Many of us tend to think of the Internet, and most other networks, as inherently client-server systems. Web developers spend a lot of time building powerful sites that serve information and services to the thousands of browser clients that visit them. But peer-to-peer (P2P) applications like KaZaA, Napster, and SETI have demonstrated the true power of the Internet: the millions of information stores—common PCs—sitting idle on desks around the world. Peer-to-peer technologies harness the CPUs and storage devices of these PCs to produce huge data stores, communications systems, and processing engines.
Due to a lack of standards and toolkits, early P2P application developers spent much of their time reinventing the wheel building the same system “plumbing” for each new app they wrote. Developers at Sun created the JXTA specification to solve this problem. The specification is a basic building block from which developers can produce applications that.
Humanity’s interactions with the supporting environment are, to state the obvious, complex. Humanity’s industrial activities effect the environment over time and space, and the same activities even produce different results in different locations. Since the complexities of these interactions may preclude the successful use of eco-performance metrics, humanity may need a means of informing environmental management decisions that accounts for changes with time, spatial patterns and local uniqueness.
The objective of this effort is to interface engineering and ecological systems models to better estimate environmental impacts by modeling the dynamic, spatially explicit and location dependent changes caused by industrial activities. Building upon previously developed, dynamic, spatially explicit, location specific ecosystem modeling software, a technical framework for estimating the impacts of industrial systems in ecosystems is developed. Ecological disturbances endemic to engineering systems are integrated into these existing ecosystem models.
Although the media is often modeled as a faceless institution, its main output news content is generated by specific people. This is important because unlike, say, making tires or processing paper, writing is a fiercely individualistic craft that allows the author’s style, persuasion, views, or bias to be injected into the finished product. In this paper, we present direct evidence that the writing of specific journalists has a casual effect on aggregate market outcomes.
