analytical model and measurements of the target erosion depth profile of balanced and unbalanced planar magnetron cathodes

The erosion depth profile of planar targets in balanced and unbalanced magnetron cathodes with cylindrical symmetry is measured along the target radius. The magnetic fields have rotational symmetry. The horizontal and vertical components of the magnetic field B are measured at points above the cathode target with z = 2 x 10(-3) m. The experimental data reveal that the target erosion depth profile is a function of the angle. made by B with a horizontal line defined by z = 2 x 10(-3) m. To explain this dependence a simplified model of the discharge is developed. In the scope of the model, the pathway lengths of the secondary electrons in the pre-sheath region are calculated by analytical integration of the Lorentz differential equations. Weighting these lengths by using the distribution law of the mean free path of the secondary electrons, we estimate the densities of the ionizing events over the cathode and the relative flux of the sputtered atoms. The expression so deduced correlates for the first time the erosion depth profile of the target with the angle theta. The model shows reasonably good fittings to the experimental target erosion depth profiles confirming that ionization occurs mainly in the pre-sheath zone.

Profile of women who carried out smoking cessation treatment: a systematic review

OBJECTIVE Analyze the profile of women, in health services, who carry out treatment for smoking cessation.METHODS Systematic review that used the following sources of information: Cummulative Index to Nursing and Allied Health Literature (CINAHL), PubMed,Biblioteca Virtual em Saúde (BVS), Scopus and Web of Science. We included quantitative studies that addressed the characterization of women, in health services, who carried out treatment for smoking cessation, resulting in 12 articles for analysis. The assessment of the methodological quality of the studies was performed using the instrument MAStARI from Joanna Briggs Institute.RESULTS The predominant profile of women who carried out treatment for smoking cessation in health services was composed of white, married, employed, and highly level educated women. Women who carried out the treatment for smoking cessation in specialized services had a more advanced age, were white, were married and had a diagnosis of depression. The quality level of most studies was moderate.CONCLUSIONS The profile of women who carry out treatment for smoking cessation, either in general or specialized health services, is composed of white, married, and highly level educated women. Publications about smoking women are scarce and the lack of Brazilian studies characterizing the profile of women who start treatment for smoking cessation shows the need for studies that explore this subject.

Electric vehicles as a mean to reduce, energy, emissions and electricity costs

Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs), which obtain their fuel from the grid by charging a battery, are set to be introduced into the mass market and expected to contribute to oil consumption reduction. This research is concerned with studying the potential impacts on the electric utilities of large-scale adoption of plug-in electric vehicles from the perspective of electricity demand, fossil fuels use, CO2 emissions and energy costs. Simulations were applied to the Portuguese case study in order to analyze what would be the optimal recharge profile and EV penetration in an energy-oriented, an emissions-oriented and a cost-oriented objective. The objectives considered were: The leveling of load profiles, minimization of daily emissions and minimization of daily wholesale costs. Almost all solutions point to an off-peak recharge and a 50% reduction in daily wholesale costs can be verified from a peak recharge scenario to an off-peak recharge for a 2 million EVs in 2020. A 15% improvement in the daily total wholesale costs can be verified in the costs minimization objective when compared with the off-peak scenario result.

Using the Common Cartridge profile to enhance learning content interoperability

The concept of Learning Object (LO) is crucial for the standardization on eLearning. The latest LO standard from IMS Global Learning Consortium is the IMS Common Cartridge (IMS CC) that organizes and distributes digital learning content. By analyzing this new specification we considered two interoperability levels: content and communication. A common content format is the backbone of interoperability and is the basis for content exchange among eLearning systems. Communication is more than just exchanging content; it includes also accessing to specialized systems and services and reporting on content usage. This is particularly important when LOs are used for evaluation. In this paper we analyze the Common Cartridge profile based on the two interoperability levels we proposed. We detail its data model that comprises a set of derived schemata referenced on the CC schema and we explore the use of the IMS Learning Tools Interoperability (LTI) to allow remote tools and content to be integrated into a Learning Management System (LMS). In order to test the applicability of IMS CC for automatic evaluation we define a representation of programming exercises using this standard. This representation is intended to be the cornerstone of a network of eLearning systems where students can solve computer programming exercises and obtain feedback automatically. The CC learning object is automatically generated based on a XML dialect called PExIL that aims to consolidate all the data need to describe resources within the programming exercise life-cycle. Finally, we test the generated cartridge on the IMS CC online validator to verify its conformance with the IMS CC specification.

Differences in the antigenic profile of bloodstream and cell culture derived trypomastigotes of Trypanosoma cruzi

A comparative study of the antigenic profile of bloodstream and cell culture derived trypomastigotes showed many differences in their components. Using mouse anti-T. cruzi antibodies the differences were located mostly in the 120 kDa band, whereas using chagasic patient sera the differences were located in the 85 and 52 kDa bands. These findings might explain known physiological differences between trypomatigotes obtained from cell culture and from infected blood. A brief report of this work has already been published9.

Dynamic load management in a smart home to participate in demand response events

In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

Phenylketonuria: Protein content and amino acids profile of dishes for phenylketonuric patients. The relevance of phenylalanine

Phenylketonuria is an inborn error of metabolism, involving, in most cases, a deficient activity of phenylalanine hydroxylase. Neonatal diagnosis and a prompt special diet (low phenylalanine and natural-protein restricted diets) are essential to the treatment. The lack of data concerning phenylalanine contents of processed foodstuffs is an additional limitation for an already very restrictive diet. Our goals were to quantify protein (Kjeldahl method) and amino acid (18) content (HPLC/fluorescence) in 16 dishes specifically conceived for phenylketonuric patients, and compare the most relevant results with those of several international food composition databases. As might be expected, all the meals contained low protein levels (0.67–3.15 g/100 g) with the highest ones occurring in boiled rice and potatoes. These foods also contained the highest amounts of phenylalanine (158.51 and 62.65 mg/100 g, respectively). In contrast to the other amino acids, it was possible to predict phenylalanine content based on protein alone. Slight deviations were observed when comparing results with the different food composition databases.

The role of functional polymorphisms in immune response genes as biomarkers of BCG Immunotherapy outcome in bladder cancer: Establishment of a predictive profile in a Southern Europe population

OBJECTIVE: To evaluate the predictive value of genetic polymorphisms in the context of BCG immunotherapy outcome and create a predictive profile that may allow discriminating the risk of recurrence. MATERIAL AND METHODS: In a dataset of 204 patients treated with BCG, we evaluate 42 genetic polymorphisms in 38 genes involved in the BCG mechanism of action, using Sequenom MassARRAY technology. Stepwise multivariate Cox Regression was used for data mining. RESULTS: In agreement with previous studies we observed that gender, age, tumor multiplicity and treatment scheme were associated with BCG failure. Using stepwise multivariate Cox Regression analysis we propose the first predictive profile of BCG immunotherapy outcome and a risk score based on polymorphisms in immune system molecules (SNPs in TNFA-1031T/C (rs1799964), IL2RA rs2104286 T/C, IL17A-197G/A (rs2275913), IL17RA-809A/G (rs4819554), IL18R1 rs3771171 T/C, ICAM1 K469E (rs5498), FASL-844T/C (rs763110) and TRAILR1-397T/G (rs79037040) in association with clinicopathological variables. This risk score allows the categorization of patients into risk groups: patients within the Low Risk group have a 90% chance of successful treatment, whereas patients in the High Risk group present 75% chance of recurrence after BCG treatment. CONCLUSION: We have established the first predictive score of BCG immunotherapy outcome combining clinicopathological characteristics and a panel of genetic polymorphisms. Further studies using an independent cohort are warranted. Moreover, the inclusion of other biomarkers may help to improve the proposed model.

Ultrasound velocity profile (UVP) measurements in shallow open-channel flows

1st European IAHR Congress, 6-4 May, Edinburgh, Scotland

Experimental dam-break waves profile analysis: horizontal mobile bed

River Flow, Vol. 2

O papel dos sistemas de Non-Intrusive Load Monitoring para a eficiência energética do setor residencial

A sustentabilidade energética do planeta é uma preocupação corrente e, neste sentido, a eficiência energética afigura-se como sendo essencial para a redução do consumo em todos os setores de atividade. No que diz respeito ao setor residencial, o indevido comportamento dos utilizadores aliado ao desconhecimento do consumo dos diversos aparelhos, são factores impeditivos para a redução do consumo energético. Uma ferramenta importante, neste sentido, é a monitorização de consumos nomeadamente a monitorização não intrusiva, que apresenta vantagens económicas relativamente à monitorização intrusiva, embora levante alguns desafios na desagregação de cargas. Abordou-se então, neste documento, a temática da monitorização não intrusiva onde se desenvolveu uma ferramenta de desagregação de cargas residenciais, sobretudo de aparelhos que apresentavam elevados consumos. Para isso, monitorizaram-se os consumos agregados de energia elétrica, água e gás de seis habitações do município de Vila Nova de Gaia. Através da incorporação dos vetores de água e gás, a acrescentar ao da energia elétrica, provou-se que a performance do algoritmo de desagregação de aparelhos poderá aumentar, no caso de aparelhos que utilizem simultaneamente energia elétrica e água ou energia elétrica e gás. A eficiência energética é também parte constituinte deste trabalho e, para tal, implementaram-se medidas de eficiência energética para uma das habitações em estudo, de forma a concluir as que exibiam maior potencial de poupança, assim como rápidos períodos de retorno de investimento. De um modo geral, os objetivos propostos foram alcançados e espera-se que num futuro próximo, a monitorização de consumos não intrusiva se apresente como uma solução de referência no que respeita à sustentabilidade energética do setor residencial.

Lysotypes and plasmidial profile of Salmonella Serovar Typhimurium isolated from children with enteric processes in the cities of Rio de Janeiro, RJ, and Salvador, BA - Brazil

The lysotypes, plasmidial profiles, and profiles of resistance to antimicrobial agents were determined in 111 Salmonella Typhimurium strains isolated from feces and blood of children treated in Rio de Janeiro and in Salvador. Six distinct lysotypes (19, 41, 97, 105, 120 and 193) were recognized, with a predominance of lysotype 193 (59.7%) in Rio de Janeiro and of phage type 105 (38.4) in Salvador. Approximately 86.7% of the lysotype 193 strains presented multiple resistance to more than six antimicrobial agents, whereas 93% of lysotype 105 strains were fully susceptible. More than 90% of the strains presented plasmids distributed into 36 different profiles in Rio de Janeiro and into 10 profiles in Salvador. A 40 MDa plasmid was the most frequent (47%) in the strains from Rio de Janeiro, whereas a 61 MDa plasmid predominated (14.5%) in Salvador. Combined analysis of plasmid profile and classification into lysotypes (especially those belonging to types 105 and 103, proved to be more discriminatory than the other methods applied).

A Data Mining Framework for Electric Load Profiling

This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.

Stochastic Framework for Strategic Decision-making of Load-serving Entities for Day-ahead Market

The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.