Chloroplast microsatellites: new tools for studies in plant ecology and systematics

The nonrecombinant, uniparentally inherited nature of organelle genomes
makes them useful tools for evolutionary studies. However, in plants, detecting
useful polymorphism at the population level is often difficult because of the
low level of substitutions in the chloroplast genome, and because of the slow
substitution rates and intramolecular recombination of mtDNA. Chloroplast
microsatellites represent potentially useful markers to circumvent this problem
and, to date, studies have demonstrated high levels of intraspecific variability.
Here,we discuss the use of these markers in ecological and evolutionary
studies of plants, as well as highlighting some of the potential problems
associated with such use.

Assistive software tools for secondary-level students with literacy difficulties.

Study conducted to evaluate the effectiveness of four assistive technology (AT) tools on literacy: (1) speech synthesis, (2) spellchecker, (3) homophone tool, and (4) dictionary. All four of these programs are featured in TextHelp’s Read&Write Gold software package. A total of 93 secondary-level students with reading disabilities participated in the study. The participants completed a number of computer-based literacy tests after being assigned to a Read&Write group or a control group that utilized Microsoft Word. The results indicated that improvements in the following areas for the Read&Write group: (1) reading comprehension, (2) homophone error detection, (3) spelling error detection, and (4) word meanings. The Microsoft Word group also improved in the areas of word meanings and error detection, though performed worse on homophone error detection. The authors contend that these results indicate that speech synthesis, spell checkers, homophone tools, and dictionary programs have a positive effect on literacy among students with reading disabilities. This study was conducted by researchers at the Queen’s University in Belfast, Ireland.

A machine vision approach to the grading of crushed aggregate

The grading of crushed aggregate is carried out usually by sieving. We describe a new image-based approach to the automatic grading of such materials. The operational problem addressed is where the camera is located directly over a conveyor belt. Our approach characterizes the information content of each image, taking into account relative variation in the pixel data, and resolution scale. In feature space, we find very good class separation using a multidimensional linear classifier. The innovation in this work includes (i) introducing an effective image-based approach into this application area, and (ii) our supervised classification using wavelet entropy-based features.