Desenvolvimento de métodos para quantificação de benzilpenicilina em medicamentos veterinários e seus resíduos em leite bovino e caprino por UFLC-DAD

The Benzylpenicillin (PENG) have been as the active ingredient in veterinary medicinal products, to increase productivity, due to its therapeutic properties. However, one of unfortunate quality and used indiscriminately, resulting in residues in foods exposed to human consumption, especially in milk that is essential to the diet of children and the ageing. Thus, it is indispensable to develop new methods able to detect this waste food, at levels that are toxic to human health, in order to contribute to the food security of consumers and collaborate with regulatory agencies in an efficient inspection. In this work, were developed methods for the quality control of veterinary drugs based on Benzylpenicillin (PENG) that are used in livestock production. Additionally, were validated methodologies for identifying and quantifying the antibiotic residues in milk bovine and caprine. For this, the analytical control was performed two steps. At first, the groups of samples of medicinal products I, II, III, IV and V, individually, were characterized by medium infrared spectroscopy (4000 – 600 cm-1). Besides, 37 samples, distributed in these groups, were analyzed by spectroscopy in the ultraviolet and near infrared region (UV VIS NIR) and Ultra Fast Liquid Chromatograph coupled to linear arrangement photodiodes (UFLC-DAD). The results of the characterization indicated similarities, between PENG and reference standard samples, primarily in regions of 1818 to 1724 cm-1 of ν C=O that shows primary amides features of PENG. The method by UFLC-DAD presented R on 0.9991. LOD of 7.384 × 10-4 μg mL-1. LOQ of 2.049 × 10-3 μg mL-1. The analysis shows that 62.16% the samples presented purity ≥ 81.21%. The method by spectroscopy in the UV VIS NIR presented medium error ≤ 8 – 12% between the reference and experimental criteria, indicating is a secure choice for rapid determination of PENG. In the second stage, was acquiring a method for the extraction and isolation of PENG by the addition of buffer McIlvaine, used for precipitation of proteins total, at pH 4.0. The results showed excellent recovery values PENG, being close to 92.05% of samples of bovine milk (method 1). While samples of milk goats (method 2) the recovery of PENG were 95.83%. The methods for UFLC-DAD have been validated in accordance with the maximum residue limit (LMR) of 4 μg Kg-1 standardized by CAC/GL16. Validation of the method 1 indicated R by 0.9975. LOD of 7.246 × 10-4 μg mL-1. LOQ de 2.196 × 10-3 μg mL-1. The application of the method 1 showed that 12% the samples presented concentration of residues of PENG > LMR. The method 2 indicated R by 0.9995. LOD 8.251 × 10-4 μg mL-1. LOQ de 2.5270 × 10-3 μg mL-1. The application of the method showed that 15% of the samples were above the tolerable. The comparative analysis between the methods pointed better validation for LCP samples, because the reduction of the matrix effect, on this account the tcalculs < ttable, caused by the increase of recovery of the PENG. In this mode, all the operations developed to deliver simplicity, speed, selectivity, reduced analysis time and reagent use and toxic solvents, particularly if compared to the established methodologies.

Desenvolvimento e validação de testes de fluxo lateral para a detecção de cultivares geneticamente modificados e de aflatoxinas em produtos agrícolas

The expansion of cultivated areas with genetically modified crops (GM) is a worldwide phenomenon, stimulating regulatory authorities to implement strict procedures to monitor and verify the presence of GM varieties in agricultural crops. With the constant growing of plant cultivating areas all over the world, consumption of aflatoxin-contaminated food also increased. Aflatoxins correspond to a class of highly toxic contaminants found in agricultural products that can have harmful effects on human and animal health. Therefore, the safety and quality evaluation of agricultural products are important issues for consumers. Lateral flow tests (strip tests) is a promising method for the detection both proteins expressed in GM crops and aflatoxins-contaminated food samples. The advantages of this technique include its simplicity, rapidity and cost-effective when compared to the conventional methods. In this study, two novel and sensitive strip tests assay were developed for the identification of: (i) Cry1Ac and Cry8Ka5 proteins expressed in GM cotton crops and; (ii) aflatoxins from agricultural products. The first strip test was developed using a sandwhich format, while the second one was developed using a competitive format. Gold colloidal nanoparticles were used as detector reagent when coated with monoclonal antibodies. An anti-species specific antibody was sprayed at the nitrocellulose membrane to be used as a control line. To validate the first strip test, GM (Bollgard I® e Planta 50- EMBRAPA) and non-GM cotton leaf (Cooker 312) were used. The results showed that the strip containing antibodies for the identification of Cry1Ac and Cry8Ka5 proteins was capable of correctly distinguishing between GM samples (positive result) and non-GM samples (negative result), in a high sensitivity manner. To validate the second strip test, artificially contaminated soybean with Aspergillus flavus (aflatoxin-producing fungus) was employed. Food samples, such as milk and soybean, were also evaluated for the presence of aflatoxins. The strip test was capable to distinguish between samples with and without aflatoxins samples, at a sensitivity concentration of 0,5 μg/Kg. Therefore, these results suggest that the strip tests developed in this study can be a potential tool as a rapid and cost-effective method for detection of insect resistant GM crops expressing Cry1Ac and Cry8Ka5 and aflatoxins from food samples.

Desenvolvimento e validação de testes de fluxo lateral para a detecção de cultivares geneticamente modificados e de aflatoxinas em produtos agrícolas

The expansion of cultivated areas with genetically modified crops (GM) is a worldwide phenomenon, stimulating regulatory authorities to implement strict procedures to monitor and verify the presence of GM varieties in agricultural crops. With the constant growing of plant cultivating areas all over the world, consumption of aflatoxin-contaminated food also increased. Aflatoxins correspond to a class of highly toxic contaminants found in agricultural products that can have harmful effects on human and animal health. Therefore, the safety and quality evaluation of agricultural products are important issues for consumers. Lateral flow tests (strip tests) is a promising method for the detection both proteins expressed in GM crops and aflatoxins-contaminated food samples. The advantages of this technique include its simplicity, rapidity and cost-effective when compared to the conventional methods. In this study, two novel and sensitive strip tests assay were developed for the identification of: (i) Cry1Ac and Cry8Ka5 proteins expressed in GM cotton crops and; (ii) aflatoxins from agricultural products. The first strip test was developed using a sandwhich format, while the second one was developed using a competitive format. Gold colloidal nanoparticles were used as detector reagent when coated with monoclonal antibodies. An anti-species specific antibody was sprayed at the nitrocellulose membrane to be used as a control line. To validate the first strip test, GM (Bollgard I® e Planta 50- EMBRAPA) and non-GM cotton leaf (Cooker 312) were used. The results showed that the strip containing antibodies for the identification of Cry1Ac and Cry8Ka5 proteins was capable of correctly distinguishing between GM samples (positive result) and non-GM samples (negative result), in a high sensitivity manner. To validate the second strip test, artificially contaminated soybean with Aspergillus flavus (aflatoxin-producing fungus) was employed. Food samples, such as milk and soybean, were also evaluated for the presence of aflatoxins. The strip test was capable to distinguish between samples with and without aflatoxins samples, at a sensitivity concentration of 0,5 μg/Kg. Therefore, these results suggest that the strip tests developed in this study can be a potential tool as a rapid and cost-effective method for detection of insect resistant GM crops expressing Cry1Ac and Cry8Ka5 and aflatoxins from food samples.

Modelagem da degradação de fenol em efluentes aquosos através do processo de foto-fenton

Advanced Oxidation Processes (AOP) are techniques involving the formation of hydroxyl radical (HO•) with high organic matter oxidation rate. These processes application in industry have been increasing due to their capacity of degrading recalcitrant substances that cannot be completely removed by traditional processes of effluent treatment. In the present work, phenol degrading by photo-Fenton process based on addition of H2O2, Fe2+ and luminous radiation was studied. An experimental design was developed to analyze the effect of phenol, H2O2 and Fe2+ concentration on the fraction of total organic carbon (TOC) degraded. The experiments were performed in a batch photochemical parabolic reactor with 1.5 L of capacity. Samples of the reactional medium were collected at different reaction times and analyzed in a TOC measurement instrument from Shimadzu (TOC-VWP). The results showed a negative effect of phenol concentration and a positive effect of the two other variables in the TOC degraded fraction. A statistical analysis of the experimental design showed that the hydrogen peroxide concentration was the most influent variable in the TOC degraded fraction at 45 minutes and generated a model with R² = 0.82, which predicted the experimental data with low precision. The Visual Basic for Application (VBA) tool was used to generate a neural networks model and a photochemical database. The aforementioned model presented R² = 0.96 and precisely predicted the response data used for testing. The results found indicate the possible application of the developed tool for industry, mainly for its simplicity, low cost and easy access to the program.

Modelagem da degradação de fenol em efluentes aquosos através do processo de foto-fenton

Advanced Oxidation Processes (AOP) are techniques involving the formation of hydroxyl radical (HO•) with high organic matter oxidation rate. These processes application in industry have been increasing due to their capacity of degrading recalcitrant substances that cannot be completely removed by traditional processes of effluent treatment. In the present work, phenol degrading by photo-Fenton process based on addition of H2O2, Fe2+ and luminous radiation was studied. An experimental design was developed to analyze the effect of phenol, H2O2 and Fe2+ concentration on the fraction of total organic carbon (TOC) degraded. The experiments were performed in a batch photochemical parabolic reactor with 1.5 L of capacity. Samples of the reactional medium were collected at different reaction times and analyzed in a TOC measurement instrument from Shimadzu (TOC-VWP). The results showed a negative effect of phenol concentration and a positive effect of the two other variables in the TOC degraded fraction. A statistical analysis of the experimental design showed that the hydrogen peroxide concentration was the most influent variable in the TOC degraded fraction at 45 minutes and generated a model with R² = 0.82, which predicted the experimental data with low precision. The Visual Basic for Application (VBA) tool was used to generate a neural networks model and a photochemical database. The aforementioned model presented R² = 0.96 and precisely predicted the response data used for testing. The results found indicate the possible application of the developed tool for industry, mainly for its simplicity, low cost and easy access to the program.

Projeto iterativo, simulação, análise e otimização de máquina a relutância variável monofásica

Variable reluctance motors have been increasingly used as an alternative for variable speed and high speed drives in many industrial applications, due to many advantages like the simplicity of construction, robustness, and low cost. The most common applications in recent years are related to aeronautics, electric and hybrid vehicles and wind power generation. This paper explores the theory, operation, design procedures and analysis of a variable reluctance machine. An iterative design methodology is introduced and used to design a 1.25 kW prototype. For the analysis of the machine two methods are used, an analytical method and the finite element simulation. The results obtained by both methods are compared. The results of finite element simulation are used to determine the inductance profiles and torque of the prototype. The magnetic saturation is examined visually and numerically in four critical points of the machine. The data collected in the simulation allow the verification of design and operating limits for the prototype. Moreover, the behavior of the output quantities is analyzed (inductance, torque and magnetic saturation) by variation of physical dimensions of the motor. Finally, a multiobjective optimization using Differential Evolution algorithms and Genetic Algorithms for switched reluctance machine design is proposed. The optimized variables are rotor and stator polar arcs, and the goals are to maximize the average torque, the average torque per copper losses and the average torque per core volume. Finally, the initial design and optimized design are compared.

Discriminating ambulation using a smart sensing plate

The automated sensing scheme described in this paper has the potential to automatically capture, discriminate and classify transients in gait. The mechanical simplicity of the walking platform offers advantages over standard force plates. There is less restriction on dimensions offering the opportunity for multi-contact and multiple steps. This addresses the challenge of patient targeting and the evaluation of patients in a variety of ambulatory applications. In this work the sensitivity of the distributive tactile sensing method has been investigated experimentally. Using coupled time series data from a small number of sensors, gait patterns are compared with stored templates using a pattern recognition algorithm. By using a neural network these patterns were interpreted classifying normal and affected walking events with an accuracy of just under 90%. This system has potential in gait analysis and rehabilitation as a tool for early diagnosis in walking disorders, for determining response to therapy and for identifying changes between pre and post operative gait. Copyright © 2009 by ASME.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Influence of Outlet Boundary Conditions on Cerebrovascular Aneurysm Hemodynamics

Computational fluid dynamic (CFD) studies of blood flow in cerebrovascular aneurysms have potential to improve patient treatment planning by enabling clinicians and engineers to model patient-specific geometries and compute predictors and risks prior to neurovascular intervention. However, the use of patient-specific computational models in clinical settings is unfeasible due to their complexity, computationally intensive and time-consuming nature. An important factor contributing to this challenge is the choice of outlet boundary conditions, which often involves a trade-off between physiological accuracy, patient-specificity, simplicity and speed. In this study, we analyze how resistance and impedance outlet boundary conditions affect blood flow velocities, wall shear stresses and pressure distributions in a patient-specific model of a cerebrovascular aneurysm. We also use geometrical manipulation techniques to obtain a model of the patient’s vasculature prior to aneurysm development, and study how forces and stresses may have been involved in the initiation of aneurysm growth. Our CFD results show that the nature of the prescribed outlet boundary conditions is not as important as the relative distributions of blood flow through each outlet branch. As long as the appropriate parameters are chosen to keep these flow distributions consistent with physiology, resistance boundary conditions, which are simpler, easier to use and more practical than their impedance counterparts, are sufficient to study aneurysm pathophysiology, since they predict very similar wall shear stresses, time-averaged wall shear stresses, time-averaged pressures, and blood flow patterns and velocities. The only situations where the use of impedance boundary conditions should be prioritized is if pressure waveforms are being analyzed, or if local pressure distributions are being evaluated at specific time points, especially at peak systole, where the use of resistance boundary conditions leads to unnaturally large pressure pulses. In addition, we show that in this specific patient, the region of the blood vessel where the neck of the aneurysm developed was subject to abnormally high wall shear stresses, and that regions surrounding blebs on the aneurysmal surface were subject to low, oscillatory wall shear stresses. Computational models using resistance outlet boundary conditions may be suitable to study patient-specific aneurysm progression in a clinical setting, although several other challenges must be addressed before these tools can be applied clinically.

Unraveling flp-11/flp-32 dichotomy in nematodes

FMRFamide-like peptide (FLP) signalling systems are core to nematode neuromuscular function. Novel drug discovery efforts associated with nematode FLP/FLP receptor biology are advanced through the accumulation of basic biological data that can reveal subtle complexities within the neuropeptidergic system. This study reports the characterisation of FMRFamide-like peptide encoding gene-11 (flp-11) and FMRFamide-like peptide encoding gene-32 (flp-32), two distinct flp genes which encode the analogous peptide, AMRN(A/S)LVRFamide, in multiple nematode species - the only known example of this phenomenon within the FLPergic system of nematodes. Using bioinformatics, in situ hybridisation, immunocytochemistry and behavioural assays we show that: (i) flp-11 and -32 are distinct flp genes expressed individually or in tandem across multiple nematode species, where they encode a highly similar peptide; (ii) flp-11 does not appear to be the most widely expressed flp in Caenorhabditis elegans; (iii) in species expressing both flp-11 and flp-32, flp-11 displays a conserved, restricted expression pattern across nematode clades and lifestyles; (iv) in species expressing both flp-11 and flp-32, flp-32 expression is more widespread and less conserved than flp-11; (v) in species expressing only flp-11, the flp-11 expression profile is more similar to the flp-32 profile observed in species expressing both; and (vi) FLP-11 peptides inhibit motor function in multiple nematode species. The biological significance and evolutionary origin of flp-11 and -32 peptide duplication remains unclear despite attempts to identify a common ancestor; this may become clearer as the availability of genomic data improves. This work provides insight into the complexity of the neuropeptidergic system in nematodes, and begins to examine how nematodes may compensate for structural neuronal simplicity. From a parasite control standpoint this work underscores the importance of basic biological data, and has wider implications for the utility of C. elegans as a model for parasite neurobiology.

Footbridge system identification using wireless inertial measurement units for force and response measurements

With the main focus on safety, design of structures for vibration serviceability is often overlooked or mismanaged, resulting in some high profile structures failing publicly to perform adequately under human dynamic loading due to walking, running or jumping. A standard tool to inform better design, prove fitness for purpose before entering service and design retrofits is modal testing, a procedure that typically involves acceleration measurements using an array of wired sensors and force generation using a mechanical shaker. A critical but often overlooked aspect is using input (force) to output (response) relationships to enable estimation of modal mass, which is a key parameter directly controlling vibration levels in service.

This paper describes the use of wireless inertial measurement units (IMUs), designed for biomechanics motion capture applications, for the modal testing of a 109 m footbridge. IMUs were first used for an output-only vibration survey to identify mode frequencies, shapes and damping ratios, then for simultaneous measurement of body accelerations of a human subject jumping to excite specific vibrations modes and build up bridge deck accelerations at the jumping location. Using the mode shapes and the vertical acceleration data from a suitable body landmark scaled by body mass, thus providing jumping force data, it was possible to create frequency response functions and estimate modal masses.

The modal mass estimates for this bridge were checked against estimates obtained using an instrumented hammer and known mass distributions, showing consistency among the experimental estimates. Finally, the method was used in an applied research application on a short span footbridge where the benefits of logistical and operational simplicity afforded by the highly portable and easy to use IMUs proved extremely useful for an efficient evaluation of vibration serviceability, including estimation of modal masses.

Hur grafiska formgivare runt om i världen uppfattar skandinavisk grafisk design

Syftet med föreliggande studie har varit att kartlägga hur grafiska formgivare runt om i världen uppfattar skandinavisk grafisk design. 53 deltagare från industriländer deltog i studien som använde en kombination av mail-intervjuer och enkäter. Resultaten från denna studie indikerar att, oavsett kontinent, upplevs skandinavisk grafisk design som enkel och funktionell. Layouten uppfattades som rutnätsbaserad med mycket ljusrum och få grafiska element. Monokroma färger som svart, vit och grå utan gradienter och skuggor uppfattades som typiska för skandinavisk grafisk design; följt av jord- och pastellfärger. Sanserifer var mest förknippade med skandinavisk grafisk design. Motiv ansågs i denna studie att användas sparsamt, men när de används avbildar de naturen eller geometriska former. Foton och illustrationer ansågs användas ungefär lika mycket, illustrationer hade en smärre större preferens. Den upplevda påverkan av skandinavisk grafisk design varierade mellan deltagarna. Deltagarna som tyckte att påverkan var stor, ansåg att detta berodde på förespråkandet av enkelhet och funktion, sammanflätning av designområden och/eller frammaning av hållbar grafisk design. Deltagarna som ansåg att påverkan var låg, tyckte att för lite publicitet var en bidragande faktor.De flesta deltagarna i denna undersökning ansåg att skandinavisk grafisk design var enklare i jämförelse med vad de kunde se i sina hemländer. Vidare tyckte afrikanska, asiatiska och sydamerikanska deltagare  att färgerna hade lägre kroma.

A simplified finite element model for assessing steel fibre reinforced concrete structural performance

The present numerical investigation offers evidence concerning the validity and objectivity of the predictions of a simple, yet practical, finite element model concerning the responses of steel fibre reinforced concrete structural elements under static monotonic and cyclic loading. Emphasis is focused on realistically describing the fully brittle tensile behaviour of plain concrete and the contribution of steel fibres on the post-cracking behaviour it exhibits. The good correlation exhibited between the numerical predictions and their experimental counterparts reveals that, despite its simplicity, the subject model is capable of providing realistic predictions concerning the response of steel fibre reinforced concrete structural configurations exhibiting both ductile and brittle modes of failure without requiring recalibration.

Materiais à base de Sr(Ti,Nb)O3 para sensores lambda

Os sensores lambda resistivos possuem as vantagens de simplicidade e menor custo relativamente à utilização generalizada de sensores potenciométricos de oxigénio. Nesse sentido, os titanatos de estrôncio têm sido alvo de diversos estudos. Para a produção de uma relação inequívoca entre a condutividade destes materiais e a pressão parcial de oxigénio é necessária a adição de um dopante dador que suprime a condução eletrónica do tipo-p na região de pressões parciais de oxigénio próximas de ar. Contudo, a adição de um dopante dador produz respostas lentas destes materiais quando densos a variações da pressão parcial de oxigénio. Além da preparação usual dos pós por reação do estado sólido, foram preparadas diversas composições por mecanossíntese. Tal relaciona-se com o fato exaustivamente reportado de as amostras destes materiais, especialmente quando dopados com dadores, apresentarem comportamentos dependentes das condições de processamento. Teve ainda o intuito de avaliar a viabilidade da sua preparação por este método, e consequentemente verificar se este método de preparação, que presumivelmente produzirá pós com composição mais homogénea e mais reativos, permite alterar/manipular a resposta obtida por amostras com eles produzidas. Foram preparados diversos filmes, tipologia muito usada na produção de sensores resistivos, e amostras porosas com diversas composições à base de titanato de estrôncio produzidos com variadas condições de processamento. Foram realizadas diversas caracterizações sobre estes espécimes numa tentativa de melhor compreender as propriedades destes materiais e a dependência destas com parâmetros microestruturais como o tamanho de grão e a porosidade. Foi verificado que os exemplares de titanato de estrôncio não dopado, quer em filmes quer em amostras porosas, apresentam um comportamento elétrico semelhante ao apresentado por amostras densas deste material. Apurou-se ainda, que as suas características apresentam uma variação ténue com a alteração das condições de processamento. Já espécimes de titanato de estrôncio dopados com dador revelam uma forte dependência das suas propriedades com as condições de processamento utilizadas, nomeadamente, a temperatura de sinterização e o tempo de permanência a essa temperatura. Para o fabrico de sensores resistivos de oxigénio poderá ser preferível o recurso a amostras porosas pelo facto de mais facilmente se manipularem as suas características microestruturais e devido à exclusão dos problemas associados à interação entre o substrato de alumina e o filme. As composições não dopadas são as indicadas para esta função se a gama de pressões de oxigénio a avaliar for relativamente pouco extensa sendo aconselhadas as composições dopadas com dador se for pretendida uma medição da pressão parcial de oxigénio em zonas mais extensas correspondentes à queima com deficiência ou excesso de oxigénio. Mesmo em amostras de elevada porosidade poderá ocorrer resposta transiente do material dopado com dador.

A concorrência fiscal num contexto de competitividade

Dissertação de Mestrado em Fiscalidade