. CoE prompting can not only identify the key events but also ensure the conciseness of the summary. By this method, users can access the most relevant and important information quickly, improving their decision-making processes.

Bounce-back effect of stock market returns has been found empirically using different approaches. However, few paper explains the underlying mechanism. The paper aims to discuss these issues.

This paper fills this gap and provides an explanation for bounce-back effect in stock market.

This paper contributes to the literature in threefold. The authors contribute a formal economic model to rationalize the bounce-back effect of stock market returns. It is based on a model of stock return with volatility feedback under the assumption of Markov-Switching market volatility.

The authors use the general Markov-Switching bounce-back model, developed by Bec et al. (2015), to provide empirical evidence for the existence of bounce-back effect in stock market. The empirical result shows “W” shape of bounce-back effect, which is exactly the same as predicted by the economic theoretical model. Finally, the authors propose an alternative approach to estimate the magnitude of volatility feedback and the marginal effect on the expected return of an anticipated high variance regime.

Climate change not only causes serious economic losses but also influences financial stability. The related research is still at the initial stage. This paper aims to examine and explore the impact of climate change on financial stability in China.

This paper first uses vector autoregression model to study the impact of climate change to financial stability and applies NARDL model to assess the nonlinear asymmetric effect of climate change on China’s financial stability using monthly data from 2002 to 2018.

The results show that both positive and negative climate shocks do harm to financial stability. In the short term, the effect of positive climate shocks on financial stability is greater than the negative climate shocks in the current period, but less in the lag period. In the long term, negative climate shocks bring larger adjustments to financial stability relative to positive climate shocks. Moreover, compared with the short-term effect, climate change is more destructive to financial stability in the long run.

The paper provides a quantitative reference for assessing the nexus between climate change and financial stability from a nonlinear and asymmetric perspective, which is beneficial for understanding climate-related financial risks.

Rotating machineries are widely used in manufacturing, petroleum, chemical, aircraft, and other industries. To accurately identify the operating conditions of such rotating machineries, this paper aims to propose a fault diagnosis method based on sensitive dimensionless parameters and particle swarm optimization (PSO)–support vector machine (SVM) for reducing the unexpected downtime and economic losses.

A relatively new hybrid intelligent fault classification approach is proposed by integrating multiple dimensionless parameters, the Fisher criterion and PSO–SVM. In terms of data pre-processing, a method based on wavelet packet decomposition (WPD), empirical mode decomposition (EMD) and dimensionless parameters is proposed for the extraction of the vibration signal features. The Fisher criterion is applied to reduce the redundant dimensionless parameters and search for the sensitive dimensionless parameters. Then, PSO is adapted to optimize the penalty parameter and kernel parameter for SVM. Finally, the sensitive dimensionless parameters are classified with the optimized model.

As two different time–frequency analysis methods, a method based on a combination of WPD and EMD used to extract multiple dimensionless parameters is presented. More vital diagnosis information can be obtained from the vibration signals than by only using a single time–frequency analysis method. Besides, a fault classification approach combining the sensitive dimensionless parameters and PSO-SVM classifier is proposed. The comparative experiment results show that the proposed method has a high classification accuracy and efficiency.

To the best of the authors’ knowledge, very few efforts have been performed for fault classification using multiple dimensionless parameters. In this paper, eighty dimensionless parameters have been studied intensively, which provides a new strategy in fault diagnosis field.

The purpose of this paper is to identify the energy absorption characteristics of arch micro-strut (ARCH) lattice structure (different from traditional straight micro-strut lattice structure) under high-speed impact, and promote the development of special-shaped micro-strut lattice structure.

The study serves to study the anti-impact and energy absorption characteristics of ARCH lattice structure under different strain rates and different unit layers of lattice structure. In this paper, quasi-static compression and Hopkinson compression bar experiments are used for comparative analysis.

The results show that the ARCH lattice structure has obvious strain rate effect. When the strain rate is low, the number of layers of lattice structure has a great influence on the mechanical properties. With the increase of strain rate, the influence of the number of layers on the mechanical properties gradually weakens. So the ARCH lattice structure with fewer layers (less than five layers) should be selected as the impact energy absorbing materials at lower impact rate, while at higher impact rate, the number of layers can be selected according to the actual requirements of components or devices space size.

This study shows that Arch lattice structure has excellent energy absorption performance, and provides a theoretical reference for the application of ARCH lattice structure in energy-absorbing materials. ARCH lattice structure is expected to be applied to a variety of energy absorption and anti-impact components or devices, such as aircraft black box fall buffer components, impact resistant layer of bulletproof and landing buffer device.