A PET study of the neural systems of stuttering

The cause of stuttering is unknown. Failure to develop left-hemispheric dominance for speech is a long-standing theory although others implicated the motor system more broadly, often postulating hyperactivity of the right (language nondominant) cerebral hemisphere. As knowledge of motor circuitry has advanced, theories of stuttering have become more anatomically specific, postulating hyperactivity of premotor cortex, either directly or through connectivity with the thalamus and basal ganglia. Alternative theories target the auditory and speech production systems. By contrasting stuttering with fluent speech using positron emission tomography combined with chorus reading to induce fluency, we found support for each of these hypotheses. Stuttering induced widespread overactivations of the motor system in both cerebrum and cerebellum, with right cerebral dominance. Stuttered reading lacked left-lateralized activations of the auditory system, which are thought to support the self-monitoring of speech, and selectively deactivated a frontal-temporal system implicated in speech production. Induced fluency decreased or eliminated the overactivity in most motor areas, and largely reversed the auditory-system underactivations and the deactivation of the speech production system. Thus stuttering is a disorder affecting the multiple neural systems used for speaking.     

Activated partial thromboplastin time and outcome after thrombolytic therapy for acute myocardial infarction: results from the GUSTO-I trial

BACKGROUND: Although intravenous heparin is commonly used after thrombolytic therapy, few reports have addressed the relationship between the degree of anticoagulation and clinical outcomes. We examined the activated partial thromboplastin time (aPTT) in 29,656 patients in the Global Utilization of Streptokinase and t-PA for Occluded Coronary Arteries (GUSTO-I) trial and analyzed the relationship between the aPTT and both baseline patient characteristics and clinical outcomes. METHODS AND RESULTS: Intravenous heparin was administered as a 5000-U bolus followed by an initial infusion of 1000 U/h, with dose adjustment to achieve a target aPTT of 60 to 85 seconds. aPTTs were collected 6, 12, and 24 hours after thrombolytic administration. Higher aPTT at 24 hours was strongly related to lower patient weight (P < .00001) as well as older age, female sex, and lack of cigarette smoking (all PT< .0001). At 12 hours, the aPTT associated with the lowest 30-day mortality, stroke, and bleeding rates was 50 to 70 seconds. There was an unexpected direct relationship between the aPTT and the risk of subsequent reinfarction. There was a clustering of reinfarction in the first 10 hours after discontinuation of intravenous heparin. CONCLUSIONS: Although the relationship between aPTT and clinical outcome was confounded to some degree by the influence of baseline prognostic characteristics, aPTTs higher than 70 seconds were found to be associated with higher likelihood of mortality, stroke, bleeding, and reinfarction. These findings suggest that until proven otherwise, we should consider the aPTT range of 50 to 70 seconds as optimal with intravenous heparin after thrombolytic therapy.     

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.     

Nodes on ropes: a comprehensive data and control flow for steering ensemble simulations

Flood disasters are the most common natural risk and tremendous efforts are spent to improve their simulation and management. However, simulation-based investigation of actions that can be taken in case of flood emergencies is rarely done. This is in part due to the lack of a comprehensive framework which integrates and facilitates these efforts. In this paper, we tackle several problems which are related to steering a flood simulation. One issue is related to uncertainty. We need to account for uncertain knowledge about the environment, such as levee-breach locations. Furthermore, the steering process has to reveal how these uncertainties in the boundary conditions affect the confidence in the simulation outcome. Another important problem is that the simulation setup is often hidden in a black-box. We expose system internals and show that simulation steering can be comprehensible at the same time. This is important because the domain expert needs to be able to modify the simulation setup in order to include local knowledge and experience. In the proposed solution, users steer parameter studies through the World Lines interface to account for input uncertainties. The transport of steering information to the underlying data-flow components is handled by a novel meta-flow. The meta-flow is an extension to a standard data-flow network, comprising additional nodes and ropes to abstract parameter control. The meta-flow has a visual representation to inform the user about which control operations happen. Finally, we present the idea to use the data-flow diagram itself for visualizing steering information and simulation results. We discuss a case-study in collaboration with a domain expert who proposes different actions to protect a virtual city from imminent flooding. The key to choosing the best response strategy is the ability to compare different regions of the parameter space while retaining an understanding of what is happening inside the data-flow system.     

Correspondence of projected 3‐D points and lines using a continuous GRASP

The field of computer vision has experienced rapid growth over the past 50 years. Many computer vision problems have been solved using theory and ideas from algebraic projective geometry. In this paper, we look at a previously unsolved problem from object recognition, namely object recognition when the correspondences between the object and image data are not known a priori. We formulate this problem as a mixed‐integer non‐linear optimization problem in terms of the unknown projection relating the object and image, as well as the unknown assignments of object points and lines to those in the image. The global optimum of this problem recovers the relationship between the object points and lines with those in the image. When certain assumptions are enforced on the allowable projections mapping the object into the image, a proof is provided which permits one to solve the optimization problem via a simple decomposition. We illustrate this decomposition approach on some example scenarios.