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Study of Silicon Oxycarbide(SiOC) as Anode Materials for Li-ion Batteries
No full textThe principal object of this thesis is the investigation of silicon oxycarbide (SiOC) ceramics as anode material for Li-ion batteries. The investigated materials are prepared by cross linking commercial polymer siloxanes via hydrosylilation reactions or hybrid alkoxide precursors via sol-gel. The cross linked polymer networks are then converted in to ceramic materials by a pyrolysis process in controlled argon atmosphere at 800-1300 °C.
In details the influence of carbon content on lithium storage properties is addressed for SiOC with the same O/Si atomic ratio of about 1. Detailed structural characterization studies are performed using complementary techniques which aim correlating the electrochemical behavior with the microstructure of the SiOC anodes. Results suggest that SiOC anodes behave as a composite material consisting of a disordered silicon oxycarbide phase having a very high first insertion capacity of ca 1300 mAh g-1 and a free C phase. However, the charge irreversibly trapped into the amorphous silicon oxycarbide network is also high. In consequence the maximum reversible lithium storage capacity of 650 mAh g-1 is measured on high-C content SiOCs with the ratio between amorphous silicon oxycarbide and the free C phase of 1:1. The high carbon content SiOC shows also an excellent cycling stability and performance at high charging/discharging rate with the stable capacity at 2C rate being around 200 mAh g-1.
Increasing the pyrolysis temperature has an opposite effect on the low-C and high-C materials: for the latter one the reversible capacity decreases following a known trend while the former shows an increase of
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the reversible capacity which has never been observed before for similar materials.
The influence of pyrolysis atmosphere on lithium storage capacity is investigated as well. It is found that pyrolysis in Ar/H2 mixtures, compared to the treatment under pure Ar, results into a decrease of the concentration of C dangling bonds as revealed by electron spin resonance (ESR) measurements. The sample prepared under Ar/H2 mixture shows an excellent cycling stability with an increase in the specific capacity of about 150 mAh g-1 compared to its analogues pyrolysed in pure argon atmosphere.
In order to study the role of porosity towards the lithium storage properties, a comparison of dense and porous materials obtained using same starting precursors is made. Porous SiOC ceramics are prepared by HF etching of the SiOC ceramics. HF etching removes a part of the amorphous silica phase from SiOC nanostructure leaving a porous structure. Porous ceramics with surface areas up to 640 m2 g-1 is obtained. The electrochemical charging/discharging results indicate that the porosity can help to increase the lithium storage capacity and it also leads to an enhanced cycling stability.
This work demonstrates clearly that silicon oxycarbide (SiOC) ceramics present excellent electrochemical properties to be applied as a promising anode material for lithium storage applications
Recognizing and Discovering Activities of Daily Living in Smart Environments
No full textIdentifying human activities is a key task for the development of advanced and effective ubiquitous applications in fields like Ambient Assisted Living. Depending on the availability of labeled data, recognition methods can be categorized as either supervised or unsupervised. Designing a comprehensive activity recognition system that works on a real-world setting is extremely challenging because of the difficulty for computers to process the complex nature of the human behaviors.
In the first part of this thesis we present a novel supervised approach to improve the activity recognition performance based on sequential pattern mining. The method searches for patterns characterizing time segments during which the same activity is performed. A probabilistic model is learned to represent the distribution of pattern matches along sequences, trying to maximize the coverage of an activity segment by a pattern match. The model is integrated in a segmental labeling algorithm and applied to novel sequences. Experimental evaluations show that the pattern-based segmental labeling algorithm allows improving results over sequential and segmental labeling algorithms in most of the cases. An analysis of the discovered patterns highlights non-trivial interactions spanning over a signifcant time horizon. In addition, we show that pattern usage allows incorporating long-range dependencies between distant time instants without incurring in substantial increase in computational complexity of inference.
In the second part of the thesis we propose an unsupervised activity discovery framework that aims at identifying activities within data streams in the absence of data annotation. The process starts with dividing the full sensor stream into segments by identifying differences in sensor activations characterizing potential activity changes. Then, extracted segments are clustered in order to find groups of similar segments each representing a candidate activity. Lastly, parameters of a sequential labeling algorithm are estimated using segment clusters found in the previous step and the learned model is used to smooth the initial segmentation. We present experimental evaluation for two real world datasets. The results obtained show that our segmentation approaches perform almost as good as the true segmentation and that activities are discovered with a high accuracy in most of the cases. We demonstrate the effectiveness of our model by comparing it with a technique using substantial domain knowledge. Our ongoing work is presented at the end of the section, in which we combine pattern-based method introduced in the first part of the thesis with the activity discovery framework. The results of the preliminary experiments indicate that the combined method is better in discovering similar activities than the base framework
Distances and Stability in Biological Network Theory
No full textIn this thesis we introduce, define and quantitatively assess the stability of the algorithms for the econstruction of networks. We will focus on theory,
development and implementation of operative procedures and algorithms for the assessment of stability in complex networks for biological systems, with gene regulatory networks as the key example. A major issue affecting
network inference is indeed the high variability of network reconstruction and network topology inferred after data perturbation, different parameter choices and alternative methods. Network stability will thus be used to measure reliability of inferred topology, also obtaining confidence intervals for the outcomes. The methods will be employed to introduce a new approach to reproducibility in the study of complex networks. It will also be coupled with statistical machine learning models, in order to integrate feature selection and network inference within a pathway profiling approach. The evaluation of similarity between networks will be the first and central operative procedure of the developed pipelines, the key point being the identification of distances that can compare network structures improving over classical measures based on the confusion matrix, too coarse for this task.
A combination of spectral and edit distances especially tailored for biological networks will be investigated and applied to several high-throughput biological datasets of different nature and with different tasks in oncogenomics,
neurogenomics and exposomics
Localization and spreading of matter waves in disordered potentials
Get PDFIn this thesis we address relevant problems of the physics of quantum disordered systems from a numerical and theoretical point of view, with specific attention to the connection of our findings with ultracold atomic gases experiments. We concentrate on two main issues: the interplay between localization and interaction in disordered systems and the problem of localization in correlated random potentials.
The first problem is investigated considering the expansion of a weakly interacting Bose gas in a bichromtic optical lattice. We observe that interaction has a destructive effect on the disorder-induced localization and leads to a subdiffusive expansion of the atomic gas. By comparing three characteristic energy scales of the system one can identify three different spreading regimes: weak chaos, strong chaos and self-trapping. The spreading behaviour in these regimes is predicted theoretically and verified numerically. We also interpreted existing experimental data on the basis of our findings and showed that there is a qualitative agreement between our numerical simulations and experiments.
The second problem is investigated proposing a new model of correlated disorder that can be implemented experimentally using ultracold dipolar gases. We show that this model is characterized by the presence of both short and long range correlations. We study the localization properties of the model and highlight the role played by short and long range correlations in the determination of those properties. In particular we show that when short-range correlations are dominant, extended states can appear in the spectrum. The effect of long-range correlations is instead to restore localization over the whole spectrum and lead to counterintuitive behaviours of the localization length. More precisely, depending on the localization regime they can enhance or reduce the localization length at the centre of the band
Disuguaglianze sociali nella salute, tra eterogeneità individuale e fattori sociali di rischio
Get PDFIn the first two chapters of this thesis I review the literature concerning health and obesity (indexed by the Body Mass Index, henceforth BMI) drawing on readings from sociology, epidemiology, economics and behavioral genetics. In particular, I focus on two issues: the socio-economic determinants of health and BMI and the socio-economic gradient in health and BMI, trying to integrate the standard sociological approach with findings from behavior genetics.
The third is a methodological chapter in which I describe the data and the model I use in the following chapters. As far as the data, I use both cross sectional (the Multiscopo “Aspetti della vita Quotidiana”, ISTAT and twins data coming from the “Italian Twin Registry”) and panel data (the European Community Household Panel).
In the fourth chapter I use behavioral genetics model and multilevel model in order to estimate the heritability of health status/BMI. More precisely, I try to understand which proportion of the observed inter-individual variation in health/BMI can be attributed to unique environmental factors (E), common environmental factors (C) or genetic factors (A). Then I run a Cholesky decomposition model in order to understand whether the observed covariance between education and BMI is due to common genetic/environmental factors. I find out that bivariate heritability is 0.30, meaning that around 30% of the observed covariance between these two trait is due to common genetic factors. Since genetic factors are, by definition, prior to both education and BMI this result prompts us to rethink the usual interpretation of the relationship between education and BMI as a causal one.
In the final chapter I used ECHP data in order to study the socio-economic gradient in health/BMI and to understand whether the effect of socio-economic factors on health/BMI varies over the life course or across cohorts. I first apply growth curves models, a special case of multilevel model for change, that enable us to model individual health trajectories in health and BMI. More precisely, I model the differences in these trajectories (i.e. in both their intercepts and slopes) as a function of a set of explanatory variables (income and education) and other covariates (wave, age, cohort, gender, area of residence). I then compare the results obtained from growth curves (that are random effect models) with the ones from fixed effects models. The main problem of sociological studies that aim to estimate causal effects is the problem of unobserved heterogeneity. Standard sociological models assumed the predictor to be uncorrelated with the error term. However when we study health this assumption may not hold: we know that there are different unobserved or unobservable factors (genetic or psychosocial characteristic like different time preferences or risk aversion) that may affect both an individual’s socio-economic status and his/her health, creating a correlation between the predictor and the error term. Through a process of “time demeaning the data”, the fixed effect model is able to control for time constant individual heterogeneity and to correctly estimate the effect of individual income that varies over time. With this kind of model the effect of annual income is no more significantly related to health/BMI. However, with fixed effects models we can no longer estimate the effect of time constant variables like gender and education –very interesting from a sociological point of view- that do not vary over time (and, hence, are cancelling out from the equation in the process of time demeaning the data). For my analysis I used the software Stata 11 and SPSS (AMOS)
Bone Tissue Engineering: structures and strategies for functional scaffold design and evaluation
No full textSkeletal tissue has a good ability to self-regenerate after injury through the processes of bone healing. However, bone can suffer from a wide range of pathologies, cancers or congenital defects which lead to loss of bone mass and density.
Current progresses in tissue engineering have shown great potential for creating biological alternatives and new perspectives for the treatment of bone damage and defects. In this approach, scaffolding plays a pivotal role. In particular, the principles of biomimesis have to be followed and the scaffolds have to be designed to this purpose. Furthermore, these tissue engineered systems have not only to support and guide the new tissue formation, but they have to induce a complete tissue functionality.
The aim of this research work was the application of these advanced principles to produce and evaluate scaffolds for bone regeneration.
Starting from the idea to mimic the extracellular matrix (ECM), template that characterizes the early step of the bone healing process, we design scaffolds for the evaluation of biological outputs considering the initial ECM produced by cells.
We used two polymers, naturally (silk fibroin) or synthetically (poly-d,l-lactic acid) derived, and we modulated scaffold geometry (random vs ordered pore distribution), pore size and chemical composition, combining spongy and fibrous structures.
The scaffolds were indeed considered as models, to investigate if they control cell production of type I collagen, principle component of the natural template for the final mineralization. Moreover, due to the key role of vessel formation in tissue engineering and the correlation between osteoblasts and endothelial cells, the influence of the scaffolds on angiogenesis and vascularisation was assessed.
The innovation of this study consists in the evaluation shift from the final healing stage to the earlier stages. In fact, the results emphasize the possibility to correlate the scaffold morphology to type I collagen assembly, which in turn affects the final mineralization process, allowing to evaluate the tissue produced by osteoblasts from the first steps of bone formation. Moreover, we were able to control some cell behaviours changing construct properties.
In a future research, a segmental bone defect models should be considered to better characterize the role of scaffold features during bone healing process and to determine if it would be better to use scaffolds which favour angiogenesis or mineralization to speed up a physiological bone regeneration process
Energy Efficiency in Wireless Access Networks: Measurements, Models and Algorithms
No full textWireless Telecommunication networks have become fundamental to daily activities. Today, people have access to at least one type of wireless telecommunication network. In this context, optimizing the energy consumption of wireless telecommunications infrastructure has become a new challenge for the research community, governments and industries in order to reduce CO2 emission and operational energy costs. This thesis investigates the power consumption of indoor/outdoor Wireless Access Devices (WADs, specifically WiFi and WiMAX access points) and provides novel techniques for improving the energy efficiency of wireless access networks. Our approach focuses on monitoring and analyzing the power consumption of WADs using real-testbed and experimental measurements in order to understand the fundamental limits and trade-offs involved. This, in turn, will be used to propose efficient techniques to reduce power consumption and to maximize the energy efficiency of wireless access networks. We introduce energino a novel hardware and software solution for real-time energy consumption monitoring in wireless networks. We also propose an experimentally-driven approach to (i) characterize typical WADs from a power consumption standpoint, (ii) develop simple and accurate power consumption models and metrics for such WADs, and (iii) design techniques to tune the power consumption of a wireless infrastructure to the actual network conditions in terms of both users density and traffic patterns. Our measurements from several real-life deployments show that (a) the power consumption of such WADs exhibits a linear dependence on the traffic until a saturation point is reached and (b) the developed techniques can deliver significant energy savings with minimal degradation in terms of the quality of service provided
Walter Benjamins Konzept des Eingedenkens: Über Genese, Stellung und Bedeutung eines ungebräuchlichen Begriffs in Benjamins Schriften.
No full textSi tratta di un'indagine approfondita circa il concetto di "Eingedenken" che Walter Benjamin utilizza nei suoi scritti dal 1927 fino alla morte (nel 1940)
Competitive Robotic Car: Sensing, Planning and Architecture Design
No full textResearch towards a complete autonomous car has been pushed through by industries as it offers numerous advantages such as the improvement to traffic flow, vehicle and pedestrian safety, and car efficiency. One of the main challenges faced in this area is how to deal with different uncertainties perceived by the sensors on the current state of the car and the environment. An autonomous car needs to employ efficient planning algorithm that generates the vehicle trajectory based on the environmental sensing implemented in real-time. An complete motion planning algorithm is an algorithm that returns a valid solution if one exist in finite time and returns no path exist when none exist. The algorithm is optimal when it returns an optimal path based on some criteria. In this thesis we work on a special case of motion planning problem: to find an optimal trajectory for a robotic car in order to win a car race. We propose an efficient realtime vision based technique for localization and path reconstruction. For our purpose of winning a car race we identify a characterization of the alphabet of optimal maneuvers for the car, an optimal local planning strategy and an optimal graph-based global planning strategy with obstacle avoidance. We have also implemented the hardware and software of this approach on as a testbed of the planning strategy
The Legal Status of Roma in Europe: between National Minority and Transnational People
Get PDFRecent estimates from the Council of Europe (CoE), rates Romani presence in Europe around 10-12 million individuals. In an imaginary Europe without geo-political borders, these estimates raise Romani population to the 9th most populous community, immediately after Belgians.
Notwithstanding their numerical proportion and their historical presence in Europe, both international and national legal instruments designed for minorities are currently unable to comprehensively protect and promote Roma rights. Because of their diffuse and still partially nomadic presence, the existing legal instruments are inappropriate to effectively accommodate Romani needs because they are still ensuing from a Westphalian paradigm which identifies one people in relation with a precise territorial area.
Indeed, these legal instruments either apply to social groups traditionally resident in a country (“old” minorities) or to migrants (“new” minorities) but cannot apply to Roma who on the one hand are traditionally living in Europe (as “old” minorities) and on the other hand are still moving from one country to the other (as “new” minorities).
This study investigates the possibility of identifying a minimum European set of rights for Roma by means of two complementary conceptual frameworks. The first comparatively identifies best legal practices at the national levels, whereas the second, taking into account the specific distinctive features of Roma compared to other groups, proposes the adaptation of international legal instruments designed for indigenous people to Roma as a ‘European transnational people’.
In its comparative part, this study analyzes the legal protection of Roma in terms of, linguistic, social-economic and cultural rights as well as in terms of political representation. The proposal for adapting indigenous peoples’ rights draws from the case of Sami in Northern Scandinavia as the only example of a European indigenous people living transnationally in Europe.
The results of this study contribute, both theoretically and practically, to the scientific debate on the protection of non-territorial minorities and of indigenous people in Europe