SiC-like phase and room-temperature photoluminescence of low-k SiOCH films

Carbon-doped hydrogenated silicon oxide (SiOCH) low-k films have been prepared using 13.56 MHz discharge in trimethylsilane (3MS) - oxygen gas mixtures at 3, 4, and 5 Torr sustained with RF power densities 1.3 - 2.6 W/cm2. The atomic structure of the SiOCH films appears to be a mixture the amorphous SiO2-like and the partially polycrystalline SiC-like phases. Results of the infra-red spectroscopy reflect the increment in the volume fraction of the SiC-like phase from 0.22 - 0.28 to 0.36 - 0.39 as the RF power increment. Steady-state near-UV laser-excited (364 nm wavelength, 40±2 mW) photoluminescence (PL) has been studied at room temperatures in the visible (1.8 eV - 3.1 eV) subrange of photon spectrum. Two main bands of the PL signal (at the photon energies of 2.5 - 2.6 eV and 2.8 - 2.9 eV) are observed. Intensities of the both bands are changed monotonically with RF power, whereas the bandwidth of ∼0.1 eV remains almost invariable. It is likely that the above lines are dumped by the non-radiative recombination involving E1-like centres in the amorphous-nanocrystalline SiC-like phases. Such explanation of the PL intensity dependences on the RF power density is supported by results of experimental studies of defect states spectrum in bandgap of the SiOCH films.

Differential subcellular and extracellular localisations of proteins required for insulin-like growth factor- and extracellular matrix-induced signalling events in breast cancer progression

Background: Cancer metastasis is the main contributor to breast cancer fatalities as women with the metastatic disease have poorer survival outcomes than women with localised breast cancers. There is an urgent need to develop appropriate prognostic methods to stratify patients based on the propensities of their cancers to metastasise. The insulin-like growth factor (IGF)-I:IGF binding protein (IGFBP):vitronectin complexes have been shown to stimulate changes in gene expression favouring increased breast cancer cell survival and a migratory phenotype. We therefore investigated the prognostic potential of these IGF- and extracellular matrix (ECM) interaction-induced proteins in the early identification of breast cancers with a propensity to metastasise using patient-derived tissue microarrays. Methods: Semiquantitative immunohistochemistry analyses were performed to compare the extracellular and subcellular distribution of IGF- and ECM-induced signalling proteins among matched normal, primary cancer and metastatic cancer formalin-fixed paraffin-embedded breast tissue samples. Results: The IGF- and ECM-induced signalling proteins were differentially expressed between subcellular and extracellular localisations. Vitronectin and IGFBP-5 immunoreactivity was lower while β1 integrin immunoreactivity was higher in the stroma surrounding metastatic cancer tissues, as compared to normal breast and primary cancer stromal tissues. Similarly, immunoreactive stratifin was found to be increased in the stroma of primary as well as metastatic breast tissues. Immunoreactive fibronectin and β1 integrin was found to be highly expressed at the leading edge of tumours. Based on the immunoreactivity it was apparent that the cell signalling proteins AKT1 and ERK1/2 shuffled from the nucleus to the cytoplasm with tumour progression. Conclusion: This is the first in-depth, compartmentalised analysis of the distribution of IGF- and ECM-induced signalling proteins in metastatic breast cancers. This study has provided insights into the changing pattern of cellular localisation and expression of IGF- and ECM-induced signalling proteins in different stages of breast cancer. The differential distribution of these biomarkers could provide important prognostic and predictive indicators that may assist the clinical management of breast disease, namely in the early identification of cancers with a propensity to metastasise, and/or recur following adjuvant therapy.

Mission path planning of aerial survey tasks using hybrid game evolutionary algorithm

The work presented in this report is aimed to implement a cost-effective offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. Understandably, the objectives of a practical optimisation problem are conflicting each other and the minimisation of one of them necessarily implies the impossibility to minimise the other ones. This leads to the need to find a set of optimal solutions for the problem; once such a set of available options is produced, the mission planning problem is reduced to a decision making problem for the mission specialists, who will choose the solution which best fit the requirements of the mission. The goal of this work is then to develop a Multi-Objective optimisation tool able to provide the mission specialists a set of optimal solutions for the inspection task amongst which the final trajectory will be chosen, given the environment data, the mission requirements and the definition of the objectives to minimise. All the possible optimal solutions of a Multi-Objective optimisation problem are said to form the Pareto-optimal front of the problem. For any of the Pareto-optimal solutions, it is impossible to improve one objective without worsening at least another one. Amongst a set of Pareto-optimal solutions, no solution is absolutely better than another and the final choice must be a trade-off of the objectives of the problem. Multi-Objective Evolutionary Algorithms (MOEAs) are recognised to be a convenient method for exploring the Pareto-optimal front of Multi-Objective optimization problems. Their efficiency is due to their parallelism architecture which allows to find several optimal solutions at each time

Author response to : Brough et al. in response to the recently published article : Lottering,N., MacGregor,D.M.,Barry,M.D.,Reynolds,M.S., Gregory,L.S., 2014. Introducing standardized protocols for anthropological measurement of virtual sub-adult crania using computed tomography 2(1),34–38

Firstly, we would like to thank Ms. Alison Brough and her colleagues for their positive commentary on our published work [1] and their appraisal of our utility of the “off-set plane” protocol for anthropometric analysis. The standardized protocols described in our manuscript have wide applications, ranging from forensic anthropology and paleodemographic research to clinical settings such as paediatric practice and orthopaedic surgical design. We affirm that the use of geometrically based reference tools commonly found in computer aided design (CAD) programs such as Geomagic Design X® are imperative for more automated and precise measurement protocols for quantitative skeletal analysis. Therefore we stand by our recommendation of the use of software such as Amira and Geomagic Design X® in the contexts described in our manuscript...

Large-scale analysis of soccer matches using spatiotemporal tracking data

Although the collection of player and ball tracking data is fast becoming the norm in professional sports, large-scale mining of such spatiotemporal data has yet to surface. In this paper, given an entire season's worth of player and ball tracking data from a professional soccer league (approx 400,000,000 data points), we present a method which can conduct both individual player and team analysis. Due to the dynamic, continuous and multi-player nature of team sports like soccer, a major issue is aligning player positions over time. We present a "role-based" representation that dynamically updates each player's relative role at each frame and demonstrate how this captures the short-term context to enable both individual player and team analysis. We discover role directly from data by utilizing a minimum entropy data partitioning method and show how this can be used to accurately detect and visualize formations, as well as analyze individual player behavior.

Determination of l-dopa using electropolymerized 3,3′,3″,3‴-tetraaminophthalocyanatonickel(II) film on glassy carbon electrode

Electropolymerized film of 3,3′,3″,3‴-tetraaminophthalocyanatonickel(II) (p-NiIITAPc) on glassy carbon (GC) electrode was used for the selective and stable determination of 3,4-dihydroxy-l-phenylalanine (l-dopa) in acetate buffer (pH 4.0) solution. Bare GC electrode fails to determine the concentration of l-dopa accurately in acetate buffer solution due to the cyclization reaction of dopaquinone to cyclodopa in solution. On the other hand, p-NiIITAPc electrode successfully determines the concentration of l-dopa accurately because the cyclization reaction was prevented at this electrode. It was found that the electrochemical reaction of l-dopa at the modified electrode is faster than that at the bare GC electrode. This was confirmed from the higher heterogeneous electron transfer rate constant (k0) of l-dopa at p-NiIITAPc electrode (3.35 × 10−2 cm s−1) when compared to that at the bare GC electrode (5.18 × 10−3 cm s−1). Further, it was found that p-NiIITAPc electrode separates the signals of ascorbic acid (AA) and l-dopa in a mixture with a peak separation of 220 mV. Lowest detection limit of 100 nM was achieved at the modified electrode using amperometric method. Common physiological interferents like uric acid, glucose and urea does not show any interference within the potential window of l-dopa oxidation. The present electrode system was also successfully applied to estimate the concentration of l-dopa in the commercially available tablets.

Small and medium enterprises using software as a service : exploring the different roles of intermediaries

Software as a Service (SaaS) can provide significant benefits to small and medium enterprises (SMEs) due to advantages like ease of access, 7*24 availability, and utility pricing. However, underlying the SaaS delivery model is often the assumption that SMEs will directly interact with the SaaS vendor and use a self-service approach. In practice, we see the rise of SaaS intermediaries who can support SMEs with sourcing and leveraging SaaS. This paper reports on the roles of intermediaries and how they support SMEs with using SaaS. We conducted an empirical study of two SaaS intermediaries and analysed their business models, in particular their value propositions. We identified orientation (technology or customer) and alignment (operational or strategic) as themes for understanding their roles. The contributions of this paper include: (1) the identification and description of SaaS intermediaries for SMEs based on an empirical study and (2) understanding the different roles of SaaS intermediaries, in particular a more basic role based on technology orientation and operational alignment and a more value adding role based on customer orientation and strategic alignment. We propose that SaaS intermediaries can address SaaS adoption and implementation challenges of SMEs by playing a basic role and can also aim to support SMEs in creating business value with SaaS based solutions by playing an added value role.

Pollen image classification using the classifynder system: Algorithm comparison and a case study on New Zealand honey

We describe an investigation into how Massey University’s Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University’s pollen reference collection (2,890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set.We additionally work through a real world case study where we assess the ability of the system to determine the pollen make-up of samples of New Zealand honey. In addition to the Classifynder’s native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples.

Spectrophotometric analysis of phenols, which involves a hemin-graphene hybrid nanoparticles with peroxidase-like activity

Phenols are well known noxious compounds, which are often found in various water sources. A novel analytical method has been researched and developed based on the properties of hemin–graphene hybrid nanosheets (H–GNs). These nanosheets were synthesized using a wet-chemical method, and they have peroxidase-like activity. Also, in the presence of H2O2, the nanosheets are efficient catalysts for the oxidation of the substrate, 4-aminoantipine (4-AP), and the phenols. The products of such an oxidation reaction are the colored quinone-imines (benzodiazepines). Importantly, these products enabled the differentiation of the three common phenols – pyrocatechol, resorcin and hydroquinone, with the use of a novel, spectroscopic method, which was developed for the simultaneous determination of the above three analytes. This spectroscopic method produced linear calibrations for the pyrocatechol (0.4–4.0 mg L−1), resorcin (0.2–2.0 mg L−1) and hydroquinone (0.8–8.0 mg L−1) analytes. In addition, kinetic and spectral data, obtained from the formation of the colored benzodiazepines, were used to establish multi-variate calibrations for the prediction of the three phenol analytes found in various kinds of water; partial least squares (PLS), principal component regression (PCR) and artificial neural network (ANN) models were used and the PLS model performed best.

Using DNA as a drug - bioprocessing and delivery strategies

DNA may take a leading role in a future generation of blockbuster therapeutics. DNA has inherent advantages over other biomolecules such as protein, RNA and virus-like particles including safety, production simplicity and higher stability at ambient temperatures. Vaccination is the principal measure for preventing influenza and reducing the impact of pandemics; however, vaccines take up to 8-9 months to produce, and the global production capacity is woefully low. With production times as short as 2 weeks, improved safety and stability, bioprocess engineering developments, and the ability to perform numerous therapeutic roles, DNA has the potential to meet the demands of emerging and existing diseases. DNA is experiencing sharp growths in demand as indicated by its use in gene therapy trials and DNA vaccine related patents. Of particular interest for therapeutic use is plasmid DNA (pDNA), a form of non-genomic DNA that makes use of cellular machinery to express proteins or antigens. The production stages of fermentation and downstream purification are considered in this article. Forward looking approaches to purifying and delivering DNA are reported, including affinity chromatography and nasal inhalation. The place that pDNA may take in the preparation for and protection against pandemics is considered. If DNA therapeutics and vaccines prove to be effective, the ultimate scale of production will be huge which shall require associated bioprocess engineering research and development for purification of this large, unique biomolecule.

Representing team behaviours from noisy data using player role

Due to their unobtrusive nature, vision-based approaches to tracking sports players have been preferred over wearable sensors as they do not require the players to be instrumented for each match. Unfortunately however, due to the heavy occlusion between players, variation in resolution and pose, in addition to fluctuating illumination conditions, tracking players continuously is still an unsolved vision problem. For tasks like clustering and retrieval, having noisy data (i.e. missing and false player detections) is problematic as it generates discontinuities in the input data stream. One method of circumventing this issue is to use an occupancy map, where the field is discretised into a series of zones and a count of player detections in each zone is obtained. A series of frames can then be concatenated to represent a set-play or example of team behaviour. A problem with this approach though is that the compressibility is low (i.e. the variability in the feature space is incredibly high). In this paper, we propose the use of a bilinear spatiotemporal basis model using a role representation to clean-up the noisy detections which operates in a low-dimensional space. To evaluate our approach, we used a fully instrumented field-hockey pitch with 8 fixed high-definition (HD) cameras and evaluated our approach on approximately 200,000 frames of data from a state-of-the-art real-time player detector and compare it to manually labeled data.

Developing a three-dimensional in-vitro cell culture model for studying breast and prostate cancer using starPEG-heparin hydrogels

Introduction Hydrogels prepared from poly(ethylene glycol) (PEG) and maleimide-functionalized heparin provide a potential matrix for use in developing three dimensional (3D) models. We have previously demonstrated that these hydrogels support the cultivation of human umbilical vein endothelial cells (HUVECs) (1). We extend this body of work to study the ability to create an extracellular matrix (ECM)-like model to study breast and prostate cancer cell growth in 3D. Also, we investigate the ability to produce a tri-culture mimicking tumour angiogenesis with cancer spheroids, HUVECs and mesenchymal stem cells (MSC). Materials and Methods The breast cancer cell lines, MCF-7 and MDA-MB-231, and prostate cancer cell lines, LNCaP and PC3, were seeded into starPEG-heparin hydrogels and grown for 14 Days to analyse the effects of varying hydrogel stiffness on spheroid development. Resulting hydrogel constructs were analyzed via Alamar Blue assays, light microscopy, and immunofluorescence staining for cytokeratin 8/18, Ki67 and E-Cadherin. Cancer cell lines were then pre-grown in hydrogels for 5-7 days and then re-seeded into starPEG-heparin hydrogels functionalised with RGD, SDF-1, bFGF and VEGF as spheroids with HUVECs and MSC and grown for 14 days as a tri-culture in Endothelial Cell Growth Medium (ECGM; Promocell). Cell lines were also seeded as a single cell suspension into the functionalised tri-culture system. Cultures were fixed in 4% paraformaldehyde and analysed via immunostaining for Von Willebrand Factor and CD31, as well as the above mentioned markers, and observed using confocal microscopy. Results Cultures prepared in MMP-cleavable starPEG-heparin hydrogels display spheroid formation in contrast to adherent growth on tissue culture plastic. Small differences were visualised in cancer spheroid growth between different gel stiffness across the range of cell lines. Cancer cell lines were able to be co-cultivated with HUVECs and MSC. HUVEC tube formation and cancer line spheroid formation occured after 3-4 days. Interaction was visualised between tumours and HUVECs via confocal microscopy. Slightly increased interaction was seen between cancer tumours and micro-vascular tubes when seeded as single cells compared with the pre-formed spheroid approach. Further studies intend to utilise cytokine gradients to further optimise the ECM environment of in situ tumour angiogenesis. Discussion and Conclusions Our results confirm the suitability of hydrogels constructed from starPEG-heparin for HUVECs and MSC co-cultivation with cancer cell lines to study cell-cell and cell-matrix interactions in a 3D environment. This represents a step forward in the development of 3D culture models to study the pathomechanisms of breast and prostate cancer. References 1. Tsurkan MV, Chwalek K, Prokoph S, Zieris A, Levental KR, Freudenberg U, Werner C. Advanced Materials. 25, 2606-10, 2013. Disclosures The authors declare no conflicts of interest

Coverage algorithms for an under-actuated car-like vehicle in an uncertain environment

A coverage algorithm is an algorithm that deploys a strategy as to how to cover all points in terms of a given area using some set of sensors. In the past decades a lot of research has gone into development of coverage algorithms. Initially, the focus was coverage of structured and semi-structured indoor areas, but with time and development of better sensors and introduction of GPS, the focus has turned to outdoor coverage. Due to the unstructured nature of an outdoor environment, covering an outdoor area with all its obstacles and simultaneously performing reliable localization is a difficult task. In this paper, two path planning algorithms suitable for solving outdoor coverage tasks are introduced. The algorithms take into account the kinematic constraints of an under-actuated car-like vehicle, minimize trajectory curvatures, and dynamically avoid detected obstacles in the vicinity, all in real-time. We demonstrate the performance of the coverage algorithm in the field by achieving 95% coverage using an autonomous tractor mower without the aid of any absolute localization system or constraints on the physical boundaries of the area.

If you're going to be a leader, at least act like it! Prejudice towards women who are tentative in leader roles

Role congruity theory predicts prejudice towards women who meet the agentic requirements of the leader role. In line with recent findings indicating greater acceptance of agentic behaviour from women, we find evidence for a more subtle form of prejudice towards women who fail to display agency in leader roles. Using a classic methodology, the agency of male and female leaders was manipulated using assertive or tentative speech, presented through written (Study 1, N = 167) or verbal (Study 2, N = 66) communications. Consistent with predictions, assertive women were as likeable and influential as assertive men, while being tentative in leadership reduced the likeability and influence of women, but not of men. Although approval of agentic behaviour from women in leadership reflects progress, evidence that women are quickly singled out for disapproval if they fail to show agency is important for understanding how they continue to be at a distinct disadvantage to men in leader roles.

Evidence-based business process management: Using digital opportunities to drive organizational innovation

Process improvement and innovation are risky endeavors, like swimming in unknown waters. In this chapter, I will discuss how process innovation through BPM can benefit from Research-as-a-Service, that is, from the application of research concepts in the processes of BPM projects. A further subject will be how innovations can be converted from confidence-based to evidence-based models due to affordances of digital infrastructures such as large-scale enterprise soft-ware or social media. I will introduce the relevant concepts, provide illustrations for digital capabilities that allow for innovation, and share a number of key takeaway lessons for how organizations can innovate on the basis of digital opportunities and principles of evidence-based BPM: the foundation of all process decisions in facts rather than fiction.