Low-temperature phase transformation in Li-10 at. % Mg

It is not known whether impaired hematopoiesis noted during human immunodeficiency virus (HIV) infection results from infection of stem/progenitor cells or of cells of the bone marrow microenvironment. Normal adherent primary stromal layers were exposed to HIV to determine which of this mixture of endothelial cells, fibroblasts, and macrophages are susceptible to the virus. Viral p24 in supernatants was noted with monocytotropic HIV-1Ada, HIV-1Ba-L, and HIV-1JR-FL but not with lymphotropic HIV-1LAI nor HIV-1MN strain, and only stromal macrophages expressed the viral antigens. Coculture of the layers with PHA-activated normal lymphocytes failed to rescue lymphotropic virus. No p24 was produced when macrophage-depleted stromal cells were exposed to either HIV-1Ba-L or HIV-1LAI; proviral DNA was then amplified by PCR in cells exposed to either virus, though coculture with lymphocytes rescued only HIV-1Ba-L. Altogether, these data indicate that macrophages are the major targets of HIV in cultured stromal layers. As virus replication in macrophages did not affect the profile of major cytokines involved in regulating hematopoiesis, HIV infection could alter hematopoiesis by other as yet unspecified mechanisms.     

GELYMAC: a Macintosh application for calculating DNA fragment size from gel electrophoresis migration data

A program called GELYMAC takes data on the distances migrated by DNA fragments in a one-dimensional electrophoretic gel and, using a cubic-spline best-fit of marker fragment distance migrated versus molecular size, calculates the molecular sizes of the fragments. Written in the Rascal (Real-time Pascal) programming language, the program runs on the Macintosh family of microcomputers. Rapid entry of marker and experimental fragment migration data is afforded using a scroll bar system adjacent to a graphic representation of a gel. Output includes tabular listing of the data, graphic cartoons of the gel, and the fragment locations and molecular sizes for individual gel lanes, and the calibration curve used in data computations.     

Evaluating dynamic performance: The influence of salient Gestalt characteristics on performance ratings.

It is well recognized that performance changes over time. However, the effect of these changes on overall assessments of performance is largely unknown. In a laboratory experiment, we examined the influence of salient Gestalt characteristics of a dynamic performance profile on supervisory ratings. We manipulated performance trend (flat, linear-improving, linear-deteriorating, U-shaped, and ∩-shaped), performance variation (small, large), and performance mean (negative, zero, positive) within subjects and display format (graphic, tabular) between subjects. Participants received and evaluated information about the weekly performance of different employees over a simulated 26-week period. Results showed strong main effects on performance ratings of both performance mean and performance trend, as well as interactions with display format. Theoretical and practical implications of the results are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Construction Robot Path-Planning for Earthwork Operations

In developing an intelligent mobile construction robot, a navigation system that can provide an effective and efficient path-planning algorithm is a very important element. The purpose of a path-planning method for a mobile construction robot is to find a continuous collision-free path from the initial position of the construction robot to its target position. This paper presents an improved Bug-based algorithm, called SensBug, which can produce an effective path in an unknown environment with both stationary and movable obstacles. The contributions, which make it possible to generate an effective and short path, are an improved method to select local directions, a reverse mode, and a simple leaving condition. Some emerging technologies that can be used for implementing an intelligent construction robot are introduced in this paper.     

Multifamily Housing Characteristics and Tenant Satisfaction

This paper examines the long-term impact of structural features and physical amenities on the residential satisfaction of renters in multifamily housing. A cumulative logit analysis of 7,206 rented multifamily units in the 2005 American Housing Survey indicates that features creating separated space (additional room, bathroom, garage/carport, or balcony/patio) were associated with significantly higher satisfaction, even when holding total unit area constant. Conversely, violation of space separation by noise intrusion through walls, floors, or ceilings created dramatically negative effects. Other amenities such as a fireplace, disposal, or dishwasher had no statistically significant impact. Tracking a cohort of 5,170 rented multifamily units from 1997 to 2005 revealed somewhat similar effects on the satisfaction trajectory of residents during this period. More bathrooms, bedrooms, and other rooms, as well as the presence of a balcony/patio were associated with satisfaction improvements. Analyzing cohort units undergoing modifications during the tracking period revealed that the addition of a bathroom or central air conditioning had the clearest impact on satisfaction, followed by the addition of a balcony/patio, other room, dishwasher, or garage/carport.     

Stream Classification System Based on Susceptibility to Algal Growth in Response to Nutrients

We developed a stream classification system that is based on stream’s susceptibility to algal growth using a two-step approach. The model portrays algal biomass as a result of stream’s response to nutrient concentrations and the response is governed by various stream factors. In the first step, a nutrient-chlorophyll a relationship was developed to characterize nutrient’s effects on algal biomass. Residuals of the relationship were attributed to stream’s susceptibility to algal growth in response to nutrients and referred to as “observed” susceptibility. In the second step, conditions of other contributing factors were used to explain the variation in the residuals and the developed relationship was used to generate “predicted” susceptibility. Existing data compiled from various monitoring projects of Illinois streams and rivers were used to illustrate the approach. Streams were classified into three (high, medium, and low) categories based on their observed and predicted susceptibility values, respectively. With the available data, the model showed a 40-50% success rate for classifying the streams based on three observed and predicted susceptibility categories. Model entropy also was calculated for selecting the best model. The results show the important role of both nutrients and other contributing factors in explaining the variation of algal biomass. The study also suggests ways to fine tune the model and improve its accuracy, which would make the presented model a more viable tool for stream classification for establishing nutrient criteria to prevent surface streams from eutrophication.