Adaptive Parallel Iterative Deepening Search

Many of the artificial intelligence techniques developed to date rely on heuristic search through large spaces. Unfortunately, the size of these spaces and the corresponding computational effort reduce the applicability of otherwise novel and effective algorithms. A number of parallel and distributed approaches to search have considerably improved the performance of the search process. Our goal is to develop an architecture that automatically selects parallel search strategies for optimal performance on a variety of search problems. In this paper we describe one such architecture realized in the Eureka system, which combines the benefits of many different approaches to parallel heuristic search. Through empirical and theoretical analyses we observe that features of the problem space directly affect the choice of optimal parallel search strategy. We then employ machine learning techniques to select the optimal parallel search strategy for a given problem space. When a new search task is input to the system, Eureka uses features describing the search space and the chosen architecture to automatically select the appropriate search strategy. Eureka has been tested on a MIMD parallel processor, a distributed network of workstations, and a single workstation using multithreading. Results generated from fifteen puzzle problems, robot arm motion problems, artificial search spaces, and planning problems indicate that Eureka outperforms any of the tested strategies used exclusively for all problem instances and is able to greatly reduce the search time for these applications

Nicotinic α7 acetylcholine receptor-mediated currents are not modulated by the tryptophan metabolite kynurenic acid in adult hippocampal interneurons

The  tryptophan  metabolite,  kynurenic  acid (KYNA),  is  classically  known  to  be  an antagonist  of ionotropic glutamate receptors. Within the last decade several reports have been published suggesting that KYNA also blocks nicotinic acetylcholine receptors (nAChRs) containing the α7 subunit (α7*). Most of these reports involve either indirect measurements of KYNA effects on α7 nAChR function, or are reports of KYNA effects in complicated in vivo systems.  However, a recent report investigating KYNA interactions with α7 nAChRs failed to detect an interaction using direct measurements of α7 nAChRs function.  Further, it showed that a KYNA blockade of α7 nAChR stimulated GABA release (an indirect measure of α7 nAChR function) was not due to KYNA blockade of the α7 nAChRs. The current study measured the direct effects of KYNA on α7-containing nAChRs expressed on interneurons in the hilar and CA1 stratum radiatum regions of the mouse hippocampus and on interneurons in the CA1 region of the rat hippocampus.  Here we show that KYNA does not block α7* nACHRs using direct patch-­clamp recording of α7 currents in adult brain slices

An Assessment of Wildlife Utilization between a Man-made Marsh, an Adjacent Natural Marsh, and a Nearby Natural Marsh in Virginia

The present study investigates the functions and values of man-made and natural tidal wetlands. The study is among the first to use simultaneous sampling techniques to investigate animal use preference between man-made and adjacent natural tidal wetlands

The TIGRE gamma-ray telescope

TIGRE is an advanced telescope for gamma-ray astronomy with a few arcmin resolution. From 0.3 to 10 MeV it is a Compton telescope. Above 1 MeV, its multi-layers of double sided silicon strip detectors allow for Compton recoil electron tracking and the unique determination for incident photon direction. From 10 to 100 MeV the tracking feature is utilized for gamma-ray pair event reconstruction. Here we present TIGRE energy resolutions, background simulations and the development of the electronics readout system

An Analysis of Musculoskeletal Variables, Comparative to Team Norms, Leading to an ACL Rupture

Please refer to the pdf version of the abstract located adjacent to the title

Cluster randomised trials in the medical literature: two bibliometric surveys

Background: Several reviews of published cluster randomised trials have reported that about half did not take clustering into account in the analysis, which was thus incorrect and potentially misleading. In this paper I ask whether cluster randomised trials are increasing in both number and quality of reporting. Methods: Computer search for papers on cluster randomised trials since 1980, hand search of trial reports published in selected volumes of the British Medical Journal over 20 years. Results: There has been a large increase in the numbers of methodological papers and of trial reports using the term 'cluster random' in recent years, with about equal numbers of each type of paper. The British Medical Journal contained more such reports than any other journal. In this journal there was a corresponding increase over time in the number of trials where subjects were randomised in clusters. In 2003 all reports showed awareness of the need to allow for clustering in the analysis. In 1993 and before clustering was ignored in most such trials. Conclusion: Cluster trials are becoming more frequent and reporting is of higher quality. Perhaps statistician pressure works