Tribological analysis on the effect of heat transfer towards engine in-cylinder friction

The aim of this study is to determine the effect of heat transfer towards engine in-cylinder frictional losses, generated by the piston ring pack sliding along the engine cylinder liner. A mathematical model is derived from the 1D Reynolds equation, using Reynolds’ boundary condition, to determine the contact pressure distribution along the ring-liner conjunction. Meanwhile, the lubricant temperature profile is solved using the 1D energy equation, considering heat conduction and viscous heating effect. The mathematical models are implemented in C-program. The minimum film thickness and the total friction force from the current model are showing good correlation with literature data. The results showed that heat conduction mechanism predominates the viscous heating effect in the ring-liner conjunction. Meanwhile, the boundary friction predominates the contribution of viscous friction, especially along the vicinity of dead centres. However, the boundary friction is not affected by the changes in lubricant viscosity. Hence, from an overall engine operation point of view, the effect of heat transfer towards the total friction force generated by the ring pack could be considered trivial

The Relationships Among Gender, Work Experience, and Leadership Experience in Transformational Leadership

Transformational leadership is an organizational leadership theory centered around the ability to inspire and motivate followers to achieve results greater than originally planned and for internal reward The investigation into transformational leadership began in the mid-1980s with a number of influential publications by Bass (1985), Bennis and Nanus (1985), Kouzes and Posner (1987) and Tichy and Devanna (1986). In the 1980s, the study of transformational leadership was focused on case-based research (Conger, 1999). By late 1990s, a substantial body of empirical investigations on transformational leadership had been conducted

Predicting frictional losses generated by piston connecting-rod big end journal bearing for an internal combustion engine

The aim of the study is to investigate the tribological behaviour of the connecting-rod big end journal bearing under dynamic loading for a full engine cycle.In this study, a numerical analysis is used for solving the 2-D Reynolds equation based on Reynolds boundary condition. The 2-D Reynolds solution was derived by using a combination of approaches, namely finite difference method, Newton-Raphson method, and Taylor expansion series. Then, the formulated 2-D mathematical model is used to ascertain the tribological behaviour for both rigid and deformable bearing assumptions.For low loading conditions, the simulation results from both rigid and deformation models have only shown minor differences, demonstrating correlation with existing analytical and experimental results. However, once the loading capacity is increased, the simulation results from the deformation model assumption is shown to be much closer to the experimental results obtained from real engine analysis.In short, an elastic journal bearing assumption in simulating such tribological conjunction is believed to be more practical and reliable for real engine practices as compared to a rigid journal bearing assumption

Role of structural relaxations and vibrational excitations in the high-frequency dynamics of liquids and glasses

We present theoretical investigation on the high-frequency collective dynamics in liquids and glasses at microscopic length scales and terahertz frequency region based on the mode-coupling theory for ideal liquid-glass transition. We focus on recently investigated issues from inelastic-X-ray-scattering and computer-simulation studies for dynamic structure factors and longitudinal and transversal current spectra: the anomalous dispersion of the high-frequency sound velocity and the nature of the low-frequency excitation called the boson peak. It will be discussed how the sound mode interferes with other low-lying modes present in the system. Thereby, we provide a systematic explanation of the anomalous sound-velocity dispersion in systems -- ranging from high temperature liquid down to deep inside the glass state -- in terms of the contributions from the structural-relaxation processes and from vibrational excitations called the anomalous-oscillation peak (AOP). A possibility of observing negative dispersion -- the {\em decrease} of the sound velocity upon increase of the wave number -- is argued when the sound-velocity dispersion is dominated by the contribution from the vibrational dynamics. We also show that the low-frequency excitation, observable in both of the glass-state longitudinal and transversal current spectra at the same resonance frequency, is the manifestation of the AOP. As a consequence of the presence of the AOP in the transversal current spectra, it is predicted that the transversal sound velocity also exhibits the anomalous dispersion. These results of the theory are demonstrated for a model of the Lennard-Jones system.Comment: 25 pages, 22 figure

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

Is the Convergence of Accounting Standards Good for Stock Markets?

This paper examines the impact of the convergence of Hong Kong Accounting Standard 40 (HKAS 40) with the International Financial Reporting Standard (IFRS) on the stock prices of firms in the property industry. Using a sample of 22111 firm-day observations, we show that the new standard has a negative impact on the stock performance of these firms.Hong Kong Accounting Standard 40, Event Window, Stock Return.

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

Textural and rheological properties of stevia ice cream

Ice cream contains high sugar content and therefore it is in contradiction with the concept of healthy diet. The objective of this study is to determine the suitability of using stevia as an alternative natural sweetener in making ice cream. In-house ice cream formulation (as the control) and three different concentrations of stevia ice cream formulations of (A, B and C) were used. Physical properties of the ice cream such as the overrun, total soluble solid, meltdown rate, rheology, and textural properties were evaluated. All ice cream samples exhibited a non-Newtonian flow with pseudoplastic behavior. Stevia ice cream has a lower melting rate and has a higher sustainability. The power law also showed that apparent viscosities of stevia ice cream were higher. Therefore, stevia can be used as a natural sugar substitute in ice cream production

Essential Role of NK Cells in IgG Therapy for Experimental Autoimmune Encephalomyelitis

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Classifying the Archery Performance with Conditional Effects on Angular and Linear Shooting Techniques

The archery sports skills are commonly assessed from the physical, psychological, biomechanical and perceptual aspects. Apparently, archers also encounter outdoor obstacles that potentially affect their performances. However, little is described on the different conditions encountered during the shooting in relation to archery techniques and its performances. The study aims to investigate archer’s shooting performances under outdoor conditional stresses, considering two shooting skills: Angular Shooting Technique (AST) and Linear Shooting Technique (LST). Outdoor experimental setups involving a university-level male archer performing 36 shots (6 ends of 6 arrows) each for the 70 m distance target using AST and LST techniques, under nine different conditions: morning, noon, night, hot, rain, calm, windy, cloudy and extreme 6-arrow-shot in 2 minutes were included. Recorded scores on Archery Score Pro software were used to determine the archery performances. The shooting techniques classification were based on the recorded arrow scores using Random Tree algorithm in the Waikato Environment for Knowledge Analysis (WEKA) tool. Classification analyses showed 83.3% distinguishable by shooting conditions; accurately classified by 97.9% on the extreme conditions, 98.1% for first three end shots and last three ends shots. Findings showed that AST outperforms the LST under different outdoor conditions