Examination of the latent structure of the psychological sense of school membership scale

Despite its widespread use, there has been limited examination of the underlying factor structure of the Psychological Sense of School Membership (PSSM) scale. The current study examined the psychometric properties of the PSSM to refine its utility for researchers and practitioners using a sample of 504 Australian high school students. Results from exploratory and confirmatory factor analyses indicated that the PSSM is a multidimensional instrument. Factor analysis procedures identified three factors representing related aspects of students’ perceptions of their school membership: caring relationships, acceptance, and rejection

Large-scale fabrication of H2(H2O)Nb2O6 and Nb2O5 hollow microspheres

Hollow micro-sized H2(H2O)Nb2O6 spheres constructed by nanocrystallites have been successfully synthesized via a bubble-template assisted hydrothermal process. In the reaction process, H2O2 acts as a bubble generator and plays a key role in the formation of the hollow structure. An in situ bubble-template mechanism has been proposed for the possible formation of the hollow structure. The spherelike assemblies of these H2(H2O)Nb2O6 nanoparticles have been transformed into their corresponding pseudohexagonal phase Nb2O5 through a moderate annealing dehydration process without destroying the hierarchical structure. Optical properties of the as-prepared hollow spheres were investigated. It is exciting that the absorption edge of the hollow Nb2O5 microspheres shifts about 18 nm to the violet compared with bulk powders in the UV/vis spectra, indicating its superior optical properties.

The large-scale production of graphene flakes using magnetically-enhanced arc discharge between carbon electrodes

A novel approach to large-scale production of high-quality graphene flakes in magnetically-enhanced arc discharges between carbon electrodes is reported. A non-uniform magnetic field is used to control the growth and deposition zones, where the Y-Ni catalyst experiences a transition to the ferromagnetic state, which in turn leads to the graphene deposition in a collection area. The quality of the produced material is characterized by the SEM, TEM, AFM, and Raman techniques. The proposed growth mechanism is supported by the nucleation and growth model.

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

Listening to nature : techniques for large-scale monitoring of ecosystems using acoustics

Climate change and human activity are subjecting the environment to unprecedented rates of change. Monitoring these changes is an immense task that demands new levels of automated monitoring and analysis. We propose the use of acoustics as a proxy for the time consuming auditing of fauna, especially for determining the presence/absence of species. Acoustic monitoring is deceptively simple; seemingly all that is required is a sound recorder. However there are many major challenges if acoustics are to be used for large scale monitoring of ecosystems. Key issues are scalability and automation. This paper discusses our approach to this important research problem. Our work is being undertaken in collaboration with ecologists interested both in identifying particular species and in general ecosystem health.

The factor structure of the COPE Questionnaire in a sample of clinically depressed and anxious adults

The Coping Orientation to Problems Experienced is a multidimensional scale designed to assess how people respond to stress. The COPE has been validated in a variety of populations displaying variations in factor structure. However, in terms of mental health populations, it has only been validated in alcohol-dependent samples. This paper investigated the factor structure of the COPE in a sample of adults diagnosed with depression and anxiety. Two hundred and seventy-one patients attending cognitive behaviour therapy for anxiety and depression completed the COPE. Confirmatory factor analysis found a poor fit for both lower order and higher order factors based upon the Lyne and Roger (2000) study. Exploratory factor analyses identified six primary subscales (Active Planning, Social Support, Denial, Acceptance, Disengagement, Restraint) which explained approximately 60% of the variance in coping. These 6 subscales may assist researchers and clinicians to validly measure coping in anxious and depressed adults.

Variation in leaf structure of the invasive Madeira vine (Anredera cordifolia, Basellaceae) at different light levels

Madeira vine (Anredera cordifolia (Ten.) Steenis) is a climber in the angiosperm family Basellaceae. It is native to South America and has naturalised in Australia. It is regarded as a serious environmental weed because of the structural damage it causes to native vegetation. The present study, for the first time, documents anatomical and morphological traits of the leaves of A. cordifolia and considers their implications for its ecology and physiology. Plants were grown under three different light levels, and anatomical and morphological leaf characters were compared among light levels, among cohorts, and with documented traits of the related species, Basella alba L. Stomata were present on both the adaxial and abaxial sides of the leaf, with significantly more stomata on the abaxial side and under high light. This may account for the ability of this species to fix large amounts of carbon and rapidly respond to light gaps. The leaves had very narrow veins and no sclerenchyma, suggesting a low construction cost that is associated with invasive plants. There was no significant difference in any of the traits among different cohorts, which agrees with the claim that A. cordifolia primarily propagates vegetatively. The anatomy and morphology of A. cordifolia was similar to that of B. alba.

Large-scale testing of steel frame structures comprising non-compact sections

Application of 'advanced analysis' methods suitable for non-linear analysis and design of steel frame structures permits direct and accurate determination of ultimate system strengths, without resort to simplified elastic methods of analysis and semi-empirical specification equations. However, the application of advanced analysis methods has previously been restricted to steel frames comprising only compact sections that are not influenced by the effects of local buckling. A research project has been conducted with the aim of developing concentrated plasticity methods suitable for practical advanced analysis of steel frame structures comprising non-compact sections. A series of large-scale tests were performed in order to provide experimental results for verification of the new analytical models. Each of the test frames comprised non-compact sections, and exhibited significant local buckling behaviour prior to failure. This paper presents details of the test program including the test specimens, set-up and instrumentation, procedure, and results.

Large-scale analysis of formations in soccer

Due to the demand for better and deeper analysis in sports, organizations (both professional teams and broadcasters) are looking to use spatiotemporal data in the form of player tracking information to obtain an advantage over their competitors. However, due to the large volume of data, its unstructured nature, and lack of associated team activity labels (e.g. strategic/tactical), effective and efficient strategies to deal with such data have yet to be deployed. A bottleneck restricting such solutions is the lack of a suitable representation (i.e. ordering of players) which is immune to the potentially infinite number of possible permutations of player orderings, in addition to the high dimensionality of temporal signal (e.g. a game of soccer last for 90 mins). Leveraging a recent method which utilizes a "role-representation", as well as a feature reduction strategy that uses a spatiotemporal bilinear basis model to form a compact spatiotemporal representation. Using this representation, we find the most likely formation patterns of a team associated with match events across nearly 14 hours of continuous player and ball tracking data in soccer. Additionally, we show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.

The molecular structure of the phosphate mineral beraunite Fe2+Fe⅗+(PO4)4(OH)5⋅4H2O– A vibrational spectroscopic study

The mineral beraunite from Boca Rica pegmatite in Minas Gerais with theoretical formula Fe2+Fe5 3+(PO4)4(OH)5⋅4H2O has been studied using a combination of electron microscopy with EDX and vibrational spectroscopic techniques. Raman spectroscopy identifies an intense band at 990 cm-1 and 1011 cm-1. These bands are attributed to the PO4 3- v, symmetric stretching mode. The m3 antisymmetric stretching modes are observed by a large number of Raman bands. The Raman bands at 1034, 1051, 1058, 1069 and 1084 together with the Raman bands at 1098, 1116, 1133, 1155 and 1174 cm-1 are assigned to the m3 antisymmetric stretching vibrations of PO4 3- and the HOPO3 2- units. The observation of these multiple Raman bands in the symmetric and antisymmetric stretching region gives credence to the concept that both phosphate and hydrogen phosphate units exist in the structure of beraunite. The series of Raman bands at 567, 582,601, 644, 661, 673, and 687 cm-1 are assigned to the PO4 3- v2 bending modes. The series of Raman bands at 437, 468, 478, 491, 503 cm-1 are attributed to the PO4 3- and OPO3 2- v4 bending modes. No Raman bands of beraunite which could be attributed to the hydroxyl stretching unit were observed. Infrared bands at 3511 and 3359 cm-1 are ascribed to the OH stretching vibration of the OH units. Very broad bands at 3022 and 3299 cm-1 are attributed to the OH stretching vibrations of water. Vibrational spectroscopy offers insights into the molecular structure of the phosphate mineral beraunite.

The molecular structure of the phosphate mineral kidwellite NaFe93+(PO4)6(OH)11⋅3H2O – a vibrational spectroscopic study

The mineral kidwellite, a hydrated hydroxy phosphate of ferric iron and sodium of approximate formula NaFe93+(PO4)6(OH)11⋅3H2O, has been studied using a combination of electron microscopy with EDX and vibrational spectroscopic techniques. Raman spectroscopy identifies an intense band at 978 cm−1 and 1014 cm−1. These bands are attributed to the PO43− ν1 symmetric stretching mode. The ν3 antisymmetric stretching modes are observed by a large number of Raman bands. The series of Raman bands at 1034, 1050, 1063, 1082, 1129, 1144 and 1188 cm−1 are attributed to the ν3 antisymmetric stretching bands of the PO43− and HOPO32− units. The observation of these multiple Raman bands in the symmetric and antisymmetric stretching region gives credence to the concept that both phosphate and hydrogen phosphate units exist in the structure of kidwellite. The series of Raman bands at 557, 570, 588, 602, 631, 644 and 653 cm−1are assigned to the PO43− ν2 bending modes. The series of Raman bands at 405, 444, 453, 467, 490 and 500 cm−1 are attributed to the PO43− and HOPO32− ν4 bending modes. The spectrum is quite broad but Raman bands may be resolved at 3122, 3231, 3356, 3466 and 3580 cm−1. These bands are assigned to water stretching vibrational modes. The number and position of these bands suggests that water is in different molecular environments with differing hydrogen bond distances. Infrared bands at 3511 and 3359 cm−1 are ascribed to the OH stretching vibration of the OH units. Very broad bands at 3022 and 3299 cm−1 are attributed to the OH stretching vibrations of water. Vibrational spectroscopy offers insights into the molecular structure of the phosphate mineral kidwellite.

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.

Large Scale Simulations of Hippocampal-Neocortical Interactions in a Parallel Version of Genesis

A hippocampal-CA3 memory model was constructed with PGENESIS, a recently developed version of GENESIS that allows for distributed processing of a neural network simulation. A number of neural models of the human memory system have identified the CA3 region of the hippocampus as storing the declarative memory trace. However, computational models designed to assess the viability of the putative mechanisms of storage and retrieval have generally been too abstract to allow comparison with empirical data. Recent experimental evidence has shown that selective knock-out of NMDA receptors in the CA1 of mice leads to reduced stability of firing specificity in place cells. Here a similar reduction of stability of input specificity is demonstrated in a biologically plausible neural network model of the CA3 region, under conditions of Hebbian synaptic plasticity versus an absence of plasticity. The CA3 region is also commonly associated with seizure activity. Further simulations of the same model tested the response to continuously repeating versus randomized nonrepeating input patterns. Each paradigm delivered input of equal intensity and duration. Non-repeating input patterns elicited a greater pyramidal cell spike count. This suggests that repetitive versus non-repeating neocortical inpus has a quantitatively different effect on the hippocampus. This may be relevant to the production of independent epileptogenic zones and the process of encoding new memories.

Large scale monitoring of crowds and building utilisation: A new database and distributed approach

Public buildings and large infrastructure are typically monitored by tens or hundreds of cameras, all capturing different physical spaces and observing different types of interactions and behaviours. However to date, in large part due to limited data availability, crowd monitoring and operational surveillance research has focused on single camera scenarios which are not representative of real-world applications. In this paper we present a new, publicly available database for large scale crowd surveillance. Footage from 12 cameras for a full work day covering the main floor of a busy university campus building, including an internal and external foyer, elevator foyers, and the main external approach are provided; alongside annotation for crowd counting (single or multi-camera) and pedestrian flow analysis for 10 and 6 sites respectively. We describe how this large dataset can be used to perform distributed monitoring of building utilisation, and demonstrate the potential of this dataset to understand and learn the relationship between different areas of a building.

A large-scale analysis of genetic variants within putative miRNA binding sites in prostate cancer

Prostate cancer is the second most common malignancy among men worldwide. Genome-wide association studies have identified 100 risk variants for prostate cancer, which can explain approximately 33% of the familial risk of the disease. We hypothesized that a comprehensive analysis of genetic variations found within the 3' untranslated region of genes predicted to affect miRNA binding (miRSNP) can identify additional prostate cancer risk variants. We investigated the association between 2,169 miRSNPs and prostate cancer risk in a large-scale analysis of 22,301 cases and 22,320 controls of European ancestry from 23 participating studies. Twenty-two miRSNPs were associated (P<2.3×10(-5)) with risk of prostate cancer, 10 of which were within 7 genes previously not mapped by GWAS studies. Further, using miRNA mimics and reporter gene assays, we showed that miR-3162-5p has specific affinity for the KLK3 rs1058205 miRSNP T-allele, whereas miR-370 has greater affinity for the VAMP8 rs1010 miRSNP A-allele, validating their functional role. SIGNIFICANCE Findings from this large association study suggest that a focus on miRSNPs, including functional evaluation, can identify candidate risk loci below currently accepted statistical levels of genome-wide significance. Studies of miRNAs and their interactions with SNPs could provide further insights into the mechanisms of prostate cancer risk.