This chapter looks at the spread of English to countries of the Southern Hemisphere, notably Australia, New Zealand, and South Africa. These “Southern Hemisphere Englishes” (including the islands of Tristan da Cunha and the Falklands in the South Atlantic) have been found to have a lot in common both historically and linguistically: similar settlement periods (the late eighteenth and early nineteenth centuries) and strategies (typically large-scale, organized settlement moves of lower- and middle-class people from the British Isles, mainly southern and south-eastern England). Their descendants today constitute large native-speaking communities of direct British ancestry. They faced similar situations – unfamiliar territory and climate and, most importantly, the need to deal and communicate with earlier residents of the areas they migrated to. In the long run, these peoples – Aboriginals in Australia; Maoris in New Zealand; Africans, Afrikaners, and later also Indians in South Africa – have adopted and transformed English, using it for their own purposes, and many of them have shifted to it, thus producing new ethnic varieties like Aboriginal English or Maori English. Cast studies and language samples focus on Australian English (including a discussion of pronunciation features in a "footie" sports program) and South African varieties of English.

What really inspires learning? We know that methods of teaching where students passively listen to a professor’s lecture may no longer inspire or engage learners to be active participants in the classroom. Today, educators are learning to move outside of their comfort zones to promote active participation and student-centered learning. However, this approach still isn’t enough to engage all learners. A one-size-fits-all pedagogy is unlikely to inspire the full range of students who we may have in our classrooms, whether due to differences in cultures of learning or differences related to learning disabilities.

Mass transfer occurs whenever fluid flows; that is, some mass is transferred from one place to another. However, the focus in this chapter is on the transport of one chemical species (or component) within a mixture that occurs as a direct result of a concentration gradient, independent of a pressure gradient. This type of mass transfer is called diffusion. A familiar example of diffusion mass transfer is the humidification process that occurs when an open container of water is allowed to sit out in a room. The gas in the room is a mixture of air (which is itself a mixture of oxygen, nitrogen, and other gases) and water vapor. The air–water mixture in contact with the surface of the liquid water is nearly saturated with water vapor and so it has a relatively high concentration of water vapor. The air–water mixture further from the liquid has a lower concentration of water vapor. Therefore, there is a concentration gradient that drives a mass transfer process causing water to be transported from the liquid surface to the air in the room, thereby humidifying it.

What’s the first thing you reach for in the morning? Is it your smartphone? Do you keep it next to your bed and use it as your alarm clock? Do you glance at it numerous times during the day in response to texts, emails, or other notifications? What about your computer? Do you have a laptop that travels with you to class and the library or do you have a desktop computer you work on when you’re at home? What are other kinds of things that you do on your smartphone or other mobile device, on your laptop or desktop computer? What would your life be like if you couldn’t use those devices or even access the internet? How would your life change? Your ability to use digital technology to accomplish daily tasks and solve daily problems is called digital literacy. But it’s not something you have or don’t have. What makes a person digitally literate changes constantly because digital devices, software, and apps are always changing and what you do with them changes as well. But why does digital literacy matter? Research into digital literacy tries to answer key questions such as why using digital technologies is important, who benefits from using digital tools, and how they benefit.

In this chapter, we start the illustration of general procedure of FEA for linear static analysis through a step-by-step solution of a 1-D elasticity problem. We introduce the important concepts and numerical techniques that make up the finite element method as we go through the steps. Then, computer implementation of the procedure is discussed, and a MATLAB code for solving the 1-D elasticity problem is provided. By completing both the hand and computer calculations for the same problem, we demonstrate how the step-by-step solution can be automated by a computer code. The chapter then goes on to demonstrate that other types of physical problems (heat transfer and advection?diffusion transport) can be solved by using the same FEA procedure.

For the average person without training in linguistics, language is usually viewed prescriptively, as something for which there are grammars and dictionaries – for example, rule books that state, definitively, correct forms of the language and how it should be used. What is lost in this standard view is the fact that people use language every day to get things done (order a pizza, ask a favor of someone, apologize, borrow a pencil, greet a friend) without ever consulting the rule books. The anthropological linguist William Hanks (1996) has noted that language has been defined as both an abstract system and an everyday practice; a set of generalizable forms and as temporal action; a cultural fact as well as an individual’s utterances. This chapter will focus on the second part of each of these pairs and will introduce theories of, and methods for, observing and analyzing language as it is used in real time. We take language to be the primary symbolic and signifying (semiotic) resource used by humans for meaning-making, one that is adapted to and influenced by the contexts in which it is used. Our work is inspired by ecological views of cognitive and communicative activity. These views posit that language not only resides in the heads of individuals but is also distributed across and emerges in human interaction with one another and the material world. In particular, our research is informed by functional theories of linguistics, such as integrational and interactional linguistics, as well as by recent work in cognitive science. Understanding communication and cognition under these theories involves exploring units of analysis that capture coordination between brains, bodies, and the material world.

We describe the Poisson distribution and how it is used to detect randomness in the spatial (or temporal) pattern of objects or events. We discuss several options for testing and quantifying the nature of spatial patterns, ranging from aggregated, through randomly arranged, up to regularly positioned objects. We demonstrate an approach based on comparing the variance and mean of count data, before moving to alternative methods that use the K-function alongside other similar functions, describing the change in spatial relationships across a range of spatial scales. Finally, we introduce the binomial distribution and how to estimate its p parameter (proportion of outcomes of a particular type within a set of observed objects) together with its confidence interval. The methods described in this chapter are accompanied by a carefully-explained guide to the R code needed for their use, including the spatstat and fitdistrplus packages.

In this chapter, we discuss basic mathematical concepts and methods that will be used as tools in the development of finite element formulations and solution of finite element models. Basic knowledge of linear algebra, calculus of vectors and matrices, variational calculus, and integral equations is necessary in the derivation of finite element formulations. These fundamental mathematical concepts and methods are reviewed as the building blocks for the following content of this book. Numerical methods for numerical approximation, differentiation, integration, discretization, and solution of linear systems will be discussed in Chapter 3. The mathematical tools and numerical methods are then utilized, along with relevant physical principles, in the illustration of the FEA procedure for different types of physical problems in later chapters.

There is so much to be learned, so much we don’t know about the intersections between language, aging, and dementia (the loss of cognitive functioning). The study of language and aging itself is relatively new. In the late 1980s, Kemper and Anagnopoulos called for the study of communicative competence across the lifespan, including how older persons disclose “autobiographical reminiscences,” interact intergenerationally, and how family members and caregivers talk with disabled older adults (1989, p. 42). If we were to compare two state-of-the-art articles by Heidi Hamilton a little over fifteen years apart (Hamilton, 1999; Hamilton & Hamaguchi, 2015) we would find that they identify key differences in the study of language and aging, such as the rise of interest in their social components. However, the commonalities, the huge areas where we know very little, remain uncharted. In 1999, Hamilton identified three key areas: “the use of language for reflecting and creating identities; and how discourse can reflect the norms, values and practices of society [… and] the decline, preservation or improvement of abilities in old age” (cf. Davis & Maclagan, 2016, p. 221). By 2014, studies were blossoming about cognitive aging, social identities, communicative relationships, and what old age might be (Hamilton & Hamaguchi, 2015, p. 706). These studies open the door to new research, new questions, and new applications.

Meshing is a process of discretizing a computational domain into a set of discrete elements with simple geometries. The non-overlapping elements combined represent the geometry of a computational domain. In addition, the elements are the small volumes where the physical quantities are approximated using simple mathematical functions, and the mesh of the elements ensures that the functions are stitched together piece by piece. Depending on the characteristics of the geometry and the type of the physical problem, the computational domains and elements can be categorized into 1-D, 2-D, and 3-D types. In this chapter, we first introduce some of the basic modeling and meshing concepts and techniques for different types of computational domains. Next, we focus on 2-D domains and describe in detail the modeling method of planar straight- line graphs and the meshing approach of Delaunay triangulation, and refinement for generating 2-D meshes of triangular elements.