A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Previsão de vento baseado em técnicas de Data Mining

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Generation of high-affinity monoclonal antibodies of IgG class against native β-d-glucans from basidiomycete mushrooms

β-d-glucans from basidiomycete strains are powerful immunomodulatory agents in several clinical conditions. Therefore, their assay, purification and characterization are of great interest to understand their structure-function relationship. Hybridoma cell fusion was used to raise monoclonal antibodies (Mabs) against extracellular β-d-glucans (EBGs) from Pleurotus ostreatus. Two of the hybridoma clones (1E6-1E8-B5 and 3E8-3B4) secreting Mabs against EBGs were selected. This hybridoma cell line secreted Mabs of the IgG class which were then purified by hydroxyapatite chromatography to apparent homogeneity on native and SDS-PAGE. Mabs secreted by 1E6-1E8-B5 clone were found to recognize a common epitope on several β-d-glucans from different basidiomycete strains. This Mab exhibited high affinity constant (KA) for β-d-glucans from several mushroom strains in the range of 3.20 × 109 ± 3.32 × 103-1.51 × 1013 ± 3.58 × 107 L/mol. Moreover, they reacted to some heat-treated β-d-glucans in a different mode when compared with the native forms; these data suggest that this Mab binds to a conformational epitope on the β-d-glucan molecule. The epitope-binding studies of Mabs obtained from 1E6-1E8-B5 and 3E8-3B4 revealed that the Mabs bind to the same epitope on some β-d-glucans and to different epitopes in other antigen molecules. Therefore, these Mabs can be used to assay for β-d-glucan from basidiomycete mushrooms. © 2015 Elsevier Ltd. All rights reserved.

Geospatial database generation from digital newspapers: use case for risk and disaster domains.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Towards a unified European electricity market: The contribution of data-mining to support realistic simulation studies

Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European Electricity Market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. The continuous transformations electricity markets have been experiencing over the years create the need to use simulation platforms to support operators, regulators, and involved players for understanding and dealing with this complex environment. This paper focuses on demonstrating the advantage that real electricity markets data has for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations will bring to the participant countries. A case study using MASCEM (Multi-Agent System for Competitive Electricity Markets) is presented, with a scenario based on real data, simulating the European Electricity Market environment, and comparing its performance when using several different market mechanisms.

Integrating wind generation in the distribution network

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Energias Renováveis – Conversão Eléctrica e Utilização Sustentáveis

Experimental and modeling studies on reverse electrodialysis for sustainable power generation

A potentially renewable and sustainable source of energy is the chemical energy associated with solvation of salts. Mixing of two aqueous streams with different saline concentrations is spontaneous and releases energy. The global theoretically obtainable power from salinity gradient energy due to World’s rivers discharge into the oceans has been estimated to be within the range of 1.4-2.6 TW. Reverse electrodialysis (RED) is one of the emerging, membrane-based, technologies for harvesting the salinity gradient energy. A common RED stack is composed by alternately-arranged cation- and anion-exchange membranes, stacked between two electrodes. The compartments between the membranes are alternately fed with concentrated (e.g., sea water) and dilute (e.g., river water) saline solutions. Migration of the respective counter-ions through the membranes leads to ionic current between the electrodes, where an appropriate redox pair converts the chemical salinity gradient energy into electrical energy. Given the importance of the need for new sources of energy for power generation, the present study aims at better understanding and solving current challenges, associated with the RED stack design, fluid dynamics, ionic mass transfer and long-term RED stack performance with natural saline solutions as feedwaters. Chronopotentiometry was used to determinate diffusion boundary layer (DBL) thickness from diffusion relaxation data and the flow entrance effects on mass transfer were found to avail a power generation increase in RED stacks. Increasing the linear flow velocity also leads to a decrease of DBL thickness but on the cost of a higher pressure drop. Pressure drop inside RED stacks was successfully simulated by the developed mathematical model, in which contribution of several pressure drops, that until now have not been considered, was included. The effect of each pressure drop on the RED stack performance was identified and rationalized and guidelines for planning and/or optimization of RED stacks were derived. The design of new profiled membranes, with a chevron corrugation structure, was proposed using computational fluid dynamics (CFD) modeling. The performance of the suggested corrugation geometry was compared with the already existing ones, as well as with the use of conductive and non-conductive spacers. According to the estimations, use of chevron structures grants the highest net power density values, at the best compromise between the mass transfer coefficient and the pressure drop values. Finally, long-term experiments with natural waters were performed, during which fouling was experienced. For the first time, 2D fluorescence spectroscopy was used to monitor RED stack performance, with a dedicated focus on following fouling on ion-exchange membrane surfaces. To extract relevant information from fluorescence spectra, parallel factor analysis (PARAFAC) was performed. Moreover, the information obtained was then used to predict net power density, stack electric resistance and pressure drop by multivariate statistical models based on projection to latent structures (PLS) modeling. The use in such models of 2D fluorescence data, containing hidden, but extractable by PARAFAC, information about fouling on membrane surfaces, considerably improved the models fitting to the experimental data.

A domain-specific language for ETL patterns specification in Data Warehousing Systems

During the last few years many research efforts have been done to improve the design of ETL (Extract-Transform-Load) systems. ETL systems are considered very time-consuming, error-prone and complex involving several participants from different knowledge domains. ETL processes are one of the most important components of a data warehousing system that are strongly influenced by the complexity of business requirements, their changing and evolution. These aspects influence not only the structure of a data warehouse but also the structures of the data sources involved with. To minimize the negative impact of such variables, we propose the use of ETL patterns to build specific ETL packages. In this paper, we formalize this approach using BPMN (Business Process Modelling Language) for modelling more conceptual ETL workflows, mapping them to real execution primitives through the use of a domain-specific language that allows for the generation of specific instances that can be executed in an ETL commercial tool.

Automatic generation of ETL physical systems from BPMN conceptual models

ETL conceptual modeling is a very important activity in any data warehousing system project implementation. Owning a high-level system representation allowing for a clear identification of the main parts of a data warehousing system is clearly a great advantage, especially in early stages of design and development. However, the effort to model conceptually an ETL system rarely is properly rewarded. Translating ETL conceptual models directly into something that saves work and time on the concrete implementation of the system process it would be, in fact, a great help. In this paper we present and discuss a hybrid approach to this problem, combining the simplicity of interpretation and power of expression of BPMN on ETL systems conceptualization with the use of ETL patterns to produce automatically an ETL skeleton, a first prototype system, which has the ability to be executed in a commercial ETL tool like Kettle.

ATLAS Run 1 searches for direct pair production of third-generation squarks at the Large Hadron Collider

This paper reviews and extends searches for the direct pair production of the scalar supersymmetric partners of the top and bottom quarks in proton--proton collisions collected by the ATLAS collaboration during the LHC Run 1. Most of the analyses use 20 fb−1 of collisions at a centre-of-mass energy of s√=8 TeV, although in some case an additional 4.7 fb−1 of collision data at s√=7 TeV are used. New analyses are introduced to improve the sensitivity to specific regions of the model parameter space. Since no evidence of third-generation squarks is found, exclusion limits are derived by combining several analyses and are presented in both a simplified model framework, assuming simple decay chains, as well as within the context of more elaborate phenomenological supersymmetric models.

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

An object-oriented model for rapid prototyping of data path/control systems - a case study

Publicado em "Information control in manufacturing 1998 : (INCOM'98) : advances in industrial engineering : a proceedings volume from the 9th IFAC Symposium, Nancy-Metz, France, 24-26 June 1998. Vol. 2"

First- Versus Second-Generation Drug-Eluting Stents in Acute Coronary Syndromes (Katowice-Zabrze Registry)

Abstract Background: There are sparse data on the performance of different types of drug-eluting stents (DES) in acute and real-life setting. Objective: The aim of the study was to compare the safety and efficacy of first- versus second-generation DES in patients with acute coronary syndromes (ACS). Methods: This all-comer registry enrolled consecutive patients diagnosed with ACS and treated with percutaneous coronary intervention with the implantation of first- or second-generation DES in one-year follow-up. The primary efficacy endpoint was defined as major adverse cardiac and cerebrovascular event (MACCE), a composite of all-cause death, nonfatal myocardial infarction, target-vessel revascularization and stroke. The primary safety outcome was definite stent thrombosis (ST) at one year. Results: From the total of 1916 patients enrolled into the registry, 1328 patients were diagnosed with ACS. Of them, 426 were treated with first- and 902 with second-generation DES. There was no significant difference in the incidence of MACCE between two types of DES at one year. The rate of acute and subacute ST was higher in first- vs. second-generation DES (1.6% vs. 0.1%, p < 0.001, and 1.2% vs. 0.2%, p = 0.025, respectively), but there was no difference regarding late ST (0.7% vs. 0.2%, respectively, p = 0.18) and gastrointestinal bleeding (2.1% vs. 1.1%, p = 0.21). In Cox regression, first-generation DES was an independent predictor for cumulative ST (HR 3.29 [1.30-8.31], p = 0.01). Conclusions: In an all-comer registry of ACS, the one-year rate of MACCE was comparable in groups treated with first- and second-generation DES. The use of first-generation DES was associated with higher rates of acute and subacute ST and was an independent predictor of cumulative ST.

Linking Global Youth Tobacco Survey (GYTS) data to the WHO Framework Convention on Tobacco Control (FCTC): the case for the Seychelles

Tobacco control has been recognized as a main public health concern in Seychelles for the past two decades. Tobacco advertising, sponsoring and promotion has been banned for years, tobacco products are submitted to high taxes, high-profile awareness programs are organized regularly, and several other control measures have been implemented. The Republic of Seychelles was the first country to ratify the WHO Framework Convention on Tobacco Control (FCTC) in the African region. Three population-based surveys have been conducted in adults in Seychelles and results showed a substantial decrease in the prevalence of smoking among adults between 1989 and 2004. A first survey in adolescents was conducted in Seychelles in 2002 (the Global Youth Tobacco Survey, GYTS) in a representative sample of 1321 girls and boys aged 13-15 years. The results show that approximately half of students had tried smoking and a quarter of both boys and girls had smoked at least one cigarette during the past 30 days. Although "current smoking" is defined differently in adolescents (>or=1 cigarette during the past 30 days) and in adults (>or=1 cigarette per day), which precludes direct comparison, the high smoking prevalence in youth in Seychelles likely predicts an increasing prevalence of tobacco use in the next adult generation, particularly in women. GYTS 2002 also provides important data on a wide range of specific individual and societal factors influencing tobacco use. Hence, GYTS can be a powerful tool for monitoring the situation of tobacco use in adolescents, for highlighting the need for new policy and programs, and for evaluating the impact of current and future programs.

Chirality in the new generation of antidepressants: stereoselective analysis of the enantiomers of mirtazapine, N-demethylmirtazapine, and 8-hydroxymirtazapine by LC-MS.

Mirtazapine is an antidepressant that acts specifically on noradrenergic and sertonergic receptors. A LC-MS method was developed that allows the simultaneous analysis of the R-(-)- and S-(+)-enantiomers of mirtazapine (MIR), demethylmirtazapine (DMIR), and 8-hydroxymirtazapine (8-OH-MIR) in plasma of MIR-treated patients. The method involves a 3-step liquid-liquid extraction, an HPLC separation on a Chirobiotic V column, and MS detection in electrospray mode. The limit of quantification (LOQ) for all enantiomers was 0.5 ng/mL, and the intra- and interday CVs were within 3.3% to 11.7% (concentration ranges 5-50 ng/mL). A method is also presented for the quantitative analysis of glucuroconjugated MIR and 8-OH-MIR. S-(+)-8-OH-MIR is present in plasma mainly as its glucuronide. Preliminary data suggest that in all patients, except in those comedicated with CYP2D6 inhibitors such as fluoxetine and thioridazine, R-(-)-MIR concentrations were higher than those of S-(+)MIR. Moreover, fluvoxamine seems also to inhibit the metabolism of MIR. Therefore, this method seems to be suitable for the stereoselective assay of MIR and its metabolites in plasma of patients comedicated with MIR and other drugs for routine and research purposes.