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This paper aims to investigate the influence of slurry concentration on the erosion behavior of AISI 5117 steel and high-chromium white cast iron by using a whirling-arm rig. In this study, the slurry erosion mechanism with particle concentration has been studied.

The tests were carried out with particle concentrations in the range of 1-7 Wt.%, and the impact velocity of slurry stream was 15 m/s. Silica sand with a nominal size range of 500-710 µm was used as an erodent. The study revealed that the failure mode was independent of concentration.

The results showed that the erosion rate decreases with the increase in particle concentration and the variation in the reduction depends on the material. It was found that the variation of fractal dimension calculated from slope of linearized power spectral density of eroded surface image for different concentrations can be used to characterize the slurry erosion intensity in a similar manner to the erosion rate. It was also found that the variation of fractal dimension versus concentration of sand has a general trend that does not depend on magnification factor.

Using the gravitational measurement and image analysis, the variation of the wear with slurry concentration has been analyzed to investigate the implicated mechanisms of erosion during the process.

Purpose – This chapter provides details of research that attempts to relate traffic operational conditions on uninterrupted flow facilities (e.g., freeways and expressways) with real-time crash likelihood. Unlike incident detection, the purpose of this line of work is to proactively assess crash likelihood and potentially reduce the likelihood through proactive traffic management techniques, including variable speed limit and ramp metering among others.

Methodology – The chapter distinguishes between the traditional aggregate crash frequency-based approach to safety evaluation and the approach needed for real-time crash risk estimation. Key references from the literature are summarised in terms of the reported effect of different traffic characteristics that can be derived in near real-time, including average speed, temporal variation in speed, volume and lane-occupancy, on crash occurrence.

Findings – Traffic and weather parameters are among the real-time crash-contributing factors. Among the most significant traffic parameters is speed particularly in the form of coefficient of variation of speed.

Research implications – In the traffic safety field, traditional data sources are infrastructure-based traffic detection systems. In the future, if automatic traffic detection systems could provide reliable data at the vehicle level, new variables such as headway could be introduced. Transferability of real-time crash prediction models is also of interest. Also, the potential effects of different management strategies to reduce real-time crash risk could be evaluated in a simulation environment.

Practical implications – This line of research has been at the forefront of bringing data mining and other machine-learning techniques into the traffic management arena. We expect these analysis techniques to play a more important role in real-time traffic management, not just for safety evaluation but also for congestion pricing and alternate routing.

The purpose of this study was to determine the effects of chickpea (Cicer arietinum) protein hydrolysates prepared at two degrees of hydrolysis (DH) on lipoprotein profile and on oxidant status in cholesterol-fed rats.

Eighteen male Wistar rats (220 ± 10 g) were divided into three groups and fed for 30 days a diet containing 20 per cent casein supplemented with 1 per cent cholesterol and 0.5 per cent cholic acid. During the experimentation, the first and the second groups received daily by gavage 250 mg of chickpea protein hydrolysates/rat at DH = 8 per cent (CPH8) and DH = 17 per cent (CPH17), respectively. The third group, named control group (CG), received water under the same conditions.

Serum total cholesterol concentrations were reduced in CPH8 (p < 0.0073) and CPH17 (p < 0.0004) groups versus CG. This reduction corresponded to a lower very-low-density lipoprotein (VLDL)-cholesterol (p < 0,0019). CPH17 reduced low-density lipoprotein- and high-density lipoprotein (HDL)-cholesterol (p < 0.0001) but increased apolipoprotein A4 (p < 0.002) concentrations and lecithin-cholesterol acyltransferase activity (p < 0.0001). APOA1 remained unchanged in the treated groups. Liver total and esterified cholesterol contents were twofold lower in both treated groups versus CG. CPH8 increased triacylglycerols and phospholipids (p < 0.0001) contents, while CPH17 decreased those of unesterified cholesterol (p < 0.0016). Compared with CG, CPH8 and CPH17 reduced serum (p < 0.0001) and lipoprotein hydroperoxides by stimulating paraoxonase activity (p < 0.0001). However, only CPH17 treatment reduced serum, VLDL- and HDL-malondialdehyde contents and improved glutathione peroxidase activity (p < 0.061).

Thus, chickpea protein hydrolysates and especially hydrolysed at DH = 17 per cent may have a great potential for use as a nutraceutical to reduce hypercholesterolaemia and, by consequence, oxidative stress. Therefore, the degree of enzymatic hydrolysis has a significant influence on the production of potent bioactive peptides.

This study aims to discover a practical and effective way to apply the quality cost concept in Strategic Cost Management (SCM) framework. The interaction of preventive, appraisal and failure (PAF) activities in a company's internal value chain will be the starting point of SCM implementation.

This study begins by establishing value chain and quality costs as the scope of conceptual analysis. Discussions on the interrelationships between activities, quality and costs were gathered to clarify conceptual and practical gaps in the scope of the study. The PAF quality cost model is applied to find viable, practical solutions. The costs of activities will serve as performance indicators.

The PAF quality cost model depicts opportunities to lower costs and increase profit in a business simultaneously; current poor quality costs are the benchmark. Identifying PAF activities and costs in the business value chain and linking it with others is crucial in evaluating SCM applications. These linkages will generate a Quality Cost Chain (QCC). The leading indicator of improvement is a higher ratio between new possible failure costs (FC) and the combination of prevention and appraisal costs (PAC) than the current value, followed by a lower total quality cost (TQC). The subsequent attention is a lower ratio between the appraisal cost (AC) and prevention cost (PC). Mathematically, for assessing the operability of new quality-related activities, ΔPAC_new < ΔFC_new, TQC_new < TQC_current, (FC/PC)_new>(FC/PC)_current and (AC/PC)_new<(AC/PC)_current are proposed as feasible conditional-quantitative improvement criteria.

This study only discusses the relationship between quality costs and activities related to quality management in the PAF quality cost model, not cost behavior. This limitation opens up opportunities for future research that intends to link QCC with cost behavior in the context of managerial accounting and Strategic Cost Management. The use of QCC in certain industrial areas is the next research opportunity. The variety of PAF activities this study addresses originates from a wide range of industrial sectors; QCC research by sector may produce unique industrial quality cost phenomena.

QCC will make it easier for managers to evaluate how strategically their departments or activities contribute to quality costs at the departmental or organizational level, as well as to effectively and efficiently improve quality cost performance.

The quality-related activity and quality cost issues are still rarely treated as subjects of research studies in the field of Strategic Cost Management. Even so, the discussion tends to be very broad, complex and difficult to apply. This study combines a simple diagrammatic and mathematical approach to simplify the discussion and, at the same time, manage the value of strategic quality management.

This study investigates the nature of the association between profit warnings and stock price informativeness in the context of Jordan as an emerging country.

The authors used a large panel data set that related to stock price synchronicity and profit warnings percentages on the Amman Stock Exchange for the period spanning 2007–2018. Robust regression was used as a parametric test. This enabled us to obtain stronger results that fall in line with our prediction that a profit warning encourages firm investors to collect and process more firm-specific information than common market information.

Our findings show a significant positive effect of profit warnings on the amount of firm-specific information incorporated into stock price, which means that the greater the percentage of profit warnings the more likely that more firm-specific information will be incorporated in stock price synchronicity. In addition, corporate governance characteristics (moderating variables) significantly increase the level of the relationship between profit warnings and stock price synchronicity.

Our study results could be useful to investors, senior managers, and regulators in Jordanian firms, particularly in relation to decisions about enhancing the quality of financial statements. In addition, our results provide new evidence about the consequences of earnings announcements for information content and the informativeness of stock prices. Our methodology and evaluation of profit warnings may also demonstrate useful evidence for future researchers on profit warnings and stock price informativeness in developing economies, especially given that such evidence is scarce in developing economies.

This research is the first study of its kind on emerging markets, particularly in the Middle East. Moreover, entering the corporate governance variables as moderating variables to the robust regression was found to be more powerful than other regressions.

Private telecommunication companies in Yemen face huge challenges to improve their competitive position. Many of them suffer from performance management systems (PMS) that are not aligned nor integrated and do not give adequate support. This research aims at identifying the current state and quality of PMS in Yemeni private telecom companies and developing recommendations that will assist in improving their performance and competitive position.

As research tools, the performance management analysis – used to measure the quality of a PMS – and the high performance organization (HPO) framework – used to measure the quality of an organization and thereby its ability to achieve sustainable high competitive performance – are applied at three Yemeni private telecom companies.

There is a considerable performance gap between the actual and the ideal PMS in the Yemeni private telecom companies; this performance gap is highly correlated with competitive performance in a negative relationship. Both the structural and behavioral dimensions’ performance gaps have a significant impact on competitive performance, with the impact of the behavioral dimensions being considerably higher than that of the structural dimensions.

The current academic literature on HPOs and PMS in Yemen is scarce. This study adds knowledge to these areas, and thus provides a basis for further study. This research results also help managers of the Yemeni private telecom companies to take strategic action to redesign and implement new and improved PMS to increase their competitive performance.

This chapter provided systematic and comprehensive analysis on trawl fisheries management and conservation measures in the Straits of Malacca. Detailed analysis is conducted on Malaysian fishery management framework particularly domestic country's trawl fishery status, legal structure, input-control strategies, ecosystem protection plan, pollution, law enforcement, and complementary measures that designed to reduce and prevent overfishing in the exclusive economic zone (EEZ) of Malacca Straits. Gaps and challenges found in existing trawl fisheries literature are presented followed by recommendations for improvement in the management and conservation of trawl fisheries.

It is important to understand the factors that are significant in supply chain (SC) collaboration decision making and whether supply chain collaborative factors that are considered in the literature are still valid. To date, SC collaboration has not been extensively studied in the literature with supply chain finance (SCF) factors to evaluate SCF performance. Therefore, in this paper, the authors investigate the interrelationships between SCF and supply chain collaborative (SCC) factors for achieving SCF performance. The authors identified the most important factors from the literature on SCF and SCC and with inputs from experts in the textile industry in Pakistan.

The authors employed the Gray-Decision Making Trial and Evaluation Laboratory approach to help examine the cause-and-effect relationship between the factors and identify the influence of each factor on the others.

The findings showed that the most prominent factors of the study are “level of digitalization”, “information sharing”, and “collaborative communication”, and “most effect factors of this study are incentive alignment” and “information quality”. Furthermore, the “Level of digitalization” was identified as the factor with the central role and most significant correlation with other factors.

The major implication of the study is that textile industries should effectively develop their supply chain decisions after analyzing their internal and external factors, which will help in developing strategies that will facilitate better management of SCF relationships. The limitations of the study are that only 15 SCF and supply chain collaborative factors were considered, and time and scope are also limited. This study is only applied in the textile industry, so generalization may be limited.

To date, this study is the only one that has taken into consideration SCC with SCF factors to evaluate supply chain performance. This paper therefore makes this initial attempt and original contribution to this discussion, which can be helpful for those working to enhance supply chain performance, such as practitioners and policymakers.

The purpose of this paper is to generate nitrogen-containing groups in the cotton fabric surface via low-temperature nitrogen plasma as an eco-friendly physical/zero-effluent process. This was done for rendering cotton dye-able with Acid Blue 284, which in fact does not have any direct affinity to fix on it.

Dyeing characteristics of the samples such as color strength (K/S), fastness properties to light, rubbing and perspiration and durability, as well as tensile strength, elongation at break, whiteness, weight loss and wettability in addition to zeta potential of the dyed samples, were determined and compared with untreated fabric. Confirmation and characterization of the plasma-treated samples via chemical modifications and zeta potential was also studied using Fourier transform infrared spectroscopy (FTIR) and Malvern Zetasizer instrumental analysis.

The obtained results of the plasma-treated fabric reflect the following findings: FTIR results indicate the formation of nitrogen-containing groups on cotton fabrics; notable enhancement in the fabric wettability, zeta potential to more positive values and improvement in the dyeability and overall fastness properties of treated cotton fabrics in comparison with untreated fabric; the tensile strength, elongation at break, whiteness and weight % of the plasma treated fabrics are lower than that untreated one; and the durability of the plasma treated fabric decreased with increasing the number of washing cycles.

The novelty addressed here is rendering cotton fabrics dye-able with acid dye via the creation of new cationic nitrogen-containing groups on their surface via nitrogen plasma treatment as an eco-friendly and efficient tool with a physical/zero-effluent process.