Effects of bilateral eye movements on the retrieval of item, associative, and contextual information.

Two experiments are reported that investigate the effects of saccadic bilateral eye movements on the retrieval of item, associative, and contextual information. Experiment 1 compared the effects of bilateral versus vertical versus no eye movements on tests of item recognition, followed by remember-know responses and associative recognition. Supporting previous research, bilateral eye movements enhanced item recognition by increasing the hit rate and decreasing the false alarm rate. Analysis of remember-know responses indicated that eye movement effects were accompanied by increases in remember responses. The test of associative recognition found that bilateral eye movements increased correct responses to intact pairs and decreased false alarms to rearranged pairs. Experiment 2 assessed the effects of eye movements on the recall of intrinsic (color) and extrinsic (spatial location) context. Bilateral eye movements increased correct recall for both types of context. The results are discussed within the framework of dual-process models of memory and the possible neural underpinnings of these effects are considered. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Relating aviation service difficulty reports to accident data for safety trend prediction

Commercial aviation fatalities are predicted (Fulwood et al., ‘Relating aviation service difficulty reports to accident data for safety trend prediction’, BNL Tech. Rpt 63018, March 1996) using linear superposition of the time-dependent spectra of key aircraft systems difficulties reporting in FAA's Service Difficulty Reports (SDR (DOT, FAA, ‘Flight standards service difficulty program’, Order 8010.2, Feb. 22, 1978, reissued 4:5/14/81)) data base. The fitting coefficients are found by a linear regression model (referred to as ‘the model’) to FAA's Accident Incident Data System (AIDS (DOT/FAA, ‘Aviation standards accident/incident data system—AIDS’, Users Guide VS ASAS-D-335, July 1982)) covering 5.5 years beginning January 1990. The model was tested by dividing the data approximately in half, using the first half to calibrate the model for prediction of the second half. A second test did the opposite. A third test used the first 60 months of data to predict the following 6 months. These tests (Fig. 5) showed good agreement between the model and AIDS data.The deficiency frequency of ATA (Aircraft Transportation Association) systems is reported (Table 2). Third-order fitting of the AIDS data was also used for prediction. All methods are compared in Fig. 4. The model was deemed superior because it reflects inspections and may be updated with SDR data from the Internet. The magnitude of the model's fitting coefficients indicate systems importances to the results.     

Improved sensitivity of biological sequence database searches

We have increased the sensitivity of DNA and protein sequence database searches by allowing similar but non-identical amino acids or nucleotides to match. In addition, one can match k-tuples or words instead of matching individual residues in order to speed the search. A matching matrix species which k-tuples match each other. The matching matrix can be calculated from a similarity matrix of amino acids and a threshold of similarity required for matching. This permits amino acid similarity matrices or replacement matrices (PAM matrices) to be used in the first step of a sequence comparison rather than in a secondary scoring phase. The concept of matching non-identical k-tuples also increases the power of DNA database searches. For example, a matrix that specifies that any 3-tuple in a DNA sequence can match any other 3-tuple encoding the same amino acid permits a DNA database search using a DNA query sequence for regions that would encode a similar amino acid sequence.     

Maintaining the balance [replenishment and inventory]

Demand and replenishment are critically dependent on how effectively information systems are used and how well demand signals, batching rules and effective forecasting, are managed and converted into plans and procurement actions. The supply and inventory relationship are more concerned with what is actually made, where inventory is placed and how it is moved through the supply chain. A better understanding of the issues and strategies can be achieved by examining the many combinations of supply and demand and consider them as different scenarios. In this paper three scenarios are cited.