INTERNATIONAL EDUCATION & RESEARCH FOR OH. Experiences of international networks for collaborative education and research using the One Health approach.

The Authors describe first-hand experiences carried out within the framework of selected International projects aimed at developing collaborative research and education using the One Health (OH) approach. Special emphasis is given to SAPUVETNET, a series of projects co-financed under the EU-ALFA program, and aimed to support an International network on Veterinary Public Health (VPH) formed by Veterinary Faculties from Latin-America (LA) and Europe (EU). SAPUVETNET has envisaged a series of objectives/activities aimed at promoting and enhancing VPH research/training and intersectoral collaboration across LA and EU using the OH approach, as well as participating in research and/or education projects/networks under the OH umbrella, namely EURNEGVEC-European Network for Neglected Vectors & Vector-Borne Infections, CYSTINET-European Network on Taeniosis/Cysticercosis, and NEOH-Network for Evaluation of One Health; the latter includes expertise in multiple disciplines (e.g. ecology, economics, human and animal health, epidemiology, social and environmental sciences, etc.) and has the primary purpose of enabling quantitative evaluation of OH initiatives by developing a standardized evaluation protocol. The Authors give also an account of the ongoing creation of OHIN-OH International Network, founded as a spin-off result of SAPUVETNET. Finally, some examples of cooperation development projects characterised by an OH approach are also briefly mentioned.

Chemiluminescence DNA-based Nanotechnologies for Bioanalytical Applications

DNA as powerful building molecule, is widely used for the assembly of molecular structures and dynamic molecular devices with different potential applications, ranging from synthetic biology to diagnostics. The feature of sequence programmability, which makes it possible to predict how single stranded DNA molecules fold and interact with one another, allowed the development of spatiotemporally controlled nanostructures and the engineering of supramolecular devices. The first part of this thesis addresses the development of an integrated chemiluminescence (CL)-based lab-on-chip sensor for detection of Adenosine-5-triphosphate (ATP) life biomarker in extra-terrestrial environments.Subsequently, we investigated whether it is possible to study the interaction and the recognition between biomolecules and their targets, mimicking the intracellular environment in terms of crowding, confinement and compartmentalization. To this purpose, we developed a split G-quadruplex DNAzyme platform for the chemiluminescent and quantitative detection of antibodies based on antibody-induced co-localization proximity mechanism in which a split G-quadruplex DNAzyme is led to reassemble into the functional native G-quadruplex conformation as the effect of a guided spatial nanoconfinement.The following part of this thesis aims at developing chemiluminescent nanoparticles for bioimaging and photodynamic therapy applications.In chapter5 a realistic and accurate evaluation of the potentiality of electrochemistry and chemiluminescence (CL) for biosensors development (i.e., is it better to “measure an electron or a photon”?), has been achieved.In chapter 6 the emission anisotropy phenomenon for an emitting dipole bound to the interface between two media with different refractive index has been investigated for chemiluminescence detection.

Chemiluminescence – based bioanalytical devices for astrobiological, food safety and clinical applications

At the intersection of biology, chemistry, and engineering, biosensors are a multidisciplinary innovation that provide a cost-effective alternative to traditional laboratory techniques. Due to their advantages, biosensors are used in medical diagnostics, environmental monitoring, food safety and many other fields. The first part of the thesis is concerned with learning the state of the art of paper-based immunosensors with bioluminescent (BL) and chemiluminescent (CL) detection. The use of biospecific assays combined with CL detection and paper-based technology offers an optimal approach to creating analytical tools for on-site applications and we have focused on the specific areas that need to be considered more in order to ensure a future practical implementation of these methods in routine analyses. The subsequent part of the thesis addresses the development of an autonomous lab-on-chip platform for performing chemiluminescent-based bioassays in space environment, exploiting a CubeSat platform for astrobiological investigations. An origami-inspired microfluidic paper-based analytical device has been developed with the purpose of assesses its performance in space and to evaluate its functionality and the resilience of the (bio)molecules when exposed to a radiation-rich environment. Subsequently, we designed a paper-based assay to detect traces of ovalbumin in food samples, creating a user-friendly immunosensing platform. To this purpose, we developed an origami device that exploits a competitive immunoassay coupled with chemiluminescence detection and magnetic microbeads used to immobilize ovalbumin on paper. Finally, with the aim of exploring the use of biomimetic materials, an hydrogel-based chemiluminescence biosensor for the detection of H2O2 and glucose was developed. A guanosine hydrogel was prepared and loaded with luminol and hemin, miming a DNAzyme activity. Subsequently, the hydrogel was modified by incorporating glucose oxidase enzyme to enable glucose biosensing. The emitted photons were detected using a portable device equipped with a smartphone's CMOS (complementary metal oxide semiconductor) camera for CL emission detection.

Analysis, Design, and Hardware-in-the-Loop Validation of Multi-Active Bridge Converters

This master's thesis investigates different aspects of Dual-Active-Bridge (DAB) Converter and extends aspects further to Multi-Active-Bridges (MAB). The thesis starts with an overview of the applications of the DAB and MAB and their importance. The analytical part of the thesis includes the derivation of the peak and RMS currents, which is required for finding the losses present in the system. The power converters, considered in this thesis are DAB, Triple-Active Bridge (TAB) and Quad-Active Bridge (QAB). All the theoretical calculations are compared with the simulation results from PLECS software for identifying the correctness of the reviewed and developed theory. The Hardware-in-the-Loop (HIL) simulation is conducted for checking the control operation in real-time with the help of the RT box from the Plexim. Additionally, as in real systems digital signal processor (DSP), system-on-chip or field programmable gate array is employed for the control of the power electronic systems, and the execution of the control in the real-time simulation (RTS) conducted is performed by DSP.

Mitigating non-Lambertian surfaces issues in Stereo Matching with Neural Radiance Fields

Depth estimation from images has long been regarded as a preferable alternative compared to expensive and intrusive active sensors, such as LiDAR and ToF. The topic has attracted the attention of an increasingly wide audience thanks to the great amount of application domains, such as autonomous driving, robotic navigation and 3D reconstruction. Among the various techniques employed for depth estimation, stereo matching is one of the most widespread, owing to its robustness, speed and simplicity in setup. Recent developments has been aided by the abundance of annotated stereo images, which granted to deep learning the opportunity to thrive in a research area where deep networks can reach state-of-the-art sub-pixel precision in most cases. Despite the recent findings, stereo matching still begets many open challenges, two among them being finding pixel correspondences in presence of objects that exhibits a non-Lambertian behaviour and processing high-resolution images. Recently, a novel dataset named Booster, which contains high-resolution stereo pairs featuring a large collection of labeled non-Lambertian objects, has been released. The work shown that training state-of-the-art deep neural network on such data improves the generalization capabilities of these networks also in presence of non-Lambertian surfaces. Regardless being a further step to tackle the aforementioned challenge, Booster includes a rather small number of annotated images, and thus cannot satisfy the intensive training requirements of deep learning. This thesis work aims to investigate novel view synthesis techniques to augment the Booster dataset, with ultimate goal of improving stereo matching reliability in presence of high-resolution images that displays non-Lambertian surfaces.

Digital surveillance based on video CODEC System-on-a-Chip (SoC) platforms

Today, most conventional surveillance networks are based on analog system, which has a lot of constraints like manpower and high-bandwidth requirements. It becomes the barrier for today's surveillance network development. This dissertation describes a digital surveillance network architecture based on the H.264 coding/decoding (CODEC) System-on-a-Chip (SoC) platform. The proposed digital surveillance network architecture includes three major layers: software layer, hardware layer, and the network layer. The following outlines the contributions to the proposed digital surveillance network architecture. (1) We implement an object recognition system and an object categorization system on the software layer by applying several Digital Image Processing (DIP) algorithms. (2) For better compression ratio and higher video quality transfer, we implement two new modules on the hardware layer of the H.264 CODEC core, i.e., the background elimination module and the Directional Discrete Cosine Transform (DDCT) module. (3) Furthermore, we introduce a Digital Signal Processor (DSP) sub-system on the main bus of H.264 SoC platforms as the major hardware support system for our software architecture. Thus we combine the software and hardware platforms to be an intelligent surveillance node. Lab results show that the proposed surveillance node can dramatically save the network resources like bandwidth and storage capacity.

Nectar Robbery By A Hermit Hummingbird: Association To Floral Phenotype And Its Influence On Flowers And Network Structure.

Interactions between flowers and their visitors span the spectrum from mutualism to antagonism. The literature is rich in studies focusing on mutualism, but nectar robbery has mostly been investigated using phytocentric approaches focused on only a few plant species. To fill this gap, we studied the interactions between a nectar-robbing hermit hummingbird, Phaethornis ruber, and the array of flowers it visits. First, based on a literature review of the interactions involving  P. ruber, we characterized the association of floral larceny to floral phenotype. We then experimentally examined the effects of nectar robbing on nectar standing crop and number of visits of the pollinators to the flowers of Canna paniculata. Finally, we asked whether the incorporation of illegitimate interactions into the analysis affects plant-hummingbird network structure. We identified 97 plant species visited by P. ruber and found that P. ruber engaged in floral larceny in almost 30 % of these species. Nectar robbery was especially common in flowers with longer corolla. In terms of the effect on C. paniculata, the depletion of nectar due to robbery by P. ruber was associated with decreased visitation rates of legitimate pollinators. At the community level, the inclusion of the illegitimate visits of P. ruber resulted in modifications of how modules within the network were organized, notably giving rise to a new module consisting of P. ruber and mostly robbed flowers. However, although illegitimate visits constituted approximately 9 % of all interactions in the network, changes in nestedness, modularity, and network-level specialization were minor. Our results indicate that although a flower robber may have a strong effect on the pollination of a particular plant species, the inclusion of its illegitimate interactions has limited capacity to change overall network structure.

Mobility and social network effects on extremist opinions

Understanding the emergence of extreme opinions and in what kind of environment they might become less extreme is a central theme in our modern globalized society. A model combining continuous opinions and observed discrete actions (CODA) capable of addressing the important issue of measuring how extreme opinions might be has been recently proposed. In this paper I show extreme opinions to arise in a ubiquitous manner in the CODA model for a multitude of social network structures. Depending on network details reducing extremism seems to be possible. However, a large number of agents with extreme opinions is always observed. A significant decrease in the number of extremists can be observed by allowing agents to change their positions in the network.

Haplotype distribution of five nuclear genes based on network genealogies and Bayesian inference indicates that Trypanosoma cruzi hybrid strains are polyphyletic

Chagas disease is still a major public health problem in Latin America. Its causative agent, Trypanosoma cruzi, can be typed into three major groups, T. cruzi I, T. cruzi II and hybrids. These groups each have specific genetic characteristics and epidemiological distributions. Several highly virulent strains are found in the hybrid group; their origin is still a matter of debate. The null hypothesis is that the hybrids are of polyphyletic origin, evolving independently from various hybridization events. The alternative hypothesis is that all extant hybrid strains originated from a single hybridization event. We sequenced both alleles of genes encoding EF-1 alpha, actin and SSU rDNA of 26 T. cruzi strains and DHFR-TS and TR of 12 strains. This information was used for network genealogy analysis and Bayesian phylogenies. We found T. cruzi I and T. cruzi II to be monophyletic and that all hybrids had different combinations of T. cruzi I and T. cruzi II haplotypes plus hybrid-specific haplotypes. Bootstrap values (networks) and posterior probabilities (Bayesian phylogenies) of clades supporting the monophyly of hybrids were far below the 95% confidence interval, indicating that the hybrid group is polyphyletic. We hypothesize that T. cruzi I and T. cruzi II are two different species and that the hybrids are extant representatives of independent events of genome hybridization, which sporadically have sufficient fitness to impact on the epidemiology of Chagas disease.

Connection Admission Control for a WDM Optical Network Based on Traffic Monitoring and Bandwidth Release

We proposed a connection admission control (CAC) to monitor the traffic in a multi-rate WDM optical network. The CAC searches for the shortest path connecting source and destination nodes, assigns wavelengths with enough bandwidth to serve the requests, supervises the traffic in the most required nodes, and if needed activates a reserved wavelength to release bandwidth according to traffic demand. We used a scale-free network topology, which includes highly connected nodes ( hubs), to enhance the monitoring procedure. Numerical results obtained from computational simulations show improved network performance evaluated in terms of blocking probability.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

On the basic reproduction number and the topological properties of the contact network: An epidemiological study in mainly locally connected cellular automata

We study the spreading of contagious diseases in a population of constant size using susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations (ODEs) and probabilistic cellular automata (PCA). In the PCA model, each individual (represented by a cell in the lattice) is mainly locally connected to others. We investigate how the topological properties of the random network representing contacts among individuals influence the transient behavior and the permanent regime of the epidemiological system described by ODE and PCA. Our main conclusions are: (1) the basic reproduction number (commonly called R(0)) related to a disease propagation in a population cannot be uniquely determined from some features of transient behavior of the infective group; (2) R(0) cannot be associated to a unique combination of clustering coefficient and average shortest path length characterizing the contact network. We discuss how these results can embarrass the specification of control strategies for combating disease propagations. (C) 2009 Elsevier B.V. All rights reserved.

Effect of pore-network connectivity on multicomponent adsorption of large molecules

The effect of pore-network connectivity on binary liquid-phase adsorption equilibria using the ideal adsorbed solution theory (LAST) was studied. The liquid-phase binary adsorption experiments used ethyl propionate, ethyl butyrate, and ethyl isovalerate as the adsorbates and commercial activated carbons Filtrasorb-400 and Norit ROW 0.8 as adsorbents. As the single-component isotherm, a modified Dubinin-Radushkevich equation was used. A comparison with experimental data shows that incorporating the connectivity of the pore network and considering percolation processes associated with different molecular sizes of the adsorptives in the mixture, as well as their different corresponding accessibility, can improve the prediction of binary adsorption equilibria using the LAST Selectivity of adsorption for the larger molecule in binary systems increases with an increase in the pore-network coordination number, as well with an increase in the mean pore width and in the spread of the pore-size distribution.

Investment optimization in distribution network based on fuzzy outage parameters

This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.

On the use of IEEE 802.15.4/Zigbee for time-sensitive wireless sensor network applications

Mestrado em Engenharia Electrotécnica e de Computadores