Found in translation : debating the abstract elements of cultures through actor training styles

While the synthesis of acting methodologies in intercultural acting has been discussed at length, little discussion has focussed on the potential of diverse actor training styles to affect performance making and audience reception. This article explores a project where the abstract elements of the British and American cultures were translated in rehearsal and in production through the purposeful juxtaposition of two differing actor training styles: the British ‘traditional’ approach and the American Method. William Nicholson’s Shadowlands was produced by Crossbow Productions at the Brisbane Powerhouse in 2010. Nicholson’s play contains a discourse on the cultural cringe of British – American relations. As a research project, the production aimed to extend and augment audience experience of the socio-cultural tensions inherent in the play by juxtaposing two seemingly culturally inscribed approaches to acting. Actors were chosen who had been trained under a traditional conservatoire approach and the American Method. A brief overview of these acting approaches is followed by a discussion centred on the project. This article analyses how from the casting room to the rehearsal room to the mise en scene and into the audience discussions, cultural issues were articulated, translated and debated through the language of acting.

A Near-Infrared Reflectance Spectroscopy Method for Direct Analysis of Several Chemical Components and Properties of Fruit, for Example, Chinese Hawthorn

Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.

The Tarim picrite-basalt-rhyolite suite, a Permian flood basalt from Northwest China with contrasting rhyolites produced by fractional crystallization and anatexis

We report major and trace element composition, Sr–Nd isotopic and seismological data for a picrite–basalt–rhyolite suite from the northern Tarim uplift (NTU), northwest China. The samples were recovered from 13 boreholes at depths between 5,166 and 6,333 m. The picritic samples have high MgO (14.5–16.8 wt%, volatiles included) enriched in incompatible element and have high 87Sr/86Sr and low 143Nd/144Nd isotopic ratios (εNd (t) = −5.3; Sri = 0.707), resembling the Karoo high-Ti picrites. All the basaltic samples are enriched in TiO2 (2.1–3.2 wt%, volatiles free), have high FeOt abundances (11.27–15.75 wt%, volatiles free), are enriched in incompatible elements and have high Sr and low Nd isotopic ratios (Sri = 0.7049–0.7065; εNd (t) = −4.1 to −0.4). High Nb/La ratios (0.91–1.34) of basalts attest that they are mantle-derived magma with negligible crustal contamination. The rhyolite samples can be subdivided into two coeval groups with overlapping U–Pb zircon ages between 291 ± 4 and 272 ± 2 Ma. Group 1 rhyolites are enriched in Nb and Ta, have similar Nb/La, Nb/U, and Sr–Nd isotopic compositions to the associated basalts, implying that they are formed by fractional crystallization of the basalts. Group 2 rhyolites are depleted in Nb and Ta, have low Nb/La ratios, and have very high Sr and low Nd isotopic ratios, implying that crustal materials have been extensively, if not exclusively, involved in their source. The picrite–basalt–rhyolite suite from the NTU, together with Permian volcanic rocks from elsewhere Tarim basin, constitute a Large Igneous Province (LIP) that is characterized by large areal extent, rapid eruption, OIB-type chemical composition, and eruption of high temperature picritic magma. The Early Permian magmatism, which covered an area >300,000 km2, is therefore named the Tarim Flood Basalt.

Effect of chemical conjugation of L-leucine to chitosan on the dispersibility and drug release of a dry powder inhaler nanoparticle formulation

Purpose: This study investigated the effect of chemical conjugation of the amino acid L-leucine to the polysaccharide chitosan on the dispersibility and drug release pattern of a polymeric nanoparticle (NP)-based controlled release dry powder inhaler (DPI) formulation. Methods: A chemical conjugate of L-leucine with chitosan was synthesized and characterized by Infrared (IR) Spectroscopy, Nuclear Magnetic Resonance (NMR) Spectroscopy, Elemental Analysis and X-ray Photoelectron Spectroscopy (XPS). Nanoparticles of both chitosan and its conjugate were prepared by a water-in-oil emulsification – glutaraldehyde cross-linking method using the antihypertensive agent, diltiazem (Dz) hydrochloride as the model drug. The surface morphology and particle size distribution of the nanoparticles were determined by Scanning Electron Microscopy (SEM) and Dynamic Light Scattering (DLS). The dispersibility of the nanoparticle formulation was analysed by a Twin Stage Impinger (TSI) with a Rotahaler as the DPI device. Deposition of the particles in the different stages was determined by gravimetry and the amount of drug released was analysed by UV spectrophotometry. The release profile of the drug was studied in phosphate buffered saline at 37 ⁰C and analyzed by UV spectrophotometry. Results: The TSI study revealed that the fine particle fractions (FPF), as determined gravimetrically, for empty and drug-loaded conjugate nanoparticles were significantly higher than for the corresponding chitosan nanoparticles (24±1.2% and 21±0.7% vs 19±1.2% and 15±1.5% respectively; n=3, p<0.05). The FPF of drug-loaded chitosan and conjugate nanoparticles, in terms of the amount of drug determined spectrophotometrically, had similar values (21±0.7% vs 16±1.6%). After an initial burst, both chitosan and conjugate nanoparticles showed controlled release that lasted about 8 to 10 days, but conjugate nanoparticles showed twice as much total drug release compared to chitosan nanoparticles (~50% vs ~25%). Conjugate nanoparticles also showed significantly higher dug loading and entrapment efficiency than chitosan nanoparticles (conjugate: 20±1% & 46±1%, chitosan: 16±1% & 38±1%, n=3, p<0.05). Conclusion: Although L-leucine conjugation to chitosan increased dispersibility of formulated nanoparticles, the FPF values are still far from optimum. The particles showed a high level of initial burst release (chitosan, 16% and conjugate, 31%) that also will need further optimization.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Strain engineering of selective chemical adsorption on monolayer MoS2

Nanomaterials are prone to influence by chemical adsorption because of their large surface to volume ratios. This enables sensitive detection of adsorbed chemical species which, in turn, can tune the property of the host material. Recent studies discovered that single and multi-layer molybdenum disulfide (MoS2) films are ultra-sensitive to several important environmental molecules. Here we report new findings from ab inito calculations that reveal substantially enhanced adsorption of NO and NH3 on strained monolayer MoS2 with significant impact on the properties of the adsorbates and the MoS2 layer. The magnetic moment of adsorbed NO can be tuned between 0 and 1 μB; strain also induces an electronic phase transition between half-metal and metal. Adsorption of NH3 weakens the MoS2 layer considerably, which explains the large discrepancy between the experimentally measured strength and breaking strain of MoS2 films and previous theoretical predictions. On the other hand, adsorption of NO2, CO, and CO2 is insensitive to the strain condition in the MoS2 layer. This contrasting behavior allows sensitive strain engineering of selective chemical adsorption on MoS2 with effective tuning of mechanical, electronic, and magnetic properties. These results suggest new design strategies for constructing MoS2-based ultrahigh-sensitivity nanoscale sensors and electromechanical devices.

Toxic state–corporate crimes, Neo-liberalism and green criminology : the hazards and legacies of the oil, chemical and mineral industries

This paper uses examples from the history and practices of multi-national and large companies in the oil, chemical and asbestos industries to examine their legal and illegal despoiling and destruction of the environment and impact on human and non-human life. The discussion draws on the literature on green criminology and state-corporate crime and considers measures and arrangements that might mitigate or prevent such damaging acts. This paper is part of ongoing work on green criminology and crimes of the economy. It places these actions and crimes in the context of a global neo-liberal economic system and considers and critiques the distorting impact of the GDP model of ‘economic health’ and its consequences for the environment.

Multidirectional effects of Sr, Mg and Si-containing bioceramic coatings with high bonding strength on inflammation, osteoclastogenesis and osteogenesis

Ideal coating materials for implants should be able to induce excellent osseointegration, which requires several important parameters, such as good bonding strength, limited inflammatory reaction, balanced osteoclastogenesis and osteogenesis, to gain well-functioning coated implants with long-term life span after implantation. Bioactive elements, like Sr, Mg and Si, have been found to play important roles in regulating the biological responses. It is of great interest to combine bioactive elements for developing bioactive coatings on Ti-6Al-4V orthopedic implants to elicit multidirectional effects on the osseointegration. In this study, Sr, Mg and Si-containing bioactive Sr2MgSi2O7 (SMS) ceramic coatings on Ti-6Al-4V were successfully prepared by plasma-spray coating method. The prepared SMS coatings have significantly higher bonding strength (~37MPa) than conventional pure hydroxyapatite (HA) coatings (mostly in the range of 15-25 MPa). It was also found that the prepared SMS coatings switch the macrophage phenotype into M2 extreme, inhibiting the inflammatory reaction via the inhibition of Wnt5A/Ca2+ and Toll-like receptor (TLR) pathways of macrophages. In addition, the osteoclastic activities were also inhibited by SMS coatings. The expression of osteoclastogenesis related genes (RANKL and MCSF) in bone marrow derived mesenchymal cells (BMSCs) with the involvement of macrophages was decreased, while OPG expression was enhanced on SMS coatings compared to HA coatings, indicating that SMS coatings also downregulated the osteoclastogenesis. However, the osteogenic differentiation of BMSCs with the involvement of macrophages was comparable between SMS and HA coatings. Therefore, the prepared SMS coatings showed multidirectional effects, such as improving bonding strength, reducing inflammatory reaction and downregulating osteoclastic activities, but maintaining a comparable osteogenesis, as compared with HA coatings. The combination of bioactive elements of Sr, Mg and Si into bioceramic coatings can be a promising method to develop bioactive implants with multifunctional properties for orthopaedic application.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Elements of Better Assessment for the Improvement of Learning

Building a community of shared practice at the classroom level calls for clarity about the important assessment capabilities and dispositions of teachers, especially when teachers are expected to take a direct focus on learning. In this chapter, we present new ways of thinking about teachers’ assessment literacies, offering a formulation of better assessment for the improvement of learning, including three elements, namely (i) assessment criteria and standards; (ii) the teacher’s professional judgment; and (iii) social moderation. The potential of the first element lies in teachers’ classroom practices that deliberately embed assessment criteria and standards in pedagogy in productive ways. The second element involves the engagement of teachers and students in judgment practice, that develops the understanding that judgment involves more than the application of explicit or stated criteria. More fundamental is the matter of how teachers bring to bear stated features of quality and other intellectual and experiential resources in arriving at judgment. That is to say, they range across and orient to explicit (stated), tacit (unstated) and meta-criteria in judgment making. These insights have direct relevance to teachers’ efforts to develop students’ own evaluative experience, especially as this involves students working with stated features of quality for self-assessment and peer-assessment purposes. Further, practices for social moderation are discussed, giving examples of good practice in moderation, how teachers experience moderation and the potential benefits of various types.

The molecular structure of the vanadate mineral mottramite [PbCu(VO4)(OH)] from Tsumeb, Namibia – a vibrational spectroscopic study

We have studied a mineral sample of mottramite PbCu(VO4)(OH) from Tsumeb, Namibia using a combination of scanning electron microscopy with EDX, Raman and infrared spectroscopy. Chemical analysis shows principally the elements V, Pb and Cu. Ca occurs as partial substitution of Pb as well as P and As in substitution to V. Minor amounts of Si and Cr were also observed. The Raman band of mottramite at 829 cm-1, is assigned to the ν1 symmetric (VO-4) ) stretching mode. The complexity of the spectra is attributed to the chemical composition of the Tsumeb mottramite. The ν3 antisymmetric vibrational mode of mottramite is observed as very low intensity bands at 716 and 747 cm-1. The series of Raman bands at 411, 439, 451 cm-1 and probably also the band at 500 cm-1 are assigned to the (VO-4) ν2 bending mode. The series of Raman bands at 293, 333 and 366 cm-1 are attributed to the (VO-4) ) ν4 bending modes. The ν3, ν3 and ν4 regions are complex for both minerals and this is attributed to symmetry reduction of the vanadate unit from Td to Cs.

Tandem B1 SINE retro-elements may provide a basis for natural antisense transcription in the Magi1 locus of the mouse (Mus musculus)

Transposable elements, which are DNA sequences that can move between different sites in genomes, comprise approximately 40% of the genome of mammals and are emerging as important contributors to biological diversity. Here we report a transcription unit lying within intron 1 of the murine Magi1 (membrane associated guanylate kinase inverted 1) gene that codes for a cell-cell junction scaffolding protein. The transcription unit, termed Magi1OS (Magi1 Opposite Strand), originates from a region with tandem B1 short interspersed nuclear elements (SINEs) and is an antisense gene to Magi1. Mag1OS transcription initiates in a proximal B1 element that shows only 4% divergence from the consensus sequence, indicating that it has been recently inserted into the mouse genome and could be replication competent. Moreover, a chimaeric transcript may result from intra-chromosomal interaction and trans-splicing of the Magi1 antisense transcript (Magi1OS) and Ghrl, which codes for the multifunctional peptide hormone ghrelin. These two genes are 20 megabases apart on chromosome 6 and are transcribed in opposite directions. We propose that the Magi1OS locus may serve as a useful model system to study exaptation and retrotransposition of B1 SINEs, as well as to examine the mechanisms of intra-chromosomal trans-splicing.

Raman and infrared spectroscopic characterization of the phosphate mineral Lithiophilite—LiMnPO4

The metal lithium is very important in industry, including lithium batteries. An important source of lithium besides continental brines is granitic pegmatites as in Australia. Lithiophilite is a lithium and manganese phosphate with chemical formula LiMnPO4 and forms a solid solution with triphylite, its Fe analog, and belongs to the triphylite group that includes karenwebberite, natrophilite, and sicklerite. The mineral lithiophilite was characterized by chemical analysis and spectroscopic techniques. The chemical is: Li1.01(Mn0.60, Fe0.41, Mg0.01, Ca0.01)(PO4)0.99 and corresponds to an intermediate member of the triphylite-lithiophilite series, with predominance of the lithiophilite member. The mineral lithiophilite is readily characterized by Raman and infrared spectroscopy.

Considering the economic value of natural design elements at city scale

With increasing signs of climate change and the influence of national and international carbon-related laws and agreements, governments all over the world are grappling with how to rapidly transition to low-carbon living. This includes adapting to the impacts of climate change that are very likely to be experienced due to current emission levels (including extreme weather and sea level changes), and mitigating against further growth in greenhouse gas emissions that are likely to result in further impacts. Internationally, the concept of ‘Biophilic Urbanism’, a term coined by Professors Tim Beatley and Peter Newman to refer to the use of natural elements as design features in urban landscapes, is emerging as a key component in addressing such climate change challenges in rapidly growing urban contexts. However, the economics of incorporating such options is not well understood and requires further attention to underpin a mainstreaming of biophilic urbanism. Indeed, there appears to be an ad hoc, reactionary approach to creating economic arguments for or against the design, installation or maintenance of natural elements such as green walls, green roofs, streetscapes, and parklands. With this issue in mind, this paper will overview research as part of an industry collaborative research project that considers the potential for using a number of environmental economic valuation techniques that have evolved over the last several decades in agricultural and resource economics, to systematically value the economic value of biophilic elements in the urban context. Considering existing literature on environmental economic valuation techniques, the paper highlights opportunities for creating a standardised language for valuing biophilic elements. The conclusions have implications for expanding the field of environmental economic value to support the economic evaluations and planning of the greater use of natural elements in cities. Insights are also noted for the more mature fields of agricultural and resource economics.

An exploration into retrofitting cities with natural design elements - learning from the city of Berlin, Germany

Natural design features in the built environment or biophilic elements are emerging as a potential response to the challenges of climate change, urbanisation and population pressures which have invited issues such as rising urban heat island effect, rising pollution, increased congestion, among others. This concept of living cities was made popular by Professor Tim Beatley in his book titled ‘Biophilic Urbanism’. Evidence of biophilic urbanism can be seen in some cities from around the globe since decoupling environmental pressures from future development is a priority on many agendas. Berlin is an example of a modern economy that has adopted an ecological sustainable development approach to reduce environmental degradation while driving innovation and employment.