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The railway track system is the platform by which loads from moving trains are transferred to the underlying soil or supporting infrastructure such as bridges. The most common type of railway track system is ballasted track, which has been in use for over a century. Ballasted track has proved versatile. It can be constructed using locally available materials and with modifications to the rails and sleepers, crossings transferring trains from one route to another can be created. The structure of a ballasted track system consists of two main parts. The upper portion, termed the superstructure, comprises the rails, fastenings and sleepers. It is formed of components whose shape, stiffness and strength are designed and closely controlled. Below the superstructure is the substructure, which comprises the ballast and sub-ballast. Although the materials used in the substructure may have been specified, their engineering properties and geometric placement are less well controlled. In this chapter, we will explore how a typical ballasted track system transfers load to the ground and the ways in which the track form deteriorates, requiring maintenance and eventually renewal.

The vehicle–track interaction and the resulting dynamic response of the vehicle involve a number of complex nonlinear problems. Large vertical loads act through a small contact patch leading to very high contact pressures. Transverse loads acting through this contact induce a relative velocity between wheel and rail expressed in non-dimensional form as a creepage. The wheel and rail profiles determine the contact patch shape and affect the ability of the vehicle to run stably. If the yaw stiffness of the axles is too low, the vehicle will become unstable at a relatively low speed; conversely, if the yaw stiffness is too high, the curving behaviour will be adversely affected. The vehicle suspension, especially the secondary suspension, also affects the ride comfort of passengers. Finally, it is shown how the speed profiles of accelerating and decelerating trains can be calculated from basic assumptions about the train power, adhesion and rolling resistance.

This research investigates the impact of nonlinear career trajectories on female staff in the academy. It argues that assessment of “achievement relative to opportunity” is essential to the equitable positioning of women in the academy.

This qualitative study is based on extended structured interviews with 43 staff.

Men and women can experience career interruptions, deviations, and hijacks, but, in general, women experience more interruption, and the cumulative effect on their careers is greater.

The authors point to ways in which the assessment of achievement relative to opportunity can be implemented in universities to improve retention and career outcomes for female academic and professional staff.

Embedding the principles of achievement relative to opportunity in evaluative decision making, supports people (particularly women) who have spent time away from the workforce in becoming more competitive in assessments of suitability for leadership and advancement. Changing traditional methods of evaluating merit has the potential to allow people from diverse backgrounds to be fairly evaluated, and shift the dominance of people who have experienced little or no career interruption.

The originality is the measurement of impact of nonlinear careers within the academy. The contribution is in the applicability of the findings and practical suggestions for implementation.

Firms with linear pricing offer their customers the same price for each unit of a good or service. Anything else is nonlinear pricing. Nonlinear pricing in imperfect markets indicates a fundamental asymmetry in information between firms and consumers. Consumers are commonly expected to exhibit quality- or quantity-preference differences and have different reservation values for different product attributes. The firms, however, cannot observe consumers' preferences. When complete information regarding preferences is not observable, nonlinear pricing strategies with firms offering a menu or schedule of prices allow consumers to sort themselves according to their own preferences, resulting in market segmentation.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

Good market timing skills can be an important factor contributing to hedge funds’ outperformance. In this chapter, we use a unique semiparametric panel data model capable of providing consistent short period estimates of the return correlations with three market factors for a sample of Long/Short equity hedge funds. We find evidence of significant market timing ability by fund managers around market crisis periods. Studying the behavior of individual fund managers, we show that at the 10% significance level, 17.12% of funds exhibit good linear timing skills and 21.32% of funds possess some level of good nonlinear market timing skills. Further, we find that market timing strategies of hedge funds are different in good and bad markets, and that a significant number of managers behave more conservatively when the market return is expected to be far above average and more aggressively when the market return is expected to be far below average. We find that good market timers are also likely to possess good stock selection skills.

The authors introduce a new approach to estimate high-dimensional factor-augmented vector autoregressive models (FAVAR) where the loadings are subject to idiosyncratic regime-switching dynamics. Our Bayesian estimation method alleviates computational challenges and makes the estimation of high-dimensional FAVAR with heterogeneous regime-switching straightforward to implement. The authors perform extensive simulation experiments to study the finite sample performance of our estimation method, demonstrating its relevance in high-dimensional settings. Next, the authors illustrate the performance of the proposed framework for studying the impact of credit market disruptions on a large set of macroeconomic variables. The results of this study underline the importance of accounting for non-linearities in factor loadings when evaluating the propagation of aggregate shocks.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.