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By means of two-stage, nonlinear multivariate pattern recognition, electroencephalograms (EEG's) were analyzed during performance of verbal and spatial tasks. Complex scalp distributions of theta-, beta-, and, to a lesser extent, alpha-band spectral intensities discriminated between the two members of a pair of tasks, such as writing sentences and Koh's block design. Small EEG asymmetries were probably attributable to limb movements and other uncontrolled noncognitive aspects of tasks. Significant EEG differences beteeen cognitive tasks were eliminated when controls for inter-task differences in efferent activity, stimulus characteristics, and performance-related factors were introduced. Each controlled task was associated with an approximately 10 percent reduction, as compared with visual fixation, in the magnitude of alpha- and beta-band spectral intensity. This effect occurred bilaterally and was approximately the same over occipital, parietal, and central regions, with some minor difference over the frontal region in the beta band. With these controls, no evidence for lateralization of different cognitive functions was found in the EEG.

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In seven right-handed adults, the brain electrical patterns before accurate performance differed from the patterns before inaccurate performance. Activity overlying the left frontal cortex and the motor and parietal cortices contralateral to the performing hand preceded accurate left- or right-hand performance. Additional strong activity overlying midline motor and premotor cortices preceded left-hand performance. These measurements suggest that brief, spatially distributed neural activity patterns, or "preparatory sets," in distinct cognitive, somesthetic-motor, and integrative motor areas of the human brain may be essential precursors of accurate visuomotor performance.

Abstract-Large public cloud infrastructure can utilise power which is generated by a multiplicity of power plants. The cost of electricity will vary among the power plants and each will emit different amounts of carbon for a given amount of energy generated. This infrastructure services traffic that can come from anywhere on the planet. It is desirable, for latency purposes, to route the traffic to the data centre that is closest in terms of geographical distance, costs the least to power and emits the smallest amount of carbon for a given request. It is not always possible to achieve all of these goals so we model both the networking and computational components of the infrastructure as a graph and propose the Stratus system which utilises Voronoi partitions to determine which data centre requests should be routed to based on the relative priorities of the cloud operator.