On the need for an international effort to capture, share and use crystallization screening data

When crystallization screening is conducted many outcomes are observed but typically the only trial recorded in the literature is the condition that yielded the crystal(s) used for subsequent diffraction studies. The initial hit that was optimized and the results of all the other trials are lost. These missing results contain information that would be useful for an improved general understanding of crystallization. This paper provides a report of a crystallization data exchange (XDX) workshop organized by several international large-scale crystallization screening laboratories to discuss how this information may be captured and utilized. A group that administers a significant fraction of the worlds crystallization screening results was convened, together with chemical and structural data informaticians and computational scientists who specialize in creating and analysing large disparate data sets. The development of a crystallization ontology for the crystallization community was proposed. This paper (by the attendees of the workshop) provides the thoughts and rationale leading to this conclusion. This is brought to the attention of the wider audience of crystallographers so that they are aware of these early efforts and can contribute to the process going forward. © 2012 International Union of Crystallography All rights reserved.

Compositional data analysis (CoDA) approaches to distance in information retrieval

Many techniques in information retrieval produce counts from a sample, and it is common to analyse these counts as proportions of the whole - term frequencies are a familiar example. Proportions carry only relative information and are not free to vary independently of one another: for the proportion of one term to increase, one or more others must decrease. These constraints are hallmarks of compositional data. While there has long been discussion in other fields of how such data should be analysed, to our knowledge, Compositional Data Analysis (CoDA) has not been considered in IR. In this work we explore compositional data in IR through the lens of distance measures, and demonstrate that common measures, naïve to compositions, have some undesirable properties which can be avoided with composition-aware measures. As a practical example, these measures are shown to improve clustering. Copyright 2014 ACM.

A data mining based method for discovery of web services and their compositions

Due to the availability of huge number of web services, finding an appropriate Web service according to the requirements of a service consumer is still a challenge. Moreover, sometimes a single web service is unable to fully satisfy the requirements of the service consumer. In such cases, combinations of multiple inter-related web services can be utilised. This paper proposes a method that first utilises a semantic kernel model to find related services and then models these related Web services as nodes of a graph. An all-pair shortest-path algorithm is applied to find the best compositions of Web services that are semantically related to the service consumer requirement. The recommendation of individual and composite Web services composition for a service request is finally made. Empirical evaluation confirms that the proposed method significantly improves the accuracy of service discovery in comparison to traditional keyword-based discovery methods.

Classification of inventory data suit for managing Australian railway bridges

With a focus to optimising the life cycle performance of Australian Railway bridges, new bridge classification and environmental classification systems are proposed. The new bridge classification system is mainly to facilitate the implementation of novel Bridge Management System (BMS) which optimise the life cycle cost both at project level and network level while environment classification is mainly to improve accuracy of Remaining Service Potential (RSP) module of the proposed BMS. In fact, limited capacity of the existing BMS to trigger the maintenance intervention point is an indirect result of inadequacies of the existing bridge and environmental classification systems. The proposed bridge classification system permits to identify the intervention points based on percentage deterioration of individual elements and maintenance cost, while allowing performance based rating technique to implement for maintenance optimisation and prioritisation. Simultaneously, the proposed environment classification system will enhance the accuracy of prediction of deterioration of steel components.

Soil moisture variability in a temperate deciduous forest: insights from electrical resistivity and throughfall data

Hydrogeophysics is a growing discipline that holds significant promise to help elucidate details of dynamic processes in the near surface, built on the ability of geophysical methods to measure properties from which hydrological and geochemical variables can be derived. For example, bulk electrical conductivity is governed by, amongst others, interstitial water content, fluid salinity, and temperature, and can be measured using a range of geophysical methods. In many cases, electrical resistivity tomography (ERT) is well suited to characterize these properties in multiple dimensions and to monitor dynamic processes, such as water infiltration and solute transport. In recent years, ERT has been used increasingly for ecosystem research in a wide range of settings; in particular to characterize vegetation-driven changes in root-zone and near-surface water dynamics. This increased popularity is due to operational factors (e.g., improved equipment, low site impact), data considerations (e.g., excellent repeatability), and the fact that ERT operates at scales significantly larger than traditional point sensors. Current limitations to a more widespread use of the approach include the high equipment costs, and the need for site-specific petrophysical relationships between properties of interest. In this presentation we will discuss recent equipment advances and theoretical and methodological aspects involved in the accurate estimation of soil moisture from ERT results. Examples will be presented from two studies in a temperate climate (Michigan, USA) and one from a humid tropical location (Tapajos, Brazil).

Do dissonants in transit oriented development adjust commuting travel behaviour?

Residential dissonance signifies a mismatch between an individual’s preferred and actual proximal land use patterns in residential neighbourhoods, whereas residential consonance signifies agreement between actual and preferred proximal land uses. Residential dissonance is a relatively unexplored theme in the literature, yet it acts as a barrier to the development of sustainable transport and land use policy. This research identifies mode choice behaviour of four groups living in transit oriented development (TOD) and non-TOD areas in Brisbane, Australia using panel data from 2675 commuters: TOD consonants, TOD dissonants, non-TOD consonants, and non-TOD dissonants. The research investigates a hypothetical understanding that dissonants adjust their travel attitudes and perceptions according to their surrounding land uses over time. The adjustment process was examined by comparing the commuting mode choice behaviour of dissonants between 2009 and 2011. Six binary logistic regression models were estimated, one for each of the three modes considered (e.g. public transport, active transport, and car) and one for each of the 2009 and 2011 waves. Results indicate that TOD dissonants and non-TOD consonants were less likely to use the public transport and active transport; and more likely to use the car compared with TOD consonants. Non-TOD dissonants use public transport and active transport equally to TOD consonants. The results suggest that commuting mode choice behaviour is largely determined by travel attitudes than built environment factors; however, the latter influence public transport and car use propensity. This research also supports the view that dissonants adjust their attitudes to surrounding land uses, but very slowly. Both place (e.g. TOD development) and people-based (e.g. motivational) policies are needed for an effective travel behavioural shift.

Establishing statistical foundations early : data modeling with young learners

This paper addresses research from a three-year longitudinal study that engaged children in data modeling experiences from the beginning school year through to third year (6-8 years). A data modeling approach to statistical development differs in several ways from what is typically done in early classroom experiences with data. In particular, data modeling immerses children in problems that evolve from their own questions and reasoning, with core statistical foundations established early. These foundations include a focus on posing and refining statistical questions within and across contexts, structuring and representing data, making informal inferences, and developing conceptual, representational, and metarepresentational competence. Examples are presented of how young learners developed and sustained informal inferential reasoning and metarepresentational competence across the study to become “sophisticated statisticians”.

Surveillance snapshot of Clostridium difficile infection in hospitals across Queensland detects binary toxin producing ribotype UK 244

In North America and Europe, the binary toxin positive Clostridium difficile strains of the ribotypes 027 and 078 have been associated with death, toxic megacolon and other adverse outcomes. Following an increase in C. difficile infections (CDIs) in Queensland, a prevalence study involving 175 hospitals was undertaken in early 2012, identifying 168 cases of CDI over a 2 month period. Patient demographics and clinical characteristics were recorded, and C. difficile isolates were ribotyped and tested for the presence of binary toxin genes. Most patients (106/168, 63.1%) were aged over 60 years. Overall, 98 (58.3%) developed symptoms after hospitalisation; 89 cases (53.0%) developed symptoms more than 48 hours after admission. Furthermore, 27 of the 62 (67.7%) patients who developed symptoms in the community ad been hospitalised within the last 3 months. Thirteen of the 168 (7.7%) cases identified had severe disease, resulting in admission to the Intensive Care Unit or death within 30 days of the onset of symptoms. The 3 most common ribotypes isolated were UK 002 (22.9%), UK 014 (13.3%) and the binary toxin-positive ribotype UK 244 (8.4%). The only other binary toxin positive ribotype isolated was UK 078 (n = 1). Of concern was the detection of the binary toxin positive ribotype UK 244, which has recently been described in other parts of Australia and New Zealand. No isolates were of the international epidemic clone of ribotype UK 027, although ribotype UK 244 is genetically related to this clone. Further studies are required to track the epidemiology of ribotype UK 244 in Australia and New Zealand. Commun Dis Intell 2014;38(4):E279–E284.

Structuring representations of continuous data through investigations in grade 1

The study of data modelling with elementary students involves the analysis of a developmental process beginning with children’s investigations of meaningful contexts: visualising, structuring, and representing data and displaying data in simple graphs (English, 2012; Lehrer & Schauble, 2005; Makar, Bakker, & Ben-Zvi, 2011). A 3-year longitudinal study investigated young children’s data modelling, integrating mathematical and scientific investigations. One aspect of this study involved a researcher-led teaching experiment with 21 mathematically able Grade 1 students. The study aimed to describe explicit developmental features of students’ representations of continuous data...

The BAD project: data mining, database and prediction of protein adsorption on surfaces

Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

Veracity of the archive : a research approach to the collection and verification of urban morphological records using qualitative data analysis software

Critical to the research of urban morphologists is the availability of historical records that document the urban transformation of the study area. However, thus far little work has been done towards an empirical approach to the validation of archival data in this field. Outlined in this paper, therefore, is a new methodology for validating the accuracy of archival records and mapping data, accrued through the process of urban morphological research, so as to establish a reliable platform from which analysis can proceed. The paper particularly addresses the problems of inaccuracies in existing curated historical information, as well as errors in archival research by student assistants, which together give rise to unacceptable levels of uncertainty in the documentation. The paper discusses the problems relating to the reliability of historical information, demonstrates the importance of data verification in urban morphological research, and proposes a rigorous method for objective testing of collected archival data through the use of qualitative data analysis software.