Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.

Group analysis method for fission track thermochronology

A methodology to obtain ages and thermal histories of sets of apatite samples from localities with geologically compatible characteristics is described. A methodology exploring the fact that samples with similar geological characteristics should present the same thermal history is proposed. This approach can contribute for the obtainment of more conclusive results by analysing fewer samples than it is necessary when the samples are individually analysed. In order to determine the ages, we use the absolute neutron dosimetry through thin films of natural uranium along with lambda(f) = 8.46 x 10(-17) a(-1). As an example of application of the proposed methodology, we analyse samples collected in a Brazilian region, Sao Francisco Craton, which experienced low tectonic activity. (C) 2008 Elsevier Ltd. All rights reserved.

Thermoeconomic analysis method for optimization of combined heat and power systems

This article presents an thermoeconomic analysis of cogeneration plants, applied as a rational technique to produce electric power and saturated steam. The aim of this new methodology is the minimum exergetic manufacturing cost (EMC), based on the Second Law of Thermodynamics. The decision variables selected for the optimization are the pressure and the temperature of the steam leaving the boiler in the case of using steam turbine, and the pressure ratio, turbine exhaust temperature and mass flow in the case of using gas turbines. The equations for calculating the capital costs of the components and products are formulated as a function of these decision variables. An application of the method using real data of a multinational chemical industry located in São Paulo state is presented. The conditions which establish the minimum cost are presented as finals conclusions.

Thermoeconomic analysis method for optimization of combined heat and power systems - part II

In this paper, a thermoeconomic functional analysis method based on the Second Law of Thermodynamics and applied to analyze four cogeneration systems is presented. The objective of the developed technique is to minimize the operating costs of the cogeneration plant, namely exergetic production cost (EPC), assuming fixed rates of electricity production and process steam in exergy base. In this study a comparison is made between the same four configurations of part I. The cogeneration system consisting of a gas turbine with a heat recovery steam generator, without supplementary firing, has the lowest EPC. (C) 2004 Published by Elsevier Ltd.

Thermoeconomic analysis method for optimization of combined heat and power systems. Part I

This article presents a thermoeconomic analysis of cogeneration plants, applied as a rational technique to produce electric power and saturated steam. The aim of this new methodology is the minimum Exergetic Production Cost (EPC), based on the Second Law of Thermodynamics. The variables selected for the optimization are the pressure and the temperature of the steam leaving the boiler in the case of using steam turbine, and the pressure ratio, turbine exhaust temperature and mass flow in the case of using gas turbines. The equations for calculating the capital costs of the components and products are formulated as a function of these decision variables. An application of the method using real data of a multinational chemical industry located in São Paulo state is presented. The conditions which establish the minimum cost are presented as final output. (C) 2003 Elsevier Ltd. All rights reserved.

Isotope analysis method (δ¹³C) in clarified apple juice

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Isotopic analysis method (δ13C) in apple-flavoured soft drinks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The Modified Direct Analysis Method: an Extension of the Direct Analysis Method

The purpose of this research project is to study an innovative method for the stability assessment of structural steel systems, namely the Modified Direct Analysis Method (MDM). This method is intended to simplify an existing design method, the Direct Analysis Method (DM), by assuming a sophisticated second-order elastic structural analysis will be employed that can account for member and system instability, and thereby allow the design process to be reduced to confirming the capacity of member cross-sections. This last check can be easily completed by substituting an effective length of KL = 0 into existing member design equations. This simplification will be particularly useful for structural systems in which it is not clear how to define the member slenderness L/r when the laterally unbraced length L is not apparent, such as arches and the compression chord of an unbraced truss. To study the feasibility and accuracy of this new method, a set of 12 benchmark steel structural systems previously designed and analyzed by former Bucknell graduate student Jose Martinez-Garcia and a single column were modeled and analyzed using the nonlinear structural analysis software MASTAN2. A series of Matlab-based programs were prepared by the author to provide the code checking requirements for investigating the MDM. By comparing MDM and DM results against the more advanced distributed plasticity analysis results, it is concluded that the stability of structural systems can be adequately assessed in most cases using MDM, and that MDM often appears to be a more accurate but less conservative method in assessing stability.

Lipid-poor adenomas on unenhanced CT: does histogram analysis increase sensitivity compared with a mean attenuation threshold?

OBJECTIVE: The purpose of our study was to evaluate the efficacy of CT histogram analysis for further characterization of lipid-poor adenomas on unenhanced CT. MATERIALS AND METHODS: One hundred thirty-two adrenal nodules were identified in 104 patients with lung cancer who underwent PET/CT. Sixty-five nodules were classified as lipid-rich adenomas if they had an unenhanced CT attenuation of less than or equal to 10 H. Thirty-one masses were classified as lipid-poor adenomas if they had an unenhanced CT attenuation greater than 10 H and stability for more than 1 year. Thirty-six masses were classified as lung cancer metastases if they showed rapid growth in 1 year (n = 27) or were biopsy-proven (n = 9). Histogram analysis was performed for all lesions to provide the mean attenuation value and percentage of negative pixels. RESULTS: All lipid-rich adenomas had more than 10% negative pixels; 51.6% of lipid-poor adenomas had more than 10% negative pixels and would have been classified as indeterminate nodules on the basis of mean attenuation alone. None of the metastases had more than 10% negative pixels. Using an unenhanced CT mean attenuation threshold of less than 10 H yielded a sensitivity of 68% and specificity of 100% for the diagnosis of an adenoma. Using an unenhanced CT threshold of more than 10% negative pixels yielded a sensitivity of 84% and specificity of 100% for the diagnosis of an adenoma. CONCLUSION: CT histogram analysis is superior to mean CT attenuation analysis for the evaluation of adrenal nodules and may help decrease referrals for additional imaging or biopsy.

Continuous Flow Analysis Method for Determination of Dissolved Reactive Phosphorus in Ice Cores

Phosphorus (P) is an essential macronutrient for all living organisms. Phosphorus is often present in nature as the soluble phosphate ion PO43– and has biological, terrestrial, and marine emission sources. Thus PO43– detected in ice cores has the potential to be an important tracer for biological activity in the past. In this study a continuous and highly sensitive absorption method for detection of dissolved reactive phosphorus (DRP) in ice cores has been developed using a molybdate reagent and a 2-m liquid waveguide capillary cell (LWCC). DRP is the soluble form of the nutrient phosphorus, which reacts with molybdate. The method was optimized to meet the low concentrations of DRP in Greenland ice, with a depth resolution of approximately 2 cm and an analytical uncertainty of 1.1 nM (0.1 ppb) PO43–. The method has been applied to segments of a shallow firn core from Northeast Greenland, indicating a mean concentration level of 2.74 nM (0.26 ppb) PO43– for the period 1930–2005 with a standard deviation of 1.37 nM (0.13 ppb) PO43– and values reaching as high as 10.52 nM (1 ppb) PO43–. Similar levels were detected for the period 1771–1823. Based on impurity abundances, dust and biogenic particles were found to be the most likely sources of DRP deposited in Northeast Greenland.

Application of the Equivalent Static Analysis method to the design of a steel frame structure with added viscous dampers

All the structures designed by engineers are vulnerable to natural disasters including floods and earthquakes. The energy released during strong ground motions should be dissipated by structural elements. Before 1990’s, this energy was expected to be dissipated through the beams and columns which at the same time were a part of gravity-load-resisting system. However, the main disadvantage of this idea was that gravity-resisting-frame was not repairable. Hence, during 1990’s, the idea of designing passive energy dissipation systems, including dampers, emerged. At the beginning, main problem was lack of guidelines for passive energy dissipation systems. Although till 2000 many guidelines and procedures where published, yet most of them were based on complicated analysis which was not so convenient for engineers and practitioners. In order to solve this problem recently some alternative design methods are proposed including 1. Lopez Garcia (2001) simple procedure for optimal damper configuration in MDOF structures 2. Christopoulos and Filiatrault (2006) trial and error procedure 3. Silvestri et al. (2010) Five-Step Method. 4. Palermo et al. (2015) Direct Five-Step Method. 5. Palermo et al. (2016) Simplified Equivalent Static Analysis (ESA). In this study, effectiveness and differences between last three alternative methods have been evaluated.

Laser-induced breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

Abstract A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine.

A Risk Analysis Method to Support Virtual Organization Partners’ Selection

Part 17: Risk Analysis