Experimental Study
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2022 ◽  
Vol 388 ◽  
pp. 111645
Kohei Yoshida ◽  
Kota Fujiwara ◽  
Yuki Nakamura ◽  
Akiko Kaneko ◽  
Yutaka Abe

CivilEng ◽  
2022 ◽  
Vol 3 (1) ◽  
pp. 35-50
Akram Deiminiat ◽  
Li Li

The determination of shear strength parameters for coarse granular materials such as rockfill and waste rocks is challenging due to their oversized particles and the minimum required ratio of 10 between the specimen width (W) and the maximum particle size (dmax) of tested samples for direct shear tests. To overcome this problem, a common practice is to prepare test samples by excluding the oversized particles. This method is called the scalping scaling down technique. Making further modifications on scalped samples to achieve a specific particle size distribution curve (PSDC) leads to other scaling down techniques. Until now, the parallel scaling down technique has been the most popular and most commonly applied, generally because it produces a PSDC parallel and similar to that of field material. Recently, a critical literature review performed by the authors revealed that the methodology used by previous researchers to validate or invalidate the scaling down techniques in estimating the shear strength of field materials is inappropriate. The validity of scaling down techniques remains unknown. In addition, the minimum required W/dmax ratio of 10, stipulated in ASTM D3080/D3080M-11 for direct shear tests, is not large enough to eliminate the specimen size effect (SSE). The authors’ recent experimental study showed that a minimum W/dmax ratio of 60 is necessary to avoid any SSE in direct shear tests. In this study, a series of direct shear tests were performed on samples with different dmax values, prepared by applying scalping and parallel scaling down techniques. All tested specimens had a W/dmax ratio equal to or larger than 60. The test results of the scaled down samples with dmax values smaller than those of field samples were used to establish a predictive equation between the effective internal friction angle (hereafter named “friction angle”) and dmax, which was then used to predict the friction angles of the field samples. Comparisons between the measured and predicted friction angles of field samples demonstrated that the equations based on scalping scaling down technique correctly predicted the friction angles of field samples, whereas the equations based on parallel scaling down technique failed to correctly predict the friction angles of field samples. The scalping down technique has been validated, whereas the parallel scaling down technique has been invalidated by the experimental results presented in this study.

Coatings ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 67
Fengming Du ◽  
Changduo Chen ◽  
Kaiguang Zhang

The sliding bearing is an important component in machines. The characteristics of the oil film fluid of the sliding bearing is the key factor affecting lubrication, which will affect the wear and reliability of the sliding bearing. Herein, the lubricating oil of the sliding bearing is studied, the oil film flow model considering the cavitation effect is established, the pressure and temperature distribution of the oil film under different rotational speeds is explored, and its influence on oil film pressure and temperature are analyzed. Furthermore, wear tests are carried out to measure the wear amount of the bearing bush under different rotational speeds, and the influence of the fluid characteristics of the lubricating oil film on bearing wear is explored. The simulation and experimental study in this paper can provide a reference for the design of sliding bearings.

Pharmacy ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 9
Gouri Rani Banik ◽  
Bandar Durayb ◽  
Catherine King ◽  
Harunor Rashid

Background: This systematic review aimed to establish whether antimicrobial resistance (AMR) occurs following prolonged use of antimicrobial hand hygiene (HH) products, and, if so, in what magnitude. Methods: Key bibliographic databases were searched to locate items on HH use and AMR development from database inception to December 2020. Records were screened and full texts of all potentially eligible articles were retrieved and checked for inclusion. The following data from the included studies were abstracted: type of HH product used, including the name of antimicrobial agent, study setting, country, study year, duration of use and development of AMR including the organisms involved. Quality assessment was done using the Newcastle-Ottawa Scale (NOS). Results: Of 339 full-text articles assessed for eligibility, only four heterogeneous United States (US) studies conducted in the period between 1986 and 2015 were found eligible, and included. One hospital-based study showed evidence of AMR following long term use of HH products, two studies conducted in household settings showed no evidence of AMR, and another experimental study showed partial evidence of AMR. The overall certainty of the evidence was moderate. Conclusion: Prolonged use of HH products may cause AMR in health care settings, but perhaps not in other settings.

2022 ◽  
Vol 14 (1) ◽  
pp. 485
Ke Zhang ◽  
Jian Tao

Connection with the natural world is a fundamental human need related to sustainable development. However, such a human need is very likely to be threatened in modern, industrialized society. This paper represents the first attempt to investigate the effect of perceived disconnection from nature on consumers’ preference for automated products (e.g., virtual assistants). Based on two surveys (276 adult participants) and one experimental study (282 adult participants), we found that perceived disconnection from nature can magnify consumers’ resistance to automated products. We further examined the underlying mechanism through moderated mediation model and revealed that consumers who perceive greater nature disconnection are less likely to perceive automated products as helpful friends, leading to a lower likelihood of adopting these products. The present research unveils this novel effect of perceived disconnection with nature on consumer behavior and provides fresh insight into how consumers’ preferences for automated products can be influenced by psychology rather than technology. Additionally, these findings can extend the research regarding sustainable consumption.

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