Occurrence and abundance models of threatened plant species: Applications to mitigate the impact of hydroelectric power dams

Species occurrence and abundance models are important tools that can be used in biodiversity conservation, and can be applied to predict or plan actions needed to mitigate the environmental impacts of hydropower dams. In this study our objectives were: (i) to model the occurrence and abundance of threatened plant species, (ii) to verify the relationship between predicted occurrence and true abundance, and (iii) to assess whether models based on abundance are more effective in predicting species occurrence than those based on presence–absence data. Individual representatives of nine species were counted within 388 randomly georeferenced plots (10 m × 50 m) around the Barra Grande hydropower dam reservoir in southern Brazil. We modelled their relationship with 15 environmental variables using both occurrence (Generalised Linear Models) and abundance data (Hurdle and Zero-Inflated models). Overall, occurrence models were more accurate than abundance models. For all species, observed abundance was significantly, although not strongly, correlated with the probability of occurrence. This correlation lost significance when zero-abundance (absence) sites were excluded from analysis, but only when this entailed a substantial drop in sample size. The same occurred when analysing relationships between abundance and probability of occurrence from previously published studies on a range of different species, suggesting that future studies could potentially use probability of occurrence as an approximate indicator of abundance when the latter is not possible to obtain. This possibility might, however, depend on life history traits of the species in question, with some traits favouring a relationship between occurrence and abundance. Reconstructing species abundance patterns from occurrence could be an important tool for conservation planning and the management of threatened species, allowing scientists to indicate the best areas for collection and reintroduction of plant germplasm or choose conservation areas most likely to maintain viable populations.

Use of Coarse-resolution models of species' distributions to guide local conservation inferences

Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter ( Lutra lutra), in the Iberian Peninsula. The models, built from presence–absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measures

Inversion of ambient seismic noise HVSR to evaluate velocity and structural models of the Lower Tagus Basin, Portugal

During its history, several significant earthquakes have shaken the Lower Tagus Valley (Portugal). These earthquakes were destructive; some strong earthquakes were produced by large ruptures in offshore structures located southwest of the Portuguese coastline, and other moderate earthquakes were produced by local faults. In recent years, several studies have successfully obtained strong-ground motion syntheses for the Lower Tagus Valley using the finite difference method. To confirm the velocity model of this sedimentary basin obtained from geophysical and geological data, we analysed the ambient seismic noise measurements by applying the horizontal to vertical spectral ratio (HVSR) method. This study reveals the dependence of the frequency and amplitude of the low-frequency (HVSR) peaks (0.2–2 Hz) on the sediment thickness. We have obtained the depth of the Cenozoic basement along a profile transversal to the basin by the inversion of these ratios, imposing constraints from seismic reflection, boreholes, seismic sounding and gravimetric and magnetic potentials. This technique enables us to improve the existing three-dimensional model of the Lower Tagus Valley structure. The improved model will be decisive for the improvement of strong motion predictions in the earthquake hazard analysis of this highly populated basin. The methodology discussed can be applied to any other sedimentary basin.

Strategies of resource-use of Panicum maximum cultivars.

2016

Numerical simulations of the spine for patient-specific models of severe scoliosis

In silico methods, such as musculoskeletal modelling, may aid the selection of the optimal surgical treatment for highly complex pathologies such as scoliosis. Many musculoskeletal models use a generic, simplified representation of the intervertebral joints, which are fundamental to the flexibility of the spine. Therefore, to model and simulate the spine, a suitable representation of the intervertebral joint is crucial. The aim of this PhD was to characterise specimen-specific models of the intervertebral joint for multi-body models from experimental datasets. First, the project investigated the characterisation of a specimen-specific lumped parameter model of the intervertebral joint from an experimental dataset of a four-vertebra lumbar spine segment. Specimen-specific stiffnesses were determined with an optimisation method. The sensitivity of the parameters to the joint pose was investigate. Results showed the stiffnesses and predicted motions were highly depended on both the joint pose. Following the first study, the method was reapplied to another dataset that included six complete lumbar spine segments under three different loading conditions. Specimen-specific uniform stiffnesses across joint levels and level-dependent stiffnesses were calculated by optimisation. Specimen-specific stiffness show high inter-specimen variability and were also specific to the loading condition. Level-dependent stiffnesses are necessary for accurate kinematic predictions and should be determined independently of one another. Secondly, a framework to create subject-specific musculoskeletal models of individuals with severe scoliosis was developed. This resulted in a robust codified pipeline for creating subject-specific, severely scoliotic spine models from CT data. In conclusion, this thesis showed that specimen-specific intervertebral joint stiffnesses were highly sensitive to joint pose definition and the importance of level-dependent optimisation. Further, an open-source codified pipeline to create patient-specific scoliotic spine models from CT data was released. These studies and this pipeline can facilitate the specimen-specific characterisation of the scoliotic intervertebral joint and its incorporation into scoliotic musculoskeletal spine models.

Data driven regularization models of non-linear ill-posed inverse problems in imaging

Imaging technologies are widely used in application fields such as natural sciences, engineering, medicine, and life sciences. A broad class of imaging problems reduces to solve ill-posed inverse problems (IPs). Traditional strategies to solve these ill-posed IPs rely on variational regularization methods, which are based on minimization of suitable energies, and make use of knowledge about the image formation model (forward operator) and prior knowledge on the solution, but lack in incorporating knowledge directly from data. On the other hand, the more recent learned approaches can easily learn the intricate statistics of images depending on a large set of data, but do not have a systematic method for incorporating prior knowledge about the image formation model. The main purpose of this thesis is to discuss data-driven image reconstruction methods which combine the benefits of these two different reconstruction strategies for the solution of highly nonlinear ill-posed inverse problems. Mathematical formulation and numerical approaches for image IPs, including linear as well as strongly nonlinear problems are described. More specifically we address the Electrical impedance Tomography (EIT) reconstruction problem by unrolling the regularized Gauss-Newton method and integrating the regularization learned by a data-adaptive neural network. Furthermore we investigate the solution of non-linear ill-posed IPs introducing a deep-PnP framework that integrates the graph convolutional denoiser into the proximal Gauss-Newton method with a practical application to the EIT, a recently introduced promising imaging technique. Efficient algorithms are then applied to the solution of the limited electrods problem in EIT, combining compressive sensing techniques and deep learning strategies. Finally, a transformer-based neural network architecture is adapted to restore the noisy solution of the Computed Tomography problem recovered using the filtered back-projection method.

Incompressible limit and well-posedness of PDE models of tissue growth

Both compressible and incompressible porous medium models are used in the literature to describe the mechanical aspects of living tissues. Using a stiff pressure law, it is possible to build a link between these two different representations. In the incompressible limit, compressible models generate free boundary problems where saturation holds in the moving domain. Our work aims at investigating the stiff pressure limit of reaction-advection-porous medium equations motivated by tumor development. Our first study concerns the analysis and numerical simulation of a model including the effect of nutrients. A coupled system of equations describes the cell density and the nutrient concentration and the derivation of the pressure equation in the stiff limit was an open problem for which the strong compactness of the pressure gradient is needed. To establish it, we use two new ideas: an L3-version of the celebrated Aronson-Bénilan estimate, and a sharp uniform L4-bound on the pressure gradient. We further investigate the sharpness of this bound through a finite difference upwind scheme, which we prove to be stable and asymptotic preserving. Our second study is centered around porous medium equations including convective effects. We are able to extend the techniques developed for the nutrient case, hence finding the complementarity relation on the limit pressure. Moreover, we provide an estimate of the convergence rate at the incompressible limit. Finally, we study a multi-species system. In particular, we account for phenotypic heterogeneity, including a structured variable into the problem. In this case, a cross-(degenerate)-diffusion system describes the evolution of the phenotypic distributions. Adapting methods recently developed in the context of two-species systems, we prove existence of weak solutions and we pass to the incompressible limit. Furthermore, we prove new regularity results on the total pressure, which is related to the total density by a power law of state.

Security and privacy of resource constrained devices

The thesis aims to present a comprehensive and holistic overview on cybersecurity and privacy & data protection aspects related to IoT resource-constrained devices. Chapter 1 introduces the current technical landscape by providing a working definition and architecture taxonomy of ‘Internet of Things’ and ‘resource-constrained devices’, coupled with a threat landscape where each specific attack is linked to a layer of the taxonomy. Chapter 2 lays down the theoretical foundations for an interdisciplinary approach and a unified, holistic vision of cybersecurity, safety and privacy justified by the ‘IoT revolution’ through the so-called infraethical perspective. Chapter 3 investigates whether and to what extent the fast-evolving European cybersecurity regulatory framework addresses the security challenges brought about by the IoT by allocating legal responsibilities to the right parties. Chapters 4 and 5 focus, on the other hand, on ‘privacy’ understood by proxy as to include EU data protection. In particular, Chapter 4 addresses three legal challenges brought about by the ubiquitous IoT data and metadata processing to EU privacy and data protection legal frameworks i.e., the ePrivacy Directive and the GDPR. Chapter 5 casts light on the risk management tool enshrined in EU data protection law, that is, Data Protection Impact Assessment (DPIA) and proposes an original DPIA methodology for connected devices, building on the CNIL (French data protection authority) model.

Analytic models of self-gravitating rotating gaseous tori with central black hole

In this thesis project, I present stationary models of rotating fluids with toroidal distributions that can be used to represent the active galactic nuclei (AGN) central obscurers, i.e. molecular tori (Combes et al., 2019), as well as geometrically thick accretion discs, like ADAF discs (Narayan and Yi, 1995) or Polish doughnuts (Abramowicz, 2005). In particular, I study stationary rotating systems with a more general baroclinic distribution (with a vertical gradient of the angular velocity), which are often more realistic and less studied, due to their complexity, than the barotropic ones (with cylindrical rotation), which are easier to construct. In the thesis, I compute analytically the main intrinsic and projected properties of the power-law tori based on the potential-density pairs of Ciotti and Bertin (2005). I study the density distribution and the resulting gravitational potential for different values of α, in the range 2 < α < 5. For the same models, I compute the surface density of the systems when seen face-on and edge-on. I then apply the stationary Euler equations to obtain rotational velocity and temperature distributions of the self-gravitating models in the absence of an external gravitational potential. In the thesis I also consider the power-law tori with the presence of a central black hole in addition to the gas self-gravity, and solving analytically the stationary Euler equations, I compute how the properties of the system are modified by the black hole and how they vary as a function of the black hole mass. Finally, applying the Solberg-Høiland criterion, I show that these baroclinic stationary models are linearly stable in the absence of the black hole. In the presence of the black hole I derive the analytical condition for stability, which depends on α and on the black hole mass. I also study the stability of the tori in the hypothesis that they are weakly magnetized, finding that they are always unstable to this instability.

Hidden Schrödinger symmetry in FLRW and Bianchi I minisuperspace models of cosmology and black holes Schwarzschild dynamics

A broad sector of literature focuses on the relationship between fluid dynamics and gravitational systems. This thesis presents results that suggest the existence of a new kind of fluid/gravity duality not based on the holographic principle. The goal is to provide tools that allow us to systematically unearth hidden symmetries for reduced models of cosmology. The focus is on the field space of these models, i.e. the superspace. In fact, conformal isometries of the supermetric leave geodesics in the field space unaltered; this leads to symmetries of the models. An innovative aspect is the use of the Eisenhart-Duval’s lift. Using this method, systems constrained by a potential can be treated as free ones. Moreover, charges explicitly dependent on time, i.e. dynamical, can be found. A detailed analysis is carried out on three basic models of homogenous cosmology: i) flat Friedmann-Lemaître-Robertson-Walker’s isotropic universe filled with a massless scalar field; ii) Schwarzschild’s black hole mechanics and its extension to vacuum (A)dS gravity; iii) Bianchi’s anisotropic type I universe with a massless scalar field. The results show the presence of a hidden Schrödinger’s symmetry which, being intrinsic to both Navier-Stokes’ and Schrödinger’s equations, indicates a correspondence between cosmology and hydrodynamics. Furthermore, the central extension of this algebra explicitly relates two concepts. The first is the number of particles coming from the fluid picture; while the second is the ratio between the IR and UV cutoffs that weighs how much a theory has of “classical” over “quantum”. This suggests a spacetime that emerges from an underlying world which is described by quantum building blocks. These quanta statistically conspire to appear as gravitational phenomena from a macroscopic point of view.

Validation of microFE models of human metastatic vertebrae

La colonna vertebrale è uno dei principali siti per lo sviluppo delle metastasi ossee. Esse modificano le proprietà meccaniche della vertebra indebolendo la struttura e inducendo l’instabilità spinale. La medicina in silico e i modelli agli elementi finiti (FE) hanno trovato spazio nello studio del comportamento meccanico delle vertebre, permettendo una valutazione delle loro proprietà meccaniche anche in presenza di metastasi. In questo studio ho validato i campi di spostamento predetti da modelli microFE di vertebre umane, con e senza metastasi, rispetto agli spostamenti misurati mediante Digital Volume Correlation (DVC). Sono stati utilizzati 4 provini da donatore umano, ognuno composto da una vertebra sana e da una vertebra con metastasi litica. Per ogni vertebra è stato sviluppato un modello microFE omogeneo, lineare e isotropo basato su sequenze di immagini ad alta risoluzione ottenute con microCT (voxel size = 39 μm). Sono state imposte come condizioni al contorno gli spostamenti ottenuti con la DVC nelle fette prossimali e distali di ogni vertebra. I modelli microFE hanno mostrato buone capacità predittive degli spostamenti interni sia per le vertebre di controllo che per quelle metastatiche. Per range di spostamento superiori a 100 μm, il valore di R2 è risultato compreso tra 0.70 e 0.99 e il valore di RMSE% tra 1.01% e 21.88%. Dalle analisi dei campi di deformazione predetti dai modelli microFE sono state evidenziate regioni a maggior deformazione nelle vertebre metastatiche, in particolare in prossimità delle lesioni. Questi risultati sono in accordo con le misure sperimentali effettuate con la DVC. Si può assumere quindi che il modello microFE lineare omogeneo isotropo in campo elastico produca risultati attendibili sia per le vertebre sane sia per le vertebre metastatiche. La procedura di validazione implementata potrebbe essere utilizzata per approfondire lo studio delle proprietà meccaniche delle lesioni blastiche.

Computational Analysis Based on Parametric Models of Historic Masonry Vaulted Structures Strengthened by Fiber-Reinforced Composite Materials

Historic vaulted masonry structures often need strengthening interventions that can effectively improve their structural performance, especially during seismic events, and at the same time respect the existing setting and the modern conservation requirements. In this context, the use of innovative materials such as fiber-reinforced composite materials has been shown as an effective solution that can satisfy both aspects. This work aims to provide insight into the computational modeling of a full-scale masonry vault strengthened by fiber-reinforced composite materials and analyze the influence of the arrangement of the reinforcement on the efficiency of the intervention. At first, a parametric model of a cross vault focusing on a realistic representation of its micro-geometry is proposed. Then numerical modeling, simulating the pushover analyses, of several barrel vaults reinforced with different reinforcement configurations is performed. Finally, the results are collected and discussed in terms of force-displacement curves obtained for each proposed configuration.

Dissociation between skin conductance orienting and secondary task reaction time: Time course with a visual discrimination task

A dissociation between two putative measures of resource allocation skin conductance responding, and secondary task reaction time (RT), has been observed during auditory discrimination tasks. Four experiments investigated the time course of the dissociation effect with a visual discrimination task. participants were presented with circles and ellipses and instructed to count the number of longer-than-usual presentations of one shape (task-relevant) and to ignore presentations of the other shape (task-irrelevant). Concurrent with this task, participants made a speeded motor response to an auditory probe. Experiment 1 showed that skin conductance responses were larger during task-relevant stimuli than during task-irrelevant stimuli, whereas RT to probes presented at 150 ms following shape onset was slower during task-irrelevant stimuli. Experiments 2 to 4 found slower RT during task-irrelevant stimuli at probes presented at 300 ms before shape onset until 150 ms following shape onset. At probes presented 3,000 and 4,000 ms following shape onset probe RT was slower during task-relevant stimuli. The similarities between the observed time course and the so-called psychological refractory period (PRF) effect are discussed.

Equity in access to MRI equipment: the Portuguese case

Magnetic resonance imaging (MRI) is a method of image diagnose proven to be of undeniable importance when it comes to neuro and cardio related diseases. In fact, these diseases (such as: ischemic heart disease, stroke and acute myocardial infection) have high incidence in Portugal. For these reasons, the allocation of this medical technology should not be considered with light thoughts. In fact, making decision of resource allocation in health care can be a very complex and contested matter. The impacts of new technology allocation, such MRI, can be assessed in a variety of ways. However, a fundamental component should always be present: the use of evidence-based decision-making methods. One of these methods is Technology Assessment (TA). This paper aims to characterize the equity on access of the Portuguese population in general, to a specific medical device such as MRI, under the TA point of view. It is hoped to promote a bridge of scientific knowledge between the gap on research and policy-making through TA that can emerge as a tool to aid decision-makers in the organization of health systems. There are gaps in providing healthcare, due to geographical imbalances, with some areas unable to provide certain specialized services, as hospitals in the countryside do not provide all medical specialties. Portugal has also a large independent private sector that provides diagnostic and therapeutic services to NHS users under contracts called conventions. These medical contracts cover ambulatory health facilities for laboratory tests and examinations such as diagnostic tests and Radiology. However, there is no convention from the NHS when concerning the MRI exam. Therefore, this reality can be considered a limitation in the access of the general population to this kind of clinical exam. TA can play an useful and important role in helping the decision-makers to explore potential gains that might be achieved by introducing a more rational decision making into health care management, namely into the Radiology area, regarding the allocation of MRI equipment.

IPH response to DSD Urban Regeneration and Community Development Policy Framework Consultation

The Urban Regeneration and Community Development Policy Framework for Northern Ireland sets out for DSD and its partners, clear priorities for urban regeneration and community development programmes, both before and after the operational responsibility for these is transferred to councils under the reform of local government. Four policy objectives have been developed, which will focus on the underlying structural problems in urban areas and also help strengthen community development throughout Northern Ireland. The policy objectives are as follows: Policy Objective 1 – To tackle area-based deprivation: Policy Objective 2 – To strengthen the competitiveness of our towns and cities: Policy Objective 3 – To improve linkages between areas of need and areas of opportunity: and Policy Objective 4 –To develop more cohesive and engaged communities. Key points from IPH response Urban regeneration and community development provide a basis for addressing the social determinants of health and reducing inequalities in health. This policy framework presents an opportunity for coherence and complementarity with ‘Fit and Well - Changing Lives’ as part of government’s overall approach to tackling health inequalities. It is now well established that a focus on early years’ interventions and family support services yields significant returns, so prioritising action in these areas is essential. Defined action plans on child poverty are essential if this policy framework is to make a real and lasting difference in deprived urban areas. Development of the environmental infrastructure to improve health in deprived areas should be supported by well-planned monitoring and evaluation. Linking the policy framework to economic development and local community plans will enhance effectiveness in the areas of education, job creation, commercial investment and access to services, which in turn are critical for the economic growth and stability of urban communities. Community profile data and health intelligence (as available through IPH Health Well) could usefully inform central and local government in terms of resource allocation and targeted service delivery.