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The purpose of this paper is to optimize the structure of plough blades in a ploughshare mixer using the discrete element method (DEM) simulations.

Using the validated DEM model, three numerical tests are conducted to determine how the mixing performance evolves as structural parameters of blades change. Results from the analysis provide basis for structure optimization of blades. The structural parameters include sweep angle of blade γ, regular axial pitch p and regular circumferential angular offset α. The parameters to evaluate mixing performance include mass flow rate and Lacey index.

The DEM results show that the mixing performance at γ of 35° is better than 15°, 25° and 45°. The mixer which has a p of less than or equal to 1.11 · b is more efficient than the mixer which has a p greater than 1.11 · b, where b is tail width of blade. The circumferential symmetric distribution of blades (α = 180°) is more beneficial to improve the mixing performance in comparison with the circumferential asymmetric distribution (α < 180°). Based on the results, an optimized mixer with a γ of 35°, a p of 0.61 · b and an α of 180° is proposed, which has a better mixing performance compared to all mixers listed.

The structural parameters of blades, including γ, p and α, are found to be critical for good mixing. From the view angle of structure optimization of plough blades, a new ploughshare mixer with a γ of 35°, a p of 0.61 · b and an α of 180° is investigated and recommended for improving mixing efficiency.

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.

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.

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.