Nonlinear evolution of harmonically forced perturbations on a wingtip vortex

Wingtip vortices are created by flying airplanes due to lift generation. The vortex interaction with the trailing aircraft has sparked researchers’ interest to develop an efficient technique to destroy these vortices. Different models have been used to describe the vortex dynamics and they all show that, under real flight conditions, the most unstable modes produce a very weak amplification. Another linear instability mechanism that can produce high energy gains in short times is due to the non-normality of the system. Recently, it has been shown that these non-normal perturbations also produce this energy growth when they are excited with harmonic forcing functions. In this study, we analyze numerically the nonlinear evolution of a spatially, pointwise and temporally forced perturbation, generated by a synthetic jet at a given radial distance from the vortex core. This type of perturbation is able to produce high energy gains in the perturbed base flow (10^3), and is also a suitable candidate for use in engineering applications. The flow field is solved for using fully nonlinear three-dimensional direct numerical simulation with a spectral multidomain penalty method model. Our novel results show that the nonlinear effects are able to produce locally small bursts of instability that reduce the intensity of the primary vortex.

Vortex evolution in the wake of accelerating low-aspect-ratio plates and three-dimensional bodies of revolution

To find examples of effecient locomotion and manoeuvrability, one need only turn to the elegant solutions natural flyers and swimmers have converged upon. This dissertation is specifically motivated by processes of evolutionary convergence, which have led to the propulsors and body shapes in nature that exhibit strong geometric collapse over diverse scales. These body features are abstracted in the studies presented herein using low-aspect-ratio at plates and a three-dimensional body of revolution (a sphere). The highly-separated vortical wakes that develop during accelerations are systematically characterized as a function of planform shape, aspect ratio, Reynolds number, and initial boundary conditions. To this end, force measurements and time-resolved (planar) particle image velocimetry have been used throughout to quantify the instantaneous forces and vortex evolution in the wake of the bluff bodies. During rectilinear motions, the wake development for the flat plates is primarily dependent on plate aspect ratio, with edge discontinuities and curvature playing only a secondary role. Furthermore, the axisymmetric case, i.e. the circular plate, shows strong sensitivity to Reynolds number, while this sensitivity quickly diminishes with increasing aspect ratio. For rotational motions, global insensitivity to plate aspect ratio has been observed. For the sphere, it has been shown that accelerations play an important role in the mitigation of flow separation. These results - expounded upon in this dissertation - have begun to shed light on the specific vortex dynamics that may be coopted by flying and swimming species of all shapes and sizes towards efficient locomotion.

A practical MEMS gravimeter

The ability to measure tiny variations in the local gravitational acceleration allows – amongst other applications – the detection of hidden hydrocarbon reserves, magma build-up before volcanic eruptions, and subterranean tunnels. Several technologies are available that achieve the sensitivities required (tens of μGal/√Hz), and stabilities required (periods of days to weeks) for such applications: free-fall gravimeters, spring-based gravimeters, superconducting gravimeters, and atom interferometers. All of these devices can observe the Earth tides; the elastic deformation of the Earth’s crust as a result of tidal forces. This is a universally predictable gravitational signal that requires both high sensitivity and high stability over timescales of several days to measure. All present gravimeters, however, have limitations of excessive cost (£70 k) and high mass (<8 kg). In this thesis, the building of a microelectromechanical system (MEMS) gravimeter with a sensitivity of 40 μGal/√Hz in a package size of only a few cubic centimetres is discussed. MEMS accelerometers – found in most smart phones – can be mass-produced remarkably cheaply, but most are not sensitive enough, and none have been stable enough to be called a ‘gravimeter’. The remarkable stability and sensitivity of the device is demonstrated with a measurement of the Earth tides. Such a measurement has never been undertaken with a MEMS device, and proves the long term stability of the instrument compared to any other MEMS device, making it the first MEMS accelerometer that can be classed as a gravimeter. This heralds a transformative step in MEMS accelerometer technology. Due to their small size and low cost, MEMS gravimeters could create a new paradigm in gravity mapping: exploration surveys could be carried out with drones instead of low-flying aircraft; they could be used for distributed land surveys in exploration settings, for the monitoring of volcanoes; or built into multi-pixel density contrast imaging arrays.

Índice acumulativo de riesgo (nice) como prueba diagnóstica con base en tomografía corneal por elevación en la prevención de ectasia corneal post-lasik

Antecedentes La ectasia corneal post-lasik (ECPL) es una complicación infrecuente, pero devastadora en la cirugía lasik (queratomileusis asistida con éxcimer láser) para el tratamiento de la miopía con o sin astigmatismo. Con base en la tomografía corneal por elevación por imágenes de Scheimpflug (Sistema Pentacam HR, Oculus Wetzlar, Alemania), se propone un novedoso índice acumulativo de riesgo para ser utilizado como prueba diagnóstica de tamizaje y así prevenir esta complicación. Metodología Se realizó un estudio observacional analítico, de corte transversal tipo pruebas diagnósticas, con el fin de evaluar las características operativas del índice NICE teniendo como estándar de referencia el módulo de Belin-Ambrosio (Pentacam HR) utilizando un modelo de regresión logística binaria, tablas de contingencia y estimando el área bajo la curva ROC. Resultados Se evaluaron 361 ojos de los cuales el 59,3% provenían de pacientes de sexo femenino, la edad media global fue de 30 años (RIC 11,0). El modelo logístico binario aplicado se construyó con base en cuatro variables independientes cuantitativas (K2, PAQUI, EP e I-S) y una cualitativa (SEXO), y se determinó su relación con la variable dependiente, NICE (puntaje final). Las variables predictoras fueron estadísticamente significativas clasificando adecuadamente el 92,9% de los ojos evaluados según presencia o ausencia de riesgo. El coeficiente de Nagelkerke fue de 74,4%. Conclusiones El índice acumulativo de riesgo NICE es una herramienta diagnóstica novedosa en la evaluación de candidatos a cirugía refractiva lasik para prevenir la ectasia secundaria.

Predictors of red fox (Vulpes vulpes) helminth parasite diversity in the provinces of Spain

We analysed the viscera of 321 red foxes collected over the last 30 years in 34 of the 47 provinces of peninsular Spain, and identified their helminth parasites. We measured parasite diversity in each sampled province using four diversity indices: Species richness, Marg a l e f’s species richness index, Shannon’s species diversity index, and inverse Simpson’s index. In order to find geographical, environmental, and/or human-related predictors of fox parasite diversity, we recorded 45 variables related to topography, climate, lithology, habitat heterogeneity, land use, spatial situation, human activity, sampling effort, and fox presence probability (obtained after environmental modelling of fox distribution). We then performed a stepwise linear regression of each diversity index on these variables, to find a minimal subset of statistically significant variables that account for the variation in each diversity index. We found that most parasite diversity indices increase with the mean distance to urban centres, or in other words, foxes in more rural provinces have a more diverse helminth fauna. Sampling effort and fox presence probability (probably related to fox density) also appeared as conditioning variables for some indices, as well as soil permeability (related with water availability). We then extrapolated the models to predict these fox parasite diversity indices in non-sampled provinces and have a view of their geographical trends.

Produção de mudas de citros com diferentes combinações copa e porta-enxerto em viveiro protegido.

O objetivo deste trabalho foi avaliar a produção de mudas de laranjeiras doces 'Pera' e 'Westin', tangerineira-tangor 'Piemonte' e limeira-ácida 'Tahiti' enxertadas em 14 porta-enxertos de citros em viveiro protegido. As mudas de laranjeiras-doces 'Pera D-6' e 'Westin', tangerineira-tangor 'Piemonte' e limeira-ácida 'Tahiti CNPMF-02' foram avaliadas em viveiro protegido após a enxertia, em 11 porta-enxertos híbridos: citrandarins 'Indio', 'Riverside' e 'San Diego', citrumelo 'Swingle 4475', HTR-051, TSKC x (LCR x TR)-040 e 059, LVK x LCR-010 e 038, TSKC x CTTR-002 e TSKC x CTSW-041, além de trifoliata 'Flying Dragon', limoeiro ?Cravo Santa Cruz' e tangerineira ?Sunki Tropical?. Coletaram-se variáveis biométricas e fisiológicas, sendo o delineamento experimental em blocos ao acaso, em parcelas subdivididas, com 56 tratamentos, três repetições e dez plantas na parcela. Independentemente do porta-enxerto, a limeira-ácida 'Tahiti CNPMF-02' foi a copa mais vigorosa em viveiro, seguida da tangerineira-tangor 'Piemonte' e, por fim, pelas laranjeiras 'Pera-D6' e 'Westin'. A tangerineira 'Sunki Tropical' induziu maior crescimento vegetativo e de sistema radicular em combinação com todas as copas estudadas. O trifoliata 'Flying Dragon'e o híbrido HTR-051 necessitam de maior período para a formação das mudas em função do menor vigor desses genótipos, em combinação com todas as variedades copas avaliadas.

Modelling, simulation and control of rotary-wing aircraft in multi-agent scenario

The topic of this thesis is the design and the implementation of mathematical models and control system algorithms for rotary-wing unmanned aerial vehicles to be used in cooperative scenarios. The use of rotorcrafts has many attractive advantages, since these vehicles have the capability to take-off and land vertically, to hover and to move backward and laterally. Rotary-wing aircraft missions require precise control characteristics due to their unstable and heavy coupling aspects. As a matter of fact, flight test is the most accurate way to evaluate flying qualities and to test control systems. However, it may be very expensive and/or not feasible in case of early stage design and prototyping. A good compromise is made by a preliminary assessment performed by means of simulations and a reduced flight testing campaign. Consequently, having an analytical framework represents an important stage for simulations and control algorithm design. In this work mathematical models for various helicopter configurations are implemented. Different flight control techniques for helicopters are presented with theoretical background and tested via simulations and experimental flight tests on a small-scale unmanned helicopter. The same platform is used also in a cooperative scenario with a rover. Control strategies, algorithms and their implementation to perform missions are presented for two main scenarios. One of the main contributions of this thesis is to propose a suitable control system made by a classical PID baseline controller augmented with L1 adaptive contribution. In addition a complete analytical framework and the study of the dynamics and the stability of a synch-rotor are provided. At last, the implementation of cooperative control strategies for two main scenarios that include a small-scale unmanned helicopter and a rover.

Utilizzo integrato di metodiche molecolari per la ricerca e la caratterizzazione genetica degli agenti infettivi in carnivori domestici e selvatici

Nel periodo compreso tra il 2019 e il 2022 sono state testate differenti matrici biologiche di carnivori domestici e selvatici provenienti dall’Italia e da altri Paesi europei (Norvegia, Romania). Diversi saggi molecolari, tra cui real-time PCR, end-point PCR, semi-nested PCR, retrotrascrizione e rolling circle amplification, sono stati utilizzati per ricercare il DNA o l’RNA genomico di virus e batteri. Il sequenziamento dell’intero genoma o di geni informativi dei patogeni identificati ne ha inoltre consentito la caratterizzazione genetica e l’analisi filogenetica. Gli studi, svolti presso il Dipartimento di Scienze Mediche Veterinarie dell’Università di Bologna, erano focalizzati nei confronti di alcuni virus a DNA, come Carnivore protoparvovirus 1 in lupi dall’appennino italiano e cani dalla Romania, adenovirus canino di tipo 1 e 2 in cani e lupi provenienti dal territorio nazionale, circovirus canino in cani e lupi italiani e volpi rosse e artiche della Norvegia; virus a RNA, come il canine distemper virus in faine recuperate nel territorio italiano e il calicivirus felino in gatti con diagnosi di poliartrite; e batteri appartenenti alla specie Anaplasma phagocytophilum in gatti deceduti e sottoposti a necroscopia in Italia. Dai risultati ottenuti è emerso che gli agenti infettivi indagati circolano nelle popolazioni di carnivori domestici e selvatici in forma asintomatica o determinando talvolta sintomatologia clinica. In alcuni animali testati è stata rilevata la coinfezione con diversi agenti patogeni, condizione che può predisporre ad un aggravamento della sintomatologia clinica. Dall’analisi filogenetica sono emerse relazioni tra gli agenti infettivi rilevati nelle differenti specie animali suggerendone la trasmissione tra ospiti domestici e selvatici e confermando il ruolo epidemiologico svolto dei carnivori selvatici nel mantenimento dei patogeni nel territorio. Alla luce dei dati ottenuti, è importante sottolineare l’importanza delle misure di profilassi, in particolare la vaccinazione degli animali da compagnia, per ridurre la trasmissione e la diffusione degli agenti infettivi.

Technologies for urban and rural internet of things

Nowadays, application domains such as smart cities, agriculture or intelligent transportation, require communication technologies that combine long transmission ranges and energy efficiency to fulfill a set of capabilities and constraints to rely on. In addition, in recent years, the interest in Unmanned Aerial Vehicles (UAVs) providing wireless connectivity in such scenarios is substantially increased thanks to their flexible deployment. The first chapters of this thesis deal with LoRaWAN and Narrowband-IoT (NB-IoT), which recent trends identify as the most promising Low Power Wide Area Networks technologies. While LoRaWAN is an open protocol that has gained a lot of interest thanks to its simplicity and energy efficiency, NB-IoT has been introduced from 3GPP as a radio access technology for massive machine-type communications inheriting legacy LTE characteristics. This thesis offers an overview of the two, comparing them in terms of selected performance indicators. In particular, LoRaWAN technology is assessed both via simulations and experiments, considering different network architectures and solutions to improve its performance (e.g., a new Adaptive Data Rate algorithm). NB-IoT is then introduced to identify which technology is more suitable depending on the application considered. The second part of the thesis introduces the use of UAVs as flying Base Stations, denoted as Unmanned Aerial Base Stations, (UABSs), which are considered as one of the key pillars of 6G to offer service for a number of applications. To this end, the performance of an NB-IoT network are assessed considering a UABS following predefined trajectories. Then, machine learning algorithms based on reinforcement learning and meta-learning are considered to optimize the trajectory as well as the radio resource management techniques the UABS may rely on in order to provide service considering both static (IoT sensors) and dynamic (vehicles) users. Finally, some experimental projects based on the technologies mentioned so far are presented.

The conundrum of human visceral leishmaniasis in Emilia-Romagna, Italy: are wild and peridomestic animals potential reservoirs?

Leishmaniasis is a complex parasitic disease caused by intracellular protozoans of the genus Leishmania mainly transmitted by the bite of sand flies. In Italy, leishmaniasis is caused by Leishmania infantum, responsible for the human visceral and canine leishmaniases (HVL and CanL, respectively). Within Emilia-Romagna region, Italy, recent molecular studies indicated that L. infantum strains circulating in dogs and humans are different. This suggests that an animal reservoir other than dog should be evaluated in the epidemiology of HVL in Emilia-Romagna. Therefore, the main aim of this PhD project was to investigate the role of wild and peridomestic mammals as potential animal reservoirs of L. infantum in the regional zones where HVL foci are still active, also evaluating the possible role of arthropod vectors other than phlebotomine sandflies as vectors of Leishmania spp. in the sylvatic cycle of the protozoa. Overall, 206 specimens of different animal species (roe deer, rats, mice, badgers, hares, polecats, foxes, beech martens, bank voles, hedgehogs, and shrews), collected in Emilia-Romagna were screened for Leishmania with a real-time PCR, revealing a prevalence of 33% for roe deer (first report in this species). Positivity was also found in brown rats (10.6%), black rats (13.1%), mice (10%), badgers (25%), hedgehogs (80%) and bank voles (11%). To distinguish the two strains of L. infantum circulating in Emilia-Romagna, a nested PCR protocol optimized for animal tissues was developed, demonstrating that over 90% of L. infantum infections in roe deer were due to the strain isolated from humans and suggesting their possible role as reservoirs in the study area. Furthermore, the presence of Leishmania kDNA was detected in unfed larvae, nymphs and males of questing Ixodes ricinus ticks collected in regional parks of Emilia-Romagna suggesting their possible role in the transmission of L. infantum in a sylvatic or rural cycle.

Urban air mobility: modelling the future transport system

The advances in the aviation field, particularly the development of electric flying vehicles, as UAV and eVTOL, paved the way for setting Urban Air Mobility (UAM) services. UAM would provide services for passengers, goods and emergencies and could offer faster trips than ground ones. It is expected that early UAM operations will be performed at Very Low-Level airspace as 0-500 m Above Ground Level. The purpose of this research is to both explore the main features of UAM and test an aerial network model, which could be integrated in a multimodal transport system where ground and aerial mobility services are provided. Analyses on UAM transport system involved two sub-systems: the transport demand sub-system, i.e., the mobility requirements, and the transport supply sub-system, i.e., the service and facilities enabling mobility. At first, the UAM demand levels and features for an Airport Shuttle service have been explored through a suitable survey, by combining Revealed and Stated Preference methodologies, and by calibrating some discrete mode choice models. Then, the focus has been on the transport supply model for UAM services, by focusing on both the ground access points (vertiports) and the aerial network model. A suitable three-dimensional urban aerial network (3D-UAN) model that could support fast aerial connections between O/D pairs has been proposed. Some tests have been implemented to verify the feasibility of the proposed model. Some flying vehicles supporting an Airport Shuttle service have been simulated on the aerial network, which has been specified in terms of both topological features and link transport costs. The preliminary results have showed that the proposed 3D-UAN model could be suitable for supporting UAM services. As for transport engineering, the UAM system framework proposed in this thesis paves the way for further research on air-ground multimodality in urban areas.

Unmanned Aerial Wireless Networks For The Internet of Things

The need for data collection from sensors dispersed in the environment is an increasingly important problem in the sector of telecommunications. LoRaWAN is one of the most popular protocols for low-power wide-area networks (LPWAN) that is made to solve the aforementioned problem. The aim of this study is to test the behavior of the LoRaWAN protocol when the gateway that collects data is implemented on a flying platform or, more specifically, a drone. This will be pursued using performance data in terms of access to the channel of the sensor nodes connected to the flying gateway. The trajectory of the aircraft is precomputed using a given algorithm and sensor nodes’ clusterization. The expected results are as follows: simulate the LoraWAN system behavior including the trajectory of the drone and the deployment of nodes; compare and discuss the effectiveness of the LoRaWAN simulator by conducting on-field trials, where the trajectory design and the nodes’ deployment are the same.

Neural Network based Non Orthogonal Random Access for 6G NTN-IoT

Pervasive and distributed Internet of Things (IoT) devices demand ubiquitous coverage beyond No-man’s land. To satisfy plethora of IoT devices with resilient connectivity, Non-Terrestrial Networks (NTN) will be pivotal to assist and complement terrestrial systems. In a massiveMTC scenario over NTN, characterized by sporadic uplink data reports, all the terminals within a satellite beam shall be served during the short visibility window of the flying platform, thus generating congestion due to simultaneous access attempts of IoT devices on the same radio resource. The more terminals collide, the more average-time it takes to complete an access which is due to the decreased number of successful attempts caused by Back-off commands of legacy methods. A possible countermeasure is represented by Non-Orthogonal Multiple Access scheme, which requires the knowledge of the number of superimposed NPRACH preambles. This work addresses this problem by proposing a Neural Network (NN) algorithm to cope with the uncoordinated random access performed by a prodigious number of Narrowband-IoT devices. Our proposed method classifies the number of colliding users, and for each estimates the Time of Arrival (ToA). The performance assessment, under Line of Sight (LoS) and Non-LoS conditions in sub-urban environments with two different satellite configurations, shows significant benefits of the proposed NN algorithm with respect to traditional methods for the ToA estimation.

Continual learning on nano drones

Miniaturized flying robotic platforms, called nano-drones, have the potential to revolutionize the autonomous robots industry sector thanks to their very small form factor. The nano-drones’ limited payload only allows for a sub-100mW microcontroller unit for the on-board computations. Therefore, traditional computer vision and control algorithms are too computationally expensive to be executed on board these palm-sized robots, and we are forced to rely on artificial intelligence to trade off accuracy in favor of lightweight pipelines for autonomous tasks. However, relying on deep learning exposes us to the problem of generalization since the deployment scenario of a convolutional neural network (CNN) is often composed by different visual cues and different features from those learned during training, leading to poor inference performances. Our objective is to develop and deploy and adaptation algorithm, based on the concept of latent replays, that would allow us to fine-tune a CNN to work in new and diverse deployment scenarios. To do so we start from an existing model for visual human pose estimation, called PULPFrontnet, which is used to identify the pose of a human subject in space through its 4 output variables, and we present the design of our novel adaptation algorithm, which features automatic data gathering and labeling and on-device deployment. We therefore showcase the ability of our algorithm to adapt PULP-Frontnet to new deployment scenarios, improving the R2 scores of the four network outputs, with respect to an unknown environment, from approximately [−0.2, 0.4, 0.0,−0.7] to [0.25, 0.45, 0.2, 0.1]. Finally we demonstrate how it is possible to fine-tune our neural network in real time (i.e., under 76 seconds), using the target parallel ultra-low power GAP 8 System-on-Chip on board the nano-drone, and we show how all adaptation operations can take place using less than 2mWh of energy, a small fraction of the available battery power.