Semantic Externalism and the Mechanics of Thought

I review a widely accepted argument to the conclusion that the contents of our beliefs, desires and other mental states cannot be causally efficacious in a classical computational model of the mind. I reply that this argument rests essentially on an assumption about the nature of neural structure that we have no good scientific reason to accept. I conclude that computationalism is compatible with wide semantic causal efficacy, and suggest how the computational model might be modified to accommodate this possibility.

Computer-Mediated Word-of-Mouth Communication on RateMyProfessors.com: Expectancy Effects on Student Cognitive and Behavioral Learning

The purpose of this study was to experimentally test the influence of expectancies formed through computer-mediated word-of-mouth communication (WOM) on student learning. Increasingly, students rely on computer-mediated WOM through sites such as RateMyProfessors.com to aid in the process of information-gathering and course selection. It was hypothesized that students who received positive computer-mediated WOM about a course would demonstrate greater levels of cognitive and behavioral learning than would students who received no information or negative computer-mediated WOM. Results demonstrated the predicted effects for cognitive and behavioral learning. It was further hypothesized that observed expectancy effects would be mediated by affect toward learning. Results supported a partial mediational role for affect in the context of positive expectancies, but not negative expectancies. Results were discussed in terms of the role of computer-mediated WOM in generating expectations, the expectations-affect-behavior hypothesis, and the influence of student expectations on learning outcomes.     

Detecting Human Behavior Models From Multimodal Observation in a Smart Home

This paper addresses learning and recognition of human behavior models from multimodal observation in a smart home environment. The proposed approach is part of a framework for acquiring a high-level contextual model for human behavior in an augmented environment. A 3-D video tracking system creates and tracks entities (persons) in the scene. Further, a speech activity detector analyzes audio streams coming from head set microphones and determines for each entity, whether the entity speaks or not. An ambient sound detector detects noises in the environment. An individual role detector derives basic activity like ldquowalkingrdquo or ldquointeracting with tablerdquo from the extracted entity properties of the 3-D tracker. From the derived multimodal observations, different situations like ldquoaperitifrdquo or ldquopresentationrdquo are learned and detected using statistical models (HMMs). The objective of the proposed general framework is two-fold: the automatic offline analysis of human behavior recordings and the online detection of learned human behavior models. To evaluate the proposed approach, several multimodal recordings showing different situations have been conducted. The obtained results, in particular for offline analysis, are very good, showing that multimodality as well as multiperson observation generation are beneficial for situation recognition.     

Satellite remote sensing of surface oceanic fronts in coastal waters off west-central Florida

Two algorithms designed to detect deepwater oceanic features and arbitrary edge profiles were tuned to automatically delineate fronts in coastal waters off west-central Florida using satellite-derived sea surface temperature (SST), chlorophyll-a concentration (Chl), normalized water-leaving radiance (nL_w), and fluorescence line height (FLH) images during select periods in the spring and fall of 2004 and 2005. The dates correspond to recreational king mackerel, Scomberomorus cavalla, tournaments. A histogram-based algorithm was useful to detect coastal surface SST, nL_w, and FLH fronts, specifically. A gradient-based algorithm, with a smaller kernel box of 3 × 3 pixels, best identified nearshore (< 10 m depth) features in Chl images at the mouth of Tampa Bay, but was less effective for fronts farther offshore where gradients were weaker. Local winds and tide levels estimated from a coastal observing buoy, and bathymetric gradients were examined to help understand the factors that influenced front formation and stability. Periods of strong and variable winds led to front movement of up to 10 km per day or dissipation within 2-3 days in over 80% of the fronts detected in SST, Chl, nL_w, and FLH imagery. Short episodes of less variable wind velocities typically led to more stable and stationary fronts, within 3-5 km, for up to four days. The occurrence of fronts closely associated with the coastal bathymetry, namely at the 20 m and 30 m isobaths, was significantly higher in the fall SST imagery and in the spring Chl imagery. Fall SST fronts related to bathymetric gradients likely resulted from progressive cooling of the water with depth. Stronger Chl and nL_w443 gradients at the mouths of estuaries in the fall compared to the spring were attributed to increased precipitation and periods of stronger winds or tides. The FLH imagery was most useful in delineating coastal algal blooms. The automatic front detection techniques applied here can be an important tool for resource managers to track coastal oceanographic features daily, over synoptic spatial scales.     

A seventh-generation x86 microprocessor

An out-of-order, three-way superscalar ×86 microprocessor with a 15-stage pipeline, organized to allow 600 MHz operation, can fetch, decode, and retire up to three ×86 instructions per cycle to independent integer and floating-point schedulers. The schedulers can simultaneously dispatch up to nine operations to seven integer and three floating-point execution resources. A sophisticated, cell-based design technique and judicious application of custom circuitry permit the development of a processor with an aggressive architecture and high clock frequency with a rapid design cycle. Design-for-test techniques such as scan and clock bypassing permit straightforward testing and debugging of the part     

Effect of testosterone and its metabolites upon the level of vasopressin messenger ribonucleic acid in the hypothalamus of the hyperosmotically stimulated male rat

We examined whether the selective 5-hydroxytryptamine 1A (5-HT1A) receptor agonist 8-hydroxy-2-(di-n-propylamino)-tetralin (8-OH-DPAT) injected systemically can act directly on sympathoexcitatory neurons located in the rostral ventrolateral medulla (RVLM) to cause the hypotensive effect of this agent in rats. Microinjections of 8-OH-DPAT and buspirone into the RVLM produced a dose-dependent decrease in blood pressure. Microinjections of spiperone and pindolol, 5-HT1A antagonists, into the RVLM inhibited the depressor response to 8-OH-DPAT intravenously injected or injected into the RVLM. Microiontophoretic application of 8-OH-DPAT onto RVLM sympathoexcitatory neurons inhibited the firing of RVLM sympathoexcitatory neurons and the inhibition of unit activity by 8-OH-DPAT was blocked by microiontophoretic spiperone. Intravenous administration of 8-OH-DPAT also inhibited the firing of these neurons. Microiontophoretic application of spiperone onto the RVLM sympathoexcitatory neurons reversed the inhibitory response to intravenous 8-OH-DPAT. These results are consistent with the hypothesis that 8-OH-DPAT may exert a portion of its hypotensive effect through a direct inhibition of RVLM sympathoexcitatory neurons in rats. The receptor involved is probably the 5-HT1A type.