Airborne engineered nanoparticles : are they a health problem?

This article focuses on airborne engineered nanoparticles generated in a growing number of commercial and research facilities. Despite their presence in the air of many such facilities, there are currently no established and validated measurement methods to detect them, characterise their properties or quantify their concentrations. In relation to their possible health impacts, the key questions include: (i) Are the particles in the nano-size range are more toxic than larger particles of the same material? (ii) Does the surface chemistry of the lung alters the toxicity of inhaled nanoparticles? (iii) Do nano-fibers pose the same risk as asbestos? and (iv) Are the methods for assessing the health risk are appropriate? This article summarises the state of knowledge in relation to these issues.

Perceptions of the psychological well-being and care of older home care clients : clients and their carers

Aim. To explore and compare older home care clients’ (65+) and their professionals’ perceptions of the clients’ psychological well-being and care and to identify possible differences in these perceptions. Background. Psychological well-being is considered an important dimension of quality of life. With advancing age, older people require home care support to be able to remain in their own home. The main goal of care is to maximise their independence and quality of life. Design. Descriptive, survey design with questionnaire. Methods. A postal questionnaire was distributed to 200 older home care clients and 570 social and health care professionals in 2007. The total response rate was 63%. The questionnaire consisted of questions about clients’ psychological well-being and the provision of care by home care professionals. The differences in responses between clients and professionals were analysed using cross-tabulations, the Pearson Chi-Square Test and Fisher’s Exact Tests. Results. The professional group believed that their clients did not have plans for the future. They believed that their clients felt themselves depressed and suffering from loneliness significantly more often than the client group did. The client group were also significantly more critical of the care (motivating independent actions, physical, psychological and social care) they got from the professional group than how the professionals evaluated the care they gave. Conclusions. To be able to support older clients to continue living at home, professionals need to provide a service that meets client’s own perceptions and complex social and health care needs as well as personal sense of well-being. Relevance to clinical practice. The findings offer useful insights for the professional in planning and delivering appropriate home care services. A better understanding of differences between clients’ and professionals’ perceptions could lead to a better individualised care outcome.

Effects of dry density and grain size distribution on soil-water characteristic curves of sandy soils

The unsaturated soil mechanics is receiving increasing attention from researchers and as well as from practicing engineers. However, the requirement of sophisticated devices to measure unsaturated soil properties and time consumption have made the geotechnical engineers keep away from implication of the unsaturated soil mechanics for solving practical geotechnical problems. The application of the conventional laboratory devices with some modifications to measure unsaturated soil properties can promote the application of unsaturated soil mechanics into engineering practice. Therefore, in the present study, a conventional direct shear device was modified to measure unsaturated shear strength parameters at low suction. Specially, for the analysis of rain-induced slope failures, it is important to measure unsaturated shear strength parameters at low suction where slopes become unstable. The modified device was used to measure unsaturated shear strength of two silty soils at low suction values (0 ~ 50 kPa) that were achieved by following drying path and wetting path of soil-water characteristic curves (SWCCs) of soils. The results revealed that the internal friction angle of soil was not significantly affected by the suction and as well as the drying-wetting SWCCs of soils. The apparent cohesion of soil increased with a decreasing rate as the suction increased. Further, the apparent cohesion obtained from soil in wetting was greater than that obtained from soil in drying. Shear stress-shear displacement curves obtained from soil specimens subjected to the same net normal stress and different suction values showed a higher initial stiffness and a greater peak stress as the suction increased. In addition, it was observed that soil became more dilative with the increase of suction. A soil in wetting exhibited slightly higher peak shear stress and more contractive volume change behaviour than that of in drying at the same net normal stress and the suction.

The impacts of traffic and rainfall characteristics on heavy metals build-up and wash-off from urban roads

An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE and GAIA. Initial analyses established high, low and moderate traffic scenarios as well as low, low to moderate, moderate, high and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75µm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 - >300 µm, whereas metal concentrations in finer size range of <1-75 µm were not affected. As practical implications, solids <1 µm and organic matter from 1 - >300 µm can be targeted for removal of Ni, Cu, Pb, Cd, Cr and Zn from build-up whilst organic matter from <1 - >300 µm can be targeted for removal of Cd, Cr, Pb and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.

Alkaline hydrothermal treatment of titanate nanostructures

Since its initial proposal in 1998, alkaline hydrothermal processing has rapidly become an established technology for the production of titanate nanostructures. This simple, highly reproducible process has gained a strong research following since its conception. However, complete understanding and elucidation of nanostructure phase and formation have not yet been achieved. Without fully understanding phase, formation, and other important competing effects of the synthesis parameters on the final structure, the maximum potential of these nanostructures cannot be obtained. Therefore this study examined the influence of synthesis parameters on the formation of titanate nanostructures produced by alkaline hydrothermal treatment. The parameters included alkaline concentration, hydrothermal temperature, the precursor material‘s crystallite size and also the phase of the titanium dioxide precursor (TiO2, or titania). The nanostructure‘s phase and morphology was analysed using X-ray diffraction (XRD), Raman spectroscopy and transmission electron microscopy. X-ray photoelectron spectroscopy (XPS), dynamic light scattering (non-invasive backscattering), nitrogen sorption, and Rietveld analysis were used to determine phase, for particle sizing, surface area determinations, and establishing phase concentrations, respectively. This project rigorously examined the effect of alkaline concentration and hydrothermal temperature on three commercially sourced and two self-prepared TiO2 powders. These precursors consisted of both pure- or mixed-phase anatase and rutile polymorphs, and were selected to cover a range of phase concentrations and crystallite sizes. Typically, these precursors were treated with 5–10 M sodium hydroxide (NaOH) solutions at temperatures between 100–220 °C. Both nanotube and nanoribbon morphologies could be produced depending on the combination of these hydrothermal conditions. Both titania and titanate phases are comprised of TiO6 units which are assembled in different combinations. The arrangement of these atoms affects the binding energy between the Ti–O bonds. Raman spectroscopy and XPS were therefore employed in a preliminary study of phase determination for these materials. The change in binding energy from a titania to a titanate binding energy was investigated in this study, and the transformation of titania precursor into nanotubes and titanate nanoribbons was directly observed by these methods. Evaluation of the Raman and XPS results indicated a strengthening in the binding energies of both the Ti (2p3/2) and O (1s) bands which correlated to an increase in strength and decrease in resolution of the characteristic nanotube doublet observed between 320 and 220 cm.1 in the Raman spectra of these products. The effect of phase and crystallite size on nanotube formation was examined over a series of temperatures (100.200 �‹C in 20 �‹C increments) at a set alkaline concentration (7.5 M NaOH). These parameters were investigated by employing both pure- and mixed- phase precursors of anatase and rutile. This study indicated that both the crystallite size and phase affect nanotube formation, with rutile requiring a greater driving force (essentially �\harsher. hydrothermal conditions) than anatase to form nanotubes, where larger crystallites forms of the precursor also appeared to impede nanotube formation slightly. These parameters were further examined in later studies. The influence of alkaline concentration and hydrothermal temperature were systematically examined for the transformation of Degussa P25 into nanotubes and nanoribbons, and exact conditions for nanostructure synthesis were determined. Correlation of these data sets resulted in the construction of a morphological phase diagram, which is an effective reference for nanostructure formation. This morphological phase diagram effectively provides a .recipe book�e for the formation of titanate nanostructures. Morphological phase diagrams were also constructed for larger, near phase-pure anatase and rutile precursors, to further investigate the influence of hydrothermal reaction parameters on the formation of titanate nanotubes and nanoribbons. The effects of alkaline concentration, hydrothermal temperature, crystallite phase and size are observed when the three morphological phase diagrams are compared. Through the analysis of these results it was determined that alkaline concentration and hydrothermal temperature affect nanotube and nanoribbon formation independently through a complex relationship, where nanotubes are primarily affected by temperature, whilst nanoribbons are strongly influenced by alkaline concentration. Crystallite size and phase also affected the nanostructure formation. Smaller precursor crystallites formed nanostructures at reduced hydrothermal temperature, and rutile displayed a slower rate of precursor consumption compared to anatase, with incomplete conversion observed for most hydrothermal conditions. The incomplete conversion of rutile into nanotubes was examined in detail in the final study. This study selectively examined the kinetics of precursor dissolution in order to understand why rutile incompletely converted. This was achieved by selecting a single hydrothermal condition (9 M NaOH, 160 °C) where nanotubes are known to form from both anatase and rutile, where the synthesis was quenched after 2, 4, 8, 16 and 32 hours. The influence of precursor phase on nanostructure formation was explicitly determined to be due to different dissolution kinetics; where anatase exhibited zero-order dissolution and rutile second-order. This difference in kinetic order cannot be simply explained by the variation in crystallite size, as the inherent surface areas of the two precursors were determined to have first-order relationships with time. Therefore, the crystallite size (and inherent surface area) does not affect the overall kinetic order of dissolution; rather, it determines the rate of reaction. Finally, nanostructure formation was found to be controlled by the availability of dissolved titanium (Ti4+) species in solution, which is mediated by the dissolution kinetics of the precursor.

How do consumers react to physically larger models? Effects of model body size, weight control beliefs and product type on evaluations and body perceptions

The purpose of this article is to examine how a consumer’s weight control beliefs (WCB), a female advertising model’s body size (slim or large) and product type influence consumer evaluations and consumer body perceptions. The study uses an experiment of 371 consumers. The design of the experiment was a 2 (weight control belief: internal, external) X 2 (model size: larger sized, slim) X 2 (product type: weight controlling, non-weight controlling) between-participants factorial design. Results reveal two key contributions. First, larger sized models result in consumers feeling less pressure from society to be thin, viewing their actual shape as slimmer relative to viewing a slim model and wanting a thinner ideal body shape. Slim models result in the opposite effects. Second this research reveals a boundary condition for the extent to which endorser–product congruency theory can be generalized to endorsers of a larger body size. Results indicate that consumer WCB may be a useful variable to consider when marketers consider the use of larger models in advertising.

Visual field size criteria for mobility rehabilitation referral

Purpose. To investigate evidence-based visual field size criteria for referral of low-vision (LV) patients for mobility rehabilitation. Methods. One hundred and nine participants with LV and 41 age-matched participants with normal sight (NS) were recruited. The LV group was heterogeneous with diverse causes of visual impairment. We measured binocular kinetic visual fields with the Humphrey Field Analyzer and mobility performance on an obstacle-rich, indoor course. Mobility was assessed as percent preferred walking speed (PPWS) and number of obstacle-contact errors. The weighted kappa coefficient of association (κr) was used to discriminate LV participants with both unsafe and inefficient mobility from those with adequate mobility on the basis of their visual field size for the full sample and for subgroups according to type of visual field loss and whether or not the participants had previously received orientation and mobility training. Results. LV participants with both PPWS <38% and errors >6 on our course were classified as having inadequate (inefficient and unsafe) mobility compared with NS participants. Mobility appeared to be first compromised when the visual field was less than about 1.2 steradians (sr; solid angle of a circular visual field of about 70° diameter). Visual fields <0.23 and 0.63 sr (31 to 52° diameter) discriminated patients with at-risk mobility for the full sample and across the two subgroups. A visual field of 0.05 sr (15° diameter) discriminated those with critical mobility. Conclusions. Our study suggests that: practitioners should be alert to potential mobility difficulties when the visual field is less than about 1.2 sr (70° diameter); assessment for mobility rehabilitation may be warranted when the visual field is constricted to about 0.23 to 0.63 sr (31 to 52° diameter) depending on the nature of their visual field loss and previous history (at risk); and mobility rehabilitation should be conducted before the visual field is constricted to 0.05 sr (15° diameter; critical).

Longitudinal investigation of wandering behavior in department of veterans affairs nursing home care units

Objectives To explore the extent of and factors associated with male residents who change wandering status post nursing home admission. Design Longitudinal design with secondary data analyses. Admissions over a 4-year period were examined using repeat assessments with the Minimum Data Set (MDS) to formulate a model understanding the development of wandering behavior. Setting One hundred thirty-four Veterans Administration (VA) nursing homes throughout the United States. Participants: Included 6673 residents admitted to VA nursing homes between October 2000 and October 2004. Measurements MDS variables (cognitive impairment, mood, behavior problems, activities of daily living and wandering) included ratings recorded at residents’ admission to the nursing home and a minimum of two other time points at quarterly intervals. Results The majority (86%) of the sample were classified as non wanderers at admission and most of these (94%) remained non wanderers until discharge or the end of the study. Fifty one per cent of the wanderers changed status to non wanderers with 6% of these residents fluctuating in status more than two times. Admission variables associated with an increased risk of changing status from non-wandering to wandering included older age, greater cognitive impairment, more socially inappropriate behavior, resisting care, easier distractibility, and needing less help with personal hygiene. Requiring assistance with locomotion and having three or more medical comorbidities were associated with a decreased chance of changing from non-wandering to wandering status. Conclusion A resident’s change from non-wandering to wandering status may reflect an undetected medical event that affects cognition, but spares mobility.

Vision only pose estimation and scene reconstruction on airborne platforms

We aim to demonstrate unaided visual 3D pose estimation and map reconstruction using both monocular and stereo vision techniques. To date, our work has focused on collecting data from Unmanned Aerial Vehicles, which generates a number of significant issues specific to the application. Such issues include scene reconstruction degeneracy from planar data, poor structure initialisation for monocular schemes and difficult 3D reconstruction due to high feature covariance. Most modern Visual Odometry (VO) and related SLAM systems make use of a number of sensors to inform pose and map generation, including laser range-finders, radar, inertial units and vision [1]. By fusing sensor inputs, the advantages and deficiencies of each sensor type can be handled in an efficient manner. However, many of these sensors are costly and each adds to the complexity of such robotic systems. With continual advances in the abilities, small size, passivity and low cost of visual sensors along with the dense, information rich data that they provide our research focuses on the use of unaided vision to generate pose estimates and maps from robotic platforms. We propose that highly accurate (�5cm) dense 3D reconstructions of large scale environments can be obtained in addition to the localisation of the platform described in other work [2]. Using images taken from cameras, our algorithm simultaneously generates an initial visual odometry estimate and scene reconstruction from visible features, then passes this estimate to a bundle-adjustment routine to optimise the solution. From this optimised scene structure and the original images, we aim to create a detailed, textured reconstruction of the scene. By applying such techniques to a unique airborne scenario, we hope to expose new robotic applications of SLAM techniques. The ability to obtain highly accurate 3D measurements of an environment at a low cost is critical in a number of agricultural and urban monitoring situations. We focus on cameras as such sensors are small, cheap and light-weight and can therefore be deployed in smaller aerial vehicles. This, coupled with the ability of small aerial vehicles to fly near to the ground in a controlled fashion, will assist in increasing the effective resolution of the reconstructed maps.

Sustainability and mandatory disclosure in Queensland : an assessment of the impact on home buyer patterns

Sustainability Declarations were introduced by the Queensland State Government on 1 January 2010 as a compulsory measure for all dwelling sales. The purpose of this policy decision was to improve the relevance of sustainability in the home ownership decision making process. This paper assesses the initial impact of this initiative over its first year in operation. In partnership with the Real Estate Institute of Queensland, real estate agents and salespeople in Queensland were surveyed to determine what impact the Sustainability Declaration has had on home buyer decision making. The level of compliance by the real estate industry was also reviewed. These preliminary findings indicate a high level of compliance from the real estate industry, however results confirm that sustainability is yet to become a criterion of relevance to the majority of home buyers in Queensland. The Sustainability Declarations are a first step in raising awareness in home owners of the importance of sustainability in housing. Further monitoring of this impact will be carried out over time.

The seasonal phenology of Bactrocera tryoni (Froggatt) (Diptera: Tephritidae) in Queensland

Bactrocera tryoni is a polyphagous fruit fly, originally endemic to tropical and subtropical coastal eastern Australia, but now also widely distributed in temperate eastern Australia. In temperate parts of its range, B. tryoni populations show distinct seasonal peaks driven by changing seasonal climates, especially changing temperature. In contrast to temperate areas, the seasonal phenology of B. tryoni in subtropical and tropical parts of its range is poorly documented and the role of climate unknown. Using a large, historical (1940s and 1950s) fruit fly trapping data set, we present the seasonal phenology of B. tryoni at nine sites across Queensland for multiple (two to seven) years per site. We correlate monthly trap data for each site with monthly weather averages (temperature, rainfall and relative humidity) to investigate climatic influences. We also correlate observed population data with predicted population data generated by an existing B. tryoni population model. Supporting predictions from climate driven models, B. tryoni did show year-round breeding at most Queensland sites. However, contrary to predictions, there was a common pattern of a significant population decline in autumn and winter, followed by a rapid population increase in August and then one or more distinct peaks of abundance in spring and summer. Mean monthly fly abundance was significantly different across sites, but was not correlated with altitudinal, latitudinal or longitudinal gradients. There were very few significant correlations between monthly fly population size and weather variables for eight of the nine sites. For the southern site of Gatton fly population abundance was correlated with temperature. Results suggest that while climate factors may be influencing B. tryoni populations in southern subtropical Queensland, they appear to be having only minor or no influence in northern sub-tropical and tropical Queensland. In the discussion we focus on the role of other factors, particularly larval host plant availability, as likely drivers of B. tryoni abundance in tropical and subtropical parts of its range.

Diversity management for innovation in social enterprises in the UK

This paper examines the linkages between diversity management (DM), innovation and high performance in social enterprises. These linkages are explicated beyond traditional framing of DM limited to workforce composition, to include discussions of innovation through networked diversity practices; reconciliation; and funding options. The paper draws upon a UK-based national survey and the case study data. Multiple data collection methods were used, including semi-structured interviews, questionnaires and workshops with participant observation. NVivo and SPSS software packages were utilized in order to analyse the qualitative and quantitative data, respectively. We used thematic coding and cropping techniques in analysing the case studies in the paper. A broad range of conflicting and supporting literature was enfolded into the conversations and discussion. The paper demonstrates that social enterprises exhibit unique characteristics in terms of size and location, as well as their double remit to add value both economically and socially. As a conclusion, we argue for social enterprises to consider options for DM in the interests of maximization of innovation and business performance. We contend that further research is needed to describe how social entrepreneurs draw upon their various ‘diversity resources’ in the process of innovation

Range sensor pose estimation

This paper presents a method of recovering the 6 DoF pose (Cartesian position and angular rotation) of a range sensor mounted on a mobile platform. The method utilises point targets in a local scene and optimises over the error between their absolute position and their apparent position as observed by the range sensor. The analysis includes an investigation into the sensitivity and robustness of the method. Practical results were collected using a SICK LRS2100 mounted on a P&H electric mining shovel and present the errors in scan data relative to an independent 3D scan of the scene. A comparison to directly measuring the sensor pose is presented and shows the significant accuracy improvements in scene reconstruction using this pose estimation method.

Discovering characteristics of stochastic collections of process models

Process models in organizational collections are typically modeled by the same team and using the same conventions. As such, these models share many characteristic features like size range, type and frequency of errors. In most cases merely small samples of these collections are available due to e.g. the sensitive information they contain. Because of their sizes, these samples may not provide an accurate representation of the characteristics of the originating collection. This paper deals with the problem of constructing collections of process models, in the form of Petri nets, from small samples of a collection for accurate estimations of the characteristics of this collection. Given a small sample of process models drawn from a real-life collection, we mine a set of generation parameters that we use to generate arbitrary-large collections that feature the same characteristics of the original collection. In this way we can estimate the characteristics of the original collection on the generated collections.We extensively evaluate the quality of our technique on various sample datasets drawn from both research and industry.