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Article
Publication date: 6 August 2019

Lidan Yao, Lixin Wang, Haining Yang, Chuan Li, Hui Song and Xianguo Hu

This paper aims to investigate the influence of stearate types on the thickening ability, dropping point and fiber structure of greases.

172

Abstract

Purpose

This paper aims to investigate the influence of stearate types on the thickening ability, dropping point and fiber structure of greases.

Design/methodology/approach

Several greases were prepared from polyolefins and various stearates. The melting point of the stearates and the dropping point of the resultant greases were measured, and the intermolecular binding energies of the thickener and the radial distribution function of the metal–oxygen in the thickener were determined with the aid of molecular simulation. The microstructures of the greases were also analyzed via scanning electron microscopy.

Findings

A higher stearate binding energy was found to correlate to a higher dropping point of the resultant greases. The thickening ability of the stearate is related to the group and period of the constituent metal ion. Within a group, greater atomic numbers of the metal were correlated to lower thickening ability. In a period, as the atomic number of the metal increased, the thickening ability was enhanced. The radial distribution functions of metal and oxygen can explain the aggregation of the stearate thickeners in the grease.

Originality/value

This work compared the thickening capacity of several stearates. Guidelines for preparing stearates to tailor the resultant grease are presented.

Details

Industrial Lubrication and Tribology, vol. 71 no. 9
Type: Research Article
ISSN: 0036-8792

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Article
Publication date: 8 June 2021

Tianshu Li, Shukai Duan, Jun Liu and Lidan Wang

Stochastic computing which is an alternative method of the binary calculation has key merits such as fault-tolerant capability and low hardware cost. However, the hardware…

249

Abstract

Purpose

Stochastic computing which is an alternative method of the binary calculation has key merits such as fault-tolerant capability and low hardware cost. However, the hardware response time of it is required to be very fast due to its bit-wise calculation mode. While the complementary metal oxide semiconductor (CMOS) components are difficult to meet the requirements aforementioned. For this, the stochastic computing implementation scheme based on the memristive system is proposed to reduce the response time. The purpose of this paper is to provide the implementation scheme based memristive system for the stochastic computing.

Design/methodology/approach

The hardware structure of material logic based on the memristive system is realized according to the advantages of the memristor. After that, the scheme of NOT logic, AND logic and multiplexer are designed, which are the basic units of stochastic computing. Furthermore, a stochastic computing system based on memristive combinational logic is structured and its validity is verified successfully by operating a case.

Findings

The numbers of the elements of the proposed stochastic computing system are less than the conventional stochastic computing based on CMOS circuits.

Originality/value

The paper proposed a novel implementation scheme for stochastic computing based on the memristive systems, which are different from the conventional stochastic computing based on CMOS circuits.

Details

Circuit World, vol. 48 no. 3
Type: Research Article
ISSN: 0305-6120

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Article
Publication date: 17 October 2024

Hong Qian, Sihan Lin, Lidan Zhang, Shanglin Song and Ning Liu

This study mainly focused on the long-term effect of different risk exposure levels and prior anti-epidemic experience of healthcare workers in mitigating COVID-19 on their work…

44

Abstract

Purpose

This study mainly focused on the long-term effect of different risk exposure levels and prior anti-epidemic experience of healthcare workers in mitigating COVID-19 on their work stress in the post-COVID era.

Design/methodology/approach

The study sample included 359 physicians, 619 nurses, 229 technicians and 212 administrators, for a total of 1,419 healthcare workers working in the Lanzhou area during the investigation. Data were analyzed by multivariate regression models.

Findings

Our findings indicated that the interaction between pandemic effect mitigation experience and high-risk exposure significantly affected healthcare workers in the post-COVID era by increasing their work stress (p < 0.001) and reducing their rest time (p < 0.001). Healthcare workers may have experienced worse outcomes in the long term if they had higher levels of risk exposure and more experience in fighting epidemics. Furthermore, poor mental health (p < 0.001) and prior experience with SARS (p < 0.001) further amplified these adverse effects. However, surprisingly, we did not observe any effect of prior anti-epidemic experience or high-risk exposure on the mental health of healthcare workers in the post-COVID era (p > 0.1).

Research limitations/implications

The adverse impact of COVID-19 may have left long-lasting effects on Health professionals (HPs), particularly those with high Risk exposure (RE) and more mitigation experience. Poor Mental health (MH) and previous experience in mitigating previous similar outbreaks (such as SARS) are risk factors that should be considered. Support programs must be designed and promoted to help HPs respond and improve their performance.

Originality/value

Our study presents compelling evidence that the COVID-19 pandemic will have long-term detrimental effects on the work stress of healthcare workers.

Details

Journal of Health Organization and Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1477-7266

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