A three-dimensional representation method for noisy point clouds based on growing self-organizing maps accelerated on GPUs

The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models, without considering time constraints. It is proposed a hardware implementation leveraging the computing power of modern GPUs, which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). The proposed methods were applied to different problem and applications in the area of computer vision such as the recognition and localization of objects, visual surveillance or 3D reconstruction.

Self-Organizing Map Neural Architectures Based on Limit Cycle Attractors

Recent efforts to develop large-scale neural architectures have paid relatively little attention to the use of self-organizing maps (SOMs). Part of the reason is that most conventional SOMs use a static encoding representation: Each input is typically represented by the fixed activation of a single node in the map layer. This not only carries information in an inefficient and unreliable way that impedes building robust multi-SOM neural architectures, but it is also inconsistent with rhythmic oscillations in biological neural networks. Here I develop and study an alternative encoding scheme that instead uses limit cycle attractors of multi-focal activity patterns to represent input patterns/sequences. Such a fundamental change in representation raises several questions: Can this be done effectively and reliably? If so, will map formation still occur? What properties would limit cycle SOMs exhibit? Could multiple such SOMs interact effectively? Could robust architectures based on such SOMs be built for practical applications? The principal results of examining these questions are as follows. First, conditions are established for limit cycle attractors to emerge in a SOM through self-organization when encoding both static and temporal sequence inputs. It is found that under appropriate conditions a set of learned limit cycles are stable, unique, and preserve input relationships. In spite of the continually changing activity in a limit cycle SOM, map formation continues to occur reliably. Next, associations between limit cycles in different SOMs are learned. It is shown that limit cycles in one SOM can be successfully retrieved by another SOM’s limit cycle activity. Control timings can be set quite arbitrarily during both training and activation. Importantly, the learned associations generalize to new inputs that have never been seen during training. Finally, a complete neural architecture based on multiple limit cycle SOMs is presented for robotic arm control. This architecture combines open-loop and closed-loop methods to achieve high accuracy and fast movements through smooth trajectories. The architecture is robust in that disrupting or damaging the system in a variety of ways does not completely destroy the system. I conclude that limit cycle SOMs have great potentials for use in constructing robust neural architectures.

Self-Description Questionnaire II (versión breve): evidencia de fiabilidad y validez en una muestra de adolescentes chilenos

El objetivo de este estudio fue analizar la fiabilidad y validez de las puntuaciones de la versión breve del Self-Description Questionnaire II (SDQ-II-S) en población chilena. La muestra se compuso de 1255 adolescentes chilenos, con un rango de edad de 13 a 17 años (M = 15.10; DT = 1.30). El análisis factorial confirmatorio corroboró la estructura original de 11 factores correlacionados del SDQ-II-S. La multidimensionalidad del cuestionario también fue avalada por la pequeña magnitud de las correlaciones entre los 11 factores (M = 0.26). Los coeficientes alfa de Cronbach variaron desde 0.70 hasta 0.84, y se destacó una adecuada fiabilidad. Para profundizar en el análisis de la validez de constructo del SDQ-II-S, se relacionaron las puntuaciones de las diferentes escalas con puntuaciones en medidas de ansiedad (Inventario de Ansiedad Estado-Rasgo) y autoeficacia (Escala de Autoeficacia Percibida Específica de Situaciones Académicas). Los resultados pusieron de manifiesto que estos cuestionarios permiten analizar constructos diferenciados aunque relacionados. Los datos de este trabajo destacan que el SDQ-II-S presenta adecuadas propiedades psicométricas en población chilena, contrarrestando las carencias existentes en lo que respecta a la evaluación del autoconcepto, y resaltan interesantes aplicaciones tanto en el ámbito aplicado como en el de la investigación.

Electrochemical Immunosensing of Cortisol in an Automated Microfluidic System Towards Point-of-Care Applications

This dissertation describes the development of a label-free, electrochemical immunosensing platform integrated into a low-cost microfluidic system for the sensitive, selective and accurate detection of cortisol, a steroid hormone co-related with many physiological disorders. Abnormal levels of cortisol is indicative of conditions such as Cushing’s syndrome, Addison’s disease, adrenal insufficiencies and more recently post-traumatic stress disorder (PTSD). Electrochemical detection of immuno-complex formation is utilized for the sensitive detection of Cortisol using Anti-Cortisol antibodies immobilized on sensing electrodes. Electrochemical detection techniques such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) have been utilized for the characterization and sensing of the label-free detection of Cortisol. The utilization of nanomaterial’s as the immobilizing matrix for Anti-cortisol antibodies that leads to improved sensor response has been explored. A hybrid nano-composite of Polyanaline-Ag/AgO film has been fabricated onto Au substrate using electrophoretic deposition for the preparation of electrochemical immunosening of cortisol. Using a conventional 3-electrode electrochemical cell, a linear sensing range of 1pM to 1µM at a sensitivity of 66µA/M and detection limit of 0.64pg/mL has been demonstrated for detection of cortisol. Alternately, a self-assembled monolayer (SAM) of dithiobis(succinimidylpropionte) (DTSP) has been fabricated for the modification of sensing electrode to immobilize with Anti-Cortisol antibodies. To increase the sensitivity at lower detection limit and to develop a point-of-care sensing platform, the DTSP-SAM has been fabricated on micromachined interdigitated microelectrodes (µIDE). Detection of cortisol is demonstrated at a sensitivity of 20.7µA/M and detection limit of 10pg/mL for a linear sensing range of 10pM to 200nM using the µIDE’s. A simple, low-cost microfluidic system is designed using low-temperature co-fired ceramics (LTCC) technology for the integration of the electrochemical cortisol immunosensor and automation of the immunoassay. For the first time, the non-specific adsorption of analyte on LTCC has been characterized for microfluidic applications. The design, fabrication technique and fluidic characterization of the immunoassay are presented. The DTSP-SAM based electrochemical immunosensor on µIDE is integrated into the LTCC microfluidic system and cortisol detection is achieved in the microfluidic system in a fully automated assay. The fully automated microfluidic immunosensor hold great promise for accurate, sensitive detection of cortisol in point-of-care applications.

The actinin family of actin crosslinking proteins: natural functions and potential applications in synthetic biology

Actinin and spectrin proteins are members of the Spectrin Family of Actin Crosslinking Proteins. The importance of these proteins in the cytoskeleton is demonstrated by the fact that they are common targets for disease causing mutations. In their most prominent roles, actinin and spectrin are responsible for stabilising and maintaining the muscle architecture during contraction, and providing shape and elasticity to the red blood cell in circulation, respectively. To carry out such roles, actinin and spectrin must possess important mechanical and physical properties. These attributes are desirable when choosing a building block for protein-based nanoconstruction. In this study, I assess the contribution of several disease-associated mutations in the actinin-1 actin binding domain that have recently been linked to a rare platelet disorder, congenital macrothrombocytopenia. I investigate the suitability of both actinin and spectrin proteins as potential building blocks for nanoscale structures, and I evaluate a fusion-based assembly strategy to bring about self-assembly of protein nanostructures. I report that the actinin-1 mutant proteins display increased actin binding compared to WT actinin-1 proteins. I find that both actinin and spectrin proteins exhibit enormous potential as nano-building blocks in terms of their stability and ability to self-assemble, and I successfully design and create homodimeric and heterodimeric bivalent building blocks using the fusion-based assembly strategy. Overall, this study has gathered helpful information that will contribute to furthering the advancement of actinin and spectrin knowledge in terms of their natural functions, and potential unnatural functions in protein nanotechnology.

Self-assembly of gold nanocrystals into discrete coupled plasmonic structures

Development of methodologies for the controlled chemical assembly of nanoparticles into plasmonic molecules of predictable spatial geometry is vital in order to harness novel properties arising from the combination of the individual components constituting the resulting superstructures. This paper presents a route for fabrication of gold plasmonic structures of controlled stoichiometry obtained by the use of a di-rhenium thio-isocyanide complex as linker molecule for gold nanocrystals. Correlated scanning electron microscopy (SEM)—dark-field spectroscopy was used to characterize obtained discrete monomer, dimer and trimer plasmonic molecules. Polarization-dependent scattering spectra of dimer structures showed highly polarized scattering response, due to their highly asymmetric D∞h geometry. In contrast, some trimer structures displayed symmetric geometry (D3h), which showed small polarization dependent response. Theoretical calculations were used to further understand and attribute the origin of plasmonic bands arising during linker-induced formation of plasmonic molecules. Theoretical data matched well with experimentally calculated data. These results confirm that obtained gold superstructures possess properties which are a combination of the properties arising from single components and can, therefore, be classified as plasmonic molecules

Aproximaciones a mindfulness en la psicología contemporánea

Este trabajo es una revisión de literatura que abarca una selección de artículos disponibles en bases de datos especializadas y publicados en el periodo comprendido entre los años 2006 a 2016 para artículos científicos y entre los años 2000 a 2016 para libros. En total se revisaron: 1 tesis doctoral, 1 tesis magistral, 111 artículos y 9 libros o capítulos de libros. Se presentan diversas definiciones de mindfulness y formas de conceptualizarla, sus mecanismos de acción, sus enfoques psicoterapéuticos predominantes, los efectos de su práctica estable, sus principales campos de acción y la importancia de la formación de los docentes que imparten la práctica. Finalmente se presentan algunas conclusiones acerca del diálogo entre la literatura psicológica sobre mindfulness y algunas de las concepciones de la tradición budista en torno a la meditación.

Nanofibrous-structured polymers and their engineering applications

Monolithic materials cannot always satisfy the demands of today’s advanced requirements. Only by combining several materials at different length-scales, as nature does, the requested performances can be met. Polymer nanocomposites are intended to overcome the common drawbacks of pristine polymers, with a multidisciplinary collaboration of material science with chemistry, engineering, and nanotechnology. These materials are an active combination of polymers and nanomaterials, where at least one phase lies in the nanometer range. By mimicking nature’s materials is possible to develop new nanocomposites for structural applications demanding combinations of strength and toughness. In this perspective, nanofibers obtained by electrospinning have been increasingly adopted in the last decade to improve the fracture toughness of Fiber Reinforced Plastic (FRP) laminates. Although nanofibers have already found applications in various fields, their widespread introduction in the industrial context is still a long way to go. This thesis aims to develop methodologies and models able to predict the behaviour of nanofibrous-reinforced polymers, paving the way for their practical engineering applications. It consists of two main parts. The first one investigates the mechanisms that act at the nanoscale, systematically evaluating the mechanical properties of both the nanofibrous reinforcement phase (Chapter 1) and hosting polymeric matrix (Chapter 2). The second part deals with the implementation of different types of nanofibers for novel pioneering applications, trying to combine the well-known fracture toughness enhancement in composite laminates with improving other mechanical properties or including novel functionalities. Chapter 3 reports the development of novel adhesive carriers made of nylon 6,6 nanofibrous mats to increase the fracture toughness of epoxy-bonded joints. In Chapter 4, recently developed rubbery nanofibers are used to enhance the damping properties of unidirectional carbon fiber laminates. Lastly, in Chapter 5, a novel self-sensing composite laminate capable of detecting impacts on its surface using PVDF-TrFE piezoelectric nanofibers is presented.

Intelligent Sensor Systems for Structural Health Monitoring Applications

The convergence between the recent developments in sensing technologies, data science, signal processing and advanced modelling has fostered a new paradigm to the Structural Health Monitoring (SHM) of engineered structures, which is the one based on intelligent sensors, i.e., embedded devices capable of stream processing data and/or performing structural inference in a self-contained and near-sensor manner. To efficiently exploit these intelligent sensor units for full-scale structural assessment, a joint effort is required to deal with instrumental aspects related to signal acquisition, conditioning and digitalization, and those pertaining to data management, data analytics and information sharing. In this framework, the main goal of this Thesis is to tackle the multi-faceted nature of the monitoring process, via a full-scale optimization of the hardware and software resources involved by the {SHM} system. The pursuit of this objective has required the investigation of both: i) transversal aspects common to multiple application domains at different abstraction levels (such as knowledge distillation, networking solutions, microsystem {HW} architectures), and ii) the specificities of the monitoring methodologies (vibrations, guided waves, acoustic emission monitoring). The key tools adopted in the proposed monitoring frameworks belong to the embedded signal processing field: namely, graph signal processing, compressed sensing, ARMA System Identification, digital data communication and TinyML.

Machine Learning Unsupervised Methods in the Design of an On-board Health Monitoring System for Satellite Applications

The dissertation starts by providing a description of the phenomena related to the increasing importance recently acquired by satellite applications. The spread of such technology comes with implications, such as an increase in maintenance cost, from which derives the interest in developing advanced techniques that favor an augmented autonomy of spacecrafts in health monitoring. Machine learning techniques are widely employed to lay a foundation for effective systems specialized in fault detection by examining telemetry data. Telemetry consists of a considerable amount of information; therefore, the adopted algorithms must be able to handle multivariate data while facing the limitations imposed by on-board hardware features. In the framework of outlier detection, the dissertation addresses the topic of unsupervised machine learning methods. In the unsupervised scenario, lack of prior knowledge of the data behavior is assumed. In the specific, two models are brought to attention, namely Local Outlier Factor and One-Class Support Vector Machines. Their performances are compared in terms of both the achieved prediction accuracy and the equivalent computational cost. Both models are trained and tested upon the same sets of time series data in a variety of settings, finalized at gaining insights on the effect of the increase in dimensionality. The obtained results allow to claim that both models, combined with a proper tuning of their characteristic parameters, successfully comply with the role of outlier detectors in multivariate time series data. Nevertheless, under this specific context, Local Outlier Factor results to be outperforming One-Class SVM, in that it proves to be more stable over a wider range of input parameter values. This property is especially valuable in unsupervised learning since it suggests that the model is keen to adapting to unforeseen patterns.

Development and Implementation of the Plasma Focus Technology for Radiation Therapy Applications

A Plasma Focus device can confine in a small region a plasma generated during the pinch phase. When the plasma is in the pinch condition it creates an environment that produces several kinds of radiations. When the filling gas is nitrogen, a self-collimated backwardly emitted electron beam, slightly spread by the coulomb repulsion, can be considered one of the most interesting outputs. That beam can be converted into X-ray pulses able to transfer energy at an Ultra-High Dose-Rate (UH-DR), up to 1 Gy pulse-1, for clinical applications, research, or industrial purposes. The radiation fields have been studied with the PFMA-3 hosted at the University of Bologna, finding the radiation behavior at different operating conditions and working parameters for a proper tuning of this class of devices in clinical applications. The experimental outcomes have been compared with available analytical formalisms as benchmark and the scaling laws have been proposed. A set of Monte Carlo models have been built with direct and adjoint techniques for an accurate X-ray source characterization and for setting fast and reliable irradiation planning for patients. By coupling deterministic and Monte Carlo codes, a focusing lens for the charged particles has been designed for obtaining a beam suitable for applications as external radiotherapy or intra-operative radiation therapy. The radiobiological effectiveness of the UH PF DR, a FLASH source, has been evaluated by coupling different Monte Carlo codes estimating the overall level of DNA damage at the multi-cellular and tissue levels by considering the spatial variation effects as well as the radiation field characteristics. The numerical results have been correlated to the experimental outcomes. Finally, ambient dose measurements have been performed for tuning the numerical models and obtaining doses for radiation protection purposes. The PFMA-3 technology has been fully characterized toward clinical implementation and installation in a medical facility.

Electrochemistry of polycyclic aromatic molecules for advanced carbon nanostructures: luminescence and transistor applications

Polycyclic aromatic hydrocarbons (PAHs) are a large class of π-conjugated organic molecules with fused aromatic rings, which can be considered as fragments of 2D-graphene and have been extensively studied for their unique optical and electronic properties. The aim of this study is to understand the complex electrochemical behaviour of planar, curved, and heteroatom doped polycyclic aromatic molecules, particularly focusing on the oxidative coupling of their radical cations and the electrochemically induced cyclodehydrogenation reactions. In the first part of this thesis, the class of PAHs and aromatic nanostructures are introduced, and the reactivity of electrogenerated species is discussed, focusing on the electrochemical approach for the synthesis of extended π-conjugated structures. Subsequently, the electrochemical properties and reactivity of electrogenerated radical ions of planar and curved polyaromatics are correlated to their structures. In the third chapter, electrochemical cyclodehydrogenation of hexaphenylbenzene is used to prepare self-assembled hexabenzocoronene, directly deposited on an interdigitated electrode, which was characterised as organic electrochemical transistor. In the fourth chapter, the electrochemical behaviour of a family of azapyrene derivatives has been carefully investigated together with the electrogenerated chemiluminescence (ECL), both by ion-annihilation and co-reactant methods. Two structural azapyrene isomers with different nitrogen positions are thoroughly discussed in terms of redox and ECL properties. Interestingly, the ECL of only one of them showed a double emission with excimer formation. A detailed mechanism is discussed for the ECL by co-reactant benzoyl peroxide, to rationalise the different ECL behaviours of the two isomers on the basis of their topologically modulated electronic properties. In conclusion, the different electrochemical behaviours of PAHs were shown, focussing on the chemical reactivity of the electrogenerated species and taking advantage of it for important processes spanning from unconventional synthesis methods for carbon nanostructures to the exploitation of self-assembled nanostructured systems in organic electronics, to novel organic emitters in ECL.

Adapting The Sniffin' Sticks Olfactory Test To Diagnose Parkinson's Disease In Estonia.

The aim of the study was to develop a culturally adapted translation of the 12-item smell identification test from Sniffin' Sticks (SS-12) for the Estonian population in order to help diagnose Parkinson's disease (PD). A standard translation of the SS-12 was created and 150 healthy Estonians were questioned about the smells used as response options in the test. Unfamiliar smells were replaced by culturally familiar options. The adapted SS-12 was applied to 70 controls in all age groups, and thereafter to 50 PD patients and 50 age- and sex-matched controls. 14 response options from 48 used in the SS-12 were replaced with familiar smells in an adapted version, in which the mean rate of correct response was 87% (range 73-99) compared to 83% with the literal translation (range 50-98). In PD patients, the average adapted SS-12 score (5.4/12) was significantly lower than in controls (average score 8.9/12), p < 0.0001. A multiple linear regression using the score in the SS-12 as the outcome measure showed that diagnosis and age independently influenced the result of the SS-12. A logistic regression using the SS-12 and age as covariates showed that the SS-12 (but not age) correctly classified 79.0% of subjects into the PD and control category, using a cut-off of <7 gave a sensitivity of 76% and specificity of 86% for the diagnosis of PD. The developed SS-12 cultural adaption is appropriate for testing olfaction in Estonia for the purpose of PD diagnosis.

An Efficient Protocol For The Generation Of Monocyte Derived Dendritic Cells Using Serum-free Media For Clinical Applications In Post Remission Aml Patients.

Protocols for the generation of dendritic cells (DCs) using serum as a supplementation of culture media leads to reactions due to animal proteins and disease transmissions. Several types of serum-free media (SFM), based on good manufacture practices (GMP), have recently been used and seem to be a viable option. The aim of this study was to evaluate the results of the differentiation, maturation, and function of DCs from Acute Myeloid Leukemia patients (AML), generated in SFM and medium supplemented with autologous serum (AS). DCs were analyzed by phenotype characteristics, viability, and functionality. The results showed the possibility of generating viable DCs in all the conditions tested. In patients, the X-VIVO 15 medium was more efficient than the other media tested in the generation of DCs producing IL-12p70 (p=0.05). Moreover, the presence of AS led to a significant increase of IL-10 by DCs as compared with CellGro (p=0.05) and X-Vivo15 (p=0.05) media, both in patients and donors. We concluded that SFM was efficient in the production of DCs for immunotherapy in AML patients. However, the use of AS appears to interfere with the functional capacity of the generated DCs.

Silk Fibroin And Sodium Alginate Blend: Miscibility And Physical Characteristics.

Films of silk fibroin (SF) and sodium alginate (SA) blends were prepared by solution casting technique. The miscibility of SF and SA in those blends was evaluated and scanning electron microscopy (SEM) revealed that SF/SA 25/75 wt.% blends underwent microscopic phase separation, resulting in globular structures composed mainly of SF. X-ray diffraction indicated the amorphous nature of these blends, even after a treatment with ethanol that turned them insoluble in water. Thermal analyses of blends showed the peaks of degradation of pristine SF and SA shifted to intermediate temperatures. Water vapor permeability, swelling capacity and tensile strength of SF films could be enhanced by blending with SA. Cell viability remained between 90 and 100%, as indicated by in vitro cytotoxicity test. The SF/SA blend with self-assembled SF globules can be used to modulate structural and mechanical properties of the final material and may be used in designing high performance wound dressing.