The Application of Next Generation Phenotyping Tools to a Wheat Breeding Programme

With the advent of high-throughput genotyping modern plant breeding has reached a new frontier of high-volume, high-density, yet low-cost, genomic data. Previously the acquisition of this data has been a logistical bottleneck within breeding programmes, yet with genomic data now abundantly available to breeding programmes, it has been speculated that the collection of phenotype data will become the next operational bottleneck. That being the inability to phenotype all material for all desired traits within a programme . The journey to improve the collection of phenotypic data is well underway, with focus being placed upon next generation phenotyping (NGP) technologies, such as high-throughput field phenotyping systems, to aid in the pairing of genotype to phenotype. Numerous sensors and methods of deployment have been investigated for application within small-plot field trials and suggested as tools for wheat and other field-crop breeding programmes, though few have explored how these can be deployed at scale or the suitability of collected data for use by breeders. This thesis investigates the deployment of commercially available digital cameras and LiDAR sensors within large-scale wheat breeding field trials, assessing the suitability of collected data for its application within the analytical pipelines of breeding programmes. Digital cameras were deployed opportunistically within large-scale wheat breeding trials, and through basic open-source image analysis methods, were capable of objectively assessing colour-based traits traditionally scored with visual assessment, producing levels of heritability similar to or greater than traditional methods. As part of this process a tractor-based high-throughput phenotyping platform was developed for the deployment of digital cameras, leveraging upon infrastructure present within the breeding programme and enabling images to be captured at a speed of 7,400 plots per hour. Given the success of digital cameras to measure colour-based traits, digital cameras were also deployed manually at a small scale to measure above ground biomass, plant height and harvest index, using photogrammetric techniques. Though data capture and processing methods were low-throughput, correlations between digital and manually collected measurements were strong (up to r = 0.94), highlighting the potential of the three-dimensional point cloud data type. To further this investigation LiDAR sensors were deployed on the high-throughput phenotyping platform to collect point cloud data of wheat plots from multiple field sites and collection dates. Processed point cloud data correlated strongly to traditional measurements of above ground biomass and canopy height and was shown to be highly repeatable and suitable for integration in routine breeding analyses. The findings of this work demonstrate that commercially available digital cameras and Li- DAR sensors can be deployed within large-scale wheat breeding trials, in a high-throughput, non-destructive and non-disruptive manner, for the accurate and repeatable measurement of traits which are traditionally subjective, laborious and/or destructive. Investigation of these measurements showed their suitability for inclusion within routine breeding analyses, giving breeders confidence in the data collected by next generation phenotyping technologies. The findings of this work are not only relevant to wheat breeders, but also to breeders of other field-crops and scientists conducting field research at a large scale.Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 202

GNSS Autonomous Integrity Monitoring with Barometric Pressure Measurements and Weather Data

Vertical navigation is essential for new aviation operations like precision approaches and automatic landing which are expected to be primarily based on Global Navigation Satellite Systems (GNSS). However, achieving tighter vertical requirements with GNSS is challenging due to the inherent geometrical limitations. Current Aircraft-Based Augmentation Systems (ABAS) developments focus on proving that Advanced Receiver Autonomous Integrity Monitoring (ARAIM) is able to provide a robust operation for horizontal services and vertical guidance via the use of Multi-frequency and Multi-constellation GNSS. Although ARAIM can achieve high levels of integrity, the availability and continuity of the system may be compromised by the loss of satellites or high presence of cycle slips. For this reason, the support of onboard sensors like barometers is essential to guarantee all the vertical navigation requirements and extend the achievable accuracy and integrity for future even more stringent operations. This paper aims at augmenting GNSS navigation with geodetic altitude obtained from aircraft barometric pressure measurements and external weather data within a robust navigation architecture based on ARAIM. The present work describes the derivations of the threat and error models that are required for the inclusion of this barometric geodetic altitude into ARAIM. The improvement in availability is simulated world-wide with respect to the expected uncertainty of the geodetic barometric altitude. Then, real flight data is used to show the benefit of the barometer augmentation on the integrity of the navigation solution under real operational scenarios. The error models are obtained from several hours of flight data collected during a flight tests campaign performed in 2018 with the German Aerospace Center’s (DLR) Dassault Falcon aircraft

Phenolic Compounds: Extraction, Optimization, Identification and Applications in Food Industry

Interest has grown regarding natural plant extracts in food and beverage applications, their vital role in the food industry, and their therapeutic use against diseases. The protective effects of healthy diets are partially due to the variety of plant metabolites, particularly phenolic compounds, which are considered the most important class of compounds that originates from plant-derived metabolites. Phenolics are well renowned for their possession of a wide array of remarkable biological properties. This Special Issue (SI) aims to gather the most recent contributions concerning their chemistry, extraction methods, and analytical techniques, applications, and biological activities. This Special Issue of Processes, entitled “Phenolic Compounds: Extraction, Optimization, Identification and Applications in Food Industry”, gathers the recent work of leading researchers in a single collection, covering a variety of theoretical studies and experimental applications and focusing on the extraction, identification, and industrial applications. The advances presented in the contributions in this SI have significantly helped to accomplish this target. In addition to research articles, the Special Issue features two reviews that cover a range of topics highlighting the versatility of the area. The topics covered in this SI include advanced methodologies for the isolation, purification, and analysis of phenolics from food, food waste, and medicinal plants; biological activities and mechanisms of action; health benefits from in vivo evaluation; and the development of novel phenolics-based nutraceuticals and functional ingredients

Feasible, Robust and Reliable Automation and Control for Autonomous Systems

The Special Issue book focuses on highlighting current research and developments in the automation and control field for autonomous systems as well as showcasing state-of-the-art control strategy approaches for autonomous platforms. The book is co-edited by distinguished international control system experts currently based in Sweden, the United States of America, and the United Kingdom, with contributions from reputable researchers from China, Austria, France, the United States of America, Poland, and Hungary, among many others. The editors believe the ten articles published within this Special Issue will be highly appealing to control-systems-related researchers in applications typified in the fields of ground, aerial, maritime vehicles, and robotics as well as industrial audiences

Advances in gain-scheduling and fault tolerant control techniques

This thesis presents some contributions to the state-of-the-art of the fields of gain-scheduling and fault tolerant control (FTC). In the area of gain-scheduling, the connections between the linear parameter varying (LPV) and Takagi-Sugeno (TS) paradigms are analyzed, showing that the methods for the automated generation of models by nonlinear embedding and by sector nonlinearity, developed for one class of systems, can be easily extended to deal with the other class. Then, two measures, based on the notions of overboundedness and region of attraction estimates, are proposed in order to compare different models and choose which one can be considered the best one. Later, the problem of designing state-feedback controllers for LPV systems has been considered, providing two main contributions. First, robust LPV controllers that can guarantee some desired performances when applied to uncertain LPV systems are designed, by using a double-layer polytopic description that takes into account both the variability due to the varying parameter vector and the uncertainty. Then, the idea of designing the controller in such a way that the required performances are scheduled by the varying parameters is explored, which provides an elegant way to vary online the behavior of the closed-loop system. In both cases, the problem reduces to finding a solution to a finite number of linear matrix inequalities (LMIs), which can be done efficiently using the available solvers. In the area of fault tolerant control, the thesis first shows that the aforementioned double-layer polytopic framework can be used for FTC, in such a way that different strategies (passive, active and hybrid) are obtained depending on the amount of available information. Later, an FTC strategy for LPV systems that involves a reconfigured reference model and virtual actuators is developed. It is shown that by including the saturations in the reference model equations, it is possible to design a model reference FTC system that automatically retunes the reference states whenever the system is affected by saturation nonlinearities. In this way, a graceful performance degradation in presence of actuator saturations is incorporated in an elegant way. Finally, the problem of FTC of unstable LPV systems subject to actuator saturations is considered. In this case, the design of the virtual actuator is performed in such a way that the convergence of the state trajectory to zero is assured despite the saturations and the appearance of faults. Also, it is shown that it is possible to obtain some guarantees about the tolerated delay between the fault occurrence and its isolation, and that the nominal controller can be designed so as to maximize the tolerated delay.Aquesta tesi presenta diverses contribucions a l'estat de l'art del control per planificació del guany i del control tolerant a fallades (FTC). Pel que fa al control per planificació del guany, s'analitzen les connexions entre els paradigmes dels sistemes lineals a paràmetres variants en el temps (LPV) i de Takagi-Sugeno (TS). Es demostra que els mètodes per a la generació automàtica de models mitjançant encastament no lineal i mitjançant no linealitat sectorial, desenvolupats per una classe de sistemes, es poden estendre fàcilment per fer-los servir amb l'altra classe. Es proposen dues mesures basades en les nocions de sobrefitació i d'estimació de la regió d'atracció, per tal de comparar diferents models i triar quin d'ells pot ser considerat el millor. Després, es considera el problema de dissenyar controladors per realimentació d'estat per a sistemes LPV, proporcionant dues contribucions principals. En primer lloc, fent servir una descripció amb doble capa politòpica que té en compte tant la variabilitat deguda al vector de paràmetres variants i la deguda a la incertesa, es dissenyen controladors LPV robustos que puguin garantir unes especificacions desitjades quan s'apliquen a sistemes LPV incerts. En segon lloc, s'explora la idea de dissenyar el controlador de tal manera que les especificacions requerides siguin programades pels paràmetres variants. Això proporciona una manera elegant de variar en línia el comportament del sistema en llaç tancat. En tots dos casos, el problema es redueix a trobar una solució d'un nombre finit de desigualtats matricials lineals (LMIs), que es poden resoldre fent servir algorismes numèrics disponibles i molt eficients. En l'àrea del control tolerant a fallades, primerament la tesi mostra que la descripció amb doble capa politòpica abans esmentada es pot utilitzar per fer FTC, de tal manera que, en funció de la quantitat d'informació disponible, s'obtenen diferents estratègies (passiva, activa i híbrida). Després, es desenvolupa una estratègia de FTC per a sistemes LPV que fa servir un model de referència reconfigurat combinat amb la tècnica d'actuadors virtuals. Es mostra que mitjançant la inclusió de les saturacions en les equacions del model de referència, és possible dissenyar un sistema de control tolerant a fallades que resintonitza automàticament els estats de referència cada vegada que el sistema es veu afectat per les no linealitats de la saturació en els actuadors. D'aquesta manera s'incorpora una degradació elegant de les especificacions en presència de saturacions d'actuadors. Finalment, es considera el problema de FTC per sistemes LPV inestables afectats per saturacions d'actuadors. En aquest cas, es porta a terme el disseny de l'actuador virtual de tal manera que la convergència a zero de la trajectòria d'estat està assegurada tot i les saturacions i l'aparició de fallades. A més, es mostra que és possible obtenir garanties sobre el retard tolerat entre l'aparició d'una fallada i el seu aïllament, i que el controlador nominal es pot dissenyar maximitzant el retard tolerat

Epidemic and pandemic viral infections: impact on tuberculosis and the lung. A consensus by the World Association for Infectious Diseases and Immunological Disorders (WAidid), Global Tuberculosis Network (GTN) and members# of ESCMID Study Group for Mycobacterial Infections (ESGMYC).

Major epidemics including some that qualify as pandemics, such as Severe Acute Respiratory Syndrome (SARS), Middle-Eastern Respiratory Syndrome (MERS), Human Immunodeficiency Virus, pandemic H1N1/09 and most recently COVID-19 affect the lung. Tuberculosis (TB) remains the top infectious disease killer but apart from the TB-HIV syndemic, little is known regarding the interaction of viral epidemics and pandemics with TB. The aim of this consensus-based document is to describe the effects of the viral infections resulting in epidemics and pandemics that affect the lung (MERS, SARS, HIV, influenza A (H1N1)pdm/09 and COVID-19) and their interactions with TB. A search of the scientific literature was performed. A writing committee of international experts including the European Centre for Disease Prevention and Control Public Health Emergency (ECDC PHE) team, the World Association for Infectious Diseases and Immunological Disorders (WAidid), the Global Tuberculosis Network (GTN) and members of ESCMID Study Group for Mycobacterial Infections (ESGMYC) was established. Consensus was achieved after multiple rounds of revisions between the writing committee and a larger expert group. A Delphi process involving the core group of authors, excluding the ECDC PHE team identified the areas requiring review/consensus, followed by a second round to refine the definitive consensus elements. The epidemiology, immunology of these viral infections and their interactions with TB are discussed with implications on diagnosis, treatment and prevention of airborne infections (infection control, viral containment and workplace safety). This consensus document represents a rapid and comprehensive summary on what is known on the topic

Benelux meeting on systems and control, 23rd, March 17-19, 2004, Helvoirt, The Netherlands

Book of abstract

Active Suppression ofAerofoil Flutter via Neural-Network-Based Adaptive Nonlinear Optimal Control

This thesis deals with active flutter suppression (AFS) on aerofoils via adaptive nonlinear optimal control using neural networks (NNs). Aeroelastic flutter can damage aerofoils if not properly controlled. AFS not only ensures flutter-free flight but also enables the use of aerodynamically more efficient lightweight aerofoils. However, existing optimal controllers for AFS are generally susceptible to modelling errors while other controllers less prone to uncertainties do not provide optimal control. This thesis, thus, aims to reduce the impact of the dilemma by proposing new solutions based on nonlinear optimal control online synthesis (NOCOS) according to online updated dynamics. Existing NOCOS methods, with NNs as essential elements, require a separate initial stabilising control law for the overall system, an additional stabilising tuning loop for the actor NN, or an additional stabilising term in the critic NN tuning law, to guarantee the closed-loop stability for unstable and marginally stable systems. The resulting complexity is undesired in AFS applications due to computational concerns in real-time implementation. Moreover, the existing NOCOS methods are confined to locally nonlinear systems, while aeroelastic systems under consideration are globally nonlinear. These make all the existing NOCOS algorithms inapplicable to AFS without modification and improvement. Therefore, this thesis solves the aforementioned problems through the following step-by-step approaches. Firstly, a four degrees-of-freedom (4-DOF) aeroelastic model is considered, where leading- and trailing-edge control surfaces of the aerofoil are used to actively suppress flutter. Accordingly, a virtual stiffness-damping system (VSDS) is developed to simulate physical stiffness in the aeroelastic system. The VSDS, together with a scaled-down typical aerofoil section placed in a wind tunnel, serve as an experimental 4-DOF aeroelastic test-bed for synthesis and validation of proposed AFS controllers that follow. Secondly, a Modified form of NN-based Value Function Approximation (MVFA), tuned by gradient-descent learning, is proposed for NOCOS to address the closedloop stability in a compact controller configuration suitable for real-time implementation. Its validity and efficacy are examined by the Lyapunov stability analysis and numerical studies. Thirdly, a systematic procedure based on linear matrix inequalities is further proposed for synthesising a scheduled parameter matrix to generalise the MVFA to to globally nonlinear cases, so that the new NN controller suits AFS applications. In addition, the extended Kalman filter (EKF) is proposed for the new NN controller for fast parameter convergence. An identifier NN is also derived to capture and update aeroelastic dynamics in real time to mitigate the impact of modelling errors. Wind-tunnel experiments were conducted for validation. Finally, a non-quadratic functional is introduced to generalise the performance index to tackle the problem where control inputs are constrained. The feasibility of including the non-quadratic cost function under the proposed control scheme based on the MVFA is examined via the Lyapunov stability analysis and was also experimentally evaluated through the wind-tunnel testings. The proposed NN controllers are compact in structure and shown capable of maintaining the closed-loop stability while eliminating the need for a separate initial stabilising control law for the overall system, an additional tuning loop for the actor NN, and an additional stabilising term in the critic NN tuning law. Under the new control schemes, online synthesised nonlinear control laws are optimal in the cases with and without constraints in control. Comparisons drawn with a popular linear-parameter-varying (LPV) controller in the form of the widely used linear quadratic regulator (LQR) in experiments show that the proposed NN controllers outperform the LPV-LQR algorithm and improve AFS from the optimal control perspective. Specifically, the proposed NN controllers can effectively mitigate the impact of modelling errors, successfully solving the mentioned dilemma involved in AFS. The results also confirm that the proposed NN controllers are suitable for real-time implementation.Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 201

Systems and control : 21th Benelux meeting, 2002, March 19-21, Veldhoven, The Netherlands

Book of abstract

Forest Pathology and Entomology

The 22 papers that make up this Special Issue deal with pathogen and pest impact on forest health, from the diagnosis to the surveillance of causative agents, from the study of parasites’ biological, epidemiological, and ecological traits to their correct taxonomy and classification, and from disease and pest monitoring to sustainable control strategies