Characterization of commercial double-walled carbon nanotube material : composition, structure, and heat capacity

A purified commercial double-walled carbon nanotube (DWCNT) sample was investigated by transmission electron microscopy (TEM), thermogravimetry (TG), and Raman spectroscopy. Moreover, the heat capacity of the DWCNT sample was determined by temperature-modulated differential scanning calorimetry in the range of temperature between -50 and 290 °C. The main thermo-oxidation characterized by TG occurred at 474 °C with the loss of 90 wt% of the sample. Thermo-oxidation of the sample was also investigated by high-resolution TG, which indicated that a fraction rich in carbon nanotube represents more than 80 wt% of the material. Other carbonaceous fractions rich in amorphous coating and graphitic particles were identified by the deconvolution procedure applied to the derivative of TG curve. Complementary structural data were provided by TEM and Raman studies. The information obtained allows the optimization of composites based on this nanomaterial with reliable characteristics.

Combining ganglion cell topology and data of patients with glaucoma to determine a structure-function map

PURPOSE: To introduce techniques for deriving a map that relates visual field locations to optic nerve head (ONH) sectors and to use the techniques to derive a map relating Medmont perimetric data to data from the Heidelberg Retinal Tomograph. METHODS: Spearman correlation coefficients were calculated relating each visual field location (Medmont M700) to rim area and volume measures for 10 degrees ONH sectors (HRT III software) for 57 participants: 34 with glaucoma, 18 with suspected glaucoma, and 5 with ocular hypertension. Correlations were constrained to be anatomically plausible with a computational model of the axon growth of retinal ganglion cells (Algorithm GROW). GROW generated a map relating field locations to sectors of the ONH. The sector with the maximum statistically significant (P < 0.05) correlation coefficient within 40 degrees of the angle predicted by GROW for each location was computed. Before correlation, both functional and structural data were normalized by either normative data or the fellow eye in each participant. RESULTS: The model of axon growth produced a 24-2 map that is qualitatively similar to existing maps derived from empiric data. When GROW was used in conjunction with normative data, 31% of field locations exhibited a statistically significant relationship. This significance increased to 67% (z-test, z = 4.84; P < 0.001) when both field and rim area data were normalized with the fellow eye. CONCLUSIONS: A computational model of axon growth and normalizing data by the fellow eye can assist in constructing an anatomically plausible map connecting visual field data and sectoral ONH data.

Sound radiation characteristics of a box-type structure

The finite element and boundary element methods are employed in this study to investigate the sound radiation characteristics of a box-type structure. It has been shown [T.R. Lin, J. Pan, Vibration characteristics of a box-type structure, Journal of Vibration and Acoustics, Transactions of ASME 131 (2009) 031004-1–031004-9] that modes of natural vibration of a box-type structure can be classified into six groups according to the symmetry properties of the three panel pairs forming the box. In this paper, we demonstrate that such properties also reveal information about sound radiation effectiveness of each group of modes. The changes of radiation efficiencies and directivity patterns with the wavenumber ratio (the ratio between the acoustic and the plate bending wavenumbers) are examined for typical modes from each group. Similar characteristics of modal radiation efficiencies between a box structure and a corresponding simply supported panel are observed. The change of sound radiation patterns as a function of the wavenumber ratio is also illustrated. It is found that the sound radiation directivity of each box mode can be correlated to that of elementary sound sources (monopole, dipole, etc.) at frequencies well below the critical frequency of the plates of the box. The sound radiation pattern on the box surface also closely related to the vibration amplitude distribution of the box structure at frequencies above the critical frequency. In the medium frequency range, the radiated sound field is dominated by the edge vibration pattern of the box. The radiation efficiency of all box modes reaches a peak at frequencies above the critical frequency, and gradually approaches unity at higher frequencies.

Uncritical framing : lesson and knowledge structure in school science

There is clearly contention over the shape and formation of science curriculum and over, ultimately, what will count as scientific knowledge, skill, capacity and world view. The Cold War set the policy context for an ongoing focus on science education across Western nations. Sputnik-era US and UK educational policy offered a broad premise for the purpose of school science: in a risky geopolitical environment, high levels of advanced scientific expertise were central to the national interest and necessary for the maintenance of military/industrial and technological power. Half a century on, in the context of global economic and environmental crisis, as a justification for digital, industrial and biomedical innovation, the rationale for the production of scientific capital is central to curriculum settlements and educational policy in Europe, Asia and the Americas.

Assessing the structure of learning outcomes from counselling using the SOLO taxonomy: an exploratory study

Thirty-five clients who had received counselling completed a letter to a friend describing in as much detail as possible what they had learned from counselling. The participants' written responses were analysed and classified using the Structure of Learning Outcomes (SOLO) taxonomy. The results suggested that an expanded SOLO offers a promising and exciting way to view the outcomes of counselling within a learning framework. If the SOLO taxonomy is found to be stable in subsequent research, and clients are easily able to be classified using the taxonomy, then this approach may have implications for the process of counselling. To maximise the learning outcomes, counsellors could use strategies and techniques to enhance their clients' learning.

Micro-structure differences in kaolinite suspensions

SEM observations of the aqueous suspensions of kaolinite from Birdwood (South Australia) and Georgia (USA) show noticeable differences in number of physical behaviour which has been explained by different microstructure constitution.. Birdwood kaolinite dispersion gels are observed at very low solid loadings in comparison with Georgia KGa-1 kaolinite dispersions which remain fluid at higher solids loading. To explain this behaviour, the specific particle interactions of Birdwood kaolinite, different from interaction in Georgia kaolinite have been proposed. These interactions may be brought about by the presence of nano-bubbles on clay crystal edges and may force clay particles to aggregate by bubble coalescence. This explains the predominance of stair step edge-edge like (EE) contacts in suspension of Birdwood kaolinite. Such EE linked particles build long strings that form a spacious cell structure. Hydrocarbon contamination of colloidal kaolinite particles and low aspect ratio are discussed as possible explanations of this unusual behaviour of Birdwood kaolinite. In Georgia KGa-1 kaolinite dispersions instead of EE contact between platelets displayed in Birdwood kaolinite, most particles have edge to face (EF) contacts building a cardhouse structure. Such an arrangement is much less voluminous in comparison with the Birdwood kaolinite cellular honeycomb structure observed previously in smectite aqueous suspensions. Such structural characteristics of KGa-1 kaolinite particles enable higher solid volume fractions pulps to form before significantly networked gel consistency is attained.

Bayesian model averaging for harmful algal bloom prediction

Harmful Algal Blooms (HABs) are a worldwide problem that have been increasing in frequency and extent over the past several decades. HABs severely damage aquatic ecosystems by destroying benthic habitat, reducing invertebrate and fish populations and affecting larger species such as dugong that rely on seagrasses for food. Few statistical models for predicting HAB occurrences have been developed, and in common with most predictive models in ecology, those that have been developed do not fully account for uncertainties in parameters and model structure. This makes management decisions based on these predictions more risky than might be supposed. We used a probit time series model and Bayesian Model Averaging (BMA) to predict occurrences of blooms of Lyngbya majuscula, a toxic cyanophyte, in Deception Bay, Queensland, Australia. We found a suite of useful predictors for HAB occurrence, with Temperature figuring prominently in models with the majority of posterior support, and a model consisting of the single covariate average monthly minimum temperature showed by far the greatest posterior support. A comparison of alternative model averaging strategies was made with one strategy using the full posterior distribution and a simpler approach that utilised the majority of the posterior distribution for predictions but with vastly fewer models. Both BMA approaches showed excellent predictive performance with little difference in their predictive capacity. Applications of BMA are still rare in ecology, particularly in management settings. This study demonstrates the power of BMA as an important management tool that is capable of high predictive performance while fully accounting for both parameter and model uncertainty.