The Challenge of the Market

Identifying markets for new or improved products for minor crops threatened with extinction is one critical component of any strategy intended to enhance prospects for sustainable production and use. Typically, however, activities linked to the sustainability of these commodities avoid addressing questions associated with assessing their commercial potential. After a brief review of this avoidance syndrome, this article presents a sample of practical, low-cost procedures to help evaluate the market prospects and procedures for crops like quinoa, while citing references to other methodological materials covering similar topics.     

"Aging and forgetting in prospective and retrospective memory tasks": Correction.

Reports an error in the original article by E. A. Maylor (Psychology and Aging, 1993[Sep], Vol 8[3], 420–428). There is an error in the picture recognition data. This was one of the tasks administered in an earlier group testing session (see page 421). The number of false positives for an older S was incorrectly entered onto the data sheet as 31 instead of only 13. (The following abstract of this article originally appeared in record 1994-01191-001.) Ss (aged 52–83 yrs) named 30 famous people 4 times over the course of an hour and responded to 2 targets (a beard and a pipe) by marking the trial number on the response sheet. Initial performance in the prospective memory task was related only to a measure of incidental learning. Subsequent forgetting (i.e., success followed by failure) occurred more often for older Ss than for younger Ss, but there was no difference between the age groups in recovery (i.e., failure followed by success). Forgetting was predicted by age, even after a composite measure of general ability was included in the regression. Recovery was related to general ability alone. Results both replicate and extend those from a reanalysis of a previous study (E. A. Maylor, 1990). They provide a striking contrast with the effect of age on retrospective memory.… (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Peptide amidating activity in human bronchoalveolar lavage fluid

Monitoring respiratory epithelial biology may reveal individuals with incipient lung cancer. The expression of neuroendocrine (NE) markers in pulmonary epithelium is thought to be central to lung development, repair of injury and may contribute to carcinogenesis. In this study, we evaluate several candidate NE markers to determine the feasibility of prospective analysis of clinical specimens. The potential NE markers include the enzyme L-DOPA decarboxylase (DDC), the neuropeptide gastrin releasing peptide (GRP), and peptidyl-glycine alpha-amidating monooxygenase (PAM), the bifunctional enzyme responsible for the final bioactivation step of many neuropeptides. A comparison of PAM activity and DDC levels in 30 lung cancer cell lines indicated that peptide amidating activity may be an indicator of NE status. Bronchoalveolar lavage (BAL) fluid from subjects at risk of developing second primary lung cancer and from volunteers was obtained. The activity of the first PAM enzyme, peptidylglycine alpha-hydroxylating monooxygenase (PHM), ranged from not detectable to 507 pmol/h/mg protein in 57 specimens. The second PAM enzyme, peptidylamidoglycolate lyase (PAL), ranged from not detectable to 414 pmol/h/mg protein in 56 specimens. Using cluster analysis by the average linkage method, a group of enzyme values with PHM greater than 230 pmol/h/mg protein was determined. Long-term follow-up of these patients for new second primary lung cancers may help to determine the potential predictive value of PAM detected in the BAL fluid.     

A neural network model for the wire bonding process

A crucial step in manufacturing microcircuits is the wire bonding process in which a very thin gold wire must be formed to connect two surfaces in the microcircuit. The quality of the wire bond can be measured by visual inspection and a pull test—both of which are high-reliability, high-cost approaches to statistical process control. Westinghouse wanted to develop a high-reliability, low-cost quality assurance system. In this paper, we report on a year-long study to construct a neural network model that is capable of predicting the quality of wire bonds. The results of our modeling efforts reveal that neural networks are useful tools for statistical process control problems.