Recipe for success — Lessons learnt from using xAPI within the Connected Learning Analytics toolkit

An ongoing challenge for Learning Analytics research has been the scalable derivation of user interaction data from multiple technologies. The complexities associated with this challenge are increasing as educators embrace an ever growing number of social and content related technologies. The Experience API (xAPI) alongside the development of user specific record stores has been touted as a means to address this challenge, but a number of subtle considerations must be made when using xAPI in Learning Analytics. This paper provides a general overview to the complexities and challenges of using xAPI in a general systemic analytics solution - called the Connected Learning Analytics (CLA) toolkit. The importance of design is emphasised, as is the notion of common vocabularies and xAPI Recipes. Early decisions about vocabularies and structural relationships between statements can serve to either facilitate or handicap later analytics solutions. The CLA toolkit case study provides us with a way of examining both the strengths and the weaknesses of the current xAPI specification, and we conclude with a proposal for how xAPI might be improved by using JSON-LD to formalise Recipes in a machine readable form.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

Oral medication delivery in impaired swallowing: Thickening liquid medications for safe swallowing alters dissolution characteristics

Acetaminophen (paracetamol) is available in a wide range of oral formulations designed to meet the needs of the population across the age-spectrum, but for people with impaired swallowing, i.e. dysphagia, both solid and liquid medications can be difficult to swallow without modification. The effect of a commercial polysaccharide thickener, designed to be added to fluids to promote safe swallowing by dysphagic patients, on rheology and acetaminophen dissolution was tested using crushed immediate-release tablets in water, effervescent tablets in water, elixir and suspension. The inclusion of the thickener, comprised of xanthan gum and maltodextrin, had a considerable impact on dissolution; acetaminophen release from modified medications reached 12-50% in 30 minutes, which did not reflect the pharmacopeia specification for immediate release preparations. Flow curves reflect the high zero-shear viscosity and the apparent yield stress of the thickened products. The weak gel nature, in combination with high G’ values compared to G” (viscoelasticity) and high apparent yield stress, impact drug release. The restriction on drug release from these formulations is not influenced by the theoretical state of the drug (dissolved or dispersed), and the approach typically used in clinical practice (mixing crushed tablets into pre-prepared thickened fluid) cannot be improved by altering the order of incorporation or mixing method.

The extremophile Nicotiana benthamiana has traded viral defence for early vigour

A single lineage of Nicotiana benthamiana is widely used as a model plant1 and has been instrumental in making revolutionary discoveries about RNA interference (RNAi), viral defence and vaccine production. It is peerless in its susceptibility to viruses and its amenability in transiently expressing transgenes2,3. These unparalleled characteristics have been associated both positively and negatively with a disruptive insertion in the RNA-dependent RNA polymerase 1 gene, Rdr14–6. For a plant so routinely used in research, the origin, diversity and evolution of the species, and the basis of its unusual abilities, have been relatively unexplored. Here, by comparison with wild accessions from across the spectrum of the species’ natural distribution, we show that the laboratory strain of N. benthamiana is an extremophile originating from a population that has retained a mutation in Rdr1 for ∼0.8 Myr and thereby traded its defence capacity for early vigour and survival in the extreme habitat of central Australia. Reconstituting Rdr1 activity in this isolate provided protection. Silencing the functional allele in a wild strain rendered it hypersusceptible and was associated with a doubling of seed size and enhanced early growth rate. These findings open the way to a deeper understanding of the delicate balance between protection and vigour.

Computation of confined swirling flow using RNG and k-epsilon turbulence models

In this work we numerically model isothermal turbulent swirling flow in a cylindrical burner. Three versions of the RNG k-epsilon model are assessed against performance of the standard k-epsilon model. Sensitivity of numerical predictions to grid refinement, differing convective differencing schemes and choice of (unknown) inlet dissipation rate, were closely scrutinised to ensure accuracy. Particular attention is paid to modelling the inlet conditions to within the range of uncertainty of the experimental data, as model predictions proved to be significantly sensitive to relatively small changes in upstream flow conditions. We also examine the characteristics of the swirl--induced recirculation zone predicted by the models over an extended range of inlet conditions. Our main findings are: - (i) the standard k-epsilon model performed best compared with experiment; - (ii) no one inlet specification can simultaneously optimize the performance of the models considered; - (iii) the RNG models predict both single-cell and double-cell IRZ characteristics, the latter both with and without additional internal stagnation points. The first finding indicates that the examined RNG modifications to the standard k-e model do not result in an improved eddy viscosity based model for the prediction of swirl flows. The second finding suggests that tuning established models for optimal performance in swirl flows a priori is not straightforward. The third finding indicates that the RNG based models exhibit a greater variety of structural behaviour, despite being of the same level of complexity as the standard k-e model. The plausibility of the predicted IRZ features are discussed in terms of known vortex breakdown phenomena.

Biofilm formation by multidrug resistant Escherichia coli ST131 is dependent on type 1 fimbriae and assay conditions.

Escherichia coli sequence type 131 (ST131) have emerged as a pandemic lineage of important multidrug resistant pathogens worldwide. Despite many studies examining the epidemiology of ST131, only a few studies to date have investigated the capacity of ST131 strains to form biofilms. Some of these studies have reported contrasting findings, with no specific ST131 biofilm-promoting factors identified. Here we examined a diverse collection of ST131 isolates for in vitro biofilm formation in different media and assay conditions, including urine from healthy adult women. We found significant differences among strains and assay conditions, which offers an explanation for the contrasting findings reported by previous studies using a single condition. Importantly, we showed that expression of type 1 fimbriae is a critical determinant for biofilm formation by ST131 strains and that inhibition of the FimH adhesin significantly reduces biofilm formation. We also offer direct genetic evidence for the contribution of type 1 fimbriae in biofilm formation by the reference ST131 strain EC958, a representative of the clinically dominant H30-Rx ST131 subgroup. This is the first study of ST131 biofilm formation in biologically relevant conditions and paves the way for the application of FimH inhibitors in treating drug resistant ST131 biofilm infections.

Supporting knowledge-intensive construction management tasks in BIM

The delivery of products and services for construction-based businesses is increasingly becoming knowledge-driven and information-intensive. The proliferation of building information modelling (BIM) has increased business opportunities as well as introduced new challenges for the architectural, engineering and construction and facilities management (AEC/FM) industry. As such, the effective use, sharing and exchange of building life cycle information and knowledge management in building design, construction, maintenance and operation assumes a position of paramount importance. This paper identifies a subset of construction management (CM) relevant knowledge for different design conditions of building components through a critical, comprehensive review of synthesized literature and other information gathering and knowledge acquisition techniques. It then explores how such domain knowledge can be formalized as ontologies and, subsequently, a query vocabulary in order to equip BIM users with the capacity to query digital models of a building for the retrieval of useful and relevant domain-specific information. The formalized construction knowledge is validated through interviews with domain experts in relation to four case study projects. Additionally, retrospective analyses of several design conditions are used to demonstrate the soundness (realism), completeness, and appeal of the knowledge base and query-based reasoning approach in relation to the state-of-the-art tools, Solibri Model Checker and Navisworks. The knowledge engineering process and the methods applied in this research for information representation and retrieval could provide useful mechanisms to leverage BIM in support of a number of knowledge intensive CM/FM tasks and functions.

Augmenting process elicitation with visual priming: An empirical exploration of user behaviour and modelling outcomes

Business process models have become an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach to process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions similarly to how they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. An empirical investigation comparing both the modelling outputs and participant behaviour of this virtual world role-play elicitor with an S-BPM process modelling tool found that while the modelling approaches of the two groups varied greatly, the virtual world elicitor may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

The phylogeny and evolutionary timescale of muscoide (Diptera: Brachycera: Calyptratae) inferred from mitochondrial genomes

Muscoidea is a significant dipteran clade that includes house flies (Family Muscidae), latrine flies (F. Fannidae), dung flies (F. Scathophagidae) and root maggot flies (F. Anthomyiidae). It is comprised of approximately 7000 described species. The monophyly of the Muscoidea and the precise relationships of muscoids to the closest superfamily the Oestroidea (blow flies, flesh flies etc) are both unresolved. Until now mitochondrial (mt) genomes were available for only two of the four muscoid families precluding a thorough test of phylogenetic relationships using this data source. Here we present the first two mt genomes for the families Fanniidae (Euryomma sp.) (family Fanniidae) and Anthomyiidae (Delia platura (Meigen, 1826)). We also conducted phylogenetic analyses containing of these newly sequenced mt genomes plus 15 other species representative of dipteran diversity to address the internal relationship of Muscoidea and its systematic position. Both maximum-likelihood and Bayesian analyses suggested that Muscoidea was not a monophyletic group with the relationship: (Fanniidae + Muscidae) + ((Anthomyiidae + Scathophagidae) + (Calliphoridae + Sarcophagidae)), supported by the majority of analysed datasets. This also infers that Oestroidea was paraphyletic in the majority of analyses. Divergence time estimation suggested that the earliest split within the Calyptratae, separating (Tachinidae + Oestridae) from the remaining families, occurred in the Early Eocene. The main divergence within the paraphyletic muscoidea grade was between Fanniidae + Muscidae and the lineage ((Anthomyiidae + Scathophagidae) + (Calliphoridae + Sarcophagidae)) which occurred in the Late Eocene