Synthesis and thermal stability of hydrotalcites based upon gallium

Hydrotalcites based upon gallium as a replacement for aluminium in hydrotalcite over a Mg/Al ratio of 2:1 to 4:1 were synthesised. The d(003) spacing varied from 7.83 A ° for the 2:1 hydrotalcite to 8.15 A ° for the 3:1 gallium containing hydrotalcite. A comparison is made with the Mg Al hydrotalcite in which the d(003) spacing for the Mg/Al hydrotalcite varied from 7.62 A ° for the 2:1Mg hydrotalcite to 7.98 A ° for the 4:1 hydrotalcite. The thermal stability of the gallium containing hydrotalcite was determined using thermogravimetric analysis. Four mass loss steps at 77, 263–280,485 and 828 degrees C with mass losses of 10.23, 21.55, 5.20 and 7.58% are attributed to dehydration, dehydroxylation and decarbonation. The thermal stability of the galliumcontaining hydrotalcite is slightly less than the aluminium hydrotalcite.

Acoustic, mechanical and near-infrared profiling of osteoarthritic progression in bovine joints

Early-stage treatments for osteoarthritis are attracting considerable interest as a means to delay, or avoid altogether, the pain and lack of mobility associated with late-stage disease, and the considerable burden that it places on the community. With the development of these treatments comes a need to assess the tissue to which they are applied, both in trialling of new treatments and as an aid to clinical decision making. Here, we measure a range of mechanical indentation, ultrasound and near-infrared spectroscopy parameters in normal and osteoarthritic bovine joints in vitro to describe the role of different physical phenomena in disease progression, using this as a basis to investigate the potential value of the techniques as clinical tools. Based on 72 samples we found that mechanical and ultrasound parameters showed differences between fibrillated tissue, macroscopically normal tissue in osteoarthritic joints, and normal tissue, yet did were unable to differentiate degradation beyond that which was visible to the naked eye. Near-infrared spectroscopy showed a clear progression of degradation across the visibly normal osteoarthritic joint surface and as such, was the only technique considered useful for clinical application.

Towards robust night and day place recognition using visible and thermal imaging

The chief challenge facing persistent robotic navigation using vision sensors is the recognition of previously visited locations under different lighting and illumination conditions. The majority of successful approaches to outdoor robot navigation use active sensors such as LIDAR, but the associated weight and power draw of these systems makes them unsuitable for widespread deployment on mobile robots. In this paper we investigate methods to combine representations for visible and long-wave infrared (LWIR) thermal images with time information to combat the time-of-day-based limitations of each sensing modality. We calculate appearance-based match likelihoods using the state-of-the-art FAB-MAP [1] algorithm to analyse loop closure detection reliability across different times of day. We present preliminary results on a dataset of 10 successive traverses of a combined urban-parkland environment, recorded in 2-hour intervals from before dawn to after dusk. Improved location recognition throughout an entire day is demonstrated using the combined system compared with methods which use visible or thermal sensing alone.

Gender differences in recreational and transport cycling : a cross-sectional mixed-methods comparison of cycling patterns, motivators, and constraints

Background: Gender differences in cycling are well-documented. However, most analyses of gender differences make broad comparisons, with few studies modeling male and female cycling patterns separately for recreational and transport cycling. This modeling is important, in order to improve our efforts to promote cycling to women and men in countries like Australia with low rates of transport cycling. The main aim of this study was to examine gender differences in cycling patterns and in motivators and constraints to cycling, separately for recreational and transport cycling. Methods: Adult members of a Queensland, Australia, community bicycling organization completed an online survey about their cycling patterns; cycling purposes; and personal, social and perceived environmental motivators and constraints (47% response rate). Closed and open-end questions were completed. Using the quantitative data, multivariable linear, logistic and ordinal regression models were used to examine associations between gender and cycling patterns, motivators and constraints. The qualitative data were thematically analysed to expand upon the quantitative findings. Results: In this sample of 1862 bicyclists, men were more likely than women to cycle for recreation and for transport, and they cycled for longer. Most transport cycling was for commuting, with men more likely than women to commute by bicycle. Men were more likely to cycle on-road, and women off-road. However, most men and women did not prefer to cycle on-road without designed bicycle lanes, and qualitative data indicated a strong preference by men and women for bicycle-only off-road paths. Both genders reported personal factors (health and enjoyment related) as motivators for cycling, although women were more likely to agree that other personal, social and environmental factors were also motivating. The main constraints for both genders and both cycling purposes were perceived environmental factors related to traffic conditions, motorist aggression and safety. Women, however, reported more constraints, and were more likely to report as constraints other environmental factors and personal factors. Conclusion: Differences found in men’s and women’s cycling patterns, motivators and constraints should be considered in efforts to promote cycling, particularly in efforts to increase cycling for transport.

Numerical Modelling of Mechanical Behaviour of Graphene

Graphene, one of the allotropes (diamond, carbon nanotube, and fullerene) of element carbon, is a monolayer of honeycomb lattice of carbon atoms, which was discovered in 2004. The Nobel Prize in Physics 2010 was awarded to Andre Geim and Konstantin Novoselov for their ground breaking work on the two-dimensional (2D) graphene [1]. Since its discovery, the research communities have shown a lot of interest in this novel material owing to its intriguing electrical, mechanical and thermal properties. It has been confirmed that grapheme possesses very peculiar electrical properties such as anomalous quantum hall effect, and high electron mobility at room temperature (250000 cm2/Vs). Graphene also has exceptional mechanical properties. It is one of the stiffest (modulus ~1 TPa) and strongest (strength ~100 GPa) materials. In addition, it has exceptional thermal conductivity (5000 Wm-1K-1). Due to these exceptional properties, graphene has demonstrated its potential for broad applications in micro and nano devices, various sensors, electrodes, solar cells and energy storage devices and nanocomposites. In particular, the excellent mechanical properties of graphene make it more attractive for development next generation nanocomposites and hybrid materials...

3D thermal mapping of building interiors using an RGB-D and thermal camera

The building sector is the dominant consumer of energy and therefore a major contributor to anthropomorphic climate change. The rapid generation of photorealistic, 3D environment models with incorporated surface temperature data has the potential to improve thermographic monitoring of building energy efficiency. In pursuit of this goal, we propose a system which combines a range sensor with a thermal-infrared camera. Our proposed system can generate dense 3D models of environments with both appearance and temperature information, and is the first such system to be developed using a low-cost RGB-D camera. The proposed pipeline processes depth maps successively, forming an ongoing pose estimate of the depth camera and optimizing a voxel occupancy map. Voxels are assigned 4 channels representing estimates of their true RGB and thermal-infrared intensity values. Poses corresponding to each RGB and thermal-infrared image are estimated through a combination of timestamp-based interpolation and a pre-determined knowledge of the extrinsic calibration of the system. Raycasting is then used to color the voxels to represent both visual appearance using RGB, and an estimate of the surface temperature. The output of the system is a dense 3D model which can simultaneously represent both RGB and thermal-infrared data using one of two alternative representation schemes. Experimental results demonstrate that the system is capable of accurately mapping difficult environments, even in complete darkness.

Deformation and failure of graphene sheet and graphene-polymer interface

With a monolayer honeycomb-lattice of sp2-hybridized carbon atoms, graphene has demonstrated exceptional electrical, mechanical and thermal properties. One of its promising applications is to create graphene-polymer nanocomposites with tailored mechanical and physical properties. In general, the mechanical properties of graphene nanofiller as well as graphene-polymer interface govern the overall mechanical performance of graphene-polymer nanocomposites. However, the strengthening and toughening mechanisms in these novel nanocomposites have not been well understood. In this work, the deformation and failure of graphene sheet and graphene-polymer interface were investigated using molecular dynamics (MD) simulations. The effect of structural defects on the mechanical properties of graphene and graphene-polymer interface was investigated as well. The results showed that structural defects in graphene (e.g. Stone-Wales defect and multi-vacancy defect) can significantly deteriorate the fracture strength of graphene but may still make full utilization of corresponding strength of graphene and keep the interfacial strength and the overall mechanical performance of graphene-polymer nanocomposites.

Mechanical and biological characterization of a porous poly-L-lactic acid-co-ε-caprolactone scaffold for tissue engineering

This article presents a method for making highly porous biodegradable scaffold that may ultimately be used for tissue engineering. Poly(L-lactic-co-1-caprolactone) acid (70:30) (PLCL) scaffold was produced using the solvent casting/leaching out method, which entails dissolving the polymer and adding a porogen that is then leached out by immersing the scaffold in distillated water. Tensile tests were performed for three types of scaffolds, namely pre-wetted, dried, and UV-irradiated scaffolds and their mechanical properties were measured. The prewetted PLCL scaffold possessed a modulus of elasticity 0.92+0.09 MPa, a tensile strength of 0.12+0.03 MPa and an ultimate strain of 23+5.3%. No significant differences in the modulus elasticity, tensile strength, nor ultimate strain were found between the pre-wetted, dried, and UV irradiated scaffolds. The PLCL scaffold was seeded by human fibroblasts in order to evaluate its biocompatibility by Alamar bluew assays. After 10 days of culture, the scaffolds showed good biocompatibility and allowed cell proliferation. However, the fibroblasts stayed essentially at the surface. This study shows the possibility to use the PLCL scaffold in dynamic mechanical conditions for tissue engineering

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Comparison of mechanical and ultrasound elastic modulus of ovine tibial cortical bone

Finite element models of bones can be created by deriving geometry from anx-ray CT scan. Material properties such as the elastic modulus can then be applied using either a single or set of homogeneous values, or individual elements can have local values mapped onto them. Values for the elastic modulus can be derived from the CT density values using an elasticityversus density relationship. Many elasticity–density relationships have been reported in the literature for human bone. However, while ovine in vivo models are common in orthopaedic research, no work has been done to date on creating FE models of ovine bones. To create these models and apply relevant material properties, an ovine elasticity-density relationship needs to be determined. Using fresh frozen ovine tibias the apparent density of regions of interest was determined from a clinical CT scan. The bones were the sectioned into cuboid samples of cortical bone from the regions of interest. Ultrasound was used to determine the elastic modulus in each of three directions – longitudinally, radially and tangentially. Samples then underwent traditional compression testing in each direction. The relationships between apparent density and both ultrasound, and compression modulus in each directionwere determined. Ultrasound testing was found to be a highly repeatable non-destructive method of calculating the elastic modulus, particularly suited to samples of this size. The elasticity-density relationships determined in the longitudinal direction were very similar between the compression and ultrasound data over the density range examined.A clear difference was seen in the elastic modulus between the longitudinal and transverse directions of the bone samples, and a transverse elasticity-density relationship is also reported.

Synthesis, mechanical and electrical properties of carbon microcoils and nanocoils

The results on the synthesis, mechanical and electrical properties of carbon microcoils and nanocoils (CMCs, CNCs) synthesized using catalytic CVD and Ni-P and Co-P catalyst alloys, respectively, are reported. SEM analysis reveals that the CMCs and CNCs have unique helical morphologies, and diameters of 5.0-9.0 μm and 450-550 nm, respectively. Moreover, CMCs with flat cross-section can be stretched to 3 times their original coil lengths. Current-voltage characteristics of a single microcoil have also been obtained. It is found that the CMCs have the electrical conductivity between 100 and 160 S/cm, whereas the electrical resistance increases by about 20% during the coil extension. Besides, the microcoils can produce light in vacuum when the test voltage reaches 10 V. The emission intensity increases as the voltage increases. The mechanical and electrical properties of CMCs and CNC make them potentially useful in many applications in micromagnetic sensors, mechanical microsprings and optoelectronics.

The mechanical and inflammatory low back pain (MIL) index: development and validation

Abstract Background The purpose of this study was the development of a valid and reliable “Mechanical and Inflammatory Low Back Pain Index” (MIL) for assessment of non-specific low back pain (NSLBP). This 7-item tool assists practitioners in determining whether symptoms are predominantly mechanical or inflammatory. Methods Participants (n = 170, 96 females, age = 38 ± 14 years-old) with NSLP were referred to two Spanish physiotherapy clinics and completed the MIL and the following measures: the Roland Morris Questionnaire (RMQ), SF-12 and “Backache Index” (BAI) physical assessment test. For test-retest reliability, 37 consecutive patients were assessed at baseline and three days later during a non-treatment period. Face and content validity, practical characteristics, factor analysis, internal consistency, discriminant validity and convergent validity were assessed from the full sample. Results A total of 27 potential items that had been identified for inclusion were subsequently reduced to 11 by an expert panel. Four items were then removed due to cross-loading under confirmatory factor analysis where a two-factor model yielded a good fit to the data (χ2 = 14.80, df = 13, p = 0.37, CFI = 0.98, and RMSEA = 0.029). The internal consistency was moderate (α = 0.68 for MLBP; 0.72 for ILBP), test-retest reliability high (ICC = 0.91; 95%CI = 0.88-0.93) and discriminant validity good for either MLBP (AUC = 0.74) and ILBP (AUC = 0.92). Convergent validity was demonstrated through similar but weak correlations between the ILBP and both the RMQ and BAI (r = 0.34, p < 0.001) and the MLBP and BAI (r = 0.38, p < 0.001). Conclusions The MIL is a valid and reliable clinical tool for patients with NSLBP that discriminates between mechanical and inflammatory LBP. Keywords: Low back pain; Psychometrics properties; Pain measurement; Screening tool; Inflammatory; Mechanical