Emotional climate of a pre-service science teacher education class in Bhutan

This study explored pre-service secondary science teachers’ perceptions of classroom emotional climate in the context of the Bhutanese macro-social policy of Gross National Happiness. Drawing upon sociological perspectives of human emotions and using Interaction Ritual Theory this study investigated how pre-service science teachers may be supported in their professional development. It was a multi-method study involving video and audio recordings of teaching episodes supported by interviews and the researcher’s diary. Students also registered their perceptions of the emotional climate of their classroom at 3-minute intervals using audience response technology. In this way, emotional events were identified for video analysis. The findings of this study highlighted that the activities pre-service teachers engaged in matter to them. Positive emotional climate was identified in activities involving students’ presentations using video clips and models, coteaching, and interactive whole class discussions. Decreases in emotional climate were identified during formal lectures and when unprepared presenters led presentations. Emotions such as frustration and disappointment characterized classes with negative emotional climate. The enabling conditions to sustain a positive emotional climate are identified. Implications for sustaining macro-social policy about Gross National Happiness are considered in light of the climate that develops in science teacher education classes.

Classifying patients by their characteristics and clinical presentations; the use of latent class analysis

In this article, we introduce the general statistical analysis approach known as latent class analysis and discuss some of the issues associated with this type of analysis in practice. Two recent examples from the respiratory health literature are used to highlight the types of research questions that have been addressed using this approach.

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.

Evaluation of potential candidate genes involved in salinity tolerance in striped catfish (Pangasianodon hypophthalmus) using an RNA-Seq approach

Increasing salinity levels in freshwater and coastal environments caused by sea level rise linked to climate change is now recognized to be a major factor that can impact fish growth negatively, especially for freshwater teleost species. Striped catfish (Pangasianodon hypophthalmus) is an important freshwater teleost that is now widely farmed across the Mekong River Delta in Vietnam. Understanding the basis for tolerance and adaptation to raised environmental salinity conditions can assist the regional culture industry to mitigate predicted impacts of climate change across this region. Attempt of next generation sequencing using the ion proton platform results in more than 174 million raw reads from three tissue libraries (gill, kidney and intestine). Reads were filtered and de novo assembled using a variety of assemblers and then clustered together to generate a combined reference transcriptome. Downstream analysis resulted in a final reference transcriptome that contained 60,585 transcripts with an N50 of 683 bp. This resource was further annotated using a variety of bioinformatics databases, followed by differential gene expression analysis that resulted in 3062 transcripts that were differentially expressed in catfish samples raised under two experimental conditions (0 and 15 ppt). A number of transcripts with a potential role in salinity tolerance were then classified into six different functional gene categories based on their gene ontology assignments. These included; energy metabolism, ion transportation, detoxification, signal transduction, structural organization and detoxification. Finally, we combined the data on functional salinity tolerance genes into a hypothetical schematic model that attempted to describe potential relationships and interactions among target genes to explain the molecular pathways that control adaptive salinity responses in P. hypophthalmus. Our results indicate that P. hypophthalmus exhibit predictable plastic regulatory responses to elevated salinity by means of characteristic gene expression patterns, providing numerous candidate genes for future investigations.

Class-specific sparse codes for representing activities

In this paper we investigate the effectiveness of class specific sparse codes in the context of discriminative action classification. The bag-of-words representation is widely used in activity recognition to encode features, and although it yields state-of-the art performance with several feature descriptors it still suffers from large quantization errors and reduces the overall performance. Recently proposed sparse representation methods have been shown to effectively represent features as a linear combination of an over complete dictionary by minimizing the reconstruction error. In contrast to most of the sparse representation methods which focus on Sparse-Reconstruction based Classification (SRC), this paper focuses on a discriminative classification using a SVM by constructing class-specific sparse codes for motion and appearance separately. Experimental results demonstrates that separate motion and appearance specific sparse coefficients provide the most effective and discriminative representation for each class compared to a single class-specific sparse coefficients.

See you in class: Promoting a quality program for pre-service educators in regional locations through a virtual classroom

The quality of an online university degree is paramount to the student, the reputation of the university and most importantly, the profession that will be entered. At the School of Education within Curtin University, we aim to ensure that students within rural and remote areas are provided with high quality degrees equal to their city counterparts who access face-to-face classes on campus.In 2010, the School of Education moved to flexible delivery of a fully online Bachelor of Education degree for their rural students. In previous years, the degree had been delivered in physical locations around the state. Although this served the purpose for the time, it restricted the degree to only those rural students who were able to access the physical campus. The new model in 2010 allows access for students in any rural area who have a computer and an internet connection, regardless of their geographical location. As a result enrolments have seen a positive increase in new students. Academic staff had previously used an asynchronous environment to deliver learning modules housed within a learning management system (LMS). To enhance the learning environment and to provide high quality learning experiences to students learning at a distance, the adoption of synchronous software was introduced. This software is a real-time virtual classroom environment that allows for communication through Voice over Internet Protocol (VoIP) and videoconferencing, along with a large number of collaboration tools to engage learners. This research paper reports on the professional development of academic staff to integrate a live e-learning solution into their current LMS environment. It involved professional development, including technical orientation for teaching staff and course participants simultaneously. Further, pedagogical innovations were offered to engage the students in a collaborative learning environment. Data were collected from academic staff through semi-structured interviews and participant observation. The findings discuss the perceived value of the technology, problems encountered and solutions sought.

3D QSAR studies of N-4-arylacryloylpiperazin-1-yl-phenyl-oxazolidinones: A novel class of antibacterial agents

Three-dimensional QSAR studies for N-4-arylacryloylpiperazin-1-yl-phenyl-oxazolidinones were conducted using TSAR 3.3. The in vitro activities (MICs) of the compounds against Staphylococcus aureus ATCC 25923 exhibited a strong correlation with the prediction made by the model developed in the present study.

Development of salinity tolerance in rice by constitutive-overexpression of genes involved in the regulation of programmed cell death

Environmental factors contribute to over 70% of crop yield losses worldwide. Of these drought and salinity are the most significant causes of crop yield reduction. Rice is an important staple crop that feeds more than half of the world’s population. However among the agronomically important cereals rice is the most sensitive to salinity. In the present study we show that exogenous expression of anti-apoptotic genes from diverse origins, AtBAG4 (Arabidopsis), Hsp70 (Citrus tristeza virus) and p35 (Baculovirus), significantly improves salinity tolerance in rice at the whole plant level. Physiological, biochemical and agronomical analyses of transgenic rice expressing each of the anti-apoptotic genes subjected to salinity treatment demonstrated traits associated with tolerant varieties including, improved photosynthesis, membrane integrity, ion and ROS maintenance systems, growth rate, and yield components. Moreover, FTIR analysis showed that the chemical composition of salinity-treated transgenic plants is reminiscent of non-treated, unstressed controls. In contrast, wild type and vector control plants displayed hallmark features of stress, including pectin degradation upon subjection to salinity treatment. Interestingly, despite their diverse origins, transgenic plants expressing the anti-apoptotic genes assessed in this study displayed similar physiological and biochemical characteristics during salinity treatment thus providing further evidence that cell death pathways are conserved across broad evolutionary kingdoms. Our results reveal that anti-apoptotic genes facilitate maintenance of metabolic activity at the whole plant level to create favorable conditions for cellular survival. It is these conditions that are crucial and conducive to the plants ability to tolerate/adapt to extreme environments.

Tripogon loliiformis elicits a rapid physiological and structural response to dehydration for desiccation tolerance

Resurrection plants can withstand extreme dehydration to an air-dry state and then recover upon receiving water. Tripogon loliiformis (F.Muell.) C.E.Hubb. is a largely uncharacterised native Australian desiccation-tolerant grass that resurrects from the desiccated state within 72 h. Using a combination of structural and physiological techniques the structural and physiological features that enable T. loliiformis to tolerate desiccation were investigated. These features include: - (i) a myriad of structural changes such as leaf folding, cell wall folding and vacuole fragmentation that mitigate desiccation stress; - (ii) potential role of sclerenchymatous tissue within leaf folding and radiation protection; - (iii) retention of ~70% chlorophyll in the desiccated state; - (iv) early response of photosynthesis to dehydration by 50% reduction and ceasing completely at 80 and 70% relative water content, respectively; - (v) a sharp increase in electrolyte leakage during dehydration, and; - (vi) confirmation of membrane integrity throughout desiccation and rehydration. Taken together, these results demonstrate that T. loliiformis implements a range of structural and physiological mechanisms that minimise mechanical, oxidative and irradiation stress. These results provide powerful insights into tolerance mechanisms for potential utilisation in the enhancement of stress-tolerance in crop plants.

A potent nonporphyrin class of photodynamic therapeutic agent: Cellular localisation, cytotoxic potential and influence of hypoxia

We have developed a totally new class of nonporphyrin photodynamic therapeutic agents with a specific focus on two lead candidates azadipyrromethene (ADPM)01 and ADPM06. Confocal laser scanning microscopy imaging showed that these compounds are exclusively localised to the cytosolic compartment, with specific accumulation in the endoplasmic reticulum and to a lesser extent in the mitochondria. Light-induced toxicity assays, carried out over a broad range of human tumour cell lines, displayed EC50 values in the micro-molar range for ADPM01 and nano-molar range for ADPM06, with no discernable activity bias for a specific cell type. Strikingly, the more active agent, ADPM06, even retained significant activity under hypoxic conditions. Both photosensitisers showed low to nondeterminable dark toxicity. Flow cytometric analysis revealed that ADPM01 and ADPM06 were highly effective at inducing apoptosis as a mode of cell death. The photophysical and biological characteristics of these PDT agents suggest that they have potential for the development of new anticancer therapeutics. © 2005 Cancer Research UK.

Targeting antigen to diverse APCs inactivates memory CD8+ T cells without eliciting tissue-destructive effector function

Memory T cells develop early during the preclinical stages of autoimmune diseases and have traditionally been considered resistant to tolerance induction. As such, they may represent a potent barrier to the successful immunotherapy of established autoimmune diseases. It was recently shown that memory CD8+ T cell responses are terminated when Ag is genetically targeted to steady-state dendritic cells. However, under these conditions, inactivation of memory CD8+ T cells is slow, allowing transiently expanded memory CD8+ T cells to exert tissue-destructive effector function. In this study, we compared different Ag-targeting strategies and show, using an MHC class II promoter to drive Ag expression in a diverse range of APCs, that CD8+ memory T cells can be rapidly inactivated by MHC class II+ hematopoietic APCs through a mechanism that involves a rapid and sustained downregulation of TCR, in which the effector response of CD8+ memory cells is rapidly truncated and Ag-expressing target tissue destruction is prevented. Our data provide the first demonstration that genetically targeting Ag to a broad range of MHC class II+ APC types is a highly efficient way to terminate memory CD8+ T cell responses to prevent tissue-destructive effector function and potentially established autoimmune diseases. Copyright © 2010 by The American Association of Immunologists, Inc.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Mechanical properties and damage tolerance of Y2SiO5

Y2SiO5 has potential applications as functional-structural ceramic and environmental/thermal barrier coating material. As an important grain-boundary phase in the sintered Si3N4, it also influences the mechanical and dielectric performances of the host material. In this paper, we present the mechanical properties of Y2SiO5 including elastic moduli, hardness, strength and fracture toughness, and try to understand the mechanical features from the viewpoint of crystal structure. Y2SiO5 has low shear modulus, low hardness, as well as high capacity for dispersing mechanical damage energy and for resisting crack penetration. Particularly, it can be machined by cemented carbides tools. The crystal structure characteristics of Y2SiO5 suggest the low-energy weakly bonded atomic planes crossed only by the easily breaking Y-O bonds as well as the rotatable rigid SiO4 tetrahedra are the origins of low shear deformation, good damage tolerance and good machinability of this material. TEM observations also demonstrate that the mechanical damage energy was dispersed in the form of the micro-cleavages, stacking faults and twins along these weakly bonded atomic planes, which allows the "microscale-plasticity" for Y2SiO5.

The relationship between class participation and law students' learning, engagement and stress: Do demographics matter?

Student participation in the classroom has long been regarded as an important means of increasing student engagement and enhancing learning outcomes by promoting active learning. However, the approach to class participation common in U.S. law schools, commonly referred to as the Socratic method, has been criticised for its negative impacts on student wellbeing. A multiplicity of American studies have identified that participating in law class discussions can be alienating, intimidating and stressful for some law students, and may be especially so for women, and students from minority backgrounds. Using data from the Law School Student Assessment Survey (LSSAS), conducted at UNSW Law School in 2012, this Chapter provides preliminary insights into whether assessable class participation (ACP) at an Australian law school is similarly alienating and stressful for students, including the groups identified in the American literature. In addition, we compare the responses of undergraduate Bachelor of Laws (LLB) and graduate Juris Doctor (JD) students. The LSSAS findings indicate that most respondents recognise the potential learning and social benefits associated with class participation in legal education, but remain divided over their willingness to participate. Further, in alignment with general trends identified in American studies, LLB students, women, international students, and non-native English speakers perceive they contribute less frequently to class discussions than JD students, males, domestic students, and native English speakers, respectively. Importantly, the LSSAS indicates students are more likely to be anxious about contributing to class discussions if they are LLB students (compared to their JD counterparts), and if English is not their first language (compared to native English speakers). There were no significant differences in students’ self-reported anxiety levels based on gender, which diverges from the findings of American research.

'More like the kids than the other teachers': One working-class pre-service teacher's experiences in a middle-class profession

While teaching is largely a White, middle-class profession, some teachers, including White teachers, come from low socio-economic backgrounds. This paper examines how one working-class pe-service teacher in Australia experiences studying in a predominantly middle-class teacher education program. Drawing on Bourdieu, this paper seeks to explore what we can learn from the pre-service teaching reflections of one woman who is a member of this smaller group of teachers and who brings to her teaching the habitus and life history that aligns with many of her students and the low socio-economic communities in which she teaches.