Using three-dimensional microfluidic networks for solving computationally hard problems

This paper describes the design of a parallel algorithm that uses moving fluids in a three-dimensional microfluidic system to solve a nondeterministically polynomial complete problem (the maximal clique problem) in polynomial time. This algorithm relies on (i) parallel fabrication of the microfluidic system, (ii) parallel searching of all potential solutions by using fluid flow, and (iii) parallel optical readout of all solutions. This algorithm was implemented to solve the maximal clique problem for a simple graph with six vertices. The successful implementation of this algorithm to compute solutions for small-size graphs with fluids in microchannels is not useful, per se, but does suggest broader application for microfluidics in computation and control.

CA1-specific N-methyl-d-aspartate receptor knockout mice are deficient in solving a nonspatial transverse patterning task

In both humans and animals, the hippocampus is critical to memory across modalities of information (e.g., spatial and nonspatial memory) and plays a critical role in the organization and flexible expression of memories. Recent studies have advanced our understanding of cellular basis of hippocampal function, showing that N-methyl-d-aspartate (NMDA) receptors in area CA1 are required in both the spatial and nonspatial domains of learning. Here we examined whether CA1 NMDA receptors are specifically required for the acquisition and flexible expression of nonspatial memory. Mice lacking CA1 NMDA receptors were impaired in solving a transverse patterning problem that required the simultaneous acquisition of three overlapping odor discriminations, and their impairment was related to an abnormal strategy by which they failed to adequately sample and compare the critical odor stimuli. By contrast, they performed normally, and used normal stimulus sampling strategies, in the concurrent learning of three nonoverlapping concurrent odor discriminations. These results suggest that CA1 NMDA receptors play a crucial role in the encoding and flexible expression of stimulus relations in nonspatial memory.

The roles of language processing in a spoken language interface.

This paper provides an overview of the colloquium's discussion session on natural language understanding, which followed presentations by M. Bates [Bates, M. (1995) Proc. Natl. Acad. Sci. USA 92, 9977-9982] and R. C. Moore [Moore, R. C. (1995) Proc. Natl. Acad. Sci. USA 92, 9983-9988]. The paper reviews the dual role of language processing in providing understanding of the spoken input and an additional source of constraint in the recognition process. To date, language processing has successfully provided understanding but has provided only limited (and computationally expensive) constraint. As a result, most current systems use a loosely coupled, unidirectional interface, such as N-best or a word network, with natural language constraints as a postprocess, to filter or resort the recognizer output. However, the level of discourse context provides significant constraint on what people can talk about and how things can be referred to; when the system becomes an active participant, it can influence this order. But sources of discourse constraint have not been extensively explored, in part because these effects can only be seen by studying systems in the context of their use in interactive problem solving. This paper argues that we need to study interactive systems to understand what kinds of applications are appropriate for the current state of technology and how the technology can move from the laboratory toward real applications.