Depressed mood does not explain neuropsychological deficits in HIV-infected persons.

The relationship of depressed mood to cognitive disturbance in HIV infection was examined in a sample of 139 homosexual men. Ss were grouped according to the classification of the Centers for Disease Control: 39 were in Group IV, 62 were in Group II or Group III, and 38 were HIV-negative. Ss completed the Profile of Mood States and 10 neuropsychological tests. Analysis employing a classification approach indicated that, although symptoms of depression and neuropsychological impairment were more common in Ss who were HIV-positive, particularly those classified as Group IV, there were no systematic relationships between depression and neuropsychological impairment. Depressed mood and cognitive disturbance each seem to have unique associations to HIV illness status. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Retrograde Amnesia in Dementia: Comparison of HIV-Associated Dementia, Alzheimer's Disease, and Huntington's Disease.

Remote memory was assessed in persons with HIV-associated dementia (HIV-D), probable Alzheimer's disease (AD), and Huntington's disease (HD) and in healthy controls. The clinical groups were similar in overall dementia severity. Each clinical group exhibited impairments on remote memory tests relative to controls; however, temporally graded memory loss with selective preservation of older information was observed in the AD group but not the HD or HIV-D group. Analysis of cued retrieval indicated a preferential cuing benefit for the HIV-D and HD groups relative to the AD group. The similar pattern of remote memory performance demonstrated by the HIV-D and HD groups is a novel finding and suggests a subcortically mediated retrograde amnesia in HIV-D. The temporally graded pattern and the abnormal cued retrieval performance in the AD group are consistent with a consolidation deficit associated with extrahippocampal (cortical) and hippocampal damage. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Nonstationary Gaussian Process Models Using Spatial Hierarchical Clustering from Finite Differences

Modern digital data production methods, such as computer simulation and remote sensing, have vastly increased the size and complexity of data collected over spatial domains. Analysis of these large spatial datasets for scientific inquiry is typically carried out using the Gaussian process. However, nonstationary behavior and computational requirements for large spatial datasets can prohibit efficient implementation of Gaussian process models. To perform computationally feasible inference for large spatial data, we consider partitioning a spatial region into disjoint sets using hierarchical clustering of observations and finite differences as a measure of dissimilarity. Intuitively, directions with large finite differences indicate directions of rapid increase or decrease and are, therefore, appropriate for partitioning the spatial region. Spatial contiguity of the resulting clusters is enforced by only clustering Voronoi neighbors. Following spatial clustering, we propose a nonstationary Gaussian process model across the clusters, which allows the computational burden of model fitting to be distributed across multiple cores and nodes. The methodology is primarily motivated and illustrated by an application to the validation of digital temperature data over the city of Houston as well as simulated datasets. Supplementary materials for this article are available online.     

ePAD: Earthquake Probability‐Based Automated Decision‐Making Framework for Earthquake Early Warning

The benefits and feasibility of earthquake early warning (EEW) are becoming more appreciated throughout the world. An EEW system detects an earthquake initiation based on a seismic sensor network and broadcasts a warning of the predicted location and magnitude shortly before an earthquake hits a site. The typical range of this lead time is very short, for example, from a few seconds up to a minute in California, which is a huge challenge for applications taking advantage of EEW. As a result, a robust automated decision process about whether to initiate a mitigation action is essential. Recent approaches based on cost–benefit analyses to properly treat the trade‐off between false alarms and missed alarms still face challenges in practical use, such as the exclusion of an important factor, lead time, in the real‐time decision process. In this study, we lay out an earthquake probability‐based automated decision‐making (ePAD) framework to give a general decision criterion based on basic decision theory and an existing cost–benefit analysis procedure. The concepts of decision function, decision contour, and surrogate model are utilized to achieve fast computation and to allow comparison between various decision criteria. A value of information model is developed to handle the lead time of EEW and its uncertainty to reduce the “false response rate” in the cost–benefit trade‐off. An illustrative example is presented to demonstrate how this framework allows more flexibility for users to adapt ePAD to correspond to their desired rational decision behavior.     

Estimation of yellow starthistle abundance through CASI-2 hyperspectral imagery using linear spectral mixture models

The invasive weed yellow starthistle (Centaurea solstitialis) has infested between 4 and 6 million hectares in California. It often forms dense infestations and rapidly depletes soil moisture, preventing the establishment of other species. Precise assessment of its canopy cover, especially low-density abundance in the earlier growing season, is the key to effective management. Compact Airborne Spectrographic Imager 2 (CASI-2) hyperspectral imagery was acquired at the western edge of California's Central Valley grasslands on July 15, 2003. Four linear spectral mixture models (LSMM) were investigated from the original CASI-2 data. Band selections based upon residual analysis and feature extraction (PCA) were further explored to reduce the data dimension. All approaches, except four band-selection unconstrained LSMMs, provide consistent results. The uncertainty of the PCA-based LSMM was estimated through a Monte-Carlo simulation. The maximum standard deviation was approximately 11%. The results suggest that unmixing CASI-2 imagery could be used for estimating and mapping yellow starthistle for larger regional areas.     

Minimum sodium nitrite levels for pinking of various cooked meats as related to use of direct or indirect-dried soy isolates in poultry rolls

The relationship between sodium nitrite level and pinking was investigated in cooked meats, as measured by panel color score, acetone extraction of NO-hemochrome, and instrumental redness values. Beef was less susceptible than poultry breast meat to nitrite-induced pinking. Minimum sodium nitrite level for pinking was 14, 4, 2, and 1 ppm for beef round, pork shoulder, turkey breast, and chicken breast, respectively. By regression analysis, minimum ppm nitrite for pinking=0.092 (ppm total pigment)+0.53 (R(2)=0.99). High levels of nitrate (>250 ppm as sodium nitrate) and nitrite (>45 ppm as sodium nitrite) were found in direct-dried (DD) soy isolates. Chicken breast rolls formulated with >2% DD soy were pink, but control rolls with 156 ppm sodium nitrate were not pink. Thus, it was concluded that nitrite was the primary pinking agent in DD soy. Indirect-dried (ID) soy isolates contained <11 ppm sodium nitrite, which was insufficient for pinking in poultry rolls.     

Therapist retrospective recall impasses in long-term psychotherapy: A qualitative analysis.

Twelve experienced therapists completed a questionnaire, and 8 of the 12 were then interviewed about their experiences with a therapeutic impasse that ended in the termination of therapy. Data were analyzed using a qualitative methodology. Results indicated that most of the clients were anxious and depressed with personality disorders and interpersonal problems. Therapists perceived impasses as having a profound negative impact on both clients and therapists. Variables associated with impasses in a majority of the cases were a client history of interpersonal problems, a lack of agreement between therapists and clients about the tasks and goals of therapy, interference in the therapy by others, transference, possible therapist mistakes, and therapist personal issues. Implications for training, practice, and research are provided. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Design and implementation of a hands-free electrolarynx device controlled by neck strap muscle electromyographic activity

The electrolarynx (EL) voice prosthesis is widely used, but suffers from the inconvenience of requiring manual control. Therefore, a hands-free EL triggered by neck muscle electromyographic (EMG) activity was developed (EMG-EL). Signal processing circuitry in a belt-mounted control unit transforms EMG activity into control signals for initiation and termination of voicing. These control signals are then fed to an EL held against the neck by an inconspicuous brace. Performance of the EMG-EL was evaluated by comparison to normal voice, manual EL voice, and tracheo-esophageal (TE) voice in a series of reaction time experiments in seven normal subjects and one laryngectomy patient. The normal subjects produced voice initiation with the EMG-EL that was as fast as both normal voice and the manual EL. The laryngectomy subject produced voice initiation that was slower than with the manual EL, but faster than with TE voice. Voice termination with the EMG-EL was slower than normal voice for the normal subjects, but not significantly different than with the manual EL. The laryngectomy subject produced voice termination with the EMG-EL that was slower than with TE or manual EL. The EMG-EL threshold was set at 10% of the range of vocal-related EMG activity above baseline. Simulations of EMG-EL behavior showed that the 10% threshold was not significantly different from the optimum threshold produced through the process of error minimization. The EMG-EL voice reaction time appears to be adequate for use in a day-to-day conversation.     

UHTC–carbon fibre composites: Preparation,oxyacetylene torch testing and characterisation

Current generation carbon–carbon (C–C) and carbon–silicon carbide (C–SiC) materials are limited to service temperatures below 1800 °C and materials are sought that can withstand higher temperatures and ablative conditions for aerospace applications. One potential materials solution is carbon fibre-based composites with matrices composed of one or more ultra-high temperature ceramics (UHTCs); the latter are intended to protect the carbon fibres at high temperatures whilst the former provides increased toughness and thermal shock resistance to the system as a whole. Carbon fibre–UHTC powder composites have been prepared via a slurry impregnation and pyrolysis route. Five different UHTC compositions have been used for impregnation, viz. ZrB₂, ZrB₂–20 vol% SiC, ZrB₂–20 vol% SiC–10 vol% LaB₆, HfB₂ and HfC. Their high-temperature oxidation resistance has been studied using a purpose built oxyacetylene torch test facility at temperatures above 2500 °C and the results are compared with that of a C–C benchmark composite.