The focus of this chapter is on neurobiologically informed and constrained models of working memory as defined by Miller, Galanter, and Pribram (1960): the holding of goals and subgoals in mind in service of planning and executing complex behaviors. In particular, the chapter focuses on models specifically addressing critical challenges and mechanisms following from the need for rapid and selective gating of working memory contents. To start, the important computational challenges posed by the tradeoff between maintaining vs. updating are discussed, providing motivation for the rest of the chapter.After that, several seminal models that have contributed to current thinking are reviewed, including the authors’ own PBWM framework that has proven influential. Finally, several recent developments from the deep learning and neurophysiology literatures are addressed and critical questions and some directions for future progress are discussed.

The Horus and other research teams have found that atherosclerosis is not uncommon in ancient people through the study of their mummified remains (Murphy et al., 2003; Allam et al., 2009, 2011; Thompson et al., 2013, 2014). However, some have postulated that traditional hunter-gatherers are in some ways healthier than modern people and that they had very little atherosclerotic disease (O’Keefe et al., 2010).

During the first decade and a half of the development of the systems ecology paradigm (SEP) most research efforts were placed on learning about how the biophysical realms of ecosystems function and how simulation models could aid gaining that understanding. Missing from that research were the obvious connections of humans as components of ecosystems, not simply as controllers. In 1981 the US National Science Foundation (NSF) Programs Ecosystems Studies and Anthropology funded the South Turkana Ecosystem Project. It was the first time that an ecosystem study had included the human component as a full actor in an ecosystem. The NSF has since created the Dynamics of Coupled Natural and Human Systems program, the sole purpose of which is to fund these types of projects. The human side of SEP has grown in other directions as well including, agro-ecosystem ecology, understanding ecosystem services and effects of land fragmentation, Citizen Science, and providing guidance to the management of natural and human-dominated systems and the improvement of human welfare. Ongoing research has led to the realization that the human residents of the ecosystems under study can engage with research scientists to co-create knowledge about the operation of their own systems.

Ecosystem modeling, a pillar of the systems ecology paradigm (SEP), addresses questions such as, how much carbon and nitrogen are cycled within ecological sites, landscapes, or indeed the earth system? Or how are human activities modifying these flows? Modeling, when coupled with field and laboratory studies, represents the essence of the SEP in that they embody accumulated knowledge and generate hypotheses to test understanding of ecosystem processes and behavior. Initially, ecosystem models were primarily used to improve our understanding about how biophysical aspects of ecosystems operate. However, current ecosystem models are widely used to make accurate predictions about how large-scale phenomena such as climate change and management practices impact ecosystem dynamics and assess potential effects of these changes on economic activity and policy making. In sum, ecosystem models embedded in the SEP remain our best mechanism to integrate diverse types of knowledge regarding how the earth system functions and to make quantitative predictions that can be confronted with observations of reality. Modeling efforts discussed are the Century ecosystem model, DayCent ecosystem model, Grassland Ecosystem Model ELM, food web models, Savanna model, agent-based and coupled systems modeling, and Bayesian modeling.

Fundamental knowledge about the processes that control the functioning of the biophysical workings of ecosystems has expanded exponentially since the late 1960s. Scientists, then, had only primitive knowledge about C, N, P, S, and H2O cycles; plant, animal, and soil microbialinteractions and dynamics; and land, atmosphere, and water interactions. With the advent of systems ecology paradigm (SEP) and the explosion of technologies supporting field and laboratory research, scientists throughout the world were able to assemble the knowledge base known today as ecosystem science. This chapter describes, through the eyes of scientists associated with the Natural Resource Ecology Laboratory (NREL) at Colorado State University (CSU), the evolution of the SEP in discovering how biophysical systems at small scales (ecological sites, landscapes) function as systems. The NREL and CSU are epicenters of the development of ecosystem science. Later, that knowledge, including humans as components of ecosystems, has been applied to small regions, regions, and the globe. Many research results that have formed the foundation for ecosystem science and management of natural resources, terrestrial environments, and its waters are described in this chapter. Throughout are direct and implicit references to the vital collaborations with the global network of ecosystem scientists.

Introduction

The perspectives of older people on dignity in care have been largely overlooked in British policies, and the tendency has been to look at ways in which care providers should ‘deliver dignity’ by reference to agreed standards. For example, the Dignity Challenge developed in 2006 identified 10 dignity tests against which services could be evaluated (Cass et al, 2009). In this project, the research team took the view that a better understanding of dignity in later life was needed, which was informed by the experiences of older people, including, but not limited to, those with experiences as service users.

Four questions shaped the research:

• 1. What preparations do older adults who are facing death at a near but uncertain time make for the process of dying and death?

• 2. What accounts are given about dignity in daily life by older adults during this phase in their life?

• 3. What resources are available to these older adults to draw on?

• 4. What factors are perceived to support or undermine a sense of dignity?

Dignity has both personal and social meanings, and the two are closely interrelated. The theoretical model developed by Nordenfelt (2004) was a valuable starting point for this project, as it takes both into account. It proposes four ‘varieties’ of dignity. First, the dignity of merit refers to the high rank of individuals because of the social role they occupy (the historical meaning of dignity) as well as to dignity earned through socially valued achievements. The dignity of moral stature concerns individual conduct and is linked to self-respect, which is shaped by prevalent cultural values, giving it a social as well as personal meaning. Importantly, this type of dignity also draws attention to the conduct of staff in care services and the impact of this on their dignity and moral stature. The third variety – the dignity of identity – is as Nordenfelt expressed it, ‘the dignity that we attach to ourselves as integrated and autonomous persons’ (2009, p 33). It is evidently challenged in old age by failing health and the loss of capacity for self-care. The dignity of identity also has social as well as personal meaning, exemplified in the institutionalisation of older people and the associated loss of individual identity. The fourth of Nordenfelt's varieties is the dignity of being human.

Introduction

The continued growth of wireless networks and services depends on the availability of adequate spectrum resources. Accelerating demand for those resources, due to the popularity of portable data-intensive wireless devices, are testing the limits of current commercial wireless networks, underscoring the need for changes in current spectrum allocations. This has prompted the Federal Communications Commission (FCC) in the United States to consider ways to increase the supply of spectrum allocated to broadband access and to introduce techniques for improving the utilization of existing allocations [1, Ch. 5].

Spectrum allocations generally fall into one of two categories: a licensed allocation gives exclusive use rights to the licensee, whereas an unlicensed allocation corresponds to the commons model in which the band can be shared by different applications and service providers [2]. Licensed spectrum typically carries restrictions on how it can be used, and is generally not transferable. Although these restrictions have been alleviated to some extent by the introduction of secondary spectrum markets [3], existing rules still inhibit the reallocation of spectrum to more efficient uses.

In contrast to the current “command and control” method for licensing spectrum, a spectrum market is based on a notion of spectrum property rights, which can be traded among buyers and sellers. The potential benefits of spectrum markets for increasing the efficiency of spectrum allocations is widely acknowledged. Thus far related discussions have focused on secondary markets, which allow service providers with licensed spectrum to lease their spectrum to other service providers. Transactions must be filed with the FCC for approval (which are automatic in some scenarios), introducing delays that increase transaction costs [3].

Here we reconsider the spectrum allocation problem without existing regulatory constraints. We start by providing general motivations for introducing spectrum markets. That is, a basic policy choice is whether to define and enforce spectrum property rights. From a social welfare point of view, this choice ultimately depends on whether spectrum is scarce, that is, if demand for it exceeds supply when it is free.