Generating Discriminative Objective Proposals via Submodular Ranking

Object recognition has long been a core problem in computer vision. To improve object spatial support and speed up object localization for object recognition, generating high-quality category-independent object proposals as the input for object recognition system has drawn attention recently. Given an image, we generate a limited number of high-quality and category-independent object proposals in advance and used as inputs for many computer vision tasks. We present an efficient dictionary-based model for image classification task. We further extend the work to a discriminative dictionary learning method for tensor sparse coding. In the first part, a multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a single-scale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the single-scale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentation and detection and outperform the state-of-art performance. To classify the object in the image, we design a discriminative, structural low-rank framework for image classification. We use a supervised learning method to construct a discriminative and reconstructive dictionary. By introducing an ideal regularization term, we perform low-rank matrix recovery for contaminated training data from all categories simultaneously without losing structural information. A discriminative low-rank representation for images with respect to the constructed dictionary is obtained. With semantic structure information and strong identification capability, this representation is good for classification tasks even using a simple linear multi-classifier.

OBSERVATIONS AND EMISSIONS OF ENERGY-ASSOCIATED OZONE PRECURSORS IN THE MID-ATLANTIC UNITED STATES

Surface ozone is formed in the presence of NOx (NO + NO2) and volatile organic compounds (VOCs) and is hazardous to human health. A better understanding of these precursors is needed for developing effective policies to improve air quality. To evaluate the year-to-year changes in source contributions to total VOCs, Positive Matrix Factorization (PMF) was used to perform source apportionment using available hourly observations from June through August at a Photochemical Assessment Monitoring Station (PAMS) in Essex, MD for each year from 2007-2015. Results suggest that while gasoline and vehicle exhaust emissions have fallen, the contribution of natural gas sources to total VOCs has risen. To investigate this increasing natural gas influence, ethane measurements from PAMS sites in Essex, MD and Washington, D.C. were examined. Following a period of decline, daytime ethane concentrations have increased significantly after 2009. This trend appears to be linked with the rapid shale gas production in upwind, neighboring states, especially Pennsylvania and West Virginia. Back-trajectory analyses similarly show that ethane concentrations at these monitors were significantly greater if air parcels had passed through counties containing a high density of unconventional natural gas wells. In addition to VOC emissions, the compressors and engines involved with hydraulic fracturing operations also emit NOx and particulate matter (PM). The Community Multi-scale Air Quality (CMAQ) Model was used to simulate air quality for the Eastern U.S. in 2020, including emissions from shale gas operations in the Appalachian Basin. Predicted concentrations of ozone and PM show the largest decreases when these natural gas resources are hypothetically used to convert coal-fired power plants, despite the increased emissions from hydraulic fracturing operations expanded into all possible shale regions in the Appalachian Basin. While not as clean as burning natural gas, emissions of NOx from coal-fired power plants can be reduced by utilizing post-combustion controls. However, even though capital investment has already been made, these controls are not always operated at optimal rates. CMAQ simulations for the Eastern U.S. in 2018 show ozone concentrations decrease by ~5 ppb when controls on coal-fired power plants limit NOx emissions to historically best rates.

Morphological traits of surveillant/activated microglia during an experimentally induced acute neuroinflammatory process

Several studies show that morphological changes of microglia over the course of inflammation are tightly coupled to function. However the progressive transformation into activated microglia is poorly characterized. AIMS: This study aimed to establish a spatiotemporal correlation between quantifiable morphological parameters of microglia and the spread of an acute ventricular inflammatory process. METHODS: Inflammation was induced by a single injection of the enzyme neuraminidase within the lateral ventricle of rats. Animals were sacrificed 2, 4 and 12 hours after injection. Coronal slices were immunostained with Iba1 to label microglia and with IL1β to delimit the spread of inflammation. Digital images were obtained by scanning the labelled sections. Single microglia images were randomly selected from periventricular areas of caudate putamen, hippocampus and hypothalamus. FracLac for ImageJ software was used to measure the following morphological parameters: fractal dimension, lacunarity, area, perimeter and density. RESULTS: Significant differences were found in fractal dimension, lacunarity, perimeter and density of microglia cells of neuraminidase injected rats compared to sham animals. However no differences were found in the parameter “area”. In hipoccampus there was a delay in the significant change of the measured parameters. These morphological changes correlated with IL1β-expression in the same areas. CONCLUSIONS: Ventricular inflammation induced by neuraminidase provokes quantifiable morphological changes in microglia restricted to areas labelled with IL1β. Morphological parameters of microglia such as fractal dimension, lacunarity, perimeter and density are sensitive and valuable tools to quantify activation. However, the extensively used parameter “area” did not change upon microglia activation.

Os fractais no urbanismo

Dissertação para obtenção do grau de Mestre em Arquitectura com Especialização em Urbanismo, apresentada na Universidade de Lisboa - Faculdade de Arquitectura.

Simulação de fluxo de fluidos em meios porosos desordenados uma análise de efeito de escala na estimativa da permeabilidade e do coeficiente de arrasto

The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study.

Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities.

Theoretical investigation of intra- and inter-cellular spatiotemporal calcium patterns in microcirculation

Microcirculatory vessels are lined by endothelial cells (ECs) which are surrounded by a single or multiple layer of smooth muscle cells (SMCs). Spontaneous and agonist induced spatiotemporal calcium (Ca2+) events are generated in ECs and SMCs, and regulated by complex bi-directional signaling between the two layers which ultimately determines the vessel tone. The contractile state of microcirculatory vessels is an important factor in the determination of vascular resistance, blood flow and blood pressure. This dissertation presents theoretical insights into some of the important and currently unresolved phenomena in microvascular tone regulation. Compartmental and continuum models of isolated EC and SMC, coupled EC-SMC and a multi-cellular vessel segment with deterministic and stochastic descriptions of the cellular components were developed, and the intra- and inter-cellular spatiotemporal Ca2+ mobilization was examined.^ Coupled EC-SMC model simulations captured the experimentally observed localized subcellular EC Ca2+ events arising from the opening of EC transient receptor vanilloid 4 (TRPV4) channels and inositol triphosphate receptors (IP3Rs). These localized EC Ca2+ events result in endothelium-derived hyperpolarization (EDH) and Nitric Oxide (NO) production which transmit to the adjacent SMCs to ultimately result in vasodilation. The model examined the effect of heterogeneous distribution of cellular components and channel gating kinetics in determination of the amplitude and spread of the Ca2+ events. The simulations suggested the necessity of co-localization of certain cellular components for modulation of EDH and NO responses. Isolated EC and SMC models captured intracellular Ca2+ wave like activity and predicted the necessity of non-uniform distribution of cellular components for the generation of Ca2+ waves. The simulations also suggested the role of membrane potential dynamics in regulating Ca2+ wave velocity. The multi-cellular vessel segment model examined the underlying mechanisms for the intercellular synchronization of spontaneous oscillatory Ca2+ waves in individual SMC. ^ From local subcellular events to integrated macro-scale behavior at the vessel level, the developed multi-scale models captured basic features of vascular Ca2+ signaling and provide insights for their physiological relevance. The models provide a theoretical framework for assisting investigations on the regulation of vascular tone in health and disease.^

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

Análise não linear de séries temporais e aplicações à Psicologia

Nesta dissertação estudámos as séries temporais que representam a complexa dinâmica do comportamento. Demos especial atenção às técnicas de dinâmica não linear. As técnicas fornecem-nos uma quantidade de índices quantitativos que servem para descrever as propriedades dinâmicas do sistema. Estes índices têm sido intensivamente usados nos últimos anos em aplicações práticas em Psicologia. Estudámos alguns conceitos básicos de dinâmica não linear, as características dos sistemas caóticos e algumas grandezas que caracterizam os sistemas dinâmicos, que incluem a dimensão fractal, que indica a complexidade de informação contida na série temporal, os expoentes de Lyapunov, que indicam a taxa com que pontos arbitrariamente próximos no espaço de fases da representação do espaço dinâmico, divergem ao longo do tempo, ou a entropia aproximada, que mede o grau de imprevisibilidade de uma série temporal. Esta informação pode então ser usada para compreender, e possivelmente prever, o comportamento. ABSTRACT: ln this thesis we studied the time series that represent the complex dynamic behavior. We focused on techniques of nonlinear dynamics. The techniques provide us a number of quantitative indices used to describe the dynamic properties of the system. These indices have been extensively used in recent years in practical applications in psychology. We studied some basic concepts of nonlinear dynamics, the characteristics of chaotic systems and some quantities that characterize the dynamic systems, including fractal dimension, indicating the complexity of information in the series, the Lyapunov exponents, which indicate the rate at that arbitrarily dose points in phase space representation of a dynamic, vary over time, or the approximate entropy, which measures the degree of unpredictability of a series. This information can then be used to understand and possibly predict the behavior.

Improving multivariate data streams clustering.

Clustering data streams is an important task in data mining research. Recently, some algorithms have been proposed to cluster data streams as a whole, but just few of them deal with multivariate data streams. Even so, these algorithms merely aggregate the attributes without touching upon the correlation among them. In order to overcome this issue, we propose a new framework to cluster multivariate data streams based on their evolving behavior over time, exploring the correlations among their attributes by computing the fractal dimension. Experimental results with climate data streams show that the clusters' quality and compactness can be improved compared to the competing method, leading to the thoughtfulness that attributes correlations cannot be put aside. In fact, the clusters' compactness are 7 to 25 times better using our method. Our framework also proves to be an useful tool to assist meteorologists in understanding the climate behavior along a period of time.

Statistical Analysis and Modelling Aspects of Thermally Driven Turbulence

The present work aims to provide a deeper understanding of thermally driven turbulence and to address some modelling aspects related to the physics of the flow. For this purpose, two idealized systems are investigated by Direct Numerical Simulation: the rotating and non-rotating Rayleigh-Bénard convection. The preliminary study of the flow topologies shows how the coherent structures organise into different patterns depending on the rotation rate. From a statistical perspective, the analysis of the turbulent kinetic energy and temperature variance budgets allows to identify the flow regions where the production, the transport, and the dissipation of turbulent fluctuations occur. To provide a multi-scale description of the flows, a theoretical framework based on the Kolmogorov and Yaglom equations is applied for the first time to the Rayleigh-Bénard convection. The analysis shows how the spatial inhomogeneity modulates the dynamics at different scales and wall-distances. Inside the core of the flow, the space of scales can be divided into an inhomogeneity-dominated range at large scales, an inertial-like range at intermediate scales and a dissipative range at small scales. This classic scenario breaks close to the walls, where the inhomogeneous mechanisms and the viscous/diffusive processes are important at every scale and entail more complex dynamics. The same theoretical framework is extended to the filtered velocity and temperature fields of non-rotating Rayleigh-Bénard convection. The analysis of the filtered Kolmogorov and Yaglom equations reveals the influence of the residual scales on the filtered dynamics both in physical and scale space, highlighting the effect of the relative position between the filter length and the crossover that separates the inhomogeneity-dominated range from the quasi-homogeneous range. The assessment of the filtered and residual physics results to be instrumental for the correct use of the existing Large-Eddy Simulation models and for the development of new ones.

Un approccio multiscala alle dinamiche fluviali di alvei montani

Questo lavoro di tesi è finalizzato allo studio delle morfodinamiche fluviali in ambiente montano, in risposta a forzanti antropiche e naturali. In particolare, si prendono in considerazione sistemi Appenninici (i.e., Fiume Santerno) e Alpini (i.e., Rii Grigno, Tolvà e Ussaia), integrando due approcci che si sviluppano su scale spazio-temporali differenti. Nel caso Appenninico vengono esaminati i cambiamenti planimetrici dell’alveo attivo del Fiume Santerno in risposta ad impatti antropici, quali l’estrazione di inerti in alveo, la costruzione di opere idrauliche e l’alterazione di uso del suolo a scala di bacino. Nei tre casi Alpini, che si differenziano in termini di forzante idro-meteorologica ed apporto di sedimento da monte, si è valutato il trasporto solido di fondo (bedload transport) mediante tecnologia RFID.

Characterization of microplastics ingested by marine benthos - a methodological and field-experimental study

Microplastics have become ubiquitous pollutants in the marine environment. Ingestion of microplastics by a wide range of marine organisms has been recorded both in laboratory and field studies. Despite growing concern for microplastics, few studies have evaluated their concentrations and distribution in wild populations. Further, there is a need to identify cost-effective standardized methodologies for microplastics extraction and analysis in organisms. In this thesis I present: (i) the results of a multi-scale field sampling to quantify and characterize microplastics occurrence and distribution in 4 benthic marine invertebrates from saltmarshes along the North Adriatic Italian coastal lagoons; (ii) a comparison of the effects and cost-effectiveness of two extraction protocols for microplastics isolation on microfibers and on wild collected organisms; (iii) the development of a novel field- based technique to quantify and characterize the microplastic uptake rates of wild and farmed populations of mussels (Mytilus galloprovincialis) through the analysis of their biodeposits. I found very low and patchy amounts of microplastics in the gastrointestinal tracts of sampled organisms. The omnivorous crab Carcinus aestuarii was the species with the highest amounts of microplastics, but there was a notable variation among individuals. There were no substantial differences between enzymatic and alkaline extraction methods. However, the alkaline extraction was quicker and cheaper. Biodeposit traps proved to be an effective method to estimate mussel ingestion rates. However their performance differed significantly among sites, suggesting that the method, as currently designed, is sensible to local environmental conditions. There were no differences in the ingestion rates of microplastics between farmed and wild mussels. The estimates of microplastic ingestion and the validated procedures for their extraction provide a strong basis for future work on microplastic pollution.

Landslide susceptibility in the Belt and Road Initiative

The Belt and Road Initiative (BRI) is a project launched by the Chinese Government whose main goal is to connect more than 65 countries in Asia, Europe, Africa and Oceania developing infrastructures and facilities. To support the prevention or mitigation of landslide hazards, which may affect the mainland infrastructures of BRI, a landslide susceptibility analysis in the countries involved has been carried out. Due to the large study area, the analysis has been carried out using a multi-scale approach which consists of mapping susceptibility firstly at continental scale, and then at national scale. The study area selected for the continental assessment is the south-Asia, where a pixel-based landslide susceptibility map has been carried out using the Weight of Evidence method and validated by Receiving Operating Characteristic (ROC) curves. Then, we selected the regions of west Tajikistan and north-east India to be investigated at national scale. Data scarcity is a common condition for many countries involved into the Initiative. Therefore in addition to the landslide susceptibility assessment of west Tajikistan, which has been conducted using a Generalized Additive Model and validated by ROC curves, we have examined, in the same study area, the effect of incomplete landslide dataset on the prediction capacity of statistical models. The entire PhD research activity has been conducted using only open data and open-source software. In this context, to support the analysis of the last years an open-source plugin for QGIS has been implemented. The SZ-tool allows the user to make susceptibility assessments from the data preprocessing, susceptibility mapping, to the final classification. All the output data of the analysis conducted are freely available and downloadable. This text describes the research activity of the last three years. Each chapter reports the text of the articles published in international scientific journal during the PhD.

Oceanic Near-inertial internal waves generation, propagation and interaction with mesoscale dynamics

Oceans play a key role in the climate system, being the largest heat sinks on Earth. Part of the energy balance of ocean circulation is driven by the Near-inertial internal waves (NIWs). Strong NIWs are observed during a multi-platform, multi-disciplinary and multi-scale campaign led by the NATO-STO CMRE in autumn 2017 in the Ligurian Sea (northwestern Mediterranean Sea). The objectives of this work are as follows: characterise the studied area at different scales; study the NIWs generation and their propagation; estimate the NIWs properties; study the interaction between NIWs and mesoscale structures. This work provides, to the author’s knowledge, the first characterization of NIWs in the Mediterranean Sea. The near-surface NIWs observed at the fixed moorings are locally generated by wind bursts while the deeper waves originate in other regions and arrive at the moorings several days later. Most of the observed NIWs energy propagates downward with a mean vertical group velocity of (2.2±0.3) ⋅10-4 m s-1. On average, the NIWs have an amplitude of 0.13 m s-1 and mean horizontal and vertical wavelengths of 43±25 km and 125±35 m, while shorter wavelengths are observed at the near-coastal mooring, 36±2 km and 33±2 m, respectively. Most of the observed NIWs are blue shifted and reach a value 9% higher than the local inertial frequency. Only two observed NIWs are characterised by a redshift (up to 3% lower than the local inertial frequency). In support of the in situ observations, a high resolution numerical model is implemented using NEMO (Madec et al., 2019). Results show that anticyclones (cyclones) shift the frequency of NIWs to lower (higher) frequencies with respect to the local inertial frequency. Anticyclones facilitate the downward propagation of NIW energy, while cyclones dampen it. Absence of NIWs energy within an anticyclone is also investigated.