Ground-level ozone prediction using a neural network model based on meteorological variables and applied to the metropolitan area of Sao Paulo

A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was developed, based on average values of meteorological variables in the morning (8:00-12:00 hr) and afternoon (13:00-17: 00 hr) periods. Outputs are the maximum and average ozone concentrations in the afternoon (12:00-17:00 hr). The correlation coefficient between computed and measured values was 0.82 and 0.88 for the maximum and average ozone concentration, respectively. The model presented good performance as a prediction tool for the maximum ozone concentration. For prediction periods from 1 to 5 days 0 to 23% failures (95% confidence) were obtained.

A general class of zero-or-one inflated beta regression models

This paper proposes a general class of regression models for continuous proportions when the data contain zeros or ones. The proposed class of models assumes that the response variable has a mixed continuous-discrete distribution with probability mass at zero or one. The beta distribution is used to describe the continuous component of the model, since its density has a wide range of different shapes depending on the values of the two parameters that index the distribution. We use a suitable parameterization of the beta law in terms of its mean and a precision parameter. The parameters of the mixture distribution are modeled as functions of regression parameters. We provide inference, diagnostic, and model selection tools for this class of models. A practical application that employs real data is presented. (C) 2011 Elsevier B.V. All rights reserved.

Local power and size properties of the LR, Wald, score and gradient tests in dispersion models

We derive asymptotic expansions for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of dispersion models, under a sequence of Pitman alternatives. The asymptotic distributions of these statistics are obtained for testing a subset of regression parameters and for testing the precision parameter. Based on these nonnull asymptotic expansions, the power of all four tests, which are equivalent to first order, are compared. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2012 Elsevier B.V. All rights reserved.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Mechanics and dynamics of liposomes and cells studied by QCM and ECIS

The present thesis introduces a novel sensitive technique based on TSM resonators that provides quantitative information about the dynamic properties of biological cells and artificial lipid systems. In order to support and complement results obtained by this method supplementary measurements based on ECIS technique were carried out. The first part (chapters 3 and 4) deals with artificial lipid systems. In chapter 3 ECIS measurements were used to monitor the adsorption of giant unilamellar vesicles as well as their thermal fluctuations. From dynamic Monte Carlo Simulations the rate constant of vesicle adsorption was determined. Furthermore, analysis of fluctuation measurements reveals Brownian motion reflecting membrane undulations of the adherent liposomes. In chapter 4 QCM-based fluctuation measurements were applied to quantify nanoscopically small deformations of giant unilamellar vesicles with an external electrical field applied simultaneously. The response of liposomes to an external voltage with shape changes was monitored as a function of cholesterol content and adhesion force. In the second part (chapters 5 - 8) attention was given to cell motility. It was shown for the first time, that QCM can be applied to monitor the dynamics of living adherent cells in real time. QCM turned out to be a highly sensitive tool to detect the vertical motility of adherent cells with a time resolution in the millisecond regime. The response of cells to environmental changes such as temperature or osmotic stress could be quantified. Furthermore, the impact of cytochalasin D (inhibits actin polymerization) and taxol (facilitate polymerization of microtubules) as well as nocodazole (depolymerizes microtubules) on the dynamic properties of cells was scrutinized. Each drug provoked a significant reduction of the monitored cell shape fluctuations as expected from their biochemical potential. However, not only the abolition of fluctuations was observed but also an increase of motility due to integrin-induced transmembrane signals. These signals were activated by peptides containing the RGD sequence, which is known to be an integrin recognition motif. Ultimately, two pancreatic carcinoma cell lines, derived from the same original tumor, but known to possess different metastatic potential were studied. Different dynamic behavior of the two cell lines was observed which was attributed to cell-cell as well as cell-substrate interactions rather than motility. Thus one may envision that it might be possible to characterize the motility of different cell types as a function of many variables by this new highly sensitive technique based on TSM resonators. Finally the origin of the broad cell resonance was investigated. Improvement of the time resolution reveals the "real" frequency of cell shape fluctuations. Several broad resonances around 3-5 Hz, 15-17 Hz and 25-29 Hz were observed and that could unequivocally be assigned to biological activity of living cells. However, the kind of biological process that provokes this synchronized collective and periodic behavior of the cells remains to be elucidated.

Analysis of optimal control problems for the incompressible MHD equations and implementation in a finite element multiphysics code

This thesis deals with the study of optimal control problems for the incompressible Magnetohydrodynamics (MHD) equations. Particular attention to these problems arises from several applications in science and engineering, such as fission nuclear reactors with liquid metal coolant and aluminum casting in metallurgy. In such applications it is of great interest to achieve the control on the fluid state variables through the action of the magnetic Lorentz force. In this thesis we investigate a class of boundary optimal control problems, in which the flow is controlled through the boundary conditions of the magnetic field. Due to their complexity, these problems present various challenges in the definition of an adequate solution approach, both from a theoretical and from a computational point of view. In this thesis we propose a new boundary control approach, based on lifting functions of the boundary conditions, which yields both theoretical and numerical advantages. With the introduction of lifting functions, boundary control problems can be formulated as extended distributed problems. We consider a systematic mathematical formulation of these problems in terms of the minimization of a cost functional constrained by the MHD equations. The existence of a solution to the flow equations and to the optimal control problem are shown. The Lagrange multiplier technique is used to derive an optimality system from which candidate solutions for the control problem can be obtained. In order to achieve the numerical solution of this system, a finite element approximation is considered for the discretization together with an appropriate gradient-type algorithm. A finite element object-oriented library has been developed to obtain a parallel and multigrid computational implementation of the optimality system based on a multiphysics approach. Numerical results of two- and three-dimensional computations show that a possible minimum for the control problem can be computed in a robust and accurate manner.

Hardware/Software Design of Dynamic Real-Time Schedulers for Embedded Multiprocessor Systems

The new generation of multicore processors opens new perspectives for the design of embedded systems. Multiprocessing, however, poses new challenges to the scheduling of real-time applications, in which the ever-increasing computational demands are constantly flanked by the need of meeting critical time constraints. Many research works have contributed to this field introducing new advanced scheduling algorithms. However, despite many of these works have solidly demonstrated their effectiveness, the actual support for multiprocessor real-time scheduling offered by current operating systems is still very limited. This dissertation deals with implementative aspects of real-time schedulers in modern embedded multiprocessor systems. The first contribution is represented by an open-source scheduling framework, which is capable of realizing complex multiprocessor scheduling policies, such as G-EDF, on conventional operating systems exploiting only their native scheduler from user-space. A set of experimental evaluations compare the proposed solution to other research projects that pursue the same goals by means of kernel modifications, highlighting comparable scheduling performances. The principles that underpin the operation of the framework, originally designed for symmetric multiprocessors, have been further extended first to asymmetric ones, which are subjected to major restrictions such as the lack of support for task migrations, and later to re-programmable hardware architectures (FPGAs). In the latter case, this work introduces a scheduling accelerator, which offloads most of the scheduling operations to the hardware and exhibits extremely low scheduling jitter. The realization of a portable scheduling framework presented many interesting software challenges. One of these has been represented by timekeeping. In this regard, a further contribution is represented by a novel data structure, called addressable binary heap (ABH). Such ABH, which is conceptually a pointer-based implementation of a binary heap, shows very interesting average and worst-case performances when addressing the problem of tick-less timekeeping of high-resolution timers.

Microarray based real-time analysis of nucleic acid hybridization kinetics and thermodynamics

Ziel dieser Dissertation ist die experimentelle Charakterisierung und quantitative Beschreibung der Hybridisierung von komplementären Nukleinsäuresträngen mit oberflächengebundenen Fängermolekülen für die Entwicklung von integrierten Biosensoren. Im Gegensatz zu lösungsbasierten Verfahren ist mit Microarray Substraten die Untersuchung vieler Nukleinsäurekombinationen parallel möglich. Als biologisch relevantes Evaluierungssystem wurde das in Eukaryoten universell exprimierte Actin Gen aus unterschiedlichen Pflanzenspezies verwendet. Dieses Testsystem ermöglicht es, nahe verwandte Pflanzenarten auf Grund von geringen Unterschieden in der Gen-Sequenz (SNPs) zu charakterisieren. Aufbauend auf dieses gut studierte Modell eines House-Keeping Genes wurde ein umfassendes Microarray System, bestehend aus kurzen und langen Oligonukleotiden (mit eingebauten LNA-Molekülen), cDNAs sowie DNA und RNA Targets realisiert. Damit konnte ein für online Messung optimiertes Testsystem mit hohen Signalstärken entwickelt werden. Basierend auf den Ergebnissen wurde der gesamte Signalpfad von Nukleinsärekonzentration bis zum digitalen Wert modelliert. Die aus der Entwicklung und den Experimenten gewonnen Erkenntnisse über die Kinetik und Thermodynamik von Hybridisierung sind in drei Publikationen zusammengefasst die das Rückgrat dieser Dissertation bilden. Die erste Publikation beschreibt die Verbesserung der Reproduzierbarkeit und Spezifizität von Microarray Ergebnissen durch online Messung von Kinetik und Thermodynamik gegenüber endpunktbasierten Messungen mit Standard Microarrays. Für die Auswertung der riesigen Datenmengen wurden zwei Algorithmen entwickelt, eine reaktionskinetische Modellierung der Isothermen und ein auf der Fermi-Dirac Statistik beruhende Beschreibung des Schmelzüberganges. Diese Algorithmen werden in der zweiten Publikation beschrieben. Durch die Realisierung von gleichen Sequenzen in den chemisch unterschiedlichen Nukleinsäuren (DNA, RNA und LNA) ist es möglich, definierte Unterschiede in der Konformation des Riboserings und der C5-Methylgruppe der Pyrimidine zu untersuchen. Die kompetitive Wechselwirkung dieser unterschiedlichen Nukleinsäuren gleicher Sequenz und die Auswirkungen auf Kinetik und Thermodynamik ist das Thema der dritten Publikation. Neben der molekularbiologischen und technologischen Entwicklung im Bereich der Sensorik von Hybridisierungsreaktionen oberflächengebundener Nukleinsäuremolekülen, der automatisierten Auswertung und Modellierung der anfallenden Datenmengen und der damit verbundenen besseren quantitativen Beschreibung von Kinetik und Thermodynamik dieser Reaktionen tragen die Ergebnisse zum besseren Verständnis der physikalisch-chemischen Struktur des elementarsten biologischen Moleküls und seiner nach wie vor nicht vollständig verstandenen Spezifizität bei.

Classificazione di oggetti in immagini attraverso il modello Bag of Visual Words

Generic object recognition is an important function of the human visual system and everybody finds it highly useful in their everyday life. For an artificial vision system it is a really hard, complex and challenging task because instances of the same object category can generate very different images, depending of different variables such as illumination conditions, the pose of an object, the viewpoint of the camera, partial occlusions, and unrelated background clutter. The purpose of this thesis is to develop a system that is able to classify objects in 2D images based on the context, and identify to which category the object belongs to. Given an image, the system can classify it and decide the correct categorie of the object. Furthermore the objective of this thesis is also to test the performance and the precision of different supervised Machine Learning algorithms in this specific task of object image categorization. Through different experiments the implemented application reveals good categorization performances despite the difficulty of the problem. However this project is open to future improvement; it is possible to implement new algorithms that has not been invented yet or using other techniques to extract features to make the system more reliable. This application can be installed inside an embedded system and after trained (performed outside the system), so it can become able to classify objects in a real-time. The information given from a 3D stereocamera, developed inside the department of Computer Engineering of the University of Bologna, can be used to improve the accuracy of the classification task. The idea is to segment a single object in a scene using the depth given from a stereocamera and in this way make the classification more accurate.

Displacement Analysis of Under-Constrained Cable-Driven Parallel Robots

This dissertation studies the geometric static problem of under-constrained cable-driven parallel robots (CDPRs) supported by n cables, with n ≤ 6. The task consists of determining the overall robot configuration when a set of n variables is assigned. When variables relating to the platform posture are assigned, an inverse geometric static problem (IGP) must be solved; whereas, when cable lengths are given, a direct geometric static problem (DGP) must be considered. Both problems are challenging, as the robot continues to preserve some degrees of freedom even after n variables are assigned, with the final configuration determined by the applied forces. Hence, kinematics and statics are coupled and must be resolved simultaneously. In this dissertation, a general methodology is presented for modelling the aforementioned scenario with a set of algebraic equations. An elimination procedure is provided, aimed at solving the governing equations analytically and obtaining a least-degree univariate polynomial in the corresponding ideal for any value of n. Although an analytical procedure based on elimination is important from a mathematical point of view, providing an upper bound on the number of solutions in the complex field, it is not practical to compute these solutions as it would be very time-consuming. Thus, for the efficient computation of the solution set, a numerical procedure based on homotopy continuation is implemented. A continuation algorithm is also applied to find a set of robot parameters with the maximum number of real assembly modes for a given DGP. Finally, the end-effector pose depends on the applied load and may change due to external disturbances. An investigation into equilibrium stability is therefore performed.

Impact of metal and metal oxide engineered nanoparticles in soil and plant systems

Nanotechnology promises huge benefits for society and capital invested in this new technology is steadily increasing, therefore there is a growing number of nanotechnology products on the market and inevitably engineered nanomaterials will be released in the atmosphere with potential risks to humans and environment. This study set out to extend the comprehension of the impact of metal (Ag, Co, Ni) and metal oxide (CeO2, Fe3O4, SnO2, TiO2) nanoparticles (NPs) on one of the most important environmental compartments potentially contaminated by NPs, the soil system, through the use of chemical and biological tools. For this purpose experiments were carried out to simulate realistic environmental conditions of wet and dry deposition of NPs, considering ecologically relevant endpoints. In detail, this thesis involved the study of three model systems and the evaluation of related issues: (i) NPs and bare soil, to assess the influence of NPs on the functions of soil microbial communities; (ii) NPs and plants, to evaluate the chronic toxicity and accumulation of NPs in edible tissues; (iii) NPs and invertebrates, to verify the effects of NPs on earthworms and the damaging of their functionality. The study highlighted that NP toxicity is generally influenced by NP core elements and the impact of NPs on organisms is specie-specific; moreover experiments conducted in media closer to real conditions showed a decrease in toxicity with respect to in vitro test or hydroponic tests. However, only a multidisciplinary approach, involving physical, chemical and biological skills, together with the use of advanced techniques, such as X-ray absorption fine structure spectroscopy, could pave the way to draw the right conclusions and accomplish a deeper comprehension of the effects of NPs on soil and soil inhabitants.

3D-ultrastructure, functions and stress responses of rhogocytes from the freshwater gastropods Biomphalaria glabrata and Lymnaea stagnalis

Rhogocytes, also termed ‘pore cells’, exist free in the hemolymph or embedded in the connective tissue of different body parts of molluscs, notably gastropods. These unique cells can be round, elongated or irregularly shaped, and up to 30 μm in diameter. Their hallmark is the so-called slit apparatus: i.e. pocket-like invaginations of the plasma membrane creating extracellular lacunae, bridged by cytoplasmic bars. These bars form distinctive slits of ca. 20 nm width. A slit diaphragm composed of proteins establishes a molecular sieve with holes of 20 x 20 nm. Different functions have been assigned to this special molluscan cell type, notably biosynthesis of the hemolymph respiratory protein hemocyanin. It has further been proposed, but not proven, that in the case of red-blooded snail species rhogocytes might synthesize the hemoglobin. However, the secretion pathway of these hemolymph proteins, and the functional role of the enigmatic slit apparatus remained unclear. Additionally proposed functions of rhogocytes, such as heavy metal detoxification or hemolymph protein degradation, are also not well studied. This work provides more detailed electron microscopical, histological and immunobiochemical information on the structure and function of rhogocytes of the freshwater snails Biomphalaria glabrata and Lymnaea stagnalis. By in situ hybridization on mantle tissues, it proves that B. glabrata rhogocytes synthesize hemoglobin and L. stagnalis rhogocytes synthesize hemocyanin. Hemocyanin is present, in endoplasmic reticulum lacunae and in vesicles, as individual molecules or pseudo-crystalline arrays. The first 3D reconstructions of rhogocytes are provided by means of electron tomography and show unprecedented details of the slit apparatus. A highly dense material in the cytoplasmic bars close to the diaphragmatic slits was shown, by immunogold labeling, to contain actin. By immunofluorescence microscopy, the protein nephrin was localized at the periphery of rhogocytes. The presence of both proteins in the slit apparatus supports the previous hypothesis, hitherto solely based on similarities of the ultrastructure, that the molluscan rhogocytes are phylogenetically related to mammalian podocytes and insect nephrocytes. A possible secretion pathway of respiratory proteins that includes a transfer mechanism of vesicles through the diaphragmatic slits is proposed and discussed. We also studied, by electron microscopy, the reaction of rhogocytes in situ to two forms of animal stress: deprivation of food and cadmium contamination of the tank water. Significant cellular reactions to both stressors were observed and documented. Notably, the slit apparatus surface and the number of electron-dense cytoplasmic vesicles increased in response to cadmium stress. Food deprivation led to an increase in hemocyanin production. These observations are also discussed in the framework of using such animals as potential environmental biomarkers.

Diversity Promotes Temporal Stability across Levels of Ecosystem Organization in Experimental Grasslands

The diversity–stability hypothesis states that current losses of biodiversity can impair the ability of an ecosystem to dampen the effect of environmental perturbations on its functioning. Using data from a long-term and comprehensive biodiversity experiment, we quantified the temporal stability of 42 variables characterizing twelve ecological functions in managed grassland plots varying in plant species richness. We demonstrate that diversity increases stability i) across trophic levels (producer, consumer), ii) at both the system (community, ecosystem) and the component levels (population, functional group, phylogenetic clade), and iii) primarily for aboveground rather than belowground processes. Temporal synchronization across studied variables was mostly unaffected with increasing species richness. This study provides the strongest empirical support so far that diversity promotes stability across different ecological functions and levels of ecosystem organization in grasslands

Framingham risk score and alternatives for prediction of coronary heart disease in older adults

Background Guidelines for the prevention of coronary heart disease (CHD) recommend use of Framingham-based risk scores that were developed in white middle-aged populations. It remains unclear whether and how CHD risk prediction might be improved among older adults. We aimed to compare the prognostic performance of the Framingham risk score (FRS), directly and after recalibration, with refit functions derived from the present cohort, as well as to assess the utility of adding other routinely available risk parameters to FRS. Methods Among 2193 black and white older adults (mean age, 73.5 years) without pre-existing cardiovascular disease from the Health ABC cohort, we examined adjudicated CHD events, defined as incident myocardial infarction, CHD death, and hospitalization for angina or coronary revascularization. Results During 8-year follow-up, 351 participants experienced CHD events. The FRS poorly discriminated between persons who experienced CHD events vs. not (C-index: 0.577 in women; 0.583 in men) and underestimated absolute risk prediction by 51% in women and 8% in men. Recalibration of the FRS improved absolute risk prediction, particulary for women. For both genders, refitting these functions substantially improved absolute risk prediction, with similar discrimination to the FRS. Results did not differ between whites and blacks. The addition of lifestyle variables, waist circumference and creatinine did not improve risk prediction beyond risk factors of the FRS. Conclusions The FRS underestimates CHD risk in older adults, particularly in women, although traditional risk factors remain the best predictors of CHD. Re-estimated risk functions using these factors improve accurate estimation of absolute risk.

The \bar{B} \to X_s γγdecay: NLL QCD contribution of the Electromagnetic Dipole operator O_7

We calculate the set of O(\alpha_s) corrections to the double differential decay width d\Gamma_{77}/(ds_1 \, ds_2) for the process \bar{B} \to X_s \gamma \gamma originating from diagrams involving the electromagnetic dipole operator O_7. The kinematical variables s_1 and s_2 are defined as s_i=(p_b - q_i)^2/m_b^2, where p_b, q_1, q_2 are the momenta of b-quark and two photons. While the (renormalized) virtual corrections are worked out exactly for a certain range of s_1 and s_2, we retain in the gluon bremsstrahlung process only the leading power w.r.t. the (normalized) hadronic mass s_3=(p_b-q_1-q_2)^2/m_b^2 in the underlying triple differential decay width d\Gamma_{77}/(ds_1 ds_2 ds_3). The double differential decay width, based on this approximation, is free of infrared- and collinear singularities when combining virtual- and bremsstrahlung corrections. The corresponding results are obtained analytically. When retaining all powers in s_3, the sum of virtual- and bremstrahlung corrections contains uncanceled 1/\epsilon singularities (which are due to collinear photon emission from the s-quark) and other concepts, which go beyond perturbation theory, like parton fragmentation functions of a quark or a gluon into a photon, are needed which is beyond the scope of our paper.