Real-Time Support in the Proposal for Fine-Grained Parallelism in Ada

Presented at Work in Progress Session, IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 3, Dec, 2015. San Antonio, U.S.A..

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Esclonamento de máquinas de cogeração utilzando programação inteira mista

As centrais termoelétricas convencionais convertem apenas parte do combustível consumido na produção de energia elétrica, sendo que outra parte resulta em perdas sob a forma de calor. Neste sentido, surgiram as unidades de cogeração, ou Combined Heat and Power (CHP), que permitem reaproveitar a energia dissipada sob a forma de energia térmica e disponibilizá-la, em conjunto com a energia elétrica gerada, para consumo doméstico ou industrial, tornando-as mais eficientes que as unidades convencionais Os custos de produção de energia elétrica e de calor das unidades CHP são representados por uma função não-linear e apresentam uma região de operação admissível que pode ser convexa ou não-convexa, dependendo das caraterísticas de cada unidade. Por estas razões, a modelação de unidades CHP no âmbito do escalonamento de geradores elétricos (na literatura inglesa Unit Commitment Problem (UCP)) tem especial relevância para as empresas que possuem, também, este tipo de unidades. Estas empresas têm como objetivo definir, entre as unidades CHP e as unidades que apenas geram energia elétrica ou calor, quais devem ser ligadas e os respetivos níveis de produção para satisfazer a procura de energia elétrica e de calor a um custo mínimo. Neste documento são propostos dois modelos de programação inteira mista para o UCP com inclusão de unidades de cogeração: um modelo não-linear que inclui a função real de custo de produção das unidades CHP e um modelo que propõe uma linearização da referida função baseada na combinação convexa de um número pré-definido de pontos extremos. Em ambos os modelos a região de operação admissível não-convexa é modelada através da divisão desta àrea em duas àreas convexas distintas. Testes computacionais efetuados com ambos os modelos para várias instâncias permitiram verificar a eficiência do modelo linear proposto. Este modelo permitiu obter as soluções ótimas do modelo não-linear com tempos computationais significativamente menores. Para além disso, ambos os modelos foram testados com e sem a inclusão de restrições de tomada e deslastre de carga, permitindo concluir que este tipo de restrições aumenta a complexidade do problema sendo que o tempo computacional exigido para a resolução do mesmo cresce significativamente.

Economic analysis in health care regulation : three essays

ABSTRACT - It is the purpose of the present thesis to emphasize, through a series of examples, the need and value of appropriate pre-analysis of the impact of health care regulation. Specifically, the thesis presents three papers on the theme of regulation in different aspects of health care provision and financing. The first two consist of economic analyses of the impact of health care regulation and the third comprises the creation of an instrument for supporting economic analysis of health care regulation, namely in the field of evaluation of health care programs. The first paper develops a model of health plan competition and pricing in order to understand the dynamics of health plan entry and exit in the presence of switching costs and alternative health premium payment systems. We build an explicit model of death spirals, in which profitmaximizing competing health plans find it optimal to adopt a pattern of increasing relative prices culminating in health plan exit. We find the steady-state numerical solution for the price sequence and the plan’s optimal length of life through simulation and do some comparative statics. This allows us to show that using risk adjusted premiums and imposing price floors are effective at reducing death spirals and switching costs, while having employees pay a fixed share of the premium enhances death spirals and increases switching costs. Price regulation of pharmaceuticals is one of the cost control measures adopted by the Portuguese government, as in many European countries. When such regulation decreases the products’ real price over time, it may create an incentive for product turnover. Using panel data for the period of 1997 through 2003 on drug packages sold in Portuguese pharmacies, the second paper addresses the question of whether price control policies create an incentive for product withdrawal. Our work builds the product survival literature by accounting for unobservable product characteristics and heterogeneity among consumers when constructing quality, price control and competition indexes. These indexes are then used as covariates in a Cox proportional hazard model. We find that, indeed, price control measures increase the probability of exit, and that such effect is not verified in OTC market where no such price regulation measures exist. We also find quality to have a significant positive impact on product survival. In the third paper, we develop a microsimulation discrete events model (MSDEM) for costeffectiveness analysis of Human Immunodeficiency Virus treatment, simulating individual paths from antiretroviral therapy (ART) initiation to death. Four driving forces determine the course of events: CD4+ cell count, viral load resistance and adherence. A novel feature of the model with respect to the previous MSDEMs is that distributions of time to event depend on individuals’ characteristics and past history. Time to event was modeled using parametric survival analysis. Events modeled include: viral suppression, regimen switch due virological failure, regimen switch due to other reasons, resistance development, hospitalization, AIDS events, and death. Disease progression is structured according to therapy lines and the model is parameterized with cohort Portuguese observational data. An application of the model is presented comparing the cost-effectiveness ART initiation with two nucleoside analogue reverse transcriptase inhibitors (NRTI) plus one non-nucleoside reverse transcriptase inhibitor(NNRTI) to two NRTI plus boosted protease inhibitor (PI/r) in HIV- 1 infected individuals. We find 2NRTI+NNRTI to be a dominant strategy. Results predicted by the model reproduce those of the data used for parameterization and are in line with those published in the literature.

Studies on the wine spoilage yeast Brettanomyces bruxellensis: 4-ethylphenol production and improved detection

Dissertação para obtenção do Grau de Mestre em Biotecnologia

A SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil

INTRODUCTION: Forecasting dengue cases in a population by using time-series models can provide useful information that can be used to facilitate the planning of public health interventions. The objective of this article was to develop a forecasting model for dengue incidence in Campinas, southeast Brazil, considering the Box-Jenkins modeling approach. METHODS: The forecasting model for dengue incidence was performed with R software using the seasonal autoregressive integrated moving average (SARIMA) model. We fitted a model based on the reported monthly incidence of dengue from 1998 to 2008, and we validated the model using the data collected between January and December of 2009. RESULTS: SARIMA (2,1,2) (1,1,1)12 was the model with the best fit for data. This model indicated that the number of dengue cases in a given month can be estimated by the number of dengue cases occurring one, two and twelve months prior. The predicted values for 2009 are relatively close to the observed values. CONCLUSIONS: The results of this article indicate that SARIMA models are useful tools for monitoring dengue incidence. We also observe that the SARIMA model is capable of representing with relative precision the number of cases in a next year.

Production of polyhydroxyalkanoates from oil-containing substrates

Different oil-containing substrates, namely, used cooking oil (UCO), fatty acids-byproduct from biodiesel production (FAB) and olive oil deodorizer distillate (OODD) were tested as inexpensive carbon sources for the production of polyhydroxyalkanoates (PHA) using twelve bacterial strains, in batch experiments. The OODD and FAB were exploited for the first time as alternative substrates for PHA production. Among the tested bacterial strains, Cupriavidus necator and Pseudomonas resinovorans exhibited the most promising results, producing poly-3-hydroxybutyrate, P(3HB), form UCO and OODD and mcl-PHA mainly composed of 3-hydroxyoctanoate (3HO) and 3-hydroxydecanoate (3HD) monomers from OODD, respectively. Afterwards, these bacterial strains were cultivated in bioreactor. C. necator were cultivated in bioreactor using UCO as carbon source. Different feeding strategies were tested for the bioreactor cultivation of C. necator, namely, batch, exponential feeding and DO-stat mode. The highest overall PHA productivity (12.6±0.78 g L-1 day-1) was obtained using DO-stat mode. Apparently, the different feeding regimes had no impact on polymer thermal properties. However, differences in polymer‟s molecular mass distribution were observed. C. necator was also tested in batch and fed-batch modes using a different type of oil-containing substrate, extracted from spent coffee grounds (SCG) by super critical carbon dioxide (sc-CO2). Under fed-batch mode (DO-stat), the overall PHA productivity were 4.7 g L-1 day-1 with a storage yield of 0.77 g g-1. Results showed that SCG can be a bioresource for production of PHA with interesting properties. Furthermore, P. resinovorans was cultivated using OODD as substrate in bioreactor under fed-batch mode (pulse feeding regime). The polymer was highly amorphous, as shown by its low crystallinity of 6±0.2%, with low melting and glass transition temperatures of 36±1.2 and -16±0.8 ºC, respectively. Due to its sticky behavior at room temperature, adhesiveness and mechanical properties were also studied. Its shear bond strength for wood (67±9.4 kPa) and glass (65±7.3 kPa) suggests it may be used for the development of biobased glues. Bioreactor operation and monitoring with oil-containing substrates is very challenging, since this substrate is water immiscible. Thus, near-infrared spectroscopy (NIR) was implemented for online monitoring of the C. necator cultivation with UCO, using a transflectance probe. Partial least squares (PLS) regression was applied to relate NIR spectra with biomass, UCO and PHA concentrations in the broth. The NIR predictions were compared with values obtained by offline reference methods. Prediction errors to these parameters were 1.18 g L-1, 2.37 g L-1 and 1.58 g L-1 for biomass, UCO and PHA, respectively, which indicates the suitability of the NIR spectroscopy method for online monitoring and as a method to assist bioreactor control. UCO and OODD are low cost substrates with potential to be used in PHA batch and fed-batch production. The use of NIR in this bioprocess also opened an opportunity for optimization and control of PHA production process.

Practice variations in the production of health

This study investigates three questions related to medical practice variation. First, it tests whether average length of stay across Portuguese National Health Service hospitals varies when controlling for differences in patients’ characteristics. Second, it looks at hospital-level characteristics in order to find out whether these are able to explain differences in average length of stay across hospitals. Finally, it proposes a best practice average length of stay for each of the six episodes of care analyzed. To perform the analysis, administrative data from the Diagnosis-Related groups’ data set for the year of 2012 was used. A replication of a hierarchical two-stage model with hospital fixed effects was carried out. The results show that after taking patients’ characteristics into account, variation in average length of stay across hospitals exists. This variation cannot be explained by hospital-level characteristics.

Polyhydroxyalkanoates production by photosynthetic mixed cultures

Polyhydroxyalkanoates (PHAs) are natural biologically synthesized polymers that have been the subject of much interest in the last decades due to their biodegradability. Thus far, its microbial production is associated with high operational costs, which increases PHA prices and limits its marketability. To address this situation, this thesis’ work proposes the utilization of photosynthetic mixed cultures (PMC) as a new PHA production system that may lead to a reduction in operational costs. In fact, the operational strategies developed in this work led to the selection of PHA accumulating PMCs that, unlike the traditional mixed microbial cultures, do not require aeration, thus permitting savings in this significant operational cost. In particular, the first PHA accumulating PMC tested in this work was selected under non-aerated illuminated conditions in a feast and famine regime, being obtained a consortium of bacteria and algae, where photosynthetic bacteria accumulated PHA during the feast phase and consumed it for growth during the famine phase, using the oxygen produced by algae. In this symbiotic system, a maximum PHA content of 20% cell dry weight (cdw) was reached, proving for the first time, the capacity of a PMC to accumulate PHA. During adaptation to dark/light alternating conditions, the culture decreased its algae content but maintained its viability, achieving a PHA content of 30% cdw. Also, the PMC was found to be able to utilize different volatile fatty acids for PHA production, accumulating up to 20% cdw of a PHA co-polymer composed of 3-hydroxybutyrate (3HB) and 3-hydroxyvalerate (HV) monomers. Finally, a new selective approach for the enrichment of PMCs in PHA accumulating bacteria was tested. Instead of imposing a feast and famine regime, a permanent feast regime was used, thus selecting a PMC that was capable of simultaneously growing and accumulating PHA, being attained a maximum PHA content of 60% cdw, the highest value reported for a PMC thus far. The results presented in this thesis prospect the utilization of cheap, VFA-rich fermented wastes as substrates for PHA production, which combined with this new photosynthetic technology opens up the possibility for direct sunlight illumination, leading to a more cost-effective and environmentally sustainable PHA production process.

Production of mexican brown macroalgae fucoidan and fucosidases under an integral green technology bioproceses by the biorefinery concept

Marine ecosystem can be considered a rather exploited source of natural substances with enormous bioactive potential. In Mexico macro-algae study remain forgotten for research and economic purposes besides the high amount of this resource along the west and east coast. For that reason the Bioferinery Group of the Autonomous University of Coahuila, have been studying the biorefinery concept in order to recover high value byproducts of Mexican brown macro-algae including polysaccharides and enzymes to be applied in food, pharmaceutical and energy industry. Brown macroalgae are an important source of fucoidan, alginate and laminarin which comprise a complex group of macromolecules with a wide range of important biological properties such as anticoagulant, antioxidant, antitumoral and antiviral and also as rich source of fermentable sugars for enzymes production. Additionally, specific enzymes able to degrade algae matrix (fucosidases, sulfatases, aliginases, etc) are important tools to establish structural characteristics and biological functions of these polysaccharides. The aims of the present work were the integral study of bioprocess for macroalgae biomass exploitation by the use of green technologies as hydrothermal extraction and solid state fermentation in order to produce polysaccharides and enzymes (fucoidan and fucoidan hydrolytic enzymes). This work comprises the use of the different bioprocess phases in order to produce high value products with lower time and wastes.

Design and optimization of an extrusion die for the production of wood–plastic composite profiles

In this work, the optimization of an extrusion die designed for the production of a wood–plastic composite (WPC) decking profile is investigated. The optimization was performed with the help of numerical tools, more precisely, by solving the continuity and momentum conservation equations that govern such flow, and aiming to balance properly the flow distribution at the extrusion die flow channel outlet. To capture the rheological behavior of the material, we used a Bird-Carreau model with parameters obtained from a fit to the (shear viscosity versus shearrate) experimental data, collected from rheological tests. To yield a balanced output flow, several numerical runs were performed by adjusting the flow restriction at different regions of the flow-channel parallel zone crosssection. The simulations were compared with the experimental results and an excellent qualitative agreement was obtained, allowing, in this way, to attain a good balancing of the output flow and emphasizing the advantages of using numerical tools to aid the design of profile extrusion dies.

Modelos de apoio às decisão na conceção e planeamento de um armazém

Programa Doutoral em Engenharia Industrial e de Sistemas.

Search for dark matter in events with heavy quarks and missing transverse momentum in pp collisions with the ATLAS detector

This article reports on a search for dark matter pair production in association with bottom or top quarks in 20.3fb−1 of pp collisions collected at s√=8 TeV by the ATLAS detector at the LHC. Events with large missing transverse momentum are selected when produced in association with high-momentum jets of which one or more are identified as jets containing b-quarks. Final states with top quarks are selected by requiring a high jet multiplicity and in some cases a single lepton. The data are found to be consistent with the Standard Model expectations and limits are set on the mass scale of effective field theories that describe scalar and tensor interactions between dark matter and Standard Model particles. Limits on the dark-matter--nucleon cross-section for spin-independent and spin-dependent interactions are also provided. These limits are particularly strong for low-mass dark matter. Using a simplified model, constraints are set on the mass of dark matter and of a coloured mediator suitable to explain a possible signal of annihilating dark matter.

Search for new phenomena in events with three or more charged leptons in pp collisions at TeV with the ATLAS detector

A generic search for anomalous production of events with at least three charged leptons is presented. The data sample consists of pp collisions at s√=8 TeV collected in 2012 by the ATLAS experiment at the CERN Large Hadron Collider, and corresponds to an integrated luminosity of 20.3 fb−1. Events are required to have at least three selected lepton candidates, at least two of which must be electrons or muons, while the third may be a hadronically decaying tau. Selected events are categorized based on their lepton flavour content and signal regions are constructed using several kinematic variables of interest. No significant deviations from Standard Model predictions are observed. Model-independent upper limits on contributions from beyond the Standard Model phenomena are provided for each signal region, along with prescription to re-interpret the limits for any model. Constraints are also placed on models predicting doubly charged Higgs bosons and excited leptons. For doubly charged Higgs bosons decaying to eτ or μτ, lower limits on the mass are set at 400 GeV at 95% confidence level. For excited leptons, constraints are provided as functions of both the mass of the excited state and the compositeness scale Λ, with the strongest mass constraints arising in regions where the mass equals Λ. In such scenarios, lower mass limits are set at 3.0 TeV for excited electrons and muons, 2.5 TeV for excited taus, and 1.6 TeV for every excited-neutrino flavour.

Left Atrial Volume Determinants in Patients with Non-Ischemic Dilated Cardiomyopathy

Background:Left atrial volume (LAV) is a predictor of prognosis in patients with heart failure.Objective:We aimed to evaluate the determinants of LAV in patients with dilated cardiomyopathy (DCM).Methods:Ninety patients with DCM and left ventricular (LV) ejection fraction ≤ 0.50 were included. LAV was measured with real-time three-dimensional echocardiography (eco3D). The variables evaluated were heart rate, systolic blood pressure, LV end-diastolic volume and end-systolic volume and ejection fraction (eco3D), mitral inflow E wave, tissue Doppler e´ wave, E/e´ ratio, intraventricular dyssynchrony, 3D dyssynchrony index and mitral regurgitation vena contracta. Pearson´s coefficient was used to identify the correlation of the LAV with the assessed variables. A multiple linear regression model was developed that included LAV as the dependent variable and the variables correlated with it as the predictive variables.Results:Mean age was 52 ± 11 years-old, LV ejection fraction: 31.5 ± 8.0% (16-50%) and LAV: 39.2±15.7 ml/m2. The variables that correlated with the LAV were LV end-diastolic volume (r = 0.38; p < 0.01), LV end-systolic volume (r = 0.43; p < 0.001), LV ejection fraction (r = -0.36; p < 0.01), E wave (r = 0.50; p < 0.01), E/e´ ratio (r = 0.51; p < 0.01) and mitral regurgitation (r = 0.53; p < 0.01). A multivariate analysis identified the E/e´ ratio (p = 0.02) and mitral regurgitation (p = 0.02) as the only independent variables associated with LAV increase.Conclusion:The LAV is independently determined by LV filling pressures (E/e´ ratio) and mitral regurgitation in DCM.