The behaviour of regional housing markets and construction: implications for modelling sub-regional housing supply

Recent advances in modelling housing investment in the UK and the United States have centred on estimation of price elasticity of supply and on estimating key relationships in the behaviour of housing prices and construction output at regional level. Yet, there are two main limitations evident in existing knowledge. First, the extent to which many operational models reconcile with underlying economic theory is limited. For example, a number of published studies fail to find construction costs or land prices to be significant predictors of new housing investment. Second, the recent focus on national and regional models has had the result that the impact of planning controls on housing investment, and price elasticity of supply in particular, is not generally well understood. Drawing on a recent project funded by the UK Government’s National Housing and Planning Advice Unit, this paper compares several approaches to modelling new housing investment at regional level in England. It advances a multi-equation approach to explain new housing construction and the behaviour of house prices. Significantly, the suggested modelling approach includes explicit recognition of the endogeneity of residential development land prices and planning controls

Do soil microbes drive Acacia species invasion in non-native ranges in Australia?

Australian acacias are one of the most notable invaders worldwide. Across Australian states, acacias became invasive or even naturalized after being introduced to ecosystems outside their natural distribution range. The relative importance of soil biota in their invasion success remains unknown, particularly that of rhizobial and fungal communities. We tested the Enemy Release Hypothesis and the Acquired Mutualism Hypothesis to disentangle the belowground invasion mechanisms that may have assisted in the invasion success of these acacias across Australia

Real-Time Path Planning in Constrained, Uncertain Environments

A key enabler of autonomous vehicles is the ability to plan the path of the vehicle to accomplish mission objectives. To be robust to realistic environments, path planners must account for uncertainty in the trajectory of the vehicle as well as uncertainty in the location of obstacles. The uncertainty in the trajectory of the vehicle is a difficult quantity to estimate, and is influenced by coupling between the vehicle dynamics, guidance, navigation, and control system as well as any disturbances acting on the vehicle. Monte Carlo analysis is the conventional approach to determine vehicle dispersion, while accounting for the coupled nature of the system. Due to the computational complexity of Monte Carlo analysis, this approach to calculating vehicle dispersion quickly becomes prohibitive for real-time applications, high dimensional systems. Modern or Closed-Loop Linear Covariance (LinCov) analysis linearizes the vehicle dynamics and GNC about a nominal trajectory, and computes the same information as Monte Carlo analysis but in a single run. This paper develops a LinCov framework capable of modeling the dynamics, guidance, navigation, and control of autonomous vehicles and validated the framework by comparison to Monte Carlo analysis. The developed framework is applied to the path planning of an unmanned aerial vehicle (UAV). The rapidly exploring random trees (RRT) algorithm is augmented with statistical information provided by the LinCov simulation and a model of the uncertainty of obstacles. It is demonstrated that the developed path planner efficiently guides the UAV through the obstacle field while maintaining the probability of collision below a user-specified value

Large scale prop-fan structural design study. Volume 1: Initial concepts

In recent years, considerable attention has been directed toward improving aircraft fuel consumption. Studies have shown that the inherent efficiency advantage that turboprop propulsion systems have demonstrated at lower cruise speeds may now be extended to the higher speeds of today's turbofan and turbojet-powered aircraft. To achieve this goal, new propeller designs will require features such as thin, high speed airfoils and aerodynamic sweep, features currently found only in wing designs for high speed aircraft. This is Volume 1 of a 2 volume study to establish structural concepts for such advanced propeller blades, to define their structural properties, to identify any new design, analysis, or fabrication techniques which were required, and to determine the structural tradeoffs involved with several blade shapes selected primarily on the basis of aero/acoustic design considerations. The feasibility of fabricating and testing dynamically scaled models of these blades for aeroelastic testing was also established. The preliminary design of a blade suitable for flight use in a testbed advanced turboprop was conducted and is described in Volume 2

Resilience for Multi-filter All-source Navigation Framework with Integrity

The Autonomous and Resilient Management of All-source Sensors (ARMAS) framework monitors residual-space test statistics across unique sensor-exclusion banks of filters, (known as subfilters) to provide a resilient, fault-resistant all-source navigation architecture with assurance. A critical assumption of this architecture, demonstrated in this paper, is fully overlapping state observability across all subfilters. All-source sensors, particularly those that only provide partial state information (altimeters, TDoA, AOB, etc.) do not intrinsically meet this requirement. This paper presents a novel method to monitor real-time overlapping position state observability and introduces an observability bank within the ARMAS framework, known as Stable Observability Monitoring (SOM). SOM uses real-time stability analysis to provide an intrinsic awareness to ARMAS of the capabilities of the fault detection and exclusion (FDE) functionality. We define the ability to maintain consistent all-source FDE to recover failed sensors as navigation resilience. A resilient FDE capability then is one that is aware of when it requires more sensor information to protect the consistency of the FDE and integrity functions from corruption. SOM is the first demonstration of such a system, for all-source sensors, that the authors are aware. A multi-agent 3D environment simulating both GNSS and position and velocity alternative navigation sensors was created and individual GNSS pseudorange sensor anomalies are utilized to demonstrate the capabilities of the novel algorithm. This paper demonstrates that SOM seamlessly integrates within the ARMAS framework, provides timely prompts to augment with new sensor information from other agents, and indicates when framework stability and preservation of all-source navigation integrity are achieved

Virtual Testbed for Monocular Visual Navigation of Small Unmanned Aircraft Systems

Monocular visual navigation methods have seen significant advances in the last decade, recently producing several real-time solutions for autonomously navigating small unmanned aircraft systems without relying on GPS. This is critical for military operations which may involve environments where GPS signals are degraded or denied. However, testing and comparing visual navigation algorithms remains a challenge since visual data is expensive to gather. Conducting flight tests in a virtual environment is an attractive solution prior to committing to outdoor testing. This work presents a virtual testbed for conducting simulated flight tests over real-world terrain and analyzing the real-time performance of visual navigation algorithms at 31 Hz. This tool was created to ultimately find a visual odometry algorithm appropriate for further GPS-denied navigation research on fixed-wing aircraft, even though all of the algorithms were designed for other modalities. This testbed was used to evaluate three current state-of-the-art, open-source monocular visual odometry algorithms on a fixed-wing platform: Direct Sparse Odometry, Semi-Direct Visual Odometry, and ORB-SLAM2 (with loop closures disabled)

Structural Transition Kinetics and Activated Behavior in the Superconducting Vortex Lattice

Using small-angle neutron scattering, we investigated the behavior of a metastable vortex lattice state in MgB2 as it is driven towards equilibrium by an AC magnetic field. This shows an activated behavior, where the AC field amplitude and cycle count are equivalent to, respectively, an effective "temperature" and "time". The activation barrier increases as the metastable state is suppressed, corresponding to an aging of the vortex lattice. Furthermore, we find a cross-over from a partial to a complete suppression of metastable domains depending on the AC field amplitude, which may empirically be described by a single free parameter. This represents a novel kind of collective vortex behavior, most likely governed by the nucleation and growth of equilibrium vortex lattice domains.Comment: 5 pages plus 3 pages of supplemental materia