The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

Damage detection in beams by using artificial neural networks and dynamical parameters

In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal flexibility. It was considered that only a number of modes were available and that only vertical degrees of freedom were measured. The reliability of the proposed methodology is assessed from the generation of random damages scenarios and the definition of three types of errors, which can be found during the damage identification process. Results show that the methodology can reliably determine the damage scenarios. However, its application to large beams may be limited by the high computational cost of training the neural network.

Riverbed: A Novel User-Steered Image Segmentation Method Based on Optimum Boundary Tracking

This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths.

Evaluation of sun protection factor of cosmetic formulations by a simple visual in vitro method mimicking the in vivo method

A new concept for in vitro visual evaluation of sun protection factor (SPF) of cosmetic formulations based on a supramolecular ultraviolet (UV) dosimeter was clearly demonstrated. The method closely parallels the method validated for in vivo evaluation and relies on the determination of the slightest perceptible bleaching of an iron-complex dye/nanocrystallinetitanium dioxide interface (UV dosimeter) in combination with an artificial skin substrate simulating the actual human skin in the presence and absence of a cosmetic formulation. The successful evaluation of SPF was ensured by the similarity of the erythema response of our dosimeter and human skin to UV light irradiation. A good linear correlation of in vitro and in vivo data up to SPF 40 confirmed the effectiveness of such a simple, cheap, and fast method. In short, here we unravel a convenient and accessible visual FPS evaluation method that can help improving the control on cosmetic products contributing to the reduction of skin cancer, one of the critical public health issues nowadays. (C) 2011 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:726732, 2012

Evaluation of Inductively Coupled Plasma Mass Spectrometry for Determining Ca, Cu, Fe, Mg, Mn, Se and Zn in Bovine Semen Samples using a Simple Sample Dilution Method

A simple and fast method for the determination of Ca, Cu, Fe, Mg, Mn, Se and Zn in bovine semen by quadrupole inductively coupled plasma spectrometry (q-ICP-MS) is described. Prior to analysis, samples (200 mu L) were diluted 1:50 in a solution containing 0.01% v/v Triton (R) X-100 and 0.5% v/v nitric acid and directly analyzed by ICP-MS. The limits of detection of the method are 0.3, 0.03, 0.2, 0.04, 0.04, 0.03 and 0.03 mu g L-1 for Ca-44, Cu-63, Fe-57, Mg-24, Zn-64, Se-82 and Mn-55, respectively. For purposes of comparison and method validation, four ordinary bovine semen samples were directly analyzed by ICP-MS and by flame atomic absorption spectrometry (FAAS) or graphite furnace atomic absorption spectrometry (GF AAS), with no statistical difference between the techniques at the 95% level when applying the t-test. Then, the proposed method was applied in the determinations of Ca, Cu, Fe, Mg, Mn, Se and Zn in collected samples of bovine semen from different breeds, which are used in reproduction programs and artificial insemination.

Chaotic encryption method based on life-like cellular automata

A chaotic encryption algorithm is proposed based on the "Life-like" cellular automata (CA), which acts as a pseudo-random generator (PRNG). The paper main focus is to use chaos theory to cryptography. Thus, CA was explored to look for this "chaos" property. This way, the manuscript is more concerning on tests like: Lyapunov exponent, Entropy and Hamming distance to measure the chaos in CA, as well as statistic analysis like DIEHARD and ENT suites. Our results achieved higher randomness quality than others ciphers in literature. These results reinforce the supposition of a strong relationship between chaos and the randomness quality. Thus, the "chaos" property of CA is a good reason to be employed in cryptography, furthermore, for its simplicity, low cost of implementation and respectable encryption power. (C) 2012 Elsevier Ltd. All rights reserved.

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks

Abstract Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.

Evaluation of inductively coupled plasma mass spectrometry for determining Ca, Cu, Fe, Mg, Mn, Se and Zn in bovine semen samples using a simple sample dilution method

A simple and fast method for the determination of Ca, Cu, Fe, Mg, Mn, Se and Zn in bovine semen by quadrupole inductively coupled plasma spectrometry (q-ICP-MS) is described. Prior to analysis, samples (200 µL) were diluted 1:50 in a solution containing 0.01% v/v Triton® X-100 and 0.5% v/v nitric acid and directly analyzed by ICP-MS. The limits of detection of the method are 0.3, 0.03, 0.2, 0.04, 0.04, 0.03 and 0.03 µg L-1 for 44Ca, 63Cu, 57Fe, 24Mg, 64Zn, 82Se and 55Mn, respectively. For purposes of comparison and method validation, four ordinary bovine semen samples were directly analyzed by ICP-MS and by flame atomic absorption spectrometry (FAAS) or graphite furnace atomic absorption spectrometry (GF AAS), with no statistical difference between the techniques at the 95% level when applying the t-test. Then, the proposed method was applied in the determinations of Ca, Cu, Fe, Mg, Mn, Se and Zn in collected samples of bovine semen from different breeds, which are used in reproduction programs and artificial insemination.

Implementation of a robust optical flow method for color images

We analyse the influence of colour information in optical flow methods. Typically, most of these techniques compute their solutions using grayscale intensities due to its simplicity and faster processing, ignoring the colour features. However, the current processing systems have minimized their computational cost and, on the other hand, it is reasonable to assume that a colour image offers more details from the scene which should facilitate finding better flow fields. The aim of this work is to determine if a multi-channel approach supposes a quite enough improvement to justify its use. In order to address this evaluation, we use a multi-channel implementation of a well-known TV-L1 method. Furthermore, we review the state-of-the-art in colour optical flow methods. In the experiments, we study various solutions using grayscale and RGB images from recent evaluation datasets to verify the colour benefits in motion estimation.

Method development using ICP-MS and LA-ICP-MS and their application in environmental and material science

Within this PhD thesis several methods were developed and validated which can find applicationare suitable for environmental sample and material science and should be applicable for monitoring of particular radionuclides and the analysis of the chemical composition of construction materials in the frame of ESS project. The study demonstrated that ICP-MS is a powerful analytical technique for ultrasensitive determination of 129I, 90Sr and lanthanides in both artificial and environmental samples such as water and soil. In particular ICP-MS with collision cell allows measuring extremely low isotope ratios of iodine. It was demonstrated that isotope ratios of 129I/127I as low as 10-7 can be measured with an accuracy and precision suitable for distinguishing sample origins. ICP-MS with collision cell, in particular in combination with cool plasma conditions, reduces the influence of isobaric interferences on m/z = 90 and is therefore well-suited for 90Sr analysis in water samples. However, the applied ICP-CC-QMS in this work is limited for the measurement of 90Sr due to the tailing of 88Sr+ and in particular Daly detector noise. Hyphenation of capillary electrophoresis with ICP-MS was shown to resolve atomic ions of all lanthanides and polyatomic interferences. The elimination of polyatomic and isobaric ICP-MS interferences was accomplished without compromising the sensitivity by the use of a high resolution mode as available on ICP-SFMS. Combination of laser ablation with ICP-MS allowed direct micro and local uranium isotope ratio measurements at the ultratrace concentrations on the surface of biological samples. In particular, the application of a cooled laser ablation chamber improves the precision and accuracy of uranium isotopic ratios measurements in comparison to the non-cooled laser ablation chamber by up to one order of magnitude. In order to reduce the quantification problem, a mono gas on-line solution-based calibration was built based on the insertion of a microflow nebulizer DS-5 directly into the laser ablation chamber. A micro local method to determine the lateral element distribution on NiCrAlY-based alloy and coating after oxidation in air was tested and validated. Calibration procedures involving external calibration, quantification by relative sensitivity coefficients (RSCs) and solution-based calibration were investigated. The analytical method was validated by comparison of the LA-ICP-MS results with data acquired by EDX.

Nondestructive evaluation of concrete compression strength by means of Artificial Neural Network (ANN)

The evaluation of structural performance of existing concrete buildings, built according to standards and materials quite different to those available today, requires procedures and methods able to cover lack of data about mechanical material properties and reinforcement detailing. To this end detailed inspections and test on materials are required. As a consequence tests on drilled cores are required; on the other end, it is stated that non-destructive testing (NDT) cannot be used as the only mean to get structural information, but can be used in conjunction with destructive testing (DT) by a representative correlation between DT and NDT. The aim of this study is to verify the accuracy of some formulas of correlation available in literature between measured parameters, i.e. rebound index, ultrasonic pulse velocity and compressive strength (SonReb Method). To this end a relevant number of DT and NDT tests has been performed on many school buildings located in Cesena (Italy). The above relationships have been assessed on site correlating NDT results to strength of core drilled in adjacent locations. Nevertheless, concrete compressive strength assessed by means of NDT methods and evaluated with correlation formulas has the advantage of being able to be implemented and used for future applications in a much more simple way than other methods, even if its accuracy is strictly limited to the analysis of concretes having the same characteristics as those used for their calibration. This limitation warranted a search for a different evaluation method for the non-destructive parameters obtained on site. To this aim, the methodology of neural identification of compressive strength is presented. Artificial Neural Network (ANN) suitable for the specific analysis were chosen taking into account the development presented in the literature in this field. The networks were trained and tested in order to detect a more reliable strength identification methodology.

Design-based stereology to quantify structural properties of artificial and natural snow using thin sections

The quantification of the structural properties of snow is traditionally based on model-based stereology. Model-based stereology requires assumptions about the shape of the investigated structure. Here, we show how the density, specific surface area, and grain boundary area can be measured using a design-based method, where no assumptions about structural properties are necessary. The stereological results were also compared to X-ray tomography to control the accuracy of the method. The specific surface area calculated with the stereological method was 19.8 ± 12.3% smaller than with X-ray tomography. For the density, the stereological method gave results that were 11.7 ± 12.1% larger than X-ray tomography. The statistical analysis of the estimates confirmed that the stereological method and the sampling used are accurate. This stereological method was successfully tested on artificially produced ice beads but also on several snow types. Combining stereology and polarisation microscopy provides a good estimate of grain boundary areas in ice beads and in natural snow, with some limitatio

Penetration ability and microleakage of a fissure sealant applied on artificial and natural enamel fissure caries

OBJECTIVES AND METHODS: This study investigated the sealing ability of a current available unfilled fissure sealant applied over sound (n=80), artificially created (n=80) and naturally carious fissures (n=80) under different humidity conditions (90+/-2 and 45+/-2% relative humidity) and etching times (40 and 60s). All samples were submitted to 5000 thermal cycles and examined by light microscopy after sectioning. Microleakage, penetration ability, fissure type, fissure entrance angle, sealant occlusal length, caries location and caries depth were assessed. RESULTS: The significantly longer sealant occlusal length and larger entrance angle exhibited by shallow fissures, contributed to their higher microleakage and smaller amounts of unfilled areas compared to deep fissures. Sealant microleakage was significantly influenced by the condition of the enamel (sound, artificial and natural caries) and the caries location in the fissures, but not by enamel caries depth (D1 and D2), etching time, or humidity condition. Natural caries exhibited significantly higher microleakage than sound or artificially created carious fissures. CONCLUSIONS: Based on the results of this study, it can be concluded that location of caries in the fissure rather than its depth should be taken into account when applying a fissure sealant. When the borders of the fissure sealant are on carious enamel, a significantly higher microleakage must be expected. The artificial caries model was not a suitable method to assess the behavior of natural fissure caries.

DEVELOPMENT OF A PREDICTIVE COMBUSTION MODEL OF A SPARK IGNITED ENGINE WITH GASOLINE DIRECT INJECTION, VARIABLE VALVE TIMING, DURATION AND LIFT TECHNOLOGIES

There is a need by engine manufactures for computationally efficient and accurate predictive combustion modeling tools for integration in engine simulation software for the assessment of combustion system hardware designs and early development of engine calibrations. This thesis discusses the process for the development and validation of a combustion modeling tool for Gasoline Direct Injected Spark Ignited Engine with variable valve timing, lift and duration valvetrain hardware from experimental data. Data was correlated and regressed from accepted methods for calculating the turbulent flow and flame propagation characteristics for an internal combustion engine. A non-linear regression modeling method was utilized to develop a combustion model to determine the fuel mass burn rate at multiple points during the combustion process. The computational fluid dynamic software Converge ©, was used to simulate and correlate the 3-D combustion system, port and piston geometry to the turbulent flow development within the cylinder to properly predict the experimental data turbulent flow parameters through the intake, compression and expansion processes. The engine simulation software GT-Power © is then used to determine the 1-D flow characteristics of the engine hardware being tested to correlate the regressed combustion modeling tool to experimental data to determine accuracy. The results of the combustion modeling tool show accurate trends capturing the combustion sensitivities to turbulent flow, thermodynamic and internal residual effects with changes in intake and exhaust valve timing, lift and duration.

Extracorporeal membrane oxygenation (ECMO): extended indications for artificial support of both heart and lungs

Extracorporeal membrane oxygenation (ECMO) was used to achieve temporary artificial support in cardiac and pulmonary function in 22 patients from 1987 to September 1990. Standard indications were postcardiotomy cardiogenic shock (n = 4), neonatal (n = 1) and adult respiratory distress syndrome (n = 4). ECMO was also used for extended indications, such as graft failure following heart (n = 11) or lung transplantation (n = 2). In six of these cases ECMO was instituted as a bridge device to subsequent retransplantation of either the heart (n = 4) or one lung (n = 2). One out of nine patients supported by ECMO for standard indications, and two out of 13 patients supported for extended indications are long-term survivors. This series illustrates the results with ECMO in emergency situations, in patients under immunosuppressive protocols, or in patients with advanced lung failure requiring almost complete artificial gas exchange. In such complex situations, ECMO does provide stabilization until additional therapeutic measures are in effect. ECMO cannot be recommended for postoperative cardiogenic shock but short-term ECMO support is an accepted method in most cases with graft failure or pulmonary failure or other origin.