Lego Universe Impressions: The Next Step In Lego Building – Lego universe impressions – Gizmodo
There are two components of the game that are pretty tightly interweaved: the more traditional MMO portions where you use your skills and interact with other players to achieve goals and defeat monsters, and the building bit, where you have your own territory and can build anything you want out of Lego pieces.
Since everyone’s more interested about the building part, we’ll cover that first. Lego says you have access to pretty much every part they have, from many of the unique Lego sets over the years (pirates, space, etc.). You have your own “home” area that you can build castles or whatever inside, invite your friends to visit and customize however you like. You can also assign behaviors and actions to what you build as well, by dragging and dropping actions onto easily-connectible UI segments
15 House Plants You Can Use As Air Purifiers
Common name Scientific name Score
1 Areca palm Chrysalidocarpus lutescens 8.5
2 Lady palm Rhapis excelsa 8.5
3 Bamboo palm Chamaedorea seifrizii 8.4
4 Rubber plant Ficus robusta 8.0
5 Dracaena “Janet Craig” Dracaena deremensis “Janet Craig” 7.8
6 English ivy Hedera helix 7.8
7 Dwarf date palm Phoenix roebelinii 7.8
8 Ficus Alii Ficus macleilandii “Alii” 7.7
9 Boston fern Nephrolepis exalta “Bostoniensis” 7.5
10 Peace lily Spathiphyllum sp. 7.5
Technology Review: Graphene Transistors that Can Work at Blistering Speeds
In theory, graphene has the material properties needed to let transistors run at terahertz speeds at room temperature.
The IBM researchers grew the graphene on the surface of a two-inch silicon-carbide wafer. The process starts when they heat the wafer until the silicon evaporates, leaving behind a thin layer of carbon, known as epitaxial graphene. This technique has been used to make transistors before, but the IBM team improved the process by using better materials for the other parts of the transistor, in particular the insulator.
PLoS Biology: Evolution of Adaptive Behaviour in Robots by Means of Darwinian Selection
In this essay we will examine key experiments that illustrate how, for example, robots whose genes are translated into simple neural networks can evolve the ability to navigate, escape predators, coadapt brains and body morphologies, and cooperate. We present mostly—but not only—experimental results performed in our laboratory, which satisfy the following criteria. First, the experiments were at least partly carried out with real robots, allowing us to present a video showing the behaviours of the evolved robots. Second, the robot’s neural networks had a simple architecture with no synaptic plasticity, no ontogenetic development, and no detailed modelling of ion channels and spike transmission. Third, the genomes were directly mapped into the neural network (i.e., no gene-to-gene interaction, time-dependent dynamics, or ontogenetic plasticity). By limiting our analysis to these studies we are able to highlight the strength of the process of Darwinian selection in comparable simple systems exposed to different environmental conditions.