Exergy-based method for analyzing the composition of the electricity cost generated in gas-fired combined cycle plants

The proposed method to analyze the composition of the cost of electricity is based on the energy conversion processes and the destruction of the exergy through the several thermodynamic processes that comprise a combined cycle power plant. The method uses thermoeconomics to evaluate and allocate the cost of exergy throughout the processes, considering costs related to inputs and investment in equipment. Although the concept may be applied to any combined cycle or cogeneration plant, this work develops only the mathematical modeling for three-pressure heat recovery steam generator (HRSG) configurations and total condensation of the produced steam. It is possible to study any n x 1 plant configuration (n sets of gas turbine and HRSGs associated to one steam turbine generator and condenser) with the developed model, assuming that every train operates identically and in steady state. The presented model was conceived from a complex configuration of a real power plant, over which variations may be applied in order to adapt it to a defined configuration under study [Borelli SJS. Method for the analysis of the composition of electricity costs in combined cycle thermoelectric power plants. Master in Energy Dissertation, Interdisciplinary Program of Energy, Institute of Eletro-technical and Energy, University of Sao Paulo, Sao Paulo, Brazil, 2005 (in Portuguese)]. The variations and adaptations include, for instance, use of reheat, supplementary firing and partial load operation. It is also possible to undertake sensitivity analysis on geometrical equipment parameters. (C) 2007 Elsevier Ltd. All rights reserved.

A genetic algorithm based method for deregulated electricity market dispatch

In a deregulated electricity market, optimizing dispatch capacity and transmission capacity are among the core concerns of market operators. Many market operators have capitalized on linear programming (LP) based methods to perform market dispatch operation in order to explore the computational efficiency of LP. In this paper, the search capability of genetic algorithms (GAs) is utilized to solve the market dispatch problem. The GA model is able to solve pool based capacity dispatch, while optimizing the interconnector transmission capacity. Case studies and corresponding analyses are performed to demonstrate the efficiency of the GA model.

Genetic Diversity and a PCR-Based Method for Xanthomonas axonopodis Detection in Passion Fruit

Xanthomonas axonopodis pv. passiflorae causes bacterial spot in passion fruit. It attacks the purple and yellow passion fruit as well as the sweet passion fruit. The diversity of 87 isolates of pv. passiflorae collected from across 22 fruit orchards in Brazil was evaluated using molecular profiles and statistical procedures, including an unweighted pair-group method with arithmetical averages-based dendrogram, analysis of molecular variance (AMOVA), and an assigning test that provides information on genetic structure at the population level. Isolates from another eight pathovars were included in the molecular analyses and all were shown to have a distinct repetitive sequence-based polymerase chain reaction profile. Amplified fragment length polymorphism technique revealed considerable diversity among isolates of pv. passiflorae, and AMOVA showed that most of the variance (49.4%) was due to differences between localities. Cluster analysis revealed that most genotypic clusters were homogeneous and that variance was associated primarily with geographic origin. The disease adversely affects fruit production and may kill infected plants. A method for rapid diagnosis of the pathogen, even before the disease symptoms become evident, has value for producers. Here, a set of primers (Xapas) was designed by exploiting a single-nucleotide polymorphism between the sequences of the intergenic 16S-23S rRNA spacer region of the pathovars. Xapas was shown to effectively detect all pv. passiflorae isolates and is recommended for disease diagnosis in passion fruit orchards.

A PCR-based method of screening individuals of all ages, from neonates to the elderly, for familial hyperaldosteronism type I

Aim: Unless specifically treated (glucocorticoids in low doses), Familial Hyperaldosteronism Type I(FH-I) may result in early death from stroke. We report the successful application of a rapid, polymerase chain reaction (PCR)-based method of detecting the 'hybrid' 11 beta-hydroxylase (11 beta-OHase)/aldosterone synthase (AS) gene as a screening test for FH-I. Methods: 'Long-PCR' was used to amplify, concurrently, a 4 kb fragment of AS gene (both primers AS-specific) and a 4 kb fragment of the hybrid gene (5' primer 11 beta-OHase-specific, 3'primer AS-specific) from DNA extracted from blood either collected locally or transported from elsewhere. Sample collection and transport were straightforward. This 4 kb fragment contains all the currently recognised hybrid gene 'crossover' points. Results: Within a single family, long-PCR identified all 21 individuals known to have FH-I. Hypertension was corrected in all 11 treated with glucocorticoids. Nine with normal blood pressure are being closely followed for development of hypertension. Long-PCR cord blood analysis excluded FH-I in three neonates born to affected individuals. Long-PCR newly identified two other affected families: (1) a female (60 years) with a personal and family history of stroke and her normotensive daughter (40 years), and (2) a female (51 years) previously treated for primary aldosteronism with amiloride, her two hypertensive sons (14 and 16 years) and her hypertensive mother (78 years). No false negative or false positive results have yet been encountered. At least seven other centres have successfully performed this test. Conclusion: Long-PCR is a reliable method of screening individuals of all ages for FH-I.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

A new wavelet-based method for the solution of the population balance equation

A new wavelet-based method for solving population balance equations with simultaneous nucleation, growth and agglomeration is proposed, which uses wavelets to express the functions. The technique is very general, powerful and overcomes the crucial problems of numerical diffusion and stability that often characterize previous techniques in this area. It is also applicable to an arbitrary grid to control resolution and computational efficiency. The proposed technique has been tested for pure agglomeration, simultaneous nucleation and growth, and simultaneous growth and agglomeration. In all cases, the predicted and analytical particle size distributions are in excellent agreement. The presence of moving sharp fronts can be addressed without the prior investigation of the characteristics of the processes. (C) 2001 Published by Elsevier Science Ltd.

Patient based method of assessing adverse events in clinical trials in rheumatology: the revised Stanford Toxicity Index

We describe the progress towards developing a patient rated toxicity index that meets all of the patient-important attributes defined by the OMERACT Drug Safety Working Party, These attributes are frequency, severity. importance to patient, importance to the clinician, impact on economics, impact on activities, and integration of adverse effects with benefits. The Stanford Toxicity Index (STI) has been revised to collect all attributes with the exception of impact on activities. However, since the STI is a part of the Health Assessment Questionnaire (HAQ). impact on activities is collected by the HAQ. In particular, a new question asks patients to rate overall satisfaction, taking into consideration both benefits and adverse effects. The nest step in the development of this tool is to ensure that the STI meets the OMERACT filter of truth, discrimination, and feasibility. Although truth and feasibility have been confirmed by comparisons within the ARAMIS database, discrimination needs to be assessed in clinical trials.

A comprehensive high-throughput FTIR spectroscopy-based method for evaluating the transfection event: estimating the transfection efficiency and extracting associated metabolic responses

Reporter genes are routinely used in every laboratory for molecular and cellular biology for studying heterologous gene expression and general cellular biological mechanisms, such as transfection processes. Although well characterized and broadly implemented, reporter genes present serious limitations, either by involving time-consuming procedures or by presenting possible side effects on the expression of the heterologous gene or even in the general cellular metabolism. Fourier transform mid-infrared (FT-MIR) spectroscopy was evaluated to simultaneously analyze in a rapid (minutes) and high-throughput mode (using 96-wells microplates), the transfection efficiency, and the effect of the transfection process on the host cell biochemical composition and metabolism. Semi-adherent HEK and adherent AGS cell lines, transfected with the plasmid pVAX-GFP using Lipofectamine, were used as model systems. Good partial least squares (PLS) models were built to estimate the transfection efficiency, either considering each cell line independently (R 2 ≥ 0.92; RMSECV ≤ 2 %) or simultaneously considering both cell lines (R 2 = 0.90; RMSECV = 2 %). Additionally, the effect of the transfection process on the HEK cell biochemical and metabolic features could be evaluated directly from the FT-IR spectra. Due to the high sensitivity of the technique, it was also possible to discriminate the effect of the transfection process from the transfection reagent on KEK cells, e.g., by the analysis of spectral biomarkers and biochemical and metabolic features. The present results are far beyond what any reporter gene assay or other specific probe can offer for these purposes.

Light memory operation based on a double pin SiC device

Experimental optoelectronic characterization of a p-i'(a-SiC:H)-n/pi(a-Si:H)-n heterostructure with low conductivity doped layers shows the feasibility of tailoring channel bandwidth and wavelength by optical bias through back and front side illumination. Front background enhances light-to-dark sensitivity of the long and medium wavelength range, and strongly quenches the others. Back violet background enhances the magnitude in short wavelength range and reduces the others. Experiments have three distinct programmed time slots: control, hibernation and data. Throughout the control time slot steady light wavelengths illuminate either or both sides of the device, followed by the hibernation without any background illumination. The third time slot allows a programmable sequence of different wavelengths with an impulse frequency of 6000Hz to shine upon the sensor. Results show that the control time slot illumination has an influence on the data time slot which is used as a volatile memory with the set, reset logical functions. © IFIP International Federation for Information Processing 2015.

COMPARISON BETWEEN AUTOMATED SYSTEM AND PCR-BASED METHOD FOR IDENTIFICATION AND ANTIMICROBIAL SUSCEPTIBILITY PROFILE OF CLINICAL Enterococcus spp

Enterococci are increasingly responsible for nosocomial infections worldwide. This study was undertaken to compare the identification and susceptibility profile using an automated MicrosScan system, PCR-based assay and disk diffusion assay of Enterococcus spp. We evaluated 30 clinical isolates of Enterococcus spp. Isolates were identified by MicrosScan system and PCR-based assay. The detection of antibiotic resistance genes (vancomycin, gentamicin, tetracycline and erythromycin) was also determined by PCR. Antimicrobial susceptibilities to vancomycin (30 µg), gentamicin (120 µg), tetracycline (30 µg) and erythromycin (15 µg) were tested by the automated system and disk diffusion method, and were interpreted according to the criteria recommended in CLSI guidelines. Concerning Enterococcus identification the general agreement between data obtained by the PCR method and by the automatic system was 90.0% (27/30). For all isolates of E. faecium and E. faecalis we observed 100% agreement. Resistance frequencies were higher in E. faecium than E. faecalis. The resistance rates obtained were higher for erythromycin (86.7%), vancomycin (80.0%), tetracycline (43.35) and gentamicin (33.3%). The correlation between disk diffusion and automation revealed an agreement for the majority of the antibiotics with category agreement rates of > 80%. The PCR-based assay, the van(A) gene was detected in 100% of vancomycin resistant enterococci. This assay is simple to conduct and reliable in the identification of clinically relevant enterococci. The data obtained reinforced the need for an improvement of the automated system to identify some enterococci.

Polymerase chain reaction-based method for the identification of Leishmania (Viannia) braziliensis and Leishmania (Viannia) guyanensis in mucosal tissues conserved in paraffin

ABSTRACTINTRODUCTION: In the Americas, mucosal leishmaniasis is primarily associated with infection by Leishmania (Viannia) braziliensis. However, Leishmania (Viannia) guyanensis is another important cause of this disease in the Brazilian Amazon. In this study, we aimed at detecting Leishmaniadeoxyribonucleic acid (DNA) within paraffin-embedded fragments of mucosal tissues, and characterizing the infecting parasite species.METHODS: We evaluated samples collected from 114 patients treated at a reference center in the Brazilian Amazon by polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) analyses.RESULTS: Direct examination of biopsy imprints detected parasites in 10 of the 114 samples, while evaluation of hematoxylin and eosin-stained slides detected amastigotes in an additional 17 samples. Meanwhile, 31/114 samples (27.2%) were positive for Leishmania spp. kinetoplast deoxyribonucleic acid (kDNA) by PCR analysis. Of these, 17 (54.8%) yielded amplification of the mini-exon PCR target, thereby allowing for PCR-RFLP-based identification. Six of the samples were identified as L. (V.) braziliensis, while the remaining 11 were identified as L. (V.) guyanensis.CONCLUSIONS: The results of this study demonstrate the feasibility of applying molecular techniques for the diagnosis of human parasites within paraffin-embedded tissues. Moreover, our findings confirm that L. (V.) guyanensisis a relevant causative agent of mucosal leishmaniasis in the Brazilian Amazon.

Typology based method for choosing old masonry walls inspection procedures

The diagnosis of historic masonry walls is an intricate and complex field and has been an object of research for many years. This paper aims to propose practical methodologies for the diagnosis of historic masonry walls, specifically based on their typological characteristics. In order to develop such procedures, information relating to historic masonry typologies in Portugal, classified as rural, urban and military was gathered and techniques for the assessment of historic masonry were studied. All information was integrated to develop a pattern typology oriented methodology. Developed methodology was tested and validated in a small diagnosis campaign carried out in the Guimarães Castle. Methodology was proven to be advantageous and although the study is limited and focused on the Portuguese architectural specificities, it still holds global classifications, and therefore can be useful for any diagnosis procedure of a historic masonry wall.

A performance-based method for seismic evaluation of masonry walls strengthened with RC layers

A conventional method for seismic strengthening of masonry walls is externally application of reinforced concrete layer (shotcrete). However, due to the lack of analytical and experimental information on the behavior of strengthened walls, the design procedures are usually followed based on the empirical relations. Using these design procedures have resulted in massive strengthening details in retrofitting projects. This paper presents a computational framework for nonlinear analysis of strengthened masonry walls and its versatility has been verified by comparing the numerical and experimental results. Based on the developed numerical model and available experimental information, design relations and failure modes are proposed for strengthened walls in accordance with the ASCE 41 standard. Finally, a sample masonry structure has been strengthened using the proposed and available conventional methods. It has been shown that using the proposed method results in lower strengthening details and appropriate (ductile) failure modes

proxel-based method : formalisation, analysis and applications

Simulation, modelling, proxels, PDEs, Markov chains, Petri nets, stochastic, performability, transient analysis

A conventional polymerase chain reaction-based method for the diagnosis of human schistosomiasis in stool samples from individuals in a low-endemicity area

The aim of this study was to evaluate the efficacy of a polymerase chain reaction (PCR)-based method to detect Schistosoma mansoni DNA in stool samples from individuals living in a low-endemicity area in Brazil. Of the 125 initial stool samples, 80 were ELISA reactive and eggs were identified in 19 of the samples by parasitological examination. For the PCR evaluations, 56 stool samples were selected and divided into five groups. Groups I-IV were scored negative for S. mansoni eggs by parasitological examination. Groups I and II were ELISA reactive, whereas Groups III and IV were ELISA nonreactive. Groups II and III were positive for other intestinal parasites. PCR testing scored eight samples as positive from these four groups. Group V represented the S. mansoni -positive group and it included ELISA-reactive samples that were scored positive for S. mansoni by one or more parasitological examinations (6/19 were positive by Kato-Katz method, 9/17 by saline gradient and 10/13 by Helmintex®). PCR scored 13 of these 19 samples as positive for S. mansoni . We conclude that while none of these methods yielded 100% sensitivity, a combination of techniques should be effective for improving the detection of S. mansoni infection in low-endemicity areas.