Creativity Bento Box: A Physical Resource Pack to Support Interaction in Virtual Space

The Creativity Bento Box is a physical resource pack, designed to support casual social interaction and break taking in an intensive, computer-mediated social activity. It was developed within the Creativity Greenhouse project, which piloted a mechanism to create research proposals and distribute funding at a distance. This involved facilitated phases of collaboration and competition over multiple days of computer-mediated work, where participants communicate and interact through a virtual world. During the iterative development process, the lack of time for socializing, the intense focus on virtual resources, and a lack of time spent away from the screen were reported as negative issues in feedback from participants. This article reports on the development of the Creativity Bento Box and how it helped to address these issues. By providing physical resources that contrasted with the properties of the virtual world, it supported people to socialize and take breaks from their primary activity, allowed them to include physical space and artifacts in their interactions, and provoked moves away from the otherwise intense focus on the computer. The article reflects on the roles of the Bento Box as a gift, in bridging between physical and virtual contexts, its higher suitability during the earlier phases of ideation and group development, and its perception by participants as something “framed.” Through this, we highlight the underexplored potential of using physical, offline resources as a means to solve difficulties in distanced social interactions.     

OXPath: A language for scalable data extraction, automation, and crawling on the deep web

The evolution of the web has outpaced itself: A growing wealth of information and increasingly sophisticated interfaces necessitate automated processing, yet existing automation and data extraction technologies have been overwhelmed by this very growth. To address this trend, we identify four key requirements for web data extraction, automation, and (focused) web crawling: (1) interact with sophisticated web application interfaces, (2) precisely capture the relevant data to be extracted, (3) scale with the number of visited pages, and (4) readily embed into existing web technologies. We introduce OXPath as an extension of XPath for interacting with web applications and extracting data thus revealed—matching all the above requirements. OXPath’s page-at-a-time evaluation guarantees memory use independent of the number of visited pages, yet remains polynomial in time. We experimentally validate the theoretical complexity and demonstrate that OXPath’s resource consumption is dominated by page rendering in the underlying browser. With an extensive study of sublanguages and properties of OXPath, we pinpoint the effect of specific features on evaluation performance. Our experiments show that OXPath outperforms existing commercial and academic data extraction tools by a wide margin.     

Kernel methods for software effort estimation

Analogy based estimation (ABE) generates an effort estimate for a new software project through adaptation of similar past projects (a.k.a. analogies). Majority of ABE methods follow uniform weighting in adaptation procedure. In this research we investigated non-uniform weighting through kernel density estimation. After an extensive experimentation of 19 datasets, 3 evaluation criteria, 5 kernels, 5 bandwidth values and a total of 2090 ABE variants, we found that: (1) non-uniform weighting through kernel methods cannot outperform uniform weighting ABE and (2) kernel type and bandwidth parameters do not produce a definite effect on estimation performance. In summary simple ABE approaches are able to perform better than much more complex approaches. Hence,—provided that similar experimental settings are adopted—we discourage the use of kernel methods as a weighting strategy in ABE.     

Restoration of stormwater retention capacity at the allotment-scale through a novel economic instrument

Urbanisation results in changes to runoff behaviour which, if not addressed, inevitably degrade receiving waters. To date, most stormwater management has focussed on the streetscape and public open space. Given that much of the catchment imperviousness is located on private land, we developed and tested a novel economic instrument (a uniform price auction) for encouraging allotment-scale stormwater retention. We evaluated bids using an integrated environmental benefit index (EBI), based on the ability of the proposed works to reduce runoff frequency, pollutant loads and to reduce potable water demand. The uniform price auction resulted in 1.4 ha of impervious areas being effectively 'disconnected' from the stormwater system. The EBI provided an objective and transparent method of comparing bids, which varied in the type of works proposed (e.g. rainwater tank, rain-garden), the cost and the resulting environmental benefit. Whilst the pilot auction was a success, the public subsidy of works undertaken was around 85%, meaning that property owners a relatively small private benefit in the works. Future auction rounds will be revised to (i) test an EBI which is more focussed on the protection of streams (assessing changes to runoff frequency, baseflow volumes and water quality) and (ii) provide an auction process which is simpler to understand, and provides greater practical support for landholders who wish to undertake works.     

Real-time control of sewer systems using turbidity measurements

Real-time control (RTC) of urban drainage systems has been proven useful as a means to reduce pollution by combined sewer overflow discharges. So far, RTC has been investigated mainly with a sole focus on water quantity aspects. However, as measurement techniques for pollution of wastewater are advancing, pollution-based RTC might be of increasing interest. For example, turbidity data sets from an extensive measurement programme in two Paris catchments allow a detailed investigation of the benefits of using pollution-based data for RTC. This paper exemplifies this, comparing pollution-based RTC with flow-based RTC. Results suggest that pollution-based RTC indeed has some potential, particularly when measurements of water-quality characteristics are readily available.     

Evaluation of realtime people tracking for indoor environments using ubiquitous motion sensors and limited wireless network infrastructure

We present the development and evaluation of a realtime indoor localisation system for tracking people. Our aim was to track a person’s indoor position using dead-reckoning, while limiting position error without depending on extensive wireless network infrastructure. The Indoor People Tracker used wearable motion sensors, a floor-plan map and a limited wireless sensor network for proximity ranging. We evaluated how the position accuracy of the Indoor People Tracker was affected by floor-plan map features, wireless proximity range and motion information. The advantage of the Indoor People Tracker was found; it was able to achieve accurate position resolution with minimal error, while not depending on wireless proximity.     

The impact of misregistration on SRTM and DEM image differences

Image differences between Shuttle Radar Topography Mission (SRTM) data and other Digital Elevation Models (DEMs) are often performed for either accuracy assessment or for estimating vegetation height across the landscape. It has been widely assumed that the effect of sub-pixel misregistration between the two models on resultant image differences is negligible, yet this has not previously been tested in detail. The aim of this study was to determine the impact that various levels of misregistration have on image differences between SRTM and DEMs. First, very accurate image co-registration was performed at two study sites between higher resolution DEMs and SRTM data, and then image differences (SRTM–DEM) were performed after various levels of misregistration were systematically introduced into the SRTM data. It was found that: (1) misregistration caused an erroneous and dominant correlation between elevation difference and aspect across the landscape; (2) the direction of the misregistration defined the direction of this erroneous and systematic elevation difference; (3) for sub-pixel misregistration the error due solely to misregistration was greater than, or equal to the true difference between the two models for substantial proportions of the landscape (e.g., greater than 33% of the area for a half-pixel misregistration); and (4) the strength of the erroneous relationship with aspect was enhanced by steeper terrain. Spatial comparisons of DEMs were found to be sensitive to even sub-pixel misregistration between the two models, which resulted in a strong erroneous correlation with aspect. This misregistration induced correlation with aspect is not likely specific to SRTM data only; we expect it to be a generic relationship present in any DEM image difference analysis.     

Aberrant protein expression in plasma and kidney tissue during experimental obstructive nephropathy

Kidney failure is a major health problem worldwide. Patients with end-stage renal disease require intensive medical support by dialysis or kidney transplantation. Current methods for diagnosis of kidney disease are either invasive or insensitive, and renal function may decline by as much as 50% before it can be detected using current techniques. The goal of this study was, therefore, to identify biomarkers of kidney disease (associated with renal fibrosis) that can be used for the development of a non-invasive clinical test for early disease detection. We utilized two protein-profiling technologies (SELDI-TOF MS and 2-D) to screen the plasma and kidney proteome for aberrantly expressed proteins in an experimental mouse model of unilateral uretric obstruction, which mimics the pathology of human renal disease. Several differentially regulated proteins were detected at the plasma level of day-3-obstructed animals, which included serum amyloid A1, fibrinogen α, haptoglobin precursor protein, haptoglobin and major urinary proteins 11 and 8. Differentially expressed proteins detected at the tissue level included ras-like activator protein 2, haptoglobin precursor protein, malate dehydrogenase, α enolase and murine urinary protein (all p<0.05 versus controls). Immunohistochemistry was used to confirm the up-regulation of fibrinogen. Interestingly, these proteins are largely separated into four major classes: (i) acute-phase reactants (ii) cell-signaling molecules (iii) molecules involved in cell growth and metabolism and (iv) urinary proteins. These results provide new insights into the pathology of obstructive nephropathy and may facilitate the development of specific assay(s) to detect and monitor renal fibrosis.     

Evaluation of a type 1 diabetes serum cohort by SELDI-TOF MS protein profiling

Proteomics analysis of serum from patients with type 1 diabetes (T1D) may lead to novel biomarkers for prediction of disease and for patient monitoring. However, the serum proteome is highly sensitive to sample processing and before proteomics biomarker research serum cohorts should preferably be examined for potential bias between sample groups. SELDI‐TOF MS protein profiling was used for preliminary evaluation of a biological‐bank with 766 serum samples from 270 patients with T1D, collected at 18 different paediatric centers representing 15 countries in Europe and Japan over 2 years (2000–2002). Samples collected 1 (n = 270), 6 (n = 248), and 12 (n = 248) months after T1D diagnosis were grouped across centers and compared. The serum protein profiles varied with collection site and day of analysis; however, markers of sample processing were not systematically different between samples collected at different times after diagnosis. Three members of the apolipoprotein family increased with time in patient serum collected 1, 6, and 12 months after diagnosis (ANOVA, p<0.001). These results support the use of this serum cohort for further proteomic studies and illustrate the potential of high‐throughput MALDI/SELDI‐TOF MS protein profiling for evaluation of serum cohorts before proteomics biomarker research.