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.
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
Keywords
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…
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
Keywords
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…
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.