Delay tolerant routing protocols for energy-neutral animal tracking

This paper investigates communication protocols for relaying sensor data from animal tracking applications back to base stations. While Delay Tolerant Networks (DTNs) are well suited to such challenging environments, most existing protocols do not consider the available energy that is particularly important when tracking devices can harvest energy. This limits both the network lifetime and delivery probability in energy-constrained applications to the point when routing performance becomes worse than using no routing at all. Our work shows that substantial improvement in data yields can be achieved through simple yet efficient energy-aware strategies. Conceptually, there is need for balancing the energy spent on sensing, data mulling, and delivery of direct packets to destination. We use empirical traces collected in a flying fox (fruit bat) tracking project and show that simple threshold-based energy-aware strategies yield up to 20% higher delivery rates. Furthermore, these results generalize well for a wide range of operating conditions.

Wear particle analysis and the evolution of the plastically deformed layer on Australian rail steel

Particle analysis methodology is presented, together with the morphology of the wear debris formed during rolling contact fatigue. Wear particles are characterised by their surface topography and in terms of wear mechanism. Rail-wheel materials are subjected to severe plastic deformation as the contact loading progresses, which contributes to a mechanism of major damage in head-hardened rail steel. Most of the current methodologies involve sectioning of the rail-wheel discs to trace material damage phenomena such as crack propagation and plastic strain accumulation. This paper proposes methodology to analyse the development of the plastically deformed layer by sectioning wear particles using the focussed ion beam (FIB) milling method. Moreover, it highlights the processes of oxidation and rail surface delamination during unlubricated rolling contact fatigue.

Flow evaluation and hemolysis analysis of BVAD centrifugal blood pump by computational fluids dynamics

Computational fluid dynamics (CFD) and particle image velocimetry (PIV) are commonly used techniques to evaluate the flow characteristics in the development stage of blood pumps. CFD technique allows rapid change to pump parameters to optimize the pump performance without having to construct a costly prototype model. These techniques are used in the construction of a bi-ventricular assist device (BVAD) which combines the functions of LVAD and RVAD in a compact unit. The BVAD construction consists of two separate chambers with similar impellers, volutes, inlet and output sections. To achieve the required flow characteristics of an average flow rate of 5 l/min and different pressure heads (left – 100mmHg and right – 20mmHg), the impellers were set at different rotating speeds. From the CFD results, a six-blade impeller design was adopted for the development of the BVAD. It was also observed that the fluid can flow smoothly through the pump with minimum shear stress and area of stagnation which are related to haemolysis and thrombosis. Based on the compatible Reynolds number the flow through the model was calculated for the left and the right pumps. As it was not possible to have both the left and right chambers in the experimental model, the left and right pumps were tested separately.

Document timespan normalisation and understanding temporality for clinical records search

Previous qualitative research has highlighted that temporality plays an important role in relevance for clinical records search. In this study, an investigation is undertaken to determine the effect that the timespan of events within a patient record has on relevance in a retrieval scenario. In addition, based on the standard practise of document length normalisation, a document timespan normalisation model that specifically accounts for timespans is proposed. Initial analysis revealed that in general relevant patient records tended to cover a longer timespan of events than non-relevant patient records. However, an empirical evaluation using the TREC Medical Records track supports the opposite view that shorter documents (in terms of timespan) are better for retrieval. These findings highlight that the role of temporality in relevance is complex and how to effectively deal with temporality within a retrieval scenario remains an open question.

Automated categorisation of patent claims that reference human genome sequences

Debates on gene patents have necessitated the analysis of patents that disclose and reference human sequences. In this study, we built an automated classifier that assigns sequences to one of nine predefined categories according to their functional roles in patent claims by applying natural language processing and supervised learning techniques. To improve its correctness, we experimented with various feature mappings, resulting in the maximal accuracy of 79%.

Programming: Reading, writing and reversing

In this paper, we look at the concept of reversibility, that is, negating opposites, counterbalances, and actions that can be reversed. Piaget identified reversibility as an indicator of the ability to reason at a concrete operational level. We investigate to what degree novice programmers manifest the ability to work with this concept of reversibility by providing them with a small piece of code and then asking them to write code that undoes the effect of that code. On testing entire cohorts of students in their first year of learning to program, we found an overwhelming majority of them could not cope with such a concept. We then conducted think aloud studies of novices where we observed them working on this task and analyzed their contrasting abilities to deal with it. The results of this study demonstrate the need for better understanding our students' reasoning abilities, and a teaching model aimed at that level of reality.

Medical free-text to concept mapping as an information retrieval problem

Concept mapping involves determining relevant concepts from a free-text input, where concepts are defined in an external reference ontology. This is an important process that underpins many applications for clinical information reporting, derivation of phenotypic descriptions, and a number of state-of-the-art medical information retrieval methods. Concept mapping can be cast into an information retrieval (IR) problem: free-text mentions are treated as queries and concepts from a reference ontology as the documents to be indexed and retrieved. This paper presents an empirical investigation applying general-purpose IR techniques for concept mapping in the medical domain. A dataset used for evaluating medical information extraction is adapted to measure the effectiveness of the considered IR approaches. Standard IR approaches used here are contrasted with the effectiveness of two established benchmark methods specifically developed for medical concept mapping. The empirical findings show that the IR approaches are comparable with one benchmark method but well below the best benchmark.

A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.

Situated interfaces for engaging citizens on the go

Insights Live screening and playfulness of the interactive space can be effective strategies for attracting the attention of passers-by and turn them into active participants. While urban screen interfaces increase participation by encouraging group interaction, privately-oriented tangible user interfaces give people a longer time to reflect upon their answers.

Improving factory performance using an integrated sugar factory model

A whole of factory model of a raw sugar factory was developed in SysCAD software to assess and improve factory operations. The integrated sugar factory model ‘Sugar-SysCAD’ includes individual models for milling, heating and clarification, evaporation, crystallisation, steam cycle, sugar dryer and process and injection water circuits. These individual unit operation models can be either used as standalone models to optimise the unit operation or in the integrated mode to provide more accurate prediction of the effects of changes in any part of the process on the outputs of the whole factory process. Using the integrated sugar factory model, the effect of specific process operations can be understood and practical solutions can be determined to address process problems. The paper presents two factory scenarios to show the capabilities of the whole of factory model.

Target acquired: Progress and promise of targeted therapeutics in the treatment of prostate cancer

Cancer is fundamentally a genomic disease caused by mutations or rearrangements in the DNA or epigenetic machinery of a patient. An emerging field in cancer treatment targets key aberrations arising from the mutational landscape of an individual patient’s disease rather than employing a cancer-wide cytotoxic therapy approach. In prostate cancer in particular, where there is an observed variation in response to standard treatments between patients with disease of a similar pathological stage and grade, mutationdirected treatment may grow to be a viable tool for clinicians to tailor more effective treatments. This review will describe a number of mutations across multiple forms of cancer that have been successfully antagonised by targeted therapeutics including their identification, the development of targeted compounds to combat them and the development of resistance to these therapies. This review will continue to examine these same mutations in the treatment and management of prostate cancer; the prevalence of targetable mutations in prostate cancer, recent clinical trials of targeted-agents and the potential or limitations for their use.

Determination of refractive and volatile elements in sediment using laser ablation inductively coupled plasma mass spectrometry

Wet-milling protocol was employed to produce pressed powder tablets with excellent cohesion and homogeneity suitable for laser ablation (LA) analysis of volatile and refractive elements in sediment. The influence of sample preparation on analytical performance was also investigated, including sample homogeneity, accuracy and limit of detection. Milling in volatile solvent for 40 min ensured sample is well mixed and could reasonably recover both volatile (Hg) and refractive (Zr) elements. With the exception of Cr (−52%) and Nb (+26%) major, minor and trace elements in STSD-1 and MESS-3 could be analysed within ±20% of the certified values. Comparison of the method with total digestion method using HF was tested by analysing 10 different sediment samples. The laser method recovers significantly higher amounts of analytes such as Ag, Cd, Sn and Sn than the total digestion method making it a more robust method for elements across the periodic table. LA-ICP-MS also eliminates the interferences from chemical reagents as well as the health and safety risks associated with digestion processes. Therefore, it can be considered as an enhanced method for the analysis of heterogeneous matrices such as river sediments.

Fusion transcript loci share many genomic features with non-fusion loci

Background Fusion transcripts are found in many tissues and have the potential to create novel functional products. Here, we investigate the genomic sequences around fusion junctions to better understand the transcriptional mechanisms mediating fusion transcription/splicing. We analyzed data from prostate (cancer) cells as previous studies have shown extensively that these cells readily undergo fusion transcription. Results We used the FusionMap program to identify high-confidence fusion transcripts from RNAseq data. The RNAseq datasets were from our (N = 8) and other (N = 14) clinical prostate tumors with adjacent non-cancer cells, and from the LNCaP prostate cancer cell line that were mock-, androgen- (DHT), and anti-androgen- (bicalutamide, enzalutamide) treated. In total, 185 fusion transcripts were identified from all RNAseq datasets. The majority (76 %) of these fusion transcripts were ‘read-through chimeras’ derived from adjacent genes in the genome. Characterization of sequences at fusion loci were carried out using a combination of the FusionMap program, custom Perl scripts, and the RNAfold program. Our computational analysis indicated that most fusion junctions (76 %) use the consensus GT-AG intron donor-acceptor splice site, and most fusion transcripts (85 %) maintained the open reading frame. We assessed whether parental genes of fusion transcripts have the potential to form complementary base pairing between parental genes which might bring them into physical proximity. Our computational analysis of sequences flanking fusion junctions at parental loci indicate that these loci have a similar propensity as non-fusion loci to hybridize. The abundance of repetitive sequences at fusion and non-fusion loci was also investigated given that SINE repeats are involved in aberrant gene transcription. We found few instances of repetitive sequences at both fusion and non-fusion junctions. Finally, RT-qPCR was performed on RNA from both clinical prostate tumors and adjacent non-cancer cells (N = 7), and LNCaP cells treated as above to validate the expression of seven fusion transcripts and their respective parental genes. We reveal that fusion transcript expression is similar to the expression of parental genes. Conclusions Fusion transcripts maintain the open reading frame, and likely use the same transcriptional machinery as non-fusion transcripts as they share many genomic features at splice/fusion junctions.

Introducing a new limit states design concept to railway concrete sleepers: An Australian experience

Over 50 years, a large number of research and development projects with respect to the use of cementitious and concrete materials for manufacturing railway sleepers have been significantly progressed in Australia, Europe, and Japan (Wang, 1996; Murray and Cai, 1998; Wakui and Okuda, 1999; Esveld, 2001; Freudenstein and Haban, 2006; Remennikov and Kaewunruen, 2008). Traditional sleeper materials are timber, steel, and concrete. Cost-efficiency, superior durability, and improved track stability are the main factors toward significant adoption of concrete materials for railway sleepers. The sleepers in a track system, as shown in Figure 1, are subjected to harsh and aggressive external forces and natural environments across a distance. Many systemic problems and technical issues associated with concrete sleepers have been tackled over decades. These include pre-mature failures of sleepers, concrete cancer or ettringite, abrasion of railseats and soffits, impact damages by rail machinery, bond-slip damage, longitudinal and lateral instability of track system, dimensional instability of sleepers, nuisance noise and vibration, and so on (Pfeil, 1997; Gustavson, 2002; Kaewunruen and Remennikov, 2008a,b, 2013). These issues are, however, becoming an emerging risk for many countries (in North and South Americas, Asia, and the Middle East) that have recently installed large volumes of concrete sleepers in their railway networks (Federal Railroad Administration, 2013). As a result, it is vital to researchers and practitioners to critically review and learn from previous experience and lessons around the world.

Design and Development of an In-Vehicle Human Machine Interface to Improve Fuel Efficiency & Safety

Road transport plays a significant role in various industries and mobility services around the globe and has a vital impact on our daily lives. However it also has serious impacts on both public health and the environment. In-vehicle feedback systems are a relatively new approach to encouraging driver behaviour change for improving fuel efficiency and safety in automotive environments. While many studies claim that the adoption of eco-driving practices, such as eco-driving training programs and in-vehicle feedback to drivers, has the potential to improve fuel efficiency, limited research has integrated safety and eco-driving. Therefore, this research seeks to use human factors related theories and practices to inform the design and evaluation of an in-vehicle Human Machine Interface (HMI) providing real-time driver feedback with the aim of improving both fuel efficiency and safety.