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.

Australia's GFC hangover

The credit crisis of the past few years has affected the development industry like no other. Whilst early signs of loosening in bank credit policy are emerging the ability of developers to proceed with new projects is still being constrained by their inability to obtain project finance.

In situ preparation and protein delivery of silicate/alginate composite microspheres with core-shell structure

It is predicted that with increased life expectancy in the developed world, there will be a greater demand for synthetic materials to repair or regenerate lost, injured or diseased bone (Hench & Thompson 2010). There are still few synthetic materials having true bone inductivity, which limits their application for bone regeneration, especially in large-size bone defects. To solve this problem, growth factors, such as bone morphogenetic proteins (BMPs), have been incorporated into synthetic materials in order to stimulate de novo bone formation in the center of large-size bone defects. The greatest obstacle with this approach is that the rapid diffusion of the protein from the carrier material, leading to a precipitous loss of bioactivity; the result is often insufficient local induction or failure of bone regeneration (Wei et al. 2007). It is critical that the protein is loaded in the carrier material in conditions which maintains its bioactivity (van de Manakker et al. 2009). For this reason, the efficient loading and controlled release of a protein from a synthetic material has remained a significant challenge. The use of microspheres as protein/drug carriers has received considerable attention in recent years (Lee et al. 2010; Pareta & Edirisinghe 2006; Wu & Zreiqat 2010). Compared to macroporous block scaffolds, the chief advantage of microspheres is their superior protein-delivery properties and ability to fill bone defects with irregular and complex shapes and sizes. Upon implantation, the microspheres are easily conformed to the irregular implant site, and the interstices between the particles provide space for both tissue and vascular ingrowth, which are important for effective and functional bone regeneration (Hsu et al. 1999). Alginates are natural polysaccharides and their production does not have the implicit risk of contamination with allo or xeno-proteins or viruses (Xie et al. 2010). Because alginate is generally cytocompatible, it has been used extensively in medicine, including cell therapy and tissue engineering applications (Tampieri et al. 2005; Xie et al. 2010; Xu et al. 2007). Calcium cross-linked alginate hydrogel is considered a promising material as a delivery matrix for drugs and proteins, since its gel microspheres form readily in aqueous solutions at room temperature, eliminating the need for harsh organic solvents, thereby maintaining the bioactivity of proteins in the process of loading into the microspheres (Jay & Saltzman 2009; Kikuchi et al. 1999). In addition, calcium cross-linked alginate hydrogel is degradable under physiological conditions (Kibat PG et al. 1990; Park K et al. 1993), which makes alginate stand out as an attractive candidate material for the protein carrier and bone regeneration (Hosoya et al. 2004; Matsuno et al. 2008; Turco et al. 2009). However, the major disadvantages of alginate microspheres is their low loading efficiency and also rapid release of proteins due to the mesh-like networks of the gel (Halder et al. 2005). Previous studies have shown that a core-shell structure in drug/protein carriers can overcome the issues of limited loading efficiencies and rapid release of drug or protein (Chang et al. 2010; Molvinger et al. 2004; Soppimath et al. 2007). We therefore hypothesized that introducing a core-shell structure into the alginate microspheres could solve the shortcomings of the pure alginate. Calcium silicate (CS) has been tested as a biodegradable biomaterial for bone tissue regeneration. CS is capable of inducing bone-like apatite formation in simulated body fluid (SBF) and its apatite-formation rate in SBF is faster than that of Bioglass® and A-W glass-ceramics (De Aza et al. 2000; Siriphannon et al. 2002). Titanium alloys plasma-spray coated with CS have excellent in vivo bioactivity (Xue et al. 2005) and porous CS scaffolds have enhanced in vivo bone formation ability compared to porous β-tricalcium phosphate ceramics (Xu et al. 2008). In light of the many advantages of this material, we decided to prepare CS/alginate composite microspheres by combining a CS shell with an alginate core to improve their protein delivery and mineralization for potential protein delivery and bone repair applications

Assessing the awareness and importance of housing sustainability in Queensland

Sustainability has been a major factor and determinant of commercial property design, construction, retro-fitting and landlord and tenant requirements over the last decade, supported by the introduction of rating tools such as NABERS and GreenStar and the recently mandated Building Energy Efficiency Certificate (BEEC). However, the movement to sustainable and energy efficient housing has not been established for the same period, and although mandatory building regulations have been in place for new residential housing construction since 2004, the requirement to improve the sustainability and energy efficiency of housing constructed prior to 2004 has not been mandatory. Residential dwelling energy efficiency and rating schemes introduced in Australia over the past decade have included rating schemes such as BASIX, NatHERS, First rate, ACTHERS, and Building Code of Australia and these have applied to new dwelling construction. At both National and State level the use of energy efficiency schemes for existing residential dwellings has been voluntary and despite significant cash incentives have not always been successful or achieved widespread take-up. In 2010, the Queensland Government regulated that all homes offered for sale, whether a new or existing dwellings require the seller to provide a ―sustainability declaration‖ that provides details of the sustainability measures associated with the dwelling being sold. The purpose of this declaration being to inform buyers and increase community awareness of home sustainability features. This paper uses an extensive review of real estate marketing material, together with a comprehensive survey of real estate agents to analyse the current market compliance, awareness and acceptance of existing green housing regulations and the importance that residential property owners and purchasers place on energy efficient and sustainable housing. The findings indicate that there is still little community awareness or concern of sustainable housing features when making home purchase decisions.

A Stochastic View of Optimal Regret through Minimax Duality

We study the regret of optimal strategies for online convex optimization games. Using von Neumann's minimax theorem, we show that the optimal regret in this adversarial setting is closely related to the behavior of the empirical minimization algorithm in a stochastic process setting: it is equal to the maximum, over joint distributions of the adversary's action sequence, of the difference between a sum of minimal expected losses and the minimal empirical loss. We show that the optimal regret has a natural geometric interpretation, since it can be viewed as the gap in Jensen's inequality for a concave functional--the minimizer over the player's actions of expected loss--defined on a set of probability distributions. We use this expression to obtain upper and lower bounds on the regret of an optimal strategy for a variety of online learning problems. Our method provides upper bounds without the need to construct a learning algorithm; the lower bounds provide explicit optimal strategies for the adversary. Peter L. Bartlett, Alexander Rakhlin

Design of decoupling networks for circulant symmetric antenna arrays

Small element spacing in compact arrays results in strong mutual coupling between array elements. Performance degradation associated with the strong coupling can be avoided through the introduction of a decoupling network consisting of interconnected reactive elements. We present a systematic design procedure for decoupling networks of symmetrical arrays with more than three elements and characterized by circulant scattering parameter matrices. The elements of the decoupling network are obtained through repeated decoupling of the characteristic eigenmodes of the array, which allows the calculation of element values using closed-form expressions.

Single-layer decoupling networks for circulant symmetric arrays

Reduced element spacing in antenna arrays gives rise to strong mutual coupling between array elements and may cause significant performance degradation. These effects can be alleviated by introducing a decoupling network consisting of interconnected reactive elements. The existing design approach for the synthesis of a decoupling network for circulant symmetric arrays allows calculation of element values using closed-form expressions, but the resulting circuit configuration requires multilayer technology for implementation. In this paper, a new structure for the decoupling of circulant symmetric arrays of more than four elements is presented. Element values are no longer obtained in closed form, but the resulting circuit is much simpler and can be implemented on a single layer.

Dual-frequency decoupling networks for compact antenna arrays

Decoupling networks can alleviate the effects of mutual coupling in antenna arrays. Conventional decoupling networks can provide decoupled and matched ports at a single frequency. This paper describes dual-frequency decoupling which is achieved by using a network of series or parallel resonant circuits instead of single reactive elements.

Design of compact coupled-line couplers

The size of rat-race and branch-line couplers can be reduced by using periodic loading or artificial transmission lines. The objective of this work is to extend the idea of size reduction through periodic loading to coupled-line 90° hybrids. A procedure for the extraction of the characteristic parameters of a coupled-line 4-port from a single set of S-parameters is described. This method can be employed to design of coupled artificial transmission line couplers of arbitrary geometry. The procedure is illustrated through the design a broadside-coupled stripline hybrid, periodically loaded with stubs. Measured results for a prototype coupler confirm the validity of the theory.

Multitask learning with expert advice

We consider the problem of prediction with expert advice in the setting where a forecaster is presented with several online prediction tasks. Instead of competing against the best expert separately on each task, we assume the tasks are related, and thus we expect that a few experts will perform well on the entire set of tasks. That is, our forecaster would like, on each task, to compete against the best expert chosen from a small set of experts. While we describe the “ideal” algorithm and its performance bound, we show that the computation required for this algorithm is as hard as computation of a matrix permanent. We present an efficient algorithm based on mixing priors, and prove a bound that is nearly as good for the sequential task presentation case. We also consider a harder case where the task may change arbitrarily from round to round, and we develop an efficient approximate randomized algorithm based on Markov chain Monte Carlo techniques.

Online discovery of similarity mappings

We consider the problem of choosing, sequentially, a map which assigns elements of a set A to a few elements of a set B. On each round, the algorithm suffers some cost associated with the chosen assignment, and the goal is to minimize the cumulative loss of these choices relative to the best map on the entire sequence. Even though the offline problem of finding the best map is provably hard, we show that there is an equivalent online approximation algorithm, Randomized Map Prediction (RMP), that is efficient and performs nearly as well. While drawing upon results from the "Online Prediction with Expert Advice" setting, we show how RMP can be utilized as an online approach to several standard batch problems. We apply RMP to online clustering as well as online feature selection and, surprisingly, RMP often outperforms the standard batch algorithms on these problems.

Optimal strategies and minimax lower bounds for online convex games

A number of learning problems can be cast as an Online Convex Game: on each round, a learner makes a prediction x from a convex set, the environment plays a loss function f, and the learner’s long-term goal is to minimize regret. Algorithms have been proposed by Zinkevich, when f is assumed to be convex, and Hazan et al., when f is assumed to be strongly convex, that have provably low regret. We consider these two settings and analyze such games from a minimax perspective, proving minimax strategies and lower bounds in each case. These results prove that the existing algorithms are essentially optimal.

Multitask learning with expert advice

We consider the problem of prediction with expert advice in the setting where a forecaster is presented with several online prediction tasks. Instead of competing against the best expert separately on each task, we assume the tasks are related, and thus we expect that a few experts will perform well on the entire set of tasks. That is, our forecaster would like, on each task, to compete against the best expert chosen from a small set of experts. While we describe the "ideal" algorithm and its performance bound, we show that the computation required for this algorithm is as hard as computation of a matrix permanent. We present an efficient algorithm based on mixing priors, and prove a bound that is nearly as good for the sequential task presentation case. We also consider a harder case where the task may change arbitrarily from round to round, and we develop an efficient approximate randomized algorithm based on Markov chain Monte Carlo techniques.

Beam steering with high front-to-back ratio and high directivity on small platforms using decoupled antenna pairs

Beam steering with high front-to-back ratio and high directivity on a small platform is proposed. Two closely spaced antenna pairs with eigenmode port decoupling are used as the basic radiating elements. Two orthogonal radiation patterns are obtained for each antenna pair. High front-to-back ratio and high directivity are achieved by combining the two orthogonal radiation patterns. With an infinite groundplane, a front-to-back ratio of 21 dB with a directivity of 9.8 dB can be achieved. Beam steering, at the expense of a slight decrease in directivity, is achieved by placing the two antenna pairs 0.5λ apart. The simulated half power beamwidth is 58°. A prototype was designed and the 2-D radiation patterns were measured. The prototype supports three directions of beam steering. The half power beamwidth was measured as 46°, 48°, and 50° for the three respective beam directions. The measured front-to-back ratio in azimuth plane is 8.5 dB, 8.0 dB and 7.6 dB, respectively.