Land price dynamics in a large Australian urban housing market

Purpose – Housing is a composite asset comprising land and improved components varying as proportions of total value over space and time. Theory suggests land and improvements (structures) are unique goods responding differently to economic stimuli. This paper aims to test the expectation of different overall house price changes in response to variation in land and improved components. Design/methodology/approach – House price dynamics are decomposed to analyse the influence of land and structure components for the city of Perth, Australia both at aggregate level and for spatially defined housing sub-regions, sample period 1995-2010. Findings – Values of land and improvements on that land evolve differently over time and are significantly influenced by the magnitude of land leverage. The study extends previous research through extensive spatial disaggregation of a larger more detailed data set than previously used in studies of this type confirming significant variation in land leverage ratios, overall price change and growth rates for land and improvements in sub-regional markets defined by spatial criteria.Research limitations/implications – The results suggest an important role for policy development with respect to housing affordability and supply side regulation of land in large urban housing markets. Practical implications – The results suggest important implications for hedonic price analysis of housing markets. The inclusion of land leverage variables in hedonic regression could remove coefficient bias associated with omitted location amenity variables. Originality/value – The paper adapts methodology from previous studies but extends previous literature through detailed analysis of a large Australian housing market (Perth) enabling extensive spatial disaggregation of the sample and providing greater insight to spatial variation of land leverage than in previous studies

Topological Defects in Twisted Bundles of Two-Dimensionally Ordered Filaments

Twisted assemblies of filaments in ropes, cables and bundles are essential structural elements in wide use in macroscopic materials as well as within the cells and tissues of living organisms. We develop the unique, non-linear elastic properties of twisted filament bundles that derive from generic properties of two-dimensional line-ordered materials. Continuum elasticity reveals a formal equivalence between the elastic stresses induced by bundle twist and those induced by the positive curvature in thin, elastic sheets. These geometrically-induced stresses can be screened by 5-fold disclination defects in lattice packing, and we predict a discrete spectrum elastic energy groundstates associated with integer numbers of disclinations in cylindrical bundles. Finally, we show that elastic-energy groundstates are extremely sensitive to defect position in the cross-section, with off-center disclinations driving the entire bundle to buckle, adopting globally writhing configurations.Comment: 4.1 pages; 3 figure

Analysis of the Maximum Efficiency of Kite-Power Systems

This paper analyzes the maximum power that a kite, or system of kites, can extract from the wind. Firstly, a number of existing results on kite system efficiency are reviewed. The results that are generally applicable require significant simplifying assumptions, usually neglecting the effects of inertia and gravity. On the other hand, the more precise analyses are usually only applicable to a particular type of kite-power system. Secondly, a novel result is derived that relates the maximum power output of a kite system to the angle of the average aerodynamic force produced by the system. This result essentially requires no limiting assumptions, and as such it is generally applicable. As it considers average forces that must be balanced, inertial forces are implicitly accounted for. In order to derive practically useful results, the maximum power output is expressed in terms of the system overall strength-to-weight ratio, the tether angle and the tether drag through an efficiency factor. The result is a simple analytic expression that can be used to calculate the maximum power-producing potential for a system of wings, flying either dynamically or statically, supported by a tether. As an example, the analysis is applied to two systems currently under development, namely, pumping-cycle generators and jet-stream wind power

A vision for global monitoring of biological invasions

Managing biological invasions relies on good global coverage of species distributions. Accurate information on alien species distributions, obtained from international policy and cross-border co-operation, is required to evaluate trans-boundary and trading partnership risks. However, a standardized approach for systematically monitoring alien species and tracking biological invasions is still lacking. This Perspective presents a vision for global observation and monitoring of biological invasions. We show how the architecture for tracking biological invasions is provided by a minimum information set of Essential Variables, global collaboration on data sharing and infrastructure, and strategic contributions by countries. We show how this novel, synthetic approach to an observation system for alien species provides a tangible and attainable solution to delivering the information needed to slow the rate of new incursions and reduce the impacts of invaders. We identify three Essential Variables for Invasion Monitoring; alien species occurrence, species alien status and alien species impact. We outline how delivery of this minimum information set by joint, complementary contributions from countries and global community initiatives is possible. Country contributions are made feasible using a modular approach where all countries are able to participate and strategically build their contributions to a global information set over time. The vision we outline will deliver wide-ranging benefits to countries and international efforts to slow the rate of biological invasions and minimize their environmental impacts. These benefits will accrue over time as global coverage and information on alien species increases

Real-Time Optimizing Control of an Experimental Crosswind Power Kite

The contribution of this article is to propose and experimentally validate an optimizing control strategy for power kites flying crosswind. The control strategy provides both path control (stability) and path optimization (efficiency). The path following part of the controller is capable of robustly following a reference path, despite significant time delays, using position measurements only. The path-optimization part adjusts the reference path in order to maximize line tension. It uses a real-time optimization algorithm that combines off-line modeling knowledge and on-line measurements. The algorithm has been tested comprehensively on a small-scale prototype, and this article focuses on experimental results

Application of Real-Time Optimization Methods to Energy Systems in the Presence of Uncertainties and Disturbances

In practice, the quest for the optimal operation of energy systems is complicated by the presence of operating constraints, which includes the need to produce the power required by the user, and by the need to account for uncertainty. The latter concept incorporates the potential inaccuracies of the models at hand but also degradation effects or unexpected changes, such as, e.g. random load changes or variations of the availability of the energy source for renewable energy systems. Since these changes affect the optimal values of the operating conditions, online adaptation is required to ensure that the system is always operated optimally. This typically implies the online solving of an optimization problem. Unfortunately, the applicability and the performances of most model-based optimization methods rely on the quality of the available model of the system under investigation. On the other hand, Real-time optimization (RTO) methods use the available online measurements in the optimization framework and are, thus, capable of bringing the desired self-optimizing control reaction. In this article, we show the benefits of using several RTO methods (co-) developed by the authors to energy systems through the successful application of (i) "Real-Time Optimization via Modifier Adaptation" to an experimental solid oxide fuel cells (SOFC) stack, of (ii) the recently released "SCFO-solver" (where SCFO stands for “Sufficient Conditions of Feasibility and Optimality”) to an industrial SOFC stack, and of (iii) Dynamic RTO to a simulated tethered kite for renewable power production. It is shown how such problems can be formulated and solved, and significant improvements of the performances of the three aforementioned energy systems are illustrated

Extension of Modifier Adaptation for Controlled Plants using Static Open-Loop Models

Model-based optimization methods suffer from the limited accuracy of the available process models. Because of plant-model mismatch, model-based optimal inputs may be suboptimal or, worse, unfeasible for the plant. Modifier adaptation (MA) overcomes this obstacle by incorporating measurements in the optimization framework. However, the standard MA formulation requires that (1) the model satisfies adequacy conditions and (2) the model and the plant share the same degrees of freedom. In this article, three extensions of MA to problems where (2) does not hold are proposed. In particular, we consider the case of controlled plants for which the only a model of the open-loop plant is available. These extensions are shown to preserve the ability of MA to converge to the plant optimum despite disturbances and plant-model mismatch. The proposed methods are illustrated in simulation for the optimization of a CSTR

Error Control Coding Techniques for Space and Satellite Communications

Turbo coding using iterative SOVA decoding and M-ary differentially coherent or non-coherent modulation can provide an effective coding modulation solution: (1) Energy efficient with relatively simple SOVA decoding and small packet lengths, depending on BEP required; (2) Low number of decoding iterations required; and (3) Robustness in fading with channel interleaving

2022 Top Trends in Academic Libraries

This article summarizes trending topics in academic librarianship from the past two years–a time of tremendous upheaval and change, including a global pandemic, difficult reflections concerning racial justice, and war between nation states. Rapid changes and uncertainty from these events have created a significant amount of shifts to academic libraries, higher education, and society in general. Such shifts have yielded new perspectives and innovations in how librarians approach delivering services, supporting student success, managing staff and physical spaces, embracing new technology, and managing data. This report attempts to provide a snapshot of developments worth noting

Moving pictures of the human microbiome

BackgroundUnderstanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn’s disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints.ResultsWe find that despite stable differences between body sites and individuals, there is pronounced variability in an individual’s microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members.ConclusionsDNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions