nl is a python library, that exposes a declarative API that allows us to build sentences and rules. These are used as input for a knowledge base built on the CLIPS production system. CLIPS builds a Rete network with the rules and sentences, which can then be queried for the consecuences of those in a most efficient way.

The main claim of nl is to offer a syntax that can accommodate any coherent theory that we may build with the natural language (in the same sense as something like the semantic web's OWL-Full would), while at the same time being based on a simple finite domain first order theory. This theory is NL, a discussion of which can be found here. This discussion is probably required reading to understand the breadth and the limits of nl, but not to start using it.

Natural Earth is a public domain map dataset available at 1:10m, 1:50m, and 1:110m scales. Featuring tightly integrated vector and raster data, with Natural Earth you can make a variety of visually pleasing, well-crafted maps with cartography or GIS software.

Well, most of the work is done by Earthdesk and GeekTool 3.

Earthdesk is set to Natural Color, Equirectangular projection, Natural Color, Real Moonlight, centered on Vienna, Background: Starfield. Zoom 80%, Clouds 80%, Brightness 80%.

In GeekTool, the times and the weathers are all separate Shell "geeklets".

Times are generated by running shell commands like

env TZ=Asia/Tokyo date " %l:%M %p"

every 20 seconds

The weather is the tricky part. The way I am doing it now, if I am not careful, gets me throttled for too many concurrent requests to the wunderground.com API server. It also fails badly if I am disconnected, so I will need to do it differently.

FWIW: I have a PHP script which I run as separate Shell Geeklets. I invoke it with the name of the city I want. It then hits wunderground and gets back an XML stream of the local weather, which I parse, format and echo. (the way I'd change this is run the script from cron, with a 30 second wait between requests, and cache the results locally, which I would then call from the Shell Geeklets)

From there it's just a question of setting fonts, sizes, colors and moving the little Geeklet boxes around as you want them.

Since I cannot tell you the final truth about the roots of the Finnish people, I shall tell you about the search for those roots. It is only natural that we search for our beginnings and use those beginnings to construct our identity. But why do we look to roots for our identity? This is the question I shall try to answer. I will use scientific and other public discourse as my material.

Waste is part of life. Human and animal bodies produce natural waste, whereas societies produce synthetic waste. While we cannot control the level of natural waste as its production is an organic part of biological survival, we can drastically reduce the production of synthetic waste. Natural and synthetic waste come in two varieties - reusable and nonreusable. The aim of a sustainable waste economy is to reuse as much waste as possible, even to the point of reducing waste surplus to zero.

This book offers a highly accessible introduction to Natural Language Processing, the field that underpins a variety of language technologies ranging from predictive text and email filtering to automatic summarization and translation. You'll learn how to write Python programs to analyze the structure and meaning of texts, drawing on techniques from the fields of linguistics and artificial intelligence.

According to the US Department of Energy (Energy Information Administration), the world consumption of energy in all of its forms (barrels of petroleum, cubic meters of natural gas, watts of hydro power, etc.) is projected to reach 678 quadrillion Btu (or 7.15 exajoules) by 2030 – a 44% increase over 2008 levels (levels for 1980 were 283 quadrillion Btu and we stand at around 500 quadrillion Btu today).

I've never liked the term "computer science." The main reason I don't like it is that there's no such thing. Computer science is a grab bag of tenuously related areas thrown together by an accident of history, like Yugoslavia. At one end you have people who are really mathematicians, but call what they're doing computer science so they can get DARPA grants. In the middle you have people working on something like the natural history of computers-- studying the behavior of algorithms for routing data through networks, for example. And then at the other extreme you have the hackers, who are trying to write interesting software, and for whom computers are just a medium of expression, as concrete is for architects or paint for painters.