Applied Threat and Error Management: Toward Crew-Centered Solutions

For an operator, a high level of understanding regarding procedures enables appropriate defenses to be built into a robust Threat and Error Management (TEM) framework. Currently, airline flightdeck crewmember training and reference information is concentrated heavily on what and how procedures are performed, but not on why they must be performed a standard way. This missing component of certainty invites misinterpretation of the standards and induces error. I propose a Crew-Centered TEM (CC/TEM) approach designed to arm flight crewmembers with more depth of procedural understanding than that currently afforded. A recent accident where human error was identified as a probable cause is used as an example of how a CC/TEM approach may have prevented the occurrence. CC/TEM solutions have further application within other safety-critical domains, such as medicine and emergency response

Neural Network Prediction of Ultimate Compression After Impact Loads in Graphite-Epoxy Coupons from Ultrasonic C-Scan Images

The purpose of this project was to investigate how accurately an artificial neural network could predict the ultimate compressive loads of impact damaged 24-ply graphite-epoxy coupons from ultrasonic C-scan images. The 24-ply graphite-epoxy coupons were manufactured with bidirectional preimpregnated tape and cut into 21 coupons, 4 inches by 6 inches each. The coupons were impacted at known impact energies of 10, 12, 14, 16, 18, and 20 Joules in order to create barely visible impact damage (BVID). The coupons were then scanned with an ultrasonic C-scan system to create an image of the damaged area. Each coupon was then compressed to failure to determine its ultimate compressive load. Numeric values for each pixel were determined from the C-scan image. Since the image was represented as a red-green-blue (RGB) map, each pixel had three numbers associated with it, one for each of the three colors. To make the image readable to the artificial neural network the columns of the resulting matrix were then summed, and these numbers were used as inputs for a backpropagation neural network (BPNN) to generate accurate predictions of the ultimate compressive loads. The BPNN was trained and optimized on 15 of the 21 sample data sets and tested on the remaining 6 sample data sets. The optimized BPNN was able to produce ultimate compression after impact (CAI) load predictions for the BVID composite coupons with a worst case error of -8.98%. This was within the ±10% goal for this research and comfortably within the B-basis allowables commonly applied to composite structures. The ultrasonic C-scan images were then preprocessed using Fast Fourier Transforms (FFTs) in an effort to remove any image noise present. The results of the BPNN that was trained and tested on the green color data only were then compared to the results yielded by the BPNN trained and tested on the images that were processed through the FFT. It was found that the FFT processed images had a worst case BPNN prediction error of 8.65%, which was only slightly lower than the -8.98% error that was generated by the unprocessed green layer only C-scan image data. This improvement suggested that the added work involved in FFT preprocessing of the worst case error was not as productive as had been hoped, leading to a few suggestions for future noise removal research. This also reinforced the notion that BPNNs, being an iterative optimization scheme, can provide accurate predictions in the presence of at least small amounts of noise. Thus, image filtering methods coupled with the iterative optimization technique that comprises a BPNN have demonstrated the ability to generate accurate CAI load predictions in composite coupons that have experienced BVID

Workplace incivility against women in STEM: Insights and best practices

As demonstrated by both empirical and non-empirical research, women are more likely than men to be a target of workplace incivility. This manifests in a variety of negative outcomes for female employees, including turnover intentions, poor performance, and higher levels of stress. The problem is exacerbated for women in STEM fields due to factors unique to these industries. Herein, we outline the unique characteristics of STEM organizations that can foster the creation and sustenance of an atmosphere promoting workplace incivility against female employees. Then, we provide five best practice recommendations geared toward reducing incivility, improving work climate, and promoting overall retention of women in STEM

The effects of effort on Stroop interference

Stroop interference was defined as the difference in time needed to name the ink colors of printed color and color-related words versus control plus signs. The effect of effort on Stroop interference was studied using an inter-subject competition procedure designed to manipulate effort. In experiment 1, subjects in the competition group were successful at inhibiting Stroop interference when compared to the performance of subjects in the no-competition group. This result is consistent with theories that postulate attentional effects on Stroop interference. In experiment 2, the significant decrease in Stroop interference was accompanied by a significant reduction in recognition memory for Stroop list items. Therefore. Stroop interference was reduced at a stage during the processing of word meaning. This result is consistent with theories that locate Stroop interference before response output. The purpose of this research is twofold: first, to investigate the effect of effort on Stroop interference; and second, to study the locus of the mechanism by which effort may influence Stroop interference

Genomewide and Enzymatic Analysis Reveals Efficient d-Galacturonic Acid Metabolism in the Basidiomycete Yeast Rhodosporidium toruloides.

Biorefining of renewable feedstocks is one of the most promising routes to replace fossil-based products. Since many common fermentation hosts, such as Saccharomyces cerevisiae, are naturally unable to convert many component plant cell wall polysaccharides, the identification of organisms with broad catabolism capabilities represents an opportunity to expand the range of substrates used in fermentation biorefinery approaches. The red basidiomycete yeast Rhodosporidium toruloides is a promising and robust host for lipid- and terpene-derived chemicals. Previous studies demonstrated assimilation of a range of substrates, from C5/C6 sugars to aromatic molecules similar to lignin monomers. In the current study, we analyzed the potential of R. toruloides to assimilate d-galacturonic acid, a major sugar in many pectin-rich agricultural waste streams, including sugar beet pulp and citrus peels. d-Galacturonic acid is not a preferred substrate for many fungi, but its metabolism was found to be on par with those of d-glucose and d-xylose in R. toruloides A genomewide analysis by combined transcriptome sequencing (RNA-seq) and RB-TDNA-seq revealed those genes with high relevance for fitness on d-galacturonic acid. While R. toruloides was found to utilize the nonphosphorylative catabolic pathway known from ascomycetes, the maximal velocities of several enzymes exceeded those previously reported. In addition, an efficient downstream glycerol catabolism and a novel transcription factor were found to be important for d-galacturonic acid utilization. These results set the basis for use of R. toruloides as a potential host for pectin-rich waste conversions and demonstrate its suitability as a model for metabolic studies with basidiomycetes.IMPORTANCE The switch from the traditional fossil-based industry to a green and sustainable bioeconomy demands the complete utilization of renewable feedstocks. Many currently used bioconversion hosts are unable to utilize major components of plant biomass, warranting the identification of microorganisms with broader catabolic capacity and characterization of their unique biochemical pathways. d-Galacturonic acid is a plant component of bioconversion interest and is the major backbone sugar of pectin, a plant cell wall polysaccharide abundant in soft and young plant tissues. The red basidiomycete and oleaginous yeast Rhodosporidium toruloides has been previously shown to utilize a range of sugars and aromatic molecules. Using state-of-the-art functional genomic methods and physiological and biochemical assays, we elucidated the molecular basis underlying the efficient metabolism of d-galacturonic acid. This study identified an efficient pathway for uronic acid conversion to guide future engineering efforts and represents the first detailed metabolic analysis of pectin metabolism in a basidiomycete fungus

Production of ent-kaurene from lignocellulosic hydrolysate in Rhodosporidium toruloides.

BACKGROUND:Rhodosporidium toruloides has emerged as a promising host for the production of bioproducts from lignocellulose, in part due to its ability to grow on lignocellulosic feedstocks, tolerate growth inhibitors, and co-utilize sugars and lignin-derived monomers. Ent-kaurene derivatives have a diverse range of potential applications from therapeutics to novel resin-based materials. RESULTS:The Design, Build, Test, and Learn (DBTL) approach was employed to engineer production of the non-native diterpene ent-kaurene in R. toruloides. Following expression of kaurene synthase (KS) in R. toruloides in the first DBTL cycle, a key limitation appeared to be the availability of the diterpene precursor, geranylgeranyl diphosphate (GGPP). Further DBTL cycles were carried out to select an optimal GGPP synthase and to balance its expression with KS, requiring two of the strongest promoters in R. toruloides, ANT (adenine nucleotide translocase) and TEF1 (translational elongation factor 1) to drive expression of the KS from Gibberella fujikuroi and a mutant version of an FPP synthase from Gallus gallus that produces GGPP. Scale-up of cultivation in a 2 L bioreactor using a corn stover hydrolysate resulted in an ent-kaurene titer of 1.4 g/L. CONCLUSION:This study builds upon previous work demonstrating the potential of R. toruloides as a robust and versatile host for the production of both mono- and sesquiterpenes, and is the first demonstration of the production of a non-native diterpene in this organism

Context reinstatement effects on eyewitness memory in autism spectrum disorder

The Cognitive Interview is among the most widely accepted forms of police interviewing techniques; however, it is ineffective for witnesses with autism spectrum disorder (ASD). One of its main components involves mentally reinstating the internal and external context that was experienced at encoding. We report evidence showing that it is the mental reinstatement instructions in the absence of any physical cues that individuals with ASD find difficult. In more supported conditions where they physically return to the same environment in which they learnt the material, they recall as much as their typical counterparts. Our findings indicate that recall in ASD is aided by context, but only when supported by the physical environment. These findings have important implications for investigative interviewing procedures for witnesses with ASD

Context reinstatement in recognition: memory and beyond

Context effects in recognition tests are twofold. First, presenting familiar contexts at a test leads to an attribution of context familiarity to a recognition probe, which has been dubbed ‘context-dependent recognition’. Second, reinstating the exact study context for a particular target in a recognition test cues recollection of an item-context association, resulting in 'context-dependent discrimination'. Here we investigated how these two context effects are expressed in metacognitive monitoring (confidence judgments) and metacognitive control ('don’t know' responding) of retrieval. We used faces as studied items, landscape photographs as study and test contexts and both free- and forced-report 2AFC recognition tests. In terms of context-dependent recognition, the results document that presenting familiar contexts at test leads to higher confidence and lower rates of 'don’t know responses compared to novel contexts, while having no effect on forced-report recognition accuracy. In terms of context-dependent discrimination, the results show that reinstated contexts further boost confidence and reduce 'don’t know' responding compared to familiar contexts, while affecting forced-report recognition accuracy only when contribution of recollection to recognition performance is high. Together, our results demonstrate that metacognitive measures are sensitive to context effects, sometimes even more so than recognition measures

The Grizzly, April 12, 1985

Construction of Three Athletic Fields is Underway • Dumb Jock Image Unfair Stereotype, Study Says • Campus Shows Concern for African Hunger Problem • Concert Review: Pink Floyd\u27s Leader Provides Powerful Performance • Bear Batters Face Tough Times • Talent Show Moments • Girl\u27s Lacrosse Wins Five, Drops Two • Men\u27s Track Places First, Second in Two Meets • Intramural Basketball Season Endshttps://digitalcommons.ursinus.edu/grizzlynews/1139/thumbnail.jp