STATISTICAL METHODS FOR ADVANCED ECONOMETRIC MODELS WITH APPLICATIONS TO VEHICLE HOLDING AND SPEED QUANTILES DISTRIBUTION

This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.

The Impact of Regulation on a Firm's Incentives to Invest in Emergent Smart Grid Technologies

This paper analyzes the implementation of new technologies in network industries through the development of a suitable regulatory scheme. The analysis focuses on Smart Grid (SG) technologies which, among others benefits, could save operational costs and reduce the need for further conventional investments in the grid. In spite of the benefits that may result from their implementation, the adoption of SGs by network operators can be hampered by the uncertainties surrounding actual performances. A decision model has been developed to assess the firms' incentives to invest in "smart" technologies under different regulatory schemes. The model also enables testing the impact of uncertainties on the reduction of operational costs, and of conventional investments. Under certain circumstances, it may be justified to support the development and early deployment of emerging innovations that have a high potential to ameliorate the efficiency of the electricity system, but whose adoption faces many uncertainties.

Vanadium Redox Flow Battery Storage System Linked to the Electric Grid

This paper focuses on technology state of the art for the charge/discharge of electric energy storage supported by vanadium redox flow battery linked to the electric grid. Properties of vanadium, the main configuration and the reaction of charge/discharge of a vanadium redox flow battery are addressed. The vanadium redox flow battery has the highest cell voltage among the other redox flow battery, implying higher power and energy density which favours application at power plants. This electric energy storage is viewed as a promising contribution to be integrated in power system due to a reasonably bulky size and to successful applications currently allowing storage of energy at power plants or at electrical grids. For instances, allowing storage of energy as an economic improvement providing spin reserve to avoid penalty for imbalances between the energy delivered and energy contracted at closing of electricity market or as an economic improvement to diminish the cost of electricity usage of a consumer. The vanadium redox flow battery has the advantages of scalability customized to meet requirements for power and energy capacity and of excellent combination of energy efficiency, capital cost and life cycle costs compared with other technology.

Offshore Wind Energy Conversion System Connected to the Electric Grid: Modeling and Simulation

This paper is on modeling and simulation for an offshore wind system equipped with a semi-submersible floating platform, a wind turbine, a permanent magnet synchronous generator, a multiple point clamped four level or five level full-power converter, a submarine cable and a second order filter. The drive train is modeled by three mass model considering the resistant stiffness torque, structure and tower in deep water due to the moving surface elevation. The system control uses PWM by space vector modulation associated with sliding mode and proportional integral controllers. The electric energy is injected into the electric grid either by an alternated current link or by a direct current link. The model is intend to be a useful tool for unveil the behavior and performance of the offshore wind system, especially for the multiple point clamped full-power converter, under normal operation or under malfunctions.

Distributed Large-scale Mixed-Integer Optimization with Application to Energy and Multi-robot Networks

Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost functions estimated online. Subsequently, we consider Mixed-Integer Linear Programs (MILPs), which are of great interest in smart grid control and cooperative robotics. We propose a distributed methodological framework to compute a feasible solution to the original MILP, with guaranteed suboptimality bounds, and extend it to general nonconvex problems. Monte Carlo simulations highlight that the approach represents a substantial breakthrough with respect to the state of the art, thus representing a valuable solution for new toolboxes addressing large-scale MILPs. We then propose a distributed Benders decomposition algorithm for asynchronous unreliable networks. The framework has been then used as starting point to develop distributed methodologies for a microgrid optimal control scenario. We develop an ad-hoc distributed strategy for a stochastic set-up with renewable energy sources, and show a case study with samples generated using Generative Adversarial Networks (GANs). We then introduce a software toolbox named ChoiRbot, based on the novel Robot Operating System 2, and show how it facilitates simulations and experiments in distributed multi-robot scenarios. Finally, we consider a Pickup-and-Delivery Vehicle Routing Problem for which we design a distributed method inspired to the approach of general MILPs, and show the efficacy through simulations and experiments in ChoiRbot with ground and aerial robots.

Integrating mobile devices into a scalable Grid Computing architecture designed to perform distributed computations

The idea of Grid Computing originated in the nineties and found its concrete applications in contexts like the SETI@home project where a lot of computers (offered by volunteers) cooperated, performing distributed computations, inside the Grid environment analyzing radio signals trying to find extraterrestrial life. The Grid was composed of traditional personal computers but, with the emergence of the first mobile devices like Personal Digital Assistants (PDAs), researchers started theorizing the inclusion of mobile devices into Grid Computing; although impressive theoretical work was done, the idea was discarded due to the limitations (mainly technological) of mobile devices available at the time. Decades have passed, and now mobile devices are extremely more performant and numerous than before, leaving a great amount of resources available on mobile devices, such as smartphones and tablets, untapped. Here we propose a solution for performing distributed computations over a Grid Computing environment that utilizes both desktop and mobile devices, exploiting the resources from day-to-day mobile users that alternatively would end up unused. The work starts with an introduction on what Grid Computing is, the evolution of mobile devices, the idea of integrating such devices into the Grid and how to convince device owners to participate in the Grid. Then, the tone becomes more technical, starting with an explanation on how Grid Computing actually works, followed by the technical challenges of integrating mobile devices into the Grid. Next, the model, which constitutes the solution offered by this study, is explained, followed by a chapter regarding the realization of a prototype that proves the feasibility of distributed computations over a Grid composed by both mobile and desktop devices. To conclude future developments and ideas to improve this project are presented.

Exposure To Bisphenol-a During Pregnancy Partially Mimics The Effects Of A High-fat Diet Altering Glucose Homeostasis And Gene Expression In Adult Male Mice.

Bisphenol-A (BPA) is one of the most widespread EDCs used as a base compound in the manufacture of polycarbonate plastics. The aim of our research has been to study how the exposure to BPA during pregnancy affects weight, glucose homeostasis, pancreatic β-cell function and gene expression in the major peripheral organs that control energy flux: white adipose tissue (WAT), the liver and skeletal muscle, in male offspring 17 and 28 weeks old. Pregnant mice were treated with a subcutaneous injection of 10 µg/kg/day of BPA or a vehicle from day 9 to 16 of pregnancy. One month old offspring were divided into four different groups: vehicle treated mice that ate a normal chow diet (Control group); BPA treated mice that also ate a normal chow diet (BPA); vehicle treated animals that had a high fat diet (HFD) and BPA treated animals that were fed HFD (HFD-BPA). The BPA group started to gain weight at 18 weeks old and caught up to the HFD group before week 28. The BPA group as well as the HFD and HFD-BPA ones presented fasting hyperglycemia, glucose intolerance and high levels of non-esterified fatty acids (NEFA) in plasma compared with the Control one. Glucose stimulated insulin release was disrupted, particularly in the HFD-BPA group. In WAT, the mRNA expression of the genes involved in fatty acid metabolism, Srebpc1, Pparα and Cpt1β was decreased by BPA to the same extent as with the HFD treatment. BPA treatment upregulated Pparγ and Prkaa1 genes in the liver; yet it diminished the expression of Cd36. Hepatic triglyceride levels were increased in all groups compared to control. In conclusion, male offspring from BPA-treated mothers presented symptoms of diabesity. This term refers to a form of diabetes which typically develops in later life and is associated with obesity.

Androgen Therapy Reverses Injuries Caused By Ethanol Consumption In The Prostate: Testosterone As A Possible Target To Ethanol-related Disorders.

Chronic ethanol consumption leads to reproductive damages, since it can act directly in the tissues or indirectly, causing a hormonal imbalance. Prostate is a hormone-dependent gland and, consequently, susceptible to ethanol. The potential of testosterone therapy in the ethanol-related disorders was investigated in the prostate microenvironment. UChB rats aged 90 days were divided into 2 experimental groups (n=20): C: drinking water only and EtOH: drinking 10% (v/v) ethanol at >2 g/kg body weight/day+water. At 150 days old, 10 rats from each group received subcutaneous injections of testosterone cypionate (5 mg/kg body weight) diluted in corn oil every other day for 4 weeks, constituting T and EtOH+T, while the remaining animals received corn oil as vehicle. Animals were euthanized at 180 days old, by decapitation. Blood was collected to obtain hormone concentrations and ventral prostate was dissected and processed for light microscope and molecular analyses. Ventral prostate weight, plasma testosterone and DHT and intraprostatic testosterone concentrations were increased after testosterone treatment. Plasma estradiol level was reduced in the EtOH+T. Inflammatory foci, metaplasia and epithelial atrophy were constantly found in the prostate of EtOH and were not observed after hormonal therapy. No differences were found in the expression of AR, ERβ and DACH-1. Additionally, testosterone treatment down-regulated ERα and increased the e-cadherin and α-actinin immunoreactivities. Testosterone was able to reverse damages caused by ethanol consumption in the prostate microenvironment and becomes a possible target to be investigated to ethanol-related disorders.

Dose-response effects of systemic anandamide administration in mice sequentially submitted to the open field and elevated plus-maze tests

The endocannabinoid system is involved in the control of many physiological functions, including the control of emotional states. In rodents, previous exposure to an open field increases the anxiety-like behavior in the elevated plus-maze. Anxiolytic-like effects of pharmacological compounds that increase endocannabinoid levels have been well documented. However, these effects are more evident in animals with high anxiety levels. Several studies have described characteristic inverted U-shaped dose-response effects of drugs that modulate the endocannabinoid levels. However, there are no studies showing the effects of different doses of exogenous anandamide, an endocannabinoid, in animal models of anxiety. Thus, in the present study, we determined the dose-response effects of exogenous anandamide at doses of 0.01, 0.1, and 1.0 mg/kg in C57BL/6 mice (N = 10/group) sequentially submitted to the open field and elevated plus-maze. Anandamide was diluted in 0.9% saline, ethyl alcohol, Emulphor® (18:1:1) and administered ip (0.1 mL/10 g body weight); control animals received the same volume of anandamide vehicle. Anandamide at the dose of 0.1 mg/kg (but not of 0.01 or 1 mg/kg) increased (P < 0.05) the time spent and the distance covered in the central zone of the open field, as well as the exploration of the open arms of the elevated plus-maze. Thus, exogenous anandamide, like pharmacological compounds that increase endocannabinoid levels, promoted a characteristic inverted U-shaped dose-response effect in animal models of anxiety. Furthermore, anandamide (0.1 mg/kg) induced an anxiolytic-like effect in the elevated plus-maze (P < 0.05) after exposing the animals to the open field test.

Therapeutic Efficacy of Cintredekin Besudotox (IL13-PE38QQR) in Murine Lung Fibrosis Is Unaffected by Immunity to Pseudomonas aeruginosa Exotoxin A

Background: We have previously explored a therapeutic strategy for specifically targeting the profibrotic activity of IL-13 during experimental pulmonary fibrosis using a fusion protein comprised of human IL-13 and a mutated form of Pseudomonas aeruginosa exotoxin A (IL13-PE) and observed that the intranasal delivery of IL13-PE reduced bleomycin-induced pulmonary fibrosis through its elimination of IL-13-responsive cells in the lung. The aim of the present study was to determine whether the presence of an immune response to P. aeruginosa and/or its exotoxin A (PE) would diminish the anti-fibrotic properties of IL13-PE. Methodology/Principal Findings: Fourteen days after P. aeruginosa infection, C57BL/6 mice were injected with bleomycin via the intratracheal route. Other groups of mice received 4 doses of saline or IL13-PE by either intranasal or intraperitoneal application, and were challenged i.t. with bleomycin 28 days later. At day 21 after bleomycin, all mice received either saline vehicle or IL13-PE by the intranasal route and histopatological analyses of whole lung samples were performed at day 28 after bleomycin. Intrapulmonary P. aeruginosa infection promoted a neutralizing IgG2A and IgA antibody response in BALF and serum. Surprisingly, histological analysis showed that a prior P. aeruginosa infection attenuated the development of bleomycin-induced pulmonary fibrosis, which was modestly further attenuated by the intranasal administration of IL13-PE. Although prior intranasal administration of IL13-PE failed to elicit an antibody response, the systemic administration of IL13-PE induced a strong neutralizing antibody response. However, the prior systemic sensitization of mice with IL13-PE did not inhibit the anti-fibrotic effect of IL13-PE in fibrotic mice. Conclusions: Thus, IL13-PE therapy in pulmonary fibrosis works regardless of the presence of a humoral immune response to Pseudomonas exotoxin A. Interestingly, a prior infection with P. aeruginosa markedly attenuated the pulmonary fibrotic response suggesting that the immune elicitation by this pathogen exerts anti-fibrotic effects.

Behavioral and Autonomic Responses to Acute Restraint Stress Are Segregated within the Lateral Septal Area of Rats

Background: The Lateral Septal Area (LSA) is involved with autonomic and behavior responses associated to stress. In rats, acute restraint (RS) is an unavoidable stress situation that causes autonomic (body temperature, mean arterial pressure (MAP) and heart rate (HR) increases) and behavioral (increased anxiety-like behavior) changes in rats. The LSA is one of several brain regions that have been involved in stress responses. The aim of the present study was to investigate if the neurotransmission blockade in the LSA would interfere in the autonomic and behavioral changes induced by RS. Methodology/Principal Findings: Male Wistar rats with bilateral cannulae aimed at the LSA, an intra-abdominal datalogger (for recording internal body temperature), and an implanted catheter into the femoral artery (for recording and cardiovascular parameters) were used. They received bilateral microinjections of the non-selective synapse blocker cobalt chloride (CoCl(2), 1 mM/ 100 nL) or vehicle 10 min before RS session. The tail temperature was measured by an infrared thermal imager during the session. Twenty-four h after the RS session the rats were tested in the elevated plus maze (EPM). Conclusions/Significance: Inhibition of LSA neurotransmission reduced the MAP and HR increases observed during RS. However, no changes were observed in the decrease in skin temperature and increase in internal body temperature observed during this period. Also, LSA inhibition did not change the anxiogenic effect induced by RS observed 24 h later in the EPM. The present results suggest that LSA neurotransmission is involved in the cardiovascular but not the temperature and behavioral changes induced by restraint stress.

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 1: Model description and evaluation

We introduce the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS). CATT-BRAMS is an on-line transport model fully consistent with the simulated atmospheric dynamics. Emission sources from biomass burning and urban-industrial-vehicular activities for trace gases and from biomass burning aerosol particles are obtained from several published datasets and remote sensing information. The tracer and aerosol mass concentration prognostics include the effects of sub-grid scale turbulence in the planetary boundary layer, convective transport by shallow and deep moist convection, wet and dry deposition, and plume rise associated with vegetation fires in addition to the grid scale transport. The radiation parameterization takes into account the interaction between the simulated biomass burning aerosol particles and short and long wave radiation. The atmospheric model BRAMS is based on the Regional Atmospheric Modeling System (RAMS), with several improvements associated with cumulus convection representation, soil moisture initialization and surface scheme tuned for the tropics, among others. In this paper the CATT-BRAMS model is used to simulate carbon monoxide and particulate material (PM(2.5)) surface fluxes and atmospheric transport during the 2002 LBA field campaigns, conducted during the transition from the dry to wet season in the southwest Amazon Basin. Model evaluation is addressed with comparisons between model results and near surface, radiosondes and airborne measurements performed during the field campaign, as well as remote sensing derived products. We show the matching of emissions strengths to observed carbon monoxide in the LBA campaign. A relatively good comparison to the MOPITT data, in spite of the fact that MOPITT a priori assumptions imply several difficulties, is also obtained.

Experimental studies of di-jet survival and surface emission bias in Au plus Au collisions via angular correlations with respect to back-to-back leading hadrons

We report first results from an analysis based on a new multi-hadron correlation technique, exploring jet-medium interactions and di-jet surface emission bias at the BNL Relativistic Heavy Ion Collider (RHIC). Pairs of back-to-back high-transverse-momentum hadrons are used for triggers to study associated hadron distributions. In contrast with two-and three-particle correlations with a single trigger with similar kinematic selections, the associated hadron distribution of both trigger sides reveals no modification in either relative pseudorapidity Delta eta or relative azimuthal angle Delta phi from d + Au to central Au + Au collisions. We determine associated hadron yields and spectra as well as production rates for such correlated back-to-back triggers to gain additional insights on medium properties.

Measurement of the Bottom Quark Contribution to Nonphotonic Electron Production in p plus p Collisions at root s=200 GeV

The contribution of B meson decays to nonphotonic electrons, which are mainly produced by the semileptonic decays of heavy-flavor mesons, in p + p collisions at root s = 200 GeV has been measured using azimuthal correlations between nonphotonic electrons and hadrons. The extracted B decay contribution is approximately 50% at a transverse momentum of p(T) >= 5 GeV/c. These measurements constrain the nuclear modification factor for electrons from B and D meson decays. The result indicates that B meson production in heavy ion collisions is also suppressed at high p(T).