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This work aims to compare the vibration behavior of roller and ball bearings operating with clean and quartz‐contaminated lubricants. Wear influence on vibration of both bearing types was also compared.

Experimental tests were run in clean and contaminated mineral oil. Contaminant quartz particles of 59 μm average size were tested in three concentration levels: 0.05, 0.25 and 0.5 g/l. Radial vibration of the roller bearing was measured by accelerometer and wear was analyzed through microscopy of the surfaces and optical spectrometry of oils.

Differences in vibration response among both bearing types were observed regarding the root mean square value of vibration data in the high frequency band (600‐10,000 Hz); differences in wear influence on vibration were also identified and correlated to the differences in the tribological features.

This paper presents a methodology for detecting contamination and wear of roller bearings by applying a simple procedure of vibration monitoring and analysis.

The purpose of this study is to draw on terror management theory (TMT) to explore the impact of pervasive mortality cues on consumer behaviour as a result of residing in a community ravaged by escalating violence.

A qualitative analysis of 27 in-depth interviews of consumers living in Ciudad Juárez, Mexico during the height of the Mexican drug war provides insight into their coping strategies and consumption.

Living under such conditions results in unrelenting mortality salience (MS), as well as the adoption of consumption-related coping strategies that can conflict with cultural worldviews and threaten self-esteem. The normalization of coping strategies severely strains worldviews. Consumers manage their ensuing intrapersonal evaluative tension by developing consumption safe havens and through identity fragmentation. Moreover, permanent proximal defences result from persistent MS.

Although cross-sectional and idiosyncratic to the Mexican culture, the findings broaden TMT by suggesting that consumers facing relentless MS experience altered brand meanings and social interactions, as they were reluctant to acquire prestige brands, while indicating an increase in the value placed on relationships over possessions.

Marketers can help consumers alleviate their death-related anxiety by eliminating telemarketing campaigns, promoting online shopping, using unique customer identification numbers and investing in visible security measures such as gates, security cameras, and guards.

This exploratory study provides a preliminary theoretical framework for consumers’ reactions to persistent MS.

In the previous chapters, I set out a conceptual model of trauma-informed servant leadership and discussed servant leadership supervision for working with burnout, compassion fatigue and secondary trauma in employees within trauma related health and social care settings. In this chapter, I further extend servant leadership to the peer support principle in trauma-informed approaches (Substance Abuse and Mental Health Services Administration, 2014). The first part of this chapter will examine peer support work (PSW) and report on the outcomes associated with it. Then, servant leadership will be discussed and used to operationalise the principle of peer support as set out in trauma-informed approaches. A servant leadership peer support approach is put forward with a theoretical basis. This theoretical model has been slightly changed from the previous servant leadership approaches discussed, in order to represent the PSW role more accurately. However, as discussed previously, it is not the characteristics of the Servant leadership (SL) model that define the approach, rather the philosophy and desire to serve first. In the last section of this chapter, Martha Griffin brings the characteristics of this model to life using her vast experience and discusses some of the potential challenges faced by peers in training and practice.

The purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.

The possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.

Results have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. On other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.

This study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.

Contamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy‐to‐use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.

This research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.

This paper aims to present a proposal for evaluating the coefficient of friction (COF), under a reciprocating test that considers the energy dissipated by the friction force. In addition, this new parameter is compared to average COF, which is often used to evaluate COF in reciprocating tests.

Samples of compacted graphite iron were extracted directly from an internal combustion engine block. The piston ring used was a nitrided martensitic stainless steel with an asymmetrical profile, and the lubricant oil was the SAE 30 CF, controlled at 40°C. Different testing conditions were carried out in a CETR-UMT-Bruker tribometer, varying loads between 25-125 N, frequencies between 1-12.5 Hz and track length between 3-10 mm. Three maps comparing the average COF and the energetic definition were built, allowing to discuss their similarities.

In general, both parameters had similarities especially for low frequencies and small tracks. However, for test conditions that imposed higher accelerations (i.e. longer track lengths and higher frequencies), the energetic COF (COFe) was lower than the average COF (COFa) and presented better agreement in Stribeck-like curves – independent on the experienced lubrication regime along the stroke. As the COFe can be interpreted as a weighted average of instantaneous COF in relation to in-track displacements, an immediate consequence is that instantaneous COF closest to mid-stroke is considered more significant. Furthermore, perturbations associated with the intrinsic accelerations of the movement test are minimized in the COFe formulation.

The energetic COF parameter (COFe) is presented and compared to the average COF. The new parameter presented less data dispersion and is attractive to evaluate the COF behavior in reciprocating tests, as its formulation minimizes perturbations associated with the intrinsic accelerations of the movement (mainly in the initial and final part of the track where the acceleration has its greatest magnitude).

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2019-0324

This paper aims to examine the friction coefficient and wear rate characteristics of SCM 440 bearing steel used in the cylinder block of a tractor engine with gas lubrication and oil lubrication.

Friction tests were performed using a pin-on-disc tester with loads of 2 to 10 N and sliding velocities of 0.06 to 0.34 m/s. The experiment was done with and without nitrogen, and paraffin oil lubricant was used to prevent wear during process.

The nondimensional characteristic number from the Stribeck curves indicated that the lubrication regime is hydrodynamic. As the velocity and load increased, the friction coefficient of the SCM 440 increased and greater applied load resulted in a smaller friction coefficient. The range of the friction coefficient was 0.017001 to 0.092904 with paraffin oil lubrication and 0.01614 to 0.4555 with nitrogen lubrication. Nitrogen is effective in reducing the friction coefficient of materials that are in contact and subjected to a load and velocity.

The experiments confirm that nitrogen is effective for reducing the friction coefficient of SCM 440 materials that are in contact with each other and subjected to a load and velocity.

A finite element method (FEM) model of the frictional behavior of two rough surfaces with a group of third-body particles confined by the surface asperities is established. By monitoring the stress distribution, friction force and the displacement of the surfaces, how the frictional instability is induced by these particles is studied. This modeling job aims to explore the relation between the meso-scale behavior and the macro-scale frictional behavior of these particles.

By using FEM, a 2D model of two frictional rough surfaces with a group of elastic or elasto-plastic particles confined by surface asperities is established. The Mises stress, macro friction force and displacements of elements are monitored during compressing and shearing steps.

The macro friction coefficient is more stable under higher pressure and smaller under higher shearing speed. The dilatancy of the interface is caused by the elevation effect of the particles sheared on the peak of the lower surface, particles collision and third body supporting. The combined effect of particles motion and surface–surface contact will induce high-frequency displacements of surface units in restricted direction.

Previous studies about third-body tribology are mainly concentrated on the frictional behavior with large number of particles distributed homogeneously across the interface, but this paper focuses on the behavior of third-body particles confined by surface asperities.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2019-0544/

The present quantitative-descriptive study aims to measure the level of English language learning autonomy of the pre-service teachers.

A short list questionnaire developed by Dixon (2011) was administered to 61 pre-service English teachers enrolled in Western Mindanao State University in order to measure their English language learning autonomy. Differences on the levels of English language learning autonomy across participants’ gender, number of languages spoken and first language were also explored.

Results revealed that participants are highly autonomous in English language learning. Gender, number of languages spoken and first language were found to have no significant influence on English language learning autonomy.

Results on the level of English language learning autonomy indicate that pre-service teachers are highly autonomous and, therefore, ready for lifelong learning. This implies pedagogical and instructional advantages, as they can learn and explore the language independently.

Since gender, number of languages spoken and first language do not significantly influence the level of English language learning autonomy, it is suggested that English teachers do not need to develop differentiated instructions and activities anymore, which will cater the three profile variables in fostering autonomous learning, as participants already exhibit a level of autonomy in English language learning.

This would allow teachers and students to be aware of the importance of autonomy in language learning. Thus, it will prepare them to be independent and lifelong learners, as they engage themselves in the professional world.

As one of the Asia’s developing countries, the Philippines have captured a small number of studies and contributions to autonomous learning in the field of research (Madrunio, Tarrayo, Tupas and Valdez, 2016 as cited in Iñigo, 2018). Specifically, there is no research study conducted that measures “language learning autonomy” in the Philippine’s higher education much to the knowledge of the researcher. Thus, this study will be the first one to determine the level of autonomy of pre-service teachers in English language learning in the Philippine context. Furthermore, the present study also intended to determine significant differences on the level of language learning autonomy of pre-service teachers across genders, number of languages spoken and their first language.

The purpose of this paper is to improve the application of neural networks on vehicle engine systems for fault detecting and analysing engine oils.

Three types of neural networks are employed to find exact neural network predictor of vehicle engine oil performance and quality. Nevertheless, two oil types are analysed for predicting performance in the engine. These oils are used and unused oils. In experimental work, two accelerometers are located at the bottom of the car engine to measure related vibrations for analysing oil quality of both cases.

The results of both computer simulation and experimental work show that the radial basis neural network predictor gives good performance at adapting different cases.

The results of the proposed neural network analyser follow the desired results of the vehicle engine's vibration variation. However, this kind of neural network scheme can be used to analyse oil quality of the car in experimental applications.

As theoretical and practical studies are evaluated together, it is hoped that oil analysers and interested researchers will obtain significant results in this application area.

This paper is an original contribution on vehicle oil quality analysis using a proposed artificial neural network and it should be helpful for industrial applications of vehicle oil quality analysis and fault detection.