A STRUCTURAL IMPACT ASSESSMENT OF FLAWS DETECTED DURING ULTRASONIC EXAMINATION OF TANK 15

Ultrasonic (UT) inspection of Tank 15 was conducted between April and July 2007 in accordance with the Tank 15 UT inspection plan. This was a planned re-inspection of this tank, the previous one was performed in 2002. Ten cracks were characterized in the previous examination. The re-inspection was performed to verify the present models and understanding for stress corrosion cracking. During this re-examination, one indication that was initially reported as a 'possible perpendicular crack <25% through wall' in 2002, was clearly shown not to be a crack. Additionally, examination of a new area immediately adjacent to other cracks along a vertical weld revealed three new cracks. It is not known when these new cracks formed as they could very well have been present in 2002 as well. Therefore, a total of twelve cracks were evaluated during the re-examination. A critical review of the information describing stress corrosion crack behavior for the SRS waste tanks, as well as a summary review of the service history of Tank 15, was performed. Each crack was then evaluated for service exposure history, consistency of the crack behavior with the current understanding of stress corrosion cracking, and present and future impact to the structural integrity of the tank. Crack instability calculations were performed on each crack for a bounding waste removal loading condition in Tank 15. In all cases, the crack behavior was determined to be consistent with the previous understanding of stress corrosion cracking in the SRS waste tank environment. The length of the cracks was limited due to the short-range nature of the residual stresses near seam, repair and attachment welds. Of the twelve cracks, nine were located in the vapor space above the sludge layer, including the three new cracks. Comparison of the crack lengths measured in 2002 and 2007 revealed that crack growth had occurred in four of the six previously measured vapor space cracks. However, the growth remained within the residual stress zone. None of the three cracks beneath the sludge showed evidence of growth. The impact of the cracks that grew on the future service of Tank 15 was also assessed. Tank 15 is expected to undergo closure activities including sludge waste removal. A bounding loading condition for waste removal of the sludge at the bottom of Tank 15 was considered for this analysis. The analysis showed that the combination of hydrostatic, seismic, pump and weld residual stresses are not expected to drive any of the cracks identified during the Tank 15 UT inspection to instability. Wall thickness mapping for general thinning and pitting was also performed. No significant wall thinning was observed. The average wall thickness values were well above nominal. Two isolated pit-like indications were observed. Both were approximately 30 mils deep. However, the remaining wall thickness was still greater than nominal specified for the original construction plate material. It was recommended that a third examination of selected cracks in Tank 15 be performed in 2014. This examination would provide information to determine whether any additional detectable degradation is occurring in Tank 15 and to supplement the basis for characterization of conditions that are non-aggressive to tank corrosion damage. The in-service inspection program is re-evaluated on a three year periodicity. The Type I and II tanks are not active receipt tanks at present, and are therefore not a part of the In-Service Inspection Program for the Type III Tanks [1]. Changes to the mission for Tank 15 and other Type I and II tanks may be considered by the In-Service Inspection Review Committee (ISIRC) and the program adjusted accordingly

Use of Local Image Information in Depth Edge Classification by Humans and Neural Networks

Humans can use local cues to distinguish image edges caused by a depth change from other types of edges (Vilankar et al., 2014). But which local cues? Here we use the SYNS database (Adams et al., 2016) to automatically label edges in images of natural scenes as depth or non-depth. We use this ground truth to identify the cues used by human observers and convolutional neural networks (CNNs) for edge classification. Eight observers viewed square image patches, each centered on an image edge, ranging in width from 0.6 to 2.4 degrees (8 to 32 pixels). Human judgments (depth/non-depth) were compared to responses of a CNN trained on the same task. Human performance improved with patch size (65%-74% correct) but remained well below CNN accuracy (82-86% correct). Agreement between humans and the CNN was above chance but lower than human-human agreement. Decision Variable Correlation (Sebastian & Geisler, in press) was used to evaluate the relationships between depth responses and local edge cues. Humans seem to rely primarily on contrast cues, specifically luminance contrast and red-green contrast across the edge. The CNN also relies on luminance contrast, but unlike humans it seems to make use of mean luminance and red-green intensity as well. These local luminance and color features provide valid cues for depth edge discrimination in natural scenes

Of Genes and Antigens: The Inheritance of Psoriasis

Psoriasis is one of a number of autoimmune diseases that display significant HLA associations. In particular, individuals with onset of disease prior to 40 years of age display striking associations with HLA-Cw6 and are much more likely to have a positive family for psoriasis. However, only about 10% of Cw6-positive individuals develop disease, suggesting that other genetic and/or environmental factors must be involved. Several compelling lines of epidemiologic evidence indicate that psoriasis susceptibility is inherited, albeit not in a simple monogenic fashion, and that genetic, rather than environmental, factors are primarily responsible for the variability in inheritance of psoriasis. Taken together, these observations suggest that one or more loci in addition to HLA are necessary for the development of psoriasis. The number of additional loci is likely to be small, because i) the disease is very common ii) substantial excess risk of psoriasis is observed in first degree relatives, and iii) nevoid variants of psoriasis have been reported, suggestive of somatic mutation of a single gene during development. The substantial homogeneity of the psoriatic phenotype and the clear evidence for increased HLA association and heritability in juvenile onset disease indicate that despite its complexity, psoriasis is a common disease whose etiology is amenable to elucidation through the techniques of modern molecular genetics. J Invest Dermatol 103:150S-153S, 199

The Southampton-York Natural Scenes (SYNS) dataset: statistics of surface attitude

Recovering 3D scenes from 2D images is an under-constrained task; optimal estimation depends upon knowledge of the underlying scene statistics. Here we introduce the Southampton-York Natural Scenes dataset (SYNS: https://syns.soton.ac.uk), which provides comprehensive scene statistics useful for understanding biological vision and for improving machine vision systems. In order to capture the diversity of environments that humans encounter, scenes were surveyed at random locations within 25 indoor and outdoor categories. Each survey includes (i) spherical LiDAR range data (ii) high-dynamic range spherical imagery and (iii) a panorama of stereo image pairs. We envisage many uses for the dataset and present one example: an analysis of surface attitude statistics, conditioned on scene category and viewing elevation. Surface normals were estimated using a novel adaptive scale selection algorithm. Across categories, surface attitude below the horizon is dominated by the ground plane (0° tilt). Near the horizon, probability density is elevated at 90°/270° tilt due to vertical surfaces (trees, walls). Above the horizon, probability density is elevated near 0° slant due to overhead structure such as ceilings and leaf canopies. These structural regularities represent potentially useful prior assumptions for human and machine observers, and may predict human biases in perceived surface attitude

Dissecting the psoriasis transcriptome: inflammatory- and cytokine-driven gene expression in lesions from 163 patients

Abstract Background Psoriasis lesions are characterized by large-scale shifts in gene expression. Mechanisms that underlie differentially expressed genes (DEGs), however, are not completely understood. We analyzed existing datasets to evaluate genome-wide expression in lesions from 163 psoriasis patients. Our aims were to identify mechanisms that drive differential expression and to characterize heterogeneity among lesions in this large sample. Results We identified 1233 psoriasis-increased DEGs and 977 psoriasis-decreased DEGs. Increased DEGs were attributed to keratinocyte activity (56%) and infiltration of lesions by T-cells (14%) and macrophages (11%). Decreased DEGs, in contrast, were associated with adipose tissue (63%), epidermis (14%) and dermis (4%). KC/epidermis DEGs were enriched for genes induced by IL-1, IL-17A and IL-20 family cytokines, and were also disproportionately associated with AP-1 binding sites. Among all patients, 50% exhibited a heightened inflammatory signature, with increased expression of genes expressed by T-cells, monocytes and dendritic cells. 66% of patients displayed an IFN-γ-strong signature, with increased expression of genes induced by IFN-γ in addition to several other cytokines (e.g., IL-1, IL-17A and TNF). We show that such differences in gene expression can be used to differentiate between etanercept responders and non-responders. Conclusions Psoriasis DEGs are partly explained by shifts in the cellular composition of psoriasis lesions. Epidermal DEGs, however, may be driven by the activity of AP-1 and cellular responses to IL-1, IL-17A and IL-20 family cytokines. Among patients, we uncovered a range of inflammatory- and cytokine-associated gene expression patterns. Such patterns may provide biomarkers for predicting individual responses to biologic therapy.http://deepblue.lib.umich.edu/bitstream/2027.42/112670/1/12864_2012_Article_5257.pd

Predicting university performance in psychology: the role of previous performance and discipline-specific knowledge

Recent initiatives to enhance retention and widen participation ensure it is crucial to understand the factors that predict students' performance during their undergraduate degree. The present research used Structural Equation Modeling (SEM) to test three separate models that examined the extent to which British Psychology students' A-level entry qualifications predicted: (1) their performance in years 1-3 of their Psychology degree, and (2) their overall degree performance. Students' overall A-level entry qualifications positively predicted performance during their first year and overall degree performance, but negatively predicted their performance during their third year. Additionally, and more specifically, students' A-level entry qualifications in Psychology positively predicted performance in the first year only. Such findings have implications for admissions tutors, as well as for students who have not studied Psychology before but who are considering applying to do so at university

Psoriasis drug development and GWAS interpretation through in silico analysis of transcription factor binding sites

BackgroundPsoriasis is a cytokine‐mediated skin disease that can be treated effectively with immunosuppressive biologic agents. These medications, however, are not equally effective in all patients and are poorly suited for treating mild psoriasis. To develop more targeted therapies, interfering with transcription factor (TF) activity is a promising strategy.MethodsMeta‐analysis was used to identify differentially expressed genes (DEGs) in the lesional skin from psoriasis patients (n = 237). We compiled a dictionary of 2935 binding sites representing empirically‐determined binding affinities of TFs and unconventional DNA‐binding proteins (uDBPs). This dictionary was screened to identify “psoriasis response elements” (PREs) overrepresented in sequences upstream of psoriasis DEGs.ResultsPREs are recognized by IRF1, ISGF3, NF‐kappaB and multiple TFs with helix‐turn‐helix (homeo) or other all‐alpha‐helical (high‐mobility group) DNA‐binding domains. We identified a limited set of DEGs that encode proteins interacting with PRE motifs, including TFs (GATA3, EHF, FOXM1, SOX5) and uDBPs (AVEN, RBM8A, GPAM, WISP2). PREs were prominent within enhancer regions near cytokine‐encoding DEGs (IL17A, IL19 and IL1B), suggesting that PREs might be incorporated into complex decoy oligonucleotides (cdODNs). To illustrate this idea, we designed a cdODN to concomitantly target psoriasis‐activated TFs (i.e., FOXM1, ISGF3, IRF1 and NF‐kappaB). Finally, we screened psoriasis‐associated SNPs to identify risk alleles that disrupt or engender PRE motifs. This identified possible sites of allele‐specific TF/uDBP binding and showed that PREs are disproportionately disrupted by psoriasis risk alleles.ConclusionsWe identified new TF/uDBP candidates and developed an approach that (i) connects transcriptome informatics to cdODN drug development and (ii) enhances our ability to interpret GWAS findings. Disruption of PRE motifs by psoriasis risk alleles may contribute to disease susceptibility.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155494/1/ctm2s4016901500545-sup-0001.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155494/2/ctm2s4016901500545-sup-0018.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155494/3/ctm2s4016901500545-sup-0002.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155494/4/ctm2s4016901500545.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155494/5/ctm2s4016901500545-sup-0009.pd