An extreme planetary system around HD 219828: one long-period super Jupiter to a hot-Neptune host star

Context. With about 2000 extrasolar planets confirmed, the results show that planetary systems have a whole range of unexpected properties. This wide diversity provides fundamental clues to the processes of planet formation and evolution. Aims: We present a full investigation of the HD 219828 system, a bright metal-rich star for which a hot Neptune has previously been detected. Methods: We used a set of HARPS, SOPHIE, and ELODIE radial velocities to search for the existence of orbiting companions to HD 219828. The spectra were used to characterise the star and its chemical abundances, as well as to check for spurious, activity induced signals. A dynamical analysis is also performed to study the stability of the system and to constrain the orbital parameters and planet masses. Results: We announce the discovery of a long period (P = 13.1 yr) massive (m sini = 15.1 MJup) companion (HD 219828 c) in a very eccentric orbit (e = 0.81). The same data confirms the existence of a hot Neptune, HD 219828 b, with a minimum mass of 21 M⊕ and a period of 3.83 days. The dynamical analysis shows that the system is stable, and that the equilibrium eccentricity of planet b is close to zero. Conclusions: The HD 219828 system is extreme and unique in several aspects. First, ammong all known exoplanet systems it presents an unusually high mass ratio. We also show that systems like HD 219828, with a hot Neptune and a long-period massive companion are more frequent than similar systems with a hot Jupiter instead. This suggests that the formation of hot Neptunes follows a different path than the formation of their hot jovian counterparts. The high mass, long period, and eccentricity of HD 219828 c also make it a good target for Gaia astrometry as well as a potential target for atmospheric characterisation, using direct imaging or high-resolution spectroscopy. Astrometric observations will allow us to derive its real mass and orbital configuration. If a transit of HD 219828 b is detected, we will be able to fully characterise the system, including the relative orbital inclinations. With a clearly known mass, HD 219828 c may become a benchmark object for the range in between giant planets and brown dwarfs.

Quarantine facilities and legal issues of the use of biocontrol agents in Brazil.

The objective of this work was to address the classical biological control of pests in Brazil, regarding procedures to import and export native biological material. A brief introduction will be given on the current legal issues on the use of biocontrol agents, as well as some considerations on the existing quarantine pests and actions already carried out in the country. The safety in the introduction of exotic organisms is important for Brazilian phytosanitary defense and for a higher adoption of classical biocontrol, making it available for integrated pest management (IPM). Legal and normative aspects establish the procedures that must to be adopted, not only to protect bioprospecting and native organisms, but also to minimize risks to the national genetic patrimony associated with the introduction of exotic organisms. Furthermore, the import/export procedures adopted for vegetal and useful organisms for pest biological control and for other genetic material must be subjected to phytosanitary measures performed in government?certified quarantine facilities and diagnostic laboratories. Finally, the quarantine activities listed here are strategic for safeguarding the country from potential problems arising from border transit of living organisms.

Connected digital cities

In the future we will have a detailed ecological model of the whole planet with capabilities to explore and predict the consequences of alternative futures. However, such a planetary eco-model will take time to develop, time to populate with data, and time to validate - time the planet doesn't have. In the interim, we can model the major concentrations of energy use and pollution - our cities - and connect them to form a "talking cities network". Such a networked city model would be much quicker to build and validate. And the advantage of this approach is that it is safer and more effective for us to interfere with the operation of our cities than to tamper directly with the behaviour of natural systems. Essentially, it could be thought of as providing the planet with a nervous system and would empower us to better develop and manage sustainable cities.

Phylogenetic placement of the sugarcane orange rust pathogen Puccinia kuehnii in a historical and regional context

Sugarcane orange rust, caused by Puccinia kuehnii, was once considered a minor disease in the Australian sugar industry. However, in 2000 a new race of the pathogen devastated the high-performing sugarcane cultivar Q124, and caused the industry Aus$150–210 million in yield losses. At the time of the epidemic, very little was known about the genetic and pathogenic diversity of the fungus in Australia and neighbouring sugar industries. DNA sequence data from three rDNA regions were used to determine the genetic relationships between isolates within two P. kuehnii collections. The first collection comprised only recent Australian field isolates and limited sequence variation was detected within this population. In the second study, Australian isolates were compared with isolates from Papua New Guinea, Indonesia, China and historical herbarium collections. Greater sequence variation was detected in this collection and phylogenetic analyses grouped the isolates into three clades. All isolates from commercial cane fields clustered together including the recent Australianfield isolates and the Australian historical isolate from 1898.The other two clades included rust isolates from wild and garden canes in Indonesia and PNG. These rusts appeared morphologically similar to P. kuehnii and could potentially pose a quarantine threat to the Australian sugar industry. The results have revealed greater diversity in sugarcane rusts than previously thought.

High porosity chained aggregates from the topsoil of the lunar regolith dust

The unusual behaviour of fine lunar regolith like stickiness and low heat conductivity is dominated by the structural arrangement of its finest fraction. Here, we show the previously unknown phenomenon of a globular 3D superstructure within the dust fraction of regolith. A study using the recently developed Transmission X-ray Microscopy (TXM) with tomographic reconstruction reveals a highly porous network of cellular voids in the finest dust fraction aggregates in lunar soil. Such porous chained aggregates are composed of sub-micron particles that form a network of cellular voids a few micrometers in diameter. Discovery of such a superstructure within the finest fraction of lunar topsoil enables a model of heat transfer to be constructed.

Info-gap theory and robust design of surveillance for invasive species : the case study of Barrow Island

Surveillance for invasive non-indigenous species (NIS) is an integral part of a quarantine system. Estimating the efficiency of a surveillance strategy relies on many uncertain parameters estimated by experts, such as the efficiency of its components in face of the specific NIS, the ability of the NIS to inhabit different environments, and so on. Due to the importance of detecting an invasive NIS within a critical period of time, it is crucial that these uncertainties be accounted for in the design of the surveillance system. We formulate a detection model that takes into account, in addition to structured sampling for incursive NIS, incidental detection by untrained workers. We use info-gap theory for satisficing (not minimizing) the probability of detection, while at the same time maximizing the robustness to uncertainty. We demonstrate the trade-off between robustness to uncertainty, and an increase in the required probability of detection. An empirical example based on the detection of Pheidole megacephala on Barrow Island demonstrates the use of info-gap analysis to select a surveillance strategy.

Computer vision onboard UAVs for civilian tasks

Computer vision is much more than a technique to sense and recover environmental information from an UAV. It should play a main role regarding UAVs’ functionality because of the big amount of information that can be extracted, its possible uses and applications, and its natural connection to human driven tasks, taking into account that vision is our main interface to world understanding. Our current research’s focus lays on the development of techniques that allow UAVs to maneuver in spaces using visual information as their main input source. This task involves the creation of techniques that allow an UAV to maneuver towards features of interest whenever a GPS signal is not reliable or sufficient, e.g. when signal dropouts occur (which usually happens in urban areas, when flying through terrestrial urban canyons or when operating on remote planetary bodies), or when tracking or inspecting visual targets—including moving ones—without knowing their exact UMT coordinates. This paper also investigates visual serving control techniques that use velocity and position of suitable image features to compute the references for flight control. This paper aims to give a global view of the main aspects related to the research field of computer vision for UAVs, clustered in four main active research lines: visual serving and control, stereo-based visual navigation, image processing algorithms for detection and tracking, and visual SLAM. Finally, the results of applying these techniques in several applications are presented and discussed: this study will encompass power line inspection, mobile target tracking, stereo distance estimation, mapping and positioning.

High porosity chained aggregates from the topsoil of the Lunar regolith Dust

The unusual behaviour of fine lunar regolith like stickiness and low heat conductivity is dominated by the structural arrangement of its finest fraction in the outer-most topsoil layer. Here, we show the previously unknown phenomenon of building a globular 3-D superstructure within the dust fraction of the regolith. New technology, Transmission X-ray Microscopy (TXM) with tomographic reconstruction, reveals a highly porous network of cellular void system in the lunar finest dust fraction aggregates. Such porous chained aggregates are composed of sub-micron in size particles that build cellular void networks. Voids are a few micrometers in diameter. Discovery of such a superstructure within the finest fraction of the lunar topsoil allow building a model of heat transfer which is discussed.

Enhancing security and continuity management at international airports

Operators of busy contemporary airports have to balance tensions between the timely flow of passengers, flight operations, the conduct of commercial business activities and the effective application of security processes. In addition to specific onsite issues airport operators liaise with a range of organisations which set and enforce aviation-related policies and regulations as well as border security agencies responsible for customs, quarantine and immigration, in addition to first response security services. The challenging demands of coordinating and planning in such complex socio-technical contexts place considerable pressure on airport management to facilitate coordination of what are often conflicting goals and expectations among groups that have standing in respect to safe and secure air travel. What are, as yet, significantly unexplored issues in large airports are options for the optimal coordination of efforts from the range of public and private sector participants active in airport security and crisis management. A further aspect of this issue is how airport management systems operate when there is a transition from business-as-usual into an emergency/crisis situation and then, on recovery, back to ‘normal’ functioning. Business Continuity Planning (BCP), incorporating sub-plans for emergency response, continuation of output and recovery of degraded operating capacity, would fit such a context. The implementation of BCP practices in such a significant high security setting offers considerable potential benefit yet entails considerable challenges. This paper presents early results of a 4 year nationally funded industry-based research project examining the merger of Business Continuity Planning and Transport Security Planning as a means of generating capability for improved security and reliability and, ultimately, enhanced resilience in major airports. The project is part of a larger research program on the Design of Secure Airports that includes most of the gazetted ‘first response’ international airports in Australia, key Aviation industry groups and all aviation-related border and security regulators as collaborative partners. The paper examines a number of initial themes in the research, including: ? Approaches to integrating Business Continuity & Aviation Security Planning within airport operations; ? Assessment of gaps in management protocols and operational capacities for identifying and responding to crises within and across critical aviation infrastructure; ? Identification of convergent and divergent approaches to crisis management used across Austral-Asia and their alignment to planned and possible infrastructure evolution.

A generative nervous system for the planet

Generative systems are now being proposed for addressing major ecological problems. The Complex Urban Systems Project (CUSP) founded in 2008 at the Queensland University of Technology, emphasises the ecological significance of the generative global networking of urban environments. It argues that the natural planetary systems for balancing global ecology are no longer able to respond sufficiently rapidly to the ecological damage caused by humankind and by dense urban conurbations in particular as evidenced by impacts such as climate change. The proposal of this research project is to provide a high speed generative nervous system for the planet by connecting major cities globally to interact directly with natural ecosystems to engender rapid ecological response. This would be achieved by active interactions of the global urban network with the natural ecosystem in the ecological principle of entropy. The key goal is to achieve ecologically positive cities by activating self-organising cities capable of full integration into natural eco-systems and to netowork the cities globally to provide the planet with a nervous system.

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.