Multimethod approach to learning from text-based construction failure data

To be sustainable, the construction industry must learn from, and avoid, repetitive failures. At present, there is heavy reliance on learning from case-studies of catastrophic events and a lack of attention to the more frequent, lower consequence and yet repetitive failures. These smaller failures can have huge cumulative impact. This is important as the construction sector is worth £113 billion per year to the UK economy (6% of UK GDP) and provides over 2.4 million jobs (7% UK jobs). This impressive contribution is undermined by a large number of construction projects which run over time and over cost. This undermining is all the more damaging for those high profile, often publicly funded, infrastructure programmes which attract severe negative publicity when they run overbudget. While other factors contribute to this overspend (for example, inaccurate tender estimates and scope or design change), previous research found that correcting quality mistakes can account for over 20% of a contract's value. Another failure of the construction industry is its safety performance. In the 2017/18 fiscal year, the fatal injury rate for those working in UK construction was four times the national average at 1.64 per 100,000 workers. Additionally, the Health and Safety Executive in its 2018 Annual Report estimated that safety injuries on site cost £490M to the UK economy. It is therefore both a moral and economic imperative that the industry is learning to avoid repetitive failure. There is a wealth of information contained within accounts of more frequent, lower consequence incidents and safety observation reports, which should be used. These reports are collected as part of the lifecycle of the project. However, to date, these data have been inaccessible to traditional analysis techniques due to physical accessibility issues and the format of unstructured text data, requiring time consuming manual analysis. This project harnessed the potential of modern data science methods, including natural language processing (NLP) and machine learning (ML), to produce automated methods and recommendations for analysing these data for the construction industry. A multi-method approach was applied. First, a qualitative investigation used semi-structured interviews and thematic analysis to explore failure in the construction industry, with particular attention to present `learning from failure' practice, human factors and biases. Second, the text-based construction site failure data was analysed using recent data science methods. This analysis relied upon the insights from the first investigation to inform methodological decisions. It was decided to transform the unstructured text data into structured attributes, using machine learning classification methods, for further analysis. Transforming the unstructured text descriptions in this way allows further analysis methods to be performed. Possible further analyses unlocked by this method include risk analysis, graphical analysis, learning, and finer trend analysis. Finally, qualitative information from the thematic analysis was used to assess usefulness and form recommendations for industrial application of the data analysis methods employed to develop techniques that allow the capture and analysis of data to measure and mitigate the cumulative impact of smaller failures

Hydrothermal venting in magma deserts : the ultraslow-spreading Gakkel and Southwest Indian Ridges

Author Posting. © American Geophysical Union, 2004. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry Geophysics Geosystems 5 (2004): Q08002, doi:10.1029/2004GC000712.Detailed hydrothermal surveys over ridges with spreading rates of 50–150 mm/yr have found a linear relation between spreading rate and the spatial frequency of hydrothermal venting, but the validity of this relation at slow and ultraslow ridges is unproved. Here we compare hydrothermal plume surveys along three sections of the Gakkel Ridge (Arctic Ocean) and the Southwest Indian Ridge (SWIR) to determine if hydrothermal activity is similarly distributed among these ultraslow ridge sections and if these distributions follow the hypothesized linear trend derived from surveys along fast ridges. Along the Gakkel Ridge, most apparent vent sites occur on volcanic highs, and the extraordinarily weak vertical density gradient of the deep Arctic permits plumes to rise above the axial bathymetry. Individual plumes can thus be extensively dispersed along axis, to distances >200 km, and ∼75% of the total axial length surveyed is overlain by plumes. Detailed mapping of these plumes points to only 9–10 active sites in 850 km, however, yielding a site frequency F s , sites/100 km of ridge length, of 1.1–1.2. Plumes detected along the SWIR are considerably less extensive for two reasons: an apparent paucity of active vent fields on volcanic highs and a normal deep-ocean density gradient that prevents extended plume rise. Along a western SWIR section (10°–23°E) we identify 3–8 sites, so F s = 0.3–0.8; along a previously surveyed 440 km section of the eastern SWIR (58°–66°E), 6 sites yield F s = 1.3. Plotting spreading rate (us) versus F s, the ultraslow ridges and eight other ridge sections, spanning the global range of spreading rate, establish a robust linear trend (F s = 0.98 + 0.015us), implying that the long-term heat supply is the first-order control on the global distribution of hydrothermal activity. Normalizing F s to the delivery rate of basaltic magma suggests that ultraslow ridges are several times more efficient than faster-spreading ridges in supporting active vent fields. This increased efficiency could derive from some combination of three-dimensional magma focusing at volcanic centers, deep mining of heat from gabbroic intrusions and direct cooling of the upper mantle, and nonmagmatic heat supplied by exothermic serpentinization.This research was partially supported the NOAA VENTS Program. P.J.M. and H.J.B.D. gratefully acknowledge NSF grant OPP 9911795 for support of the AMORE Expedition; P.J.M. and E.T.B. acknowledge NSF grant OPP 0107767 and the VENTS Program for development and construction of MAPRs for use in ice-covered seas. H.J.B.D. acknowledges NSF grant OCE-9907630 for support of SWIR studies. J.E.S. was supported by Deutsche Forschungsgemeinschaft grant SN15/2

The Early Royal Society and Visual Culture

Recent studies have fruitfully examined the intersection between early modern science and visual culture by elucidating the functions of images in shaping and disseminating scientific knowledge. Given its rich archival sources, it is possible to extend this line of research in the case of the Royal Society to an examination of attitudes towards images as artefacts –manufactured objects worth commissioning, collecting and studying. Drawing on existing scholarship and material from the Royal Society Archives, I discuss Fellows’ interests in prints, drawings, varnishes, colorants, images made out of unusual materials, and methods of identifying the painter from a painting. Knowledge of production processes of images was important to members of the Royal Society, not only as connoisseurs and collectors, but also as those interested in a Baconian mastery of material processes, including a “history of trades”. Their antiquarian interests led to discussion of painters’ styles, and they gradually developed a visual memorial to an institution through portraits and other visual records.AH/M001938/1 (AHRC

Effects of Alzheimer's peptide and alpha 1-antichymotrypsin on astrocyte gene expression

We employed gene array technology to investigate the effects of alpha 1-antichymotrypsin (ACT), soluble or fibrillar Alzheimer's peptide (A beta(1-42)) alone and the combination of ACT/A beta(1-42) on human astrocytes. Using a 1.2-fold change as significance threshold, 398 astrocyte genes showed altered expression in response to these treatments compared to controls. Of the 276 genes affected by the ACT/soluble A beta(1-42) combination, 195 (70.6%) were suppressed. The ACT/fibrillar A beta(1-42) combination affected expression of 64 genes of which 58 (90.5%) were up-regulated. The most prominent gene expression changes in response to the ACT/soluble A beta(1-42), were the down-regulation of at least 60 genes involved in transcription, signal transduction, apoptosis and neurogenesis. The ACT/fibril A beta(1-42) increased the expression of genes involved in transcription regulation and signal transduction. Surprisingly, gene expression of astrocytes exposed to soluble or fibrillar A beta(1-42) alone was largely unaffected. Thus, the molecular forms generated by the combination of ACT/A beta(1-42) alter expression of astrocyte genes more profoundly in breadth and magnitude than soluble or fibrillar A beta(1-42) alone, suggesting that pathogenic effects of A beta(1-42) may occur as a consequence of its association with other proteins. (c) 2005 Elsevier Inc. All rights reserved

Assessment of Terrigenous Nutrient Loading to Coastal Ecosystems along a Human Land-Use Gradient, Tutuila, American Samoa

Anthropogenic nutrient loading is well recognized as a stressor to coastal ecosystem health. However, resource managers are often focused on addressing point source or surface water discharge, whereas the impact of submarine groundwater discharge (SGD) as a nutrient vector is often unappreciated. This study examines connections between land use and nutrient loading through comparison of four watersheds and embayments spanning a gradient of human use impact on Tutuila, a high tropical oceanic island in American Samoa. In each study location, coastal radon-222 measurements, dissolved nutrient concentrations, and nitrogen isotope values (δ15N) in water and in situ macroalgal tissue were used to explore SGD and baseflow derived nutrient impacts, and to determine probable nutrient sources. In addition to sampling in situ macroalgae, pre-treated macroalgal specimens were deployed throughout each embayment to uptake ambient nutrients and provide a standardized assessment of differences between locations. Results show SGD-derived nutrient flux was more significant than baseflow nutrient flux in all watersheds, and δ15N values in water and algae suggested wastewater or manure are likely sources of elevated nutrient levels. While nutrient loading correlated well with expected anthropogenic impact, other factors such as differences in hydrogeology, distribution of development, and wastewater infrastructure also likely play a role in the visibility of impacts in each watershed