The validity of psychophysiological detection of information with the Guilty Knowledge Test: A meta-analytic review.

The authors performed a meta-analysis based on 169 conditions, gathered from 80 laboratory studies, to estimate the validity of the Guilty Knowledge Test (GKT) with the electrodermal measure. The over-all average effect size was 1.55, but there were considerable variations among studies. In particular, mock-crime studies produced the highest average effect size (2.09). Three additional moderators, were identified: Motivational instructions, deceptive ("no") verbal responses, and the use of at least 5 questions were associated with enhanced validity. Finally, a set of 10 studies that best approximated applications of the GKT under optimal conditions produced an average effect size of 3.12. The authors discuss factors that might limit the generalizability of these results and recommend further research of the GKT in realistic setups. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Quantum-mechanical reaction rate constants from centroid molecular dynamics simulations: Barrier crossing in an asymmetrical double-well

Quantum-mechanical reaction rate constants were calculated from centroid molecular dynamics (CMD) simulations, for the case of barrier crossing in an asymmetrical double-well potential bilinearly coupled to a harmonic bath. The calculation is based on a recently proposed formulation of the reaction rate constant in terms of the position—flux correlation function, which can be approximated via CMD in a well-defined manner. The predictions of CMD and various simplified versions of it are compared to exact results, which were obtained via the quasi-adiabatic propagator path integral (QUAPI) method, and/or path integral quantum transition state theory (PI-QTST). The predictions based on CMD are found to be in good agreement with both.     

Discrete quadratic curvature energies

We present a family of discrete isometric bending models (IBMs) for triangulated surfaces in 3-space. These models are derived from an axiomatic treatment of discrete Laplace operators, using these operators to obtain linear models for discrete mean curvature from which bending energies are assembled. Under the assumption of isometric surface deformations we show that these energies are quadratic in surface positions. The corresponding linear energy gradients and constant energy Hessians constitute an efficient model for computing bending forces and their derivatives, enabling fast time-integration of cloth dynamics with a two- to three-fold net speedup over existing nonlinear methods, and near-interactive rates for Willmore smoothing of large meshes.     

Cortical cholinergic impairment and behavioral deficits produced by kainic acid lesions of rat magnocellular basal forebrain.

The rat magnocellular basal forebrain (MNBF) is homologous to the human nucleus basalis of Meynert, a structure implicated in the cholinergic hypothesis of cognitive impairment in Alzheimer's disease (AD). In the present study, 18 male Sprague-Dawley rats with kainic acid lesions in the MNBF were compared with 6 unoperated controls, 10 sham-operated controls, and 6 controls injected with kainic acid in the cortical area directly above the MNBF. MNBF lesions depleted choline acetyltransferase in cortex but not in striatum or hippocampus. Cortical dopamine levels were unchanged; serotonin levels were unchanged in hippocampus and parietal cortex but decreased in frontal cortex. Compared with controls, MNBF-lesioned Ss were impaired in 24-hr retention, but not acquisition, of a passive avoidance task with escapable footshock. The groups did not differ in mean number of daily avoidances on a barpress active avoidance task, although learning was slower in MNBF-lesioned Ss. In a serial spatial discrimination reversal test, MNBF-lesioned Ss performed significantly worse than controls. This model may be useful for studying the role of the cholinergic system in memory and possibly for developing treatment strategies to alleviate the cognitive dysfunction of AD. (63 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Reducing Query Latencies in Web Search Using Fine-Grained Parallelism

Semantic Web search is a new application of recent advances in information retrieval (IR), natural language processing, artificial intelligence, and other fields. The Powerset group in Microsoft develops a semantic search engine that aims to answer queries not only by matching keywords, but by actually matching meaning in queries to meaning in Web documents. Compared to typical keyword search, semantic search can pose additional engineering challenges for the back-end and infrastructure designs. Of these, the main challenge addressed in this paper is how to lower query latencies to acceptable, interactive levels. Index-based semantic search requires more data processing, such as numerous synonyms, hypernyms, multiple linguistic readings, and other semantic information, both on queries and in the index. In addition, some of the algorithms can be super-linear, such as matching co-references across a document. Consequently, many semantic queries can run significantly slower than the same keyword query. Users, however, have grown to expect Web search engines to provide near-instantaneous results, and a slow search engine could be deemed unusable even if it provides highly relevant results. It is therefore imperative for any search engine to meet its users’ interactivity expectations, or risk losing them. Our approach to tackle this challenge is to exploit data parallelism in slow search queries to reduce their latency in multi-core systems. Although all search engines are designed to exploit parallelism, at the single-node level this usually translates to throughput-oriented task parallelism. This paper focuses on the engineering of two latency-oriented approaches (coarse- and fine-grained) and compares them to the task-parallel approach. We use Powerset’s deployed search engine to evaluate the various factors that affect parallel performance: workload, overhead, load balancing, and resource contention. We also discuss heuristics to selectively control the degree of parallelism and consequent overhead on a query-by-query level. Our experimental results show that using fine-grained parallelism with these dynamic heuristics can significantly reduce query latencies compared to fixed, coarse-granularity parallelization schemes. Although these results were obtained on, and optimized for, Powerset’s semantic search, they can be readily generalized to a wide class of inverted-index search engines.     

3D Printing Thermally Stable High-Performance Polymers Based on a Dual Curing Mechanism

High-performance polymers are an important class of materials that are used in challenging conditions, such as in aerospace applications. Until now, 3D printing based on stereolithography processes can not be performed due to a lack of suitable materials. There is report on new materials and printing compositions that enable 3D printing of objects having extremely high thermal resistance, with Tg of 283 °C and excellent mechanical properties. The printing is performed by a low-cost Digital Light Processing printer, and the formulation is based on a dual-cure mechanism, photo, and thermal process. The main components are a molecule that has both epoxy and acrylate groups, alkylated melamine that enables a high degree of crosslinking, and a soluble precursor of silica. The resulting objects are made of hybrid materials, in which the silicon is present in the polymeric backbone and partly as silica enforcement particles.     

Semi-linear Stochastic Difference Equations

We consider in this paper a class of vector valued processes that have the form Y _n + 1 = A _n ( Y _n ) + B _n . B _n is assumed to be stationary ergodic and A _n is assumed to have a divisibility property. This class includes linear stochastic difference equations as well as multi-type branching processes (with a discrete or with a continuous state space). We derive explicit expressions for the probability distribution as well as for the two first moments of state vectors at the stationary regime. We then apply this approach to derive two formalisms to describe the infinite server queue. The first is based on a branching process approach adapted to phase type service time distributions. The second is based on a linear stochastic difference equation and is adapted to independent and generally distributed service times with bounded support. In both cases we allow for generally distributed arrival process (not necessarily i.i.d. nor Markovian).

Fat-tree routing and node ordering providing contention free traffic for MPI global collectives

As the size of High Performance Computing clusters grows, so does the probability of interconnect hot spots that degrade the latency and effective bandwidth the network provides. This paper presents a solution to this scalability problem for real life constant bisectional-bandwidth fat-tree topologies. It is shown that maximal bandwidth and cut-through latency can be achieved for MPI global collective traffic. To form such a congestion-free configuration, MPI programs should utilize collective communication, MPI-node-order should be topology aware, and the packet routing should match the MPI communication patterns. First, we show that MPI collectives can be classified into unidirectional and bidirectional shifts. Using this property, we propose a scheme for congestion-free routing of the global collectives in fully and partially populated fat trees running a single job. The no-contention result is then obtained for multiple jobs running on the same fat-tree by applying some job size and placement restrictions. Simulation results of the proposed routing, MPI-node-order and communication patterns show no contention which provides a 40% throughput improvement over previously published results for all-to-all collectives.     

Feature‐Preserving Surface Completion Using Four Points

We present a user‐guided, semi‐automatic approach to completing large holes in a mesh. The reconstruction of the missing features in such holes is usually ambiguous. Thus, unsupervised methods may produce unsatisfactory results. To overcome this problem, we let the user indicate constraints by providing merely four points per important feature curve on the mesh. Our algorithm regards this input as an indication of an important broken feature curve. Our completion is formulated as a global energy minimization problem, with user‐defined spatial‐coherence constraints, allows for completion that adheres to the existing features. We demonstrate the method on example problems that are not handled satisfactorily by fully automatic methods.