Radiation therapy of giant aggressive keratoacanthomas

BACKGROUND AND DESIGN: Giant aggressive keratoacanthoma is a rare destructive subset of keratoacanthoma that frequently involves the facial region, grows rapidly to a large size, and often recurs after surgical management. The effectiveness of ionizing radiation therapy was examined in a retrospective study involving 16 patients; 14 of the tumors had recurred after surgical therapy. RESULTS: All tumors resolved with satisfactory cosmetic results and without recurrence following a fractionated course of superficial radiation therapy. CONCLUSIONS: Radiation therapy is an effective therapeutic modality for giant aggressive keratoacanthomas.     

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.     

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.     

Processes of memory loss, recovery, and distortion

The author proposes that many forms of memory distortion, including the progressive changes in recollection of a learning experience often observed over successive tests, are due to the same processes that yield veridical recollection in some circumstances and memory loss and recovery in others. In a framework for interpreting all of these aspects of memory, the author assumes that the objects and events of a learning experience are encoded in parallel in traces of their perceptual attributes, which are basic to recognition, and in traces of reactions made to the events during or following learning, which are basic to recall. Random perturbation of remembered attribute values in both types of traces over retention intervals is a pervasive cause of both loss and distortions of memory.     

Overly literal interpretations of speech in autism: understanding that messages arise from minds

Children with autism and children with Down's syndrome watched the following enactment. A protagonist put one item in location A and another in location B and then left the scene. Subsequently, the items were swapped the other way round. Finally, the protagonist (who remained ignorant of the swap) requested the item in A. The observing child participant was asked to judge (1) which item the protagonist wanted and (2) which item the protagonist put in A. Unlike children with Down's syndrome, those with autism made more errors in judging that the speaker wanted the item in B than in judging that the item the speaker put in A is now in B; children with autism wrongly tended to interpret utterances literally, and they did this significantly more frequently than children with Down's syndrome. We conclude that children with autism have a difficulty making nonliteral interpretations that cannot be explained as (1) a realist bias, (2) an inability to inhibit a prepotent response, and (3) a failure to keep track of the exchange of items.