Fumaric acid monoethyl ester-functionalized poly(D,L-Lactide)/N-vinyl-2- pyrrolidone Resins for the preparation of tissue engineering scaffolds by stereolithography

Polymer networks were prepared by photocross-linking fumaric acid monoethyl ester (FAME) functionalized, three-armed poly(D,L-lactide) oligomers using Af-vinyl-2-pyrrolidone (NVP) as diluent and comonomer. The use of NVP together with FAME-functionalized oligomers resulted in copolymerization at high rates, and networks with gel contents in excess of 90 were obtained. The hydrophilicity of the poly(D,L-lactide) networks increases with increasing amounts of NVP, networks containing 50 wt of NVP absorbed 40 of water. As the amount of NVP was increased from 30 to 50 wt , the Young's modulus after equilibration in water decreased from 0.8 to 0.2 GPa, as opposed to an increase from 1.5 to 2.1 GPa in the dry state. Mouse preosteoblasts readily adhered and spread onto all prepared networks. Using stereolithography, porous structures with a well-defined gyroid architecture were prepared from these novel materials. This allows the preparation of tissue engineering scaffolds with optimized pore architecture and tunable material properties.

A poly(D,L-lactide) resin for the preparation of tissue engineering scaffolds by stereolithography

Porous polylactide constructs were prepared by stereolithography, for the first time without the use of reactive diluents. Star-shaped poly(D,L-lactide) oligomers with 2, 3 and 6 arms were synthesised, end-functionalised with methacryloyl chloride and photocrosslinked in the presence of ethyl lactate as a non-reactive diluent. The molecular weights of the arms of the macromers were 0.2, 0.6, 1.1 and 5 kg/mol, allowing variation of the crosslink density of the resulting networks. Networks prepared from macromers of which the molecular weight per arm was 0.6 kg/mol or higher had good mechanical properties, similar to linear high molecular weight poly(D,L-lactide). A resin based on a 2-armed poly(D,L-lactide) macromer with a molecular weight of 0.6 kg/mol per arm (75 wt%), ethyl lactate (19 wt%), photo-initiator (6 wt%), inhibitor and dye was prepared. Using this resin, films and computer-designed porous constructs were accurately fabricated by stereolithography. Pre-osteoblasts showed good adherence to these photocrosslinked networks. The proliferation rate on these materials was comparable to that on high molecular weight poly(D,L-lactide) and tissue culture polystyrene.

Photo-cross-linked poly(D,L-lactide)-based networks. Structural characterization by HR-MAS NMR spectroscopy and hydrolytic degradation behavior

To date, biodegradable networks and particularly their kinetic chain lengths have been characterized by analysis of their degradation products in solution. We characterize the network itself by NMR analysis in the solvent-swollen state under magic angle spinning conditions. The networks were prepared by photoinitiated cross-linking of poly(dl-lactide)−dimethacrylate macromers (5 kg/mol) in the presence of an unreactive diluent. Using diffusion filtering and 2D correlation spectroscopy techniques, all network components are identified. By quantification of network-bound photoinitiator fragments, an average kinetic chain length of 9 ± 2 methacrylate units is determined. The PDLLA macromer solution was also used with a dye to prepare computer-designed structures by stereolithography. For these networks structures, the average kinetic chain length is 24 ± 4 methacrylate units. In all cases the calculated molecular weights of the polymethacrylate chains after degradation are maximally 8.8 kg/mol, which is far below the threshold for renal clearance. Upon incubation in phosphate buffered saline at 37 °C, the networks show a similar mass loss profile in time as linear high-molecular-weight PDLLA (HMW PDLLA). The mechanical properties are preserved longer for the PDLLA networks than for HMW PDLLA. The initial tensile strength of 47 ± 2 MPa does not decrease significantly for the first 15 weeks, while HMW PDLLA lost 85 ± 5% of its strength within 5 weeks. The physical properties, kinetic chain length, and degradation profile of these photo-cross-linked PDLLA networks make them most suited materials for orthopedic applications and use in (bone) tissue engineering.

Designed biodegradable hydrogel structures prepared by stereolithography using poly(ethylene glycol)/poly(D,L-lactide)-based resins

Designed three-dimensional biodegradable poly(ethylene glycol)/poly(D,L-lactide) hydrogel structures were prepared for the first time by stereolithography at high resolutions. A photopolymerisable aqueous resin comprising PDLLA-PEG-PDLLA-based macromer, visible light photo-initiator, dye and inhibitor in DMSO/water was used to build the structures. Porous and non-porous hydrogels with well-defined architectures and good mechanical properties were prepared. Porous hydrogel structures with a gyroid pore network architecture showed narrow pore size distributions, excellent pore interconnectivity and good mechanical properties. The structures showed good cell seeding characteristics, and human mesenchymal stem cells adhered and proliferated well on these materials.

Knowledge about health benefits of Vitamin D in Queensland Australia

In Queensland, Australia, the ultraviolet (UV) radiation levels are high (greater than UV Index 3) almost all year round. Although ambient UV is about three times higher in summer compared to winter, Queensland residents receive approximately equal personal doses of UV radiation within these seasons (Neale et al., 2010). Sun protection messages throughout the year are thus essential (Montague et al., 2001), need to reach all segments of the population, and should incorporate guidelines for maintenance of adequate vitamin D levels. Knowledge is an essential requirement to allow people to make health conscious decisions. Unprompted knowledge commonly requires a higher level of awareness or recency of acquisition compared to prompted recall (Waller et al., 2004). This paper thus reports further on the data from a 2008 population-based, cross-sectional telephone survey conducted in Queensland, Australia (2,001 participants; response rate=45%) (Youl et al., 2009). It was the aim of this research to establish the level of, and factors predicting, unprompted and prompted knowledge about health and vitamin D.

Properties of photo-cured poly(D,L-lactide) networks

Poly(D,L-lactide) is a degradable polymer with a long history of use in medical applications. It is strong and stiff and degrades over the course of months into lactic acid, a body-own substance. In the field of tissue engineering it is commonly used to fabricate scaffolds. Stereolithography is a high resolution rapid prototyping technique by which designed 3D objects can be built using photo-initiated radical polymerisations. Poly(D,Llactide) (PDLLA) networks can be obtained by photopolymerisation of oligomers functionalised with unsaturated groups. In this work, PDLLA oligomers of varying architectures (arm lengths, numbers of arms) were synthesised and end-functionalised with methacrylate groups. These macromers were photo-crosslinked in solution to yield PDLLA networks of different architectures. The influence of the network architecture on its physical properties was studied.

Poly(D,L-lactide)/hydroxyapatite composite tissue engineering scaffolds prepared by stereolithography

Hydroxyapatite (HAP) is a major component of bone and has osteoconductive and -inductive properties. It has been successfully applied as a substrate in bone tissue engineering, either with or without a biodegradable polymer such as polycaprolactone or polylactide. Recently, we have developed a stereolithography resin based on poly(D,L-lactide) (PDLLA) and a non-reactive diluent, that allows for the preparation of tissue engineering scaffolds with designed architectures. In this work, designed porous composite structures of PDLLA and HAP are prepared by stereolithography.

Designed poly(ethylene glycol)/poly(D,L-lactide)-based hydrogel structures prepared by stereolithography

Three-dimensional biodegradable poly(ethylene glycol)/poly(D,L-lactide) hydrogel structures were prepared by stereolithography. A photo-polymerisable liquid resin comprising PDLLA-PEG-PDLLA-based macromer, visible light photo-initiator, dye and inhibitor in DMSO/water was used to build the structures. Hydrogels with welldefined architectures and good mechanical properties were prepared. Hydrogel structures with a gyroid pore network architecture showed narrow pore size distributions, excellent pore interconnectivity and good mechanical properties. The structures showed good cell seeding characteristics, and human mesenchymal stem cells adhered and proliferated on these materials.

A regional construction R&D evaluation system for China

Expenditure on R&D in the China construction industry has been relatively low in comparison with many developed countries for a number of years – a situation considered to be a major barrier to the industry’s competitiveness in general and unsatisfactory industry development of the 31 regions involved. A major problem with this is the lack of a sufficiently sophisticated method of objectively evaluating R&D activity in what are quite complex circumstances considering the size and regional differences that exist in this part of the world. A regional construction R&D evaluation system (RCRES) is presented aimed at rectifying the situation. This is based on 12 indicators drawn from the Chinese Government’s R&D Inventory of Resources in consultation with a small group of experts in the field, and further factor analysed into three groups. From this, the required evaluation is obtained by a simple formula. Examination of the results provides a ranking list of the R&D performance of each of the 31 regions, indicating a general disproportion between coastal and inland regions and highlighting regions receiving special emphasis or currently lacking in development. The understanding on this is vital for the future of China’s construction industry.

Improving the performance of model-order selection criteria by partial-model selection search

The traditional searching method for model-order selection in linear regression is a nested full-parameters-set searching procedure over the desired orders, which we call full-model order selection. On the other hand, a method for model-selection searches for the best sub-model within each order. In this paper, we propose using the model-selection searching method for model-order selection, which we call partial-model order selection. We show by simulations that the proposed searching method gives better accuracies than the traditional one, especially for low signal-to-noise ratios over a wide range of model-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model-order selection criteria can be applied to find the optimal order. Some of the more commonly used information theoretic-based procedures include Akaike’s information criterion (AIC) [1], corrected Akaike (AICc) [2], minimum description length (MDL) [3], normalized maximum likelihood (NML) [4], Hannan-Quinn criterion (HQC) [5], conditional model-order estimation (CME) [6], and the efficient detection criterion (EDC) [7]. From a practical point of view, it is difficult to decide which model order selection criterion to use. Many of them perform reasonably well when the signal-to-noise ratio (SNR) is high. The discrepancies in their performance, however, become more evident when the SNR is low. In those situations, the performance of the given technique is not only determined by the model structure (say a polynomial trend versus a Fourier series) but, more importantly, by the relative values of the parameters within the model. This makes the comparison between the model-order selection algorithms difficult as within the same model with a given order one could find an example for which one of the methods performs favourably well or fails [6, 8]. Our aim is to improve the performance of the model order selection criteria in cases where the SNR is low by considering a model-selection searching procedure that takes into account not only the full-model order search but also a partial model order search within the given model order. Understandably, the improvement in the performance of the model order estimation is at the expense of additional computational complexity.

Model-order selection in Zernike polynomial expansion of corneal surfaces using the efficient detection criterion

Corneal-height data are typically measured with videokeratoscopes and modeled using a set of orthogonal Zernike polynomials. We address the estimation of the number of Zernike polynomials, which is formalized as a model-order selection problem in linear regression. Classical information-theoretic criteria tend to overestimate the corneal surface due to the weakness of their penalty functions, while bootstrap-based techniques tend to underestimate the surface or require extensive processing. In this paper, we propose to use the efficient detection criterion (EDC), which has the same general form of information-theoretic-based criteria, as an alternative to estimating the optimal number of Zernike polynomials. We first show, via simulations, that the EDC outperforms a large number of information-theoretic criteria and resampling-based techniques. We then illustrate that using the EDC for real corneas results in models that are in closer agreement with clinical expectations and provides means for distinguishing normal corneal surfaces from astigmatic and keratoconic surfaces.

Autonomous underwater vehicle trajectory design coupled with predictive ocean models : a case study

Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceano- graphic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to manoeuvre through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.

The smart skies project

This paper describes the Smart Skies project, an ambitious and world-leading research endeavor exploring the development of key enabling technologies, which support the efficient utilization of airspace by manned and unmanned airspace users. This paper provides a programmatic description of the research and development of: an automated separation management system, a mobile aircraft tracking system, and aircraft-based sense-and-act technologies. A summary of the results from a series of real-world flight testing campaigns is also presented.

Distributed object tracking with robot and disjoint camera networks

We describe a novel two stage approach to object localization and tracking using a network of wireless cameras and a mobile robot. In the first stage, a robot travels through the camera network while updating its position in a global coordinate frame which it broadcasts to the cameras. The cameras use this information, along with image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to track the objects. We present results with a nine node indoor camera network to demonstrate that this approach is feasible and offers acceptable level of accuracy in terms of object locations.