Stimulation of osteogenic and angiogenic ability of cells on polymers by pulsed laser deposition of uniform akermanite-glass nanolayer

Polymer biomaterials have been widely used for bone replacement/regeneration because of their unique mechanical properties and workability. Their inherent low bioactivity makes them lack osseointegration with host bone tissue. For this reason, bioactive inorganic particles have been always incorporated into the matrix of polymers to improve their bioactivity. However, mixing inorganic particles with polymers always results in inhomogeneity of particle distribution in polymer matrix with limited bioactivity. This study sets out to apply the pulsed laser deposition (PLD) technique to prepare uniform akermanite (Ca2MgSi2O7, AKT) glass nanocoatings on the surface of two polymers (non-degradable polysulfone (PSU) and degradable polylactic acid (PDLLA)) in order to improve their surface osteogenic and angiogenic activity. The results show that a uniform nanolayer composed of amorphous AKT particles (∼30nm) of thickness 130nm forms on the surface of both PSU and PDLLA films with the PLD technique. The prepared AKT-PSU and AKT-PDLLA films significantly improved the surface roughness, hydrophilicity, hardness and apatite mineralization, compared with pure PSU and PDLLA, respectively. The prepared AKT nanocoatings distinctively enhance the alkaline phosphate (ALP) activity and bone-related gene expression (ALP, OCN, OPN and Col I) of bone-forming cells on both PSU and PDLLA films. Furthermore, AKT nanocoatings on two polymers improve the attachment, proliferation, VEGF secretion and expression of proangiogenic factors and their receptors of human umbilical vein endothelial cells (HUVEC). The results suggest that PLD-prepared bioceramic nanocoatings are very useful for enhancing the physicochemical, osteogenic and angiogenic properties of both degradable and non-degradable polymers for application in bone replacement/regeneration.

Modelling of arc welding : the importance of including the arc plasma in the computational domain

We present results of computational simulations of tungsten-inert-gas and metal-inert-gas welding. The arc plasma and the electrodes (including the molten weld pool when necessary) are included self-consistently in the computational domain. It is shown, using three examples, that it would be impossible to accurately estimate the boundary conditions on the weld-pool surface without including the arc plasma in the computational domain. First, we show that the shielding gas composition strongly affects the properties of the arc that influence the weld pool: heat flux density, current density, shear stress and arc pressure at the weld-pool surface. Demixing is found to be important in some cases. Second, the vaporization of the weld-pool metal and the diffusion of the metal vapour into the arc plasma are found to decrease the heat flux density and current density to the weld pool. Finally, we show that the shape of the wire electrode in metal-inert-gas welding has a strong influence on flow velocities in the arc and the pressure and shear stress at the weld-pool surface. In each case, we present evidence that the geometry and depth of the weld pool depend strongly on the properties of the arc.

Investigation on bioactivity of titanium dioxide thin films fabricated by electron cyclotron resonance plasma aided pulsed laser deposition

Titanium dioxide thin films with a rutile crystallinite size around 20 nm were fabricated by pulsed laser deposition (PLD) aided with an electron cyclotron resonance (ECR) plasma. With annealing treatment, the crystal size of the rutile crystallinite increased to 100 nm. The apatite-forming ability of the films as deposited and after annealing was investigated in a kind of simulated body fluid with ion concentrations nearly equal to those of human blood plasma. The results indicate that ECR aided PLD is an effective way both to fabricate bioactive titanium dioxide thin films and to optimize the bioactivity of titanium dioxide, with both crystal size and defects of the film taken into account.

The impact of fuser roller temperature on laser printer particle emission

The emission of particles in the ultrafine range (<100 nm) from laser printers has not been reported until recently (Uhde et al., 2006; He et al., 2007; Morawska et al., 2009). The research reported to date has provided a body of information about printer emissions and shed light on particle formation mechanisms. However, until now, the effect of fuser roller temperature on particle emissions had not been comprehensively investigated...

Thermal effect of plasmon oscillations on the tunnel current in gold nanoisland thin film at low laser intensity

The effect of plasmon oscillations on the DC tunnel current in a gold nanoisland thin film (GNITF) is investigated using low intensity P~1W/cm2 continuous wave lasers. While DC voltages (1–150 V) were applied to the GNITF, it was irradiated with lasers at different wavelengths (k¼473, 532, and 633 nm). Because of plasmon oscillations, the tunnel current increased. It is found that the tunnel current enhancement is mainly due to the thermal effect of plasmon oscillations rather than other plasmonic effects. The results are highly relevant to applications of plasmonic effects in opto-electronic devices.

Raman-active wurtzite CdO nanophase and phonon signatures in CdO/ZnO heterostructures fabricated by nonequilibrium laser plasma ablation and stress control

A combination of laser plasma ablation and strain control in CdO/ZnO heterostructures is used to produce and stabilize a metastable wurtzite CdO nanophase. According to the Raman selection rules, this nanophase is Raman-active whereas the thermodynamically preferred rocksalt phase is inactive. The wurtzite-specific and thickness/strain-dependent Raman fingerprints and phonon modes are identified and can be used for reliable and inexpensive nanophase detection. The wurtzite nanophase formation is also confirmed by x-ray diffractometry. The demonstrated ability of the metastable phase and phonon mode control in CdO/ZnO heterostructures is promising for the development of next-generation light emitting sources and exciton-based laser diodes.

Efficiently capturing large, complex cultural heritage sites with a handheld mobile 3D laser mapping system

Accurate three-dimensional representations of cultural heritage sites are highly valuable for scientific study, conservation, and educational purposes. In addition to their use for archival purposes, 3D models enable efficient and precise measurement of relevant natural and architectural features. Many cultural heritage sites are large and complex, consisting of multiple structures spatially distributed over tens of thousands of square metres. The process of effectively digitising such geometrically complex locations requires measurements to be acquired from a variety of viewpoints. While several technologies exist for capturing the 3D structure of objects and environments, none are ideally suited to complex, large-scale sites, mainly due to their limited coverage or acquisition efficiency. We explore the use of a recently developed handheld mobile mapping system called Zebedee in cultural heritage applications. The Zebedee system is capable of efficiently mapping an environment in three dimensions by continually acquiring data as an operator holding the device traverses through the site. The system was deployed at the former Peel Island Lazaret, a culturally significant site in Queensland, Australia, consisting of dozens of buildings of various sizes spread across an area of approximately 400 × 250 m. With the Zebedee system, the site was scanned in half a day, and a detailed 3D point cloud model (with over 520 million points) was generated from the 3.6 hours of acquired data in 2.6 hours. We present results demonstrating that Zebedee was able to accurately capture both site context and building detail comparable in accuracy to manual measurement techniques, and at a greatly increased level of efficiency and scope. The scan allowed us to record derelict buildings that previously could not be measured because of the scale and complexity of the site. The resulting 3D model captures both interior and exterior features of buildings, including structure, materials, and the contents of rooms.

Understanding welding practices on shipyards : an ethnographic study for designing an interactive robot welder

The aim of this ethnographic study was to understand welding practices in shipyard environments with the purpose of designing an interactive welding robot that can help workers with their daily job. The robot is meant to be deployed for automatic welding on jack-up rig structures. The design of the robot turns out to be a challenging task due to several problematic working conditions on the shipyard, such as dust, irregular floor, high temperature, wind variations, elevated working platforms, narrow spaces, and circular welding paths requiring a robotic arm with more than 6 degrees of freedom. Additionally, the environment is very noisy and the workers – mostly foreigners – have a very basic level of English. These two issues need to be taken into account when designing the interactive user interface for the robot. Ideally, the communication flow between the two parties involved should be as frictionless as possible. The paper presents the results of our field observations and welders’ interviews, as well as our robot design recommendation for the next project stage.

Histogram matching and global initialization for laser-only SLAM in large unstructured environments

This paper presents an enhanced algorithm for matching laser scan maps using histogram correlations. The histogram representation effectively summarizes a map's salient features such that pairs of maps can be matched efficiently without any prior guess as to their alignment. The histogram matching algorithm has been enhanced in order to work well in outdoor unstructured environments by using entropy metrics, weighted histograms and proper thresholding of quality metrics. Thus our large-scale scan-matching SLAM implementation has a vastly improved ability to close large loops in real-time even when odometry is not available. Our experimental results have demonstrated a successful mapping of the largest area ever mapped to date using only a single laser scanner. We also demonstrate our ability to solve the lost robot problem by localizing a robot to a previously built map without any prior initialization.

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.