Fractal dimension applied to plant identification

This article discusses methods to identify plants by analysing leaf complexity based on estimating their fractal dimension. Leaves were analyzed according to the complexity of their internal and external shapes. A computational program was developed to process, analyze and extract the features of leaf images, thereby allowing for automatic plant identification. Results are presented from two experiments, the first to identify plant species from the Brazilian Atlantic forest and Brazilian Cerrado scrublands, using fifty leaf samples from ten different species, and the second to identify four different species from genus Passiflora, using twenty leaf samples for each class. A comparison is made of two methods to estimate fractal dimension (box-counting and multiscale Minkowski). The results are discussed to determine the best approach to analyze shape complexity based on the performance of the technique, when estimating fractal dimension and identifying plants. (C) 2008 Elsevier Inc. All rights reserved.

Identification of lift-off mechanism failure for salt drill-in drilling fluid containing polymer filter cake through adsorption/desorption studies

Drilling fluid`s contact with the productive zone of horizontal or complex wells can reduce well productivity by fluid invasion in the borehole wall. Salted drilling drill-in fluid containing polymers has often been applied in horizontal or complex petroleum wells in the poorly consolidated sandstone reservoirs of the Campos basin, Rio de Janeiro, Brazil. This fluid usually consists of natural polymers such as starch and xanthan gum, which are deposited as a filter cake on the wellbore wall during the drilling. Therefore, the identification of a lift-off mechanism failure, which can be detachment or blistering and pinholing, will enable formulation improvements. increasing the chances of success during filter cake removal in open hole operations. Likewise, knowledge of drill-in drilling fluid adsorption/desorption onto sand can help understand the filter cake-rock adhesion mechanism and consequently filter cake lift-off mechanism failures. The present study aimed to identify the lift-off failure mechanism for this type of fluid filter cake studying adsorption/desorption onto SiO(2) using solutions of natural polymers, lubricants, besides the fluid itself. Ellipsometry was employed to measure this process. The adsorption/desorption studies showed that the adsorbed layer of drilling fluid onto the walls of the rock pores is made up of clusters of polymers, linked by hydrogen bonds, which results in a force of lower cohesion compared to the electrostatic interaction between silica and polymers. Consequently, it was found that the most probable filter cake failure mechanism is rupture (blistering and pinholing), which results in the formation of ducts within the filter cake. (C) 2009 Elsevier B.V. All rights reserved.

Microwave-assisted digestion procedures for biological samples with diluted nitric acid: Identification of reaction products

Microwave-assisted sample preparation using diluted nitric acid solutions is an alternative procedure for digesting organic samples. The efficiency of this procedure depends on the chemical properties of the samples and in this work it was evaluated by the determination of crude protein amount. fat and original carbon. Soybeans grains, bovine blood. bovine muscle and bovine viscera were digested in a cavity-microwave oven using oxidant mixtures in different acid concentrations. The digestion efficiency was evaluated based on the determination of residual carbon content and element recoveries using inductively coupled plasma optical emission spectrometry (ICP OES). In order to determine the main residual organic compounds, the digests were characterized by nuclear magnetic resonance (1 H NMR). Subsequently, studies concerning separation of nitrobenzoic acid isomers were performed by ion pair reversed phase liquid chromatography using a C18 stationary phase, water:acetonitrile:methanol (75:20:5, v/v/v) +0.05% (v/v) TFA as mobile phase and ultraviolet detection at 254 nm. Sample preparation based on diluted acids proved to be feasible and a recommendable alternative for organic sample digestion, reducing both the reagent volumes and the variability of the residues as a result of the process of decomposition. It was shown that biological matt-ices containing amino acids, proteins and lipids in their composition produced nitrobenzoic acid isomers and other organic compounds after cleavage of chemical bonds. (C) 2009 Elsevier B.V. All rights reserved.

Computerized identification of motor complications in Parkinson's disease

Objective: To investigate whether spirography-based objective measures are able to effectively characterize the severity of unwanted symptom states (Off and dyskinesia) and discriminate them from motor state of healthy elderly subjects. Background: Sixty-five patients with advanced Parkinson’s disease (PD) and 10 healthy elderly (HE) subjects performed repeated assessments of spirography, using a touch screen telemetry device in their home environments. On inclusion, the patients were either treated with levodopa-carbidopa intestinal gel or were candidates for switching to this treatment. On each test occasion, the subjects were asked trace a pre-drawn Archimedes spiral shown on the screen, using an ergonomic pen stylus. The test was repeated three times and was performed using dominant hand. A clinician used a web interface which animated the spiral drawings, allowing him to observe different kinematic features, like accelerations and spatial changes, during the drawing process and to rate different motor impairments. Initially, the motor impairments of drawing speed, irregularity and hesitation were rated on a 0 (normal) to 4 (extremely severe) scales followed by marking the momentary motor state of the patient into 2 categories that is Off and Dyskinesia. A sample of spirals drawn by HE subjects was randomly selected and used in subsequent analysis. Methods: The raw spiral data, consisting of stylus position and timestamp, were processed using time series analysis techniques like discrete wavelet transform, approximate entropy and dynamic time warping in order to extract 13 quantitative measures for representing meaningful motor impairment information. A principal component analysis (PCA) was used to reduce the dimensions of the quantitative measures into 4 principal components (PC). In order to classify the motor states into 3 categories that is Off, HE and dyskinesia, a logistic regression model was used as a classifier to map the 4 PCs to the corresponding clinically assigned motor state categories. A stratified 10-fold cross-validation (also known as rotation estimation) was applied to assess the generalization ability of the logistic regression classifier to future independent data sets. To investigate mean differences of the 4 PCs across the three categories, a one-way ANOVA test followed by Tukey multiple comparisons was used. Results: The agreements between computed and clinician ratings were very good with a weighted area under the receiver operating characteristic curve (AUC) coefficient of 0.91. The mean PC scores were different across the three motor state categories, only at different levels. The first 2 PCs were good at discriminating between the motor states whereas the PC3 was good at discriminating between HE subjects and PD patients. The mean scores of PC4 showed a trend across the three states but without significant differences. The Spearman’s rank correlations between the first 2 PCs and clinically assessed motor impairments were as follows: drawing speed (PC1, 0.34; PC2, 0.83), irregularity (PC1, 0.17; PC2, 0.17), and hesitation (PC1, 0.27; PC2, 0.77). Conclusions: These findings suggest that spirography-based objective measures are valid measures of spatial- and time-dependent deficits and can be used to distinguish drug-related motor dysfunctions between Off and dyskinesia in PD. These measures can be potentially useful during clinical evaluation of individualized drug-related complications such as over- and under-medications thus maximizing the amount of time the patients spend in the On state.

The role of venture capitalists in the identification and measurement of intangible assets

The increase in the importance of intangibles in business competitiveness has made investment selection more challenging to investors that, under high information asymmetry, tend to charge higher premiums to provide capital or simply deny it. Private Equity and Venture Capital (PE/VC) organizations developed contemporarily with the increase in the relevance of intangible assets in the economy. They form a specialized breed of financial intermediaries that are better prepared to deal with information asymmetry. This paper is the result of ten interviews with PE/VC organizations in Brazil. Its objective is to describe the selection process, criteria and indicators used by these organizations to identify and measure intangible assets, as well as the methods used to valuate prospective investments. Results show that PE/VC organizations rely on sophisticated methods to assess investment proposals, with specific criteria and indicators to assess the main classes of intangible assets. However, no value is given to these assets individually. The information gathered is used to understand the sources of cash flows and risks, which are then combined by discounted cash flow methods to estimate firm's value. Due to PE/VC organizations extensive experience with innovative Small and Medium-sized Enterprises (SMEs), we believe that shedding light on how PE/VC organizations deal with intangible assets brings important insights to the intangible assets debate.

Goals Software Construction Process

Generalized hyper competitiveness in the world markets has determined the need to offer better products to potential and actual clients in order to mark an advantagefrom other competitors. To ensure the production of an adequate product, enterprises need to work on the efficiency and efficacy of their business processes (BPs) by means of the construction of Interactive Information Systems (IISs, including Interactive Multimedia Documents) so that they are processed more fluidly and correctly.The construction of the correct IIS is a major task that can only be successful if the needs from every intervenient are taken into account. Their requirements must bedefined with precision, extensively analyzed and consequently the system must be accurately designed in order to minimize implementation problems so that the IIS isproduced on schedule and with the fewer mistakes as possible. The main contribution of this thesis is the proposal of Goals, a software (engineering) construction process which aims at defining the tasks to be carried out in order to develop software. This process defines the stakeholders, the artifacts, and the techniques that should be applied to achieve correctness of the IIS. Complementarily, this process suggests two methodologies to be applied in the initial phases of the lifecycle of the Software Engineering process: Process Use Cases for the phase of requirements, and; MultiGoals for the phases of analysis and design. Process Use Cases is a UML-based (Unified Modeling Language), goal-driven and use case oriented methodology for the definition of functional requirements. It uses an information oriented strategy in order to identify BPs while constructing the enterprise’s information structure, and finalizes with the identification of use cases within the design of these BPs. This approach provides a useful tool for both activities of Business Process Management and Software Engineering. MultiGoals is a UML-based, use case-driven and architectural centric methodology for the analysis and design of IISs with support for Multimedia. It proposes the analysis of user tasks as the basis of the design of the: (i) user interface; (ii) the system behaviour that is modeled by means of patterns which can combine Multimedia and standard information, and; (iii) the database and media contents. This thesis makes the theoretic presentation of these approaches accompanied with examples from a real project which provide the necessary support for the understanding of the used techniques.

Image processing algorithm for the identification of Martian dust devil tracks in MOC and HiRISE images

This paper presents a method for automatic identification of dust devils tracks in MOC NA and HiRISE images of Mars. The method is based on Mathematical Morphology and is able to successfully process those images despite their difference in spatial resolution or size of the scene. A dataset of 200 images from the surface of Mars representative of the diversity of those track features was considered for developing, testing and evaluating our method, confronting the outputs with reference images made manually. Analysis showed a mean accuracy of about 92%. We also give some examples on how to use the results to get information about dust devils, namelly mean width, main direction of movement and coverage per scene. (c) 2012 Elsevier Ltd. All rights reserved.

Innovative molecular approach to the identification of Colossoma macropomum and its hybrids

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identification of lubricant contamination by biodiesel using vibration analysis and neural network

Purpose - The purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.Design/methodology/approach - The possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.Findings - Results have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. on other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.Research limitations/implications - This study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.Practical implications Contamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy-to-use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.Originality/value - This research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.

Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

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

Identification of a new repetitive element in the sex chromosomes of Leporinus elongatus (Teleostei : Characiformes : Anostomidae): new insights into the sex chromosomes of Leporinus

Leporinus elongatus represents an interesting model for studies on chromosome evolution since it possesses a conspicuous ZZ/ZW sex chromosome system that has been characterized mainly by basic cytogenetic techniques. In the present study we describe a dispersed repetitive element ( named Le SpeI) related to the sex chromosomes of L. elongatus. Females revealed clusters of Le SpeI on the long arm of the W chromosome and in the acrocentric NOR-bearing chromosome pair. In males, the signal was restricted to the pericentromeric region of the NOR-bearing chromosomes. Considering the results obtained in the present study using FISH, NOR and C-banding, together with findings from previous studies, it can be inferred that the sex chromosome system of L. elongatus is still undergoing an evolutionary process. The data suggest novelties in relation to the sex chromosomes of the genus Leporinus with the description of a multiple sex chromosome system involving the NOR-bearing chromosomes. Therefore, it is hypothesized that the simple ZW chromosome system previously described for L. elongatus rather is a multiple Z(1)Z(1)Z(2)Z(2)/Z(1)W(1)Z(2)W(2) system. Copyright (c) 2007 S. Karger AG, Basel

Identification of Rv3852 as a nucleoid-associated protein in Mycobacterium tuberculosis

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A fuzzy inference system for identification of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behavior. In this paper, a system based on fuzzy logic systems is developed to overcome the problems usually found in the conventional mathematical models. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the fuzzy approach. Simulation results are presented to justify the validity of the proposed approach.

Identification of polycyclic aromatic hydrocarbons in sugar cane soot by gas chromatography mass spectrometry

Fly soot samples collected in the sugar cane fields after the process of burning were extracted in a Soxhlet apparatus (methylene chloride:methanol 4:1). The extracts were fractionated on silica gel Sep-Pak cartridges into three fractions. A gas chromatographic-mass spectrometric study of the fly soot extracts allowed the identification of the PAH with mutagenic and carcinogenic properties. Large amounts of aliphatic hydrocarbons, fatty acid esters and some PAHs were identified by GCMS in full scan mode. GC-MS in the selective ion monitoring mode (SIM) was suitable for the determination of many PAHs, which are often present in the burnt biomass. 31 PAHs and 7 thiophens derivatives were identified. The presence of these compounds should be regarded as a caution to workers and the general population to avoid exposure to the fly soot.

Using artificial neural networks for identification of electrical losses in transformers during the manufacturing phase

The paper describes a novel neural model to estimate electrical losses in transformer during the manufacturing phase. The network acts as an identifier of structural features on electrical loss process, so that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through experimental data taking into account core losses, copper losses, resistance, current and temperature. The results obtained in the simulations have shown that the developed technique can be used as an alternative tool to make the analysis of electrical losses on distribution transformer more appropriate regarding to manufacturing process. Thus, this research has led to an improvement on the rational use of energy.