-regulation made people more passive (i.e., more prone to favor the passive-response option). These results suggest that the self's capacity for active volition is limited and that a range of seemingly different, unrelated acts share a common resource. Many crucial functions of the self involve volition

If self-regulation conforms to an energy or strength model, then self-control should be impaired by prior exertion. In Study 1, trying to regulate one's emotional response to an upsetting movie was followed by a decrease in physical stamina. In Study 2, suppressing forbidden thoughts led to a subsequent tendency to give up quickly on unsolvable anagrams. In Study 3, suppressing thoughts impaired subsequent efforts to control the expression of amusement and enjoyment. In Study 4, autobiographical accounts of successful versus failed emotional control linked prior regulatory de-mands and fatigue to self-regulatory failure. A strength model of self-regulation fits the data better than activation, priming, skill, or constant capacity models of self-regulation. The capacity of the human organism to override, interrupt, and otherwise alter its own responses is one of the most dramatic and impressive functions of human selfhood, with broad impli-cations for a wide range of behavior patterns (Carver & Scheier, 1981; Wegner & Pennebaker, 1993). For example, self-regula-tion has been associated with crime and criminal behavior (Gott-fredson & Hirschi, 1990), smoking (Russell, 1971), and dieting

sustained competitive advantage, all of which must be met. These include superior resources (heterogeneity within an industry), ex post limits to competition, imperfect resource mobility, and ex ante limits to competition. In the concluding section, applications of the model for both single business

We describe an operating system architecture that securely multiplexes machine resources while permitting an unprecedented degree of application-specific customization of traditional operating system abstractions. By abstracting physical hardware resources, traditional operating systems have

Composed of tens of thousands of tiny devices with very limited resources ("motes"), sensor networks are subject to novel systems problems and constraints. The large number of motes in a sensor network means that there will often be some failing nodes; networks must be easy to repopu

The highly successful architecture and protocols of today’s Internet may operate poorly in environments characterized by very long delay paths and frequent network partitions. These problems are exacerbated by end nodes with limited power or memory resources. Often deployed in mobile and extreme

and very limited energy resource at every node; this leads to scalability requirements while limiting the resources that can be used to achieve them. A new approach to time synchronization is needed for sensor networks.

of limited computational resources, and assuming communication-computation overlap. In particular, under some reasonable assumptions, we derive the optimal mapping and scheduling of tiles to physical processors.

succeeds only when networks begin with limited working memory and gradually ‘mature ’ to the adult state. This result suggests that rather than being a limitation, developmental restrictions on resources may constitute a necessary prerequisite for mastering certain complex domains. Specifically, successful

tend to be conservative in their security guarantees, typically adding 16–32 bytes of overhead. With small memories, weak processors, limited energy, and 30 byte packets, sensor networks cannot afford this luxury. TinySec addresses these extreme resource constraints with careful design; we explore