Design and optimization of na ultra wideband and compact microwave antenna for radiometric monitoring of brain temperature

We present the modeling efforts on antenna design and frequency selection to monitor brain temperature during prolonged surgery using noninvasive microwave radiometry. A tapered log-spiral antenna design is chosen for its wideband characteristics that allow higher power collection from deep brain. Parametric analysis with the software HFSS is used to optimize antenna performance for deep brain temperature sensing. Radiometric antenna efficiency (eta) is evaluated in terms of the ratio of power collected from brain to total power received by the antenna. Anatomical information extracted from several adult computed tomography scans is used to establish design parameters for constructing an accurate layered 3-D tissue phantom. This head phantom includes separate brain and scalp regions, with tissue equivalent liquids circulating at independent temperatures on either side of an intact skull. The optimized frequency band is 1.1-1.6 GHz producing an average antenna efficiency of 50.3% from a two turn log-spiral antenna. The entire sensor package is contained in a lightweight and low-profile 2.8 cm diameter by 1.5 cm high assembly that can be held in place over the skin with an electromagnetic interference shielding adhesive patch. The calculated radiometric equivalent brain temperature tracks within 0.4 degrees C of the measured brain phantom temperature when the brain phantom is lowered 10. C and then returned to the original temperature (37 degrees C) over a 4.6-h experiment. The numerical and experimental results demonstrate that the optimized 2.5-cm log-spiral antenna is well suited for the noninvasive radiometric sensing of deep brain temperature.

Machine learning Vasicek model calibration with Gaussian processes

In this article, we calibrate the Vasicek interest rate model under the risk neutral measure by learning the model parameters using Gaussian processes for machine learning regression. The calibration is done by maximizing the likelihood of zero coupon bond log prices, using mean and covariance functions computed analytically, as well as likelihood derivatives with respect to the parameters. The maximization method used is the conjugate gradients. The only prices needed for calibration are zero coupon bond prices and the parameters are directly obtained in the arbitrage free risk neutral measure.

Numerical 3D modeling of heat transfer in human tissues for microwave radiometry monitoring of Brown fat metabolismo

Background: Brown adipose tissue (BAT) plays an important role in whole body metabolism and could potentially mediate weight gain and insulin sensitivity. Although some imaging techniques allow BAT detection, there are currently no viable methods for continuous acquisition of BAT energy expenditure. We present a non-invasive technique for long term monitoring of BAT metabolism using microwave radiometry. Methods: A multilayer 3D computational model was created in HFSS™ with 1.5 mm skin, 3-10 mm subcutaneous fat, 200 mm muscle and a BAT region (2-6 cm3) located between fat and muscle. Based on this model, a log-spiral antenna was designed and optimized to maximize reception of thermal emissions from the target (BAT). The power absorption patterns calculated in HFSS™ were combined with simulated thermal distributions computed in COMSOL® to predict radiometric signal measured from an ultra-low-noise microwave radiometer. The power received by the antenna was characterized as a function of different levels of BAT metabolism under cold and noradrenergic stimulation. Results: The optimized frequency band was 1.5-2.2 GHz, with averaged antenna efficiency of 19%. The simulated power received by the radiometric antenna increased 2-9 mdBm (noradrenergic stimulus) and 4-15 mdBm (cold stimulus) corresponding to increased 15-fold BAT metabolism. Conclusions: Results demonstrated the ability to detect thermal radiation from small volumes (2-6 cm3) of BAT located up to 12 mm deep and to monitor small changes (0.5°C) in BAT metabolism. As such, the developed miniature radiometric antenna sensor appears suitable for non-invasive long term monitoring of BAT metabolism.

Soluções para monitorização, salvaguarda de configurações e segurança na rede do banco BNP Paribas Personal Finance S. A. em Vila Nova De Gaia

Mestrado em Engenharia Electrotécnica e de Computadores - Área de Especialização de Telecomunicações

Water-contact patterns and schistosoma mansoni infection in a rural community in northeast Brazil

We evaluated the influence of water-related human activities, contaminative behaviour, house location, education and socio-economic status on endemic Schistosoma mansoni infection. The study was conducted in a hilry non-irrigated area of rural northeast Brazil amongst a defined population of subsistence farmers, of whom 93% were infected by age 20. The area was mapped, water bodies were surveyed, and a detailed questionnaire was performed on each household. Infection was assessed by duplicate stool examinations using the sensitive Bell technique to quantify egg excretion. For each household, and index of intensity of infection was computed by grouping individual log-transformed egg counts as an age-sex adjusted Z score. Few households had a sanitary installation or a domestic water supply. However, neither water-contact nor contaminative behavior were indiscriminate. The people made considerable effort to defaecate far from a water source, to obtain household drinking water from the cleanest source, and to bathe only at certain sites where privacy is assured. Land ownership and literacy correlated poorly with the household index of intensity of infection. The key influence on infection status was the relative location of the house and snail-free or snail colonized water sources. In this area, a safe domestic water supply is the critical input needed to achieve definitive control of endemic Schistosomiasis.

Modelo com regimes para os preços e a liquidez de acções em bolsa

Dissertação apresentada à Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de mestre em Matemática e Aplicações - Ramo Actuariado, Estatística e Investigação Operacional

An implementation of dynamic fully compressed suffix trees

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

Sondagem de Belverde (Cenozóico, Península de Setúbal, Portugal). Diagrafias

In the aim of the project "Recognition of the Miocene of the distal region of the Lower Tagus Basin through a borehole with continuous sampling", Temperature, Natural Gamma Ray, Neutron (almost in all the borehole), Sonic, SP and SPR (in two small sections in upper and lower parts of the Miocene Series) geophysical logs were carried on. Interpretation of those logs and comparison with chronological, lithostratigraphical, micropaleontological and clay mineraIs data; helped in the definition of depositional sequences and to obtain paleoenvironmental reconstructions that could lead to a better understanding of the evolution of the Setúbal Península and Lisboa regions Miocene gulf. Log data agree with the lithologic succession observed in the Belverde borehole, essentially silty sandstones/sandy siltstones (with variable clay content) to clays, often with marly intercalations. Sonic logs (and Neutron logs, in general) reflect the sediments porosity. The higher acoustic velocities are often related to compact/massive layers as claystones and/or limestones and rather fossiliferous marly layers. Lower values are obtained for porous, silty sandstones (fossiliferous and with scarce clay content) and bio-calcareous sandstones. As indicative, we obtained the mean values of 2500-3000m/s for the higher velocities and 1300-1600m/s for the lowest ones. ln Natural Gamma Ray log, the radiation peaks can be correlated to often fossiliferous marly micaceous layers. Radioactive micas are present. It seems that the gamma peaks and the depositional sequences previously defined for the Lower Tagus Basin (see Antunes et al., 1999, 2000; Pais et al., 2002) can be correlated, taking also into account the whole available micropaleontological, palynological and isotopic evidence.

Electrochemical immunosensor for the analysis of the breast cancer biomarker HER2 ECD

Human epidermal growth factor receptor 2 (HER2) is a breast cancer biomarker that plays a major role in promoting breast cancer cell proliferation and malignant growth. The extracellular domain (ECD) of HER2 can be shed into the blood stream and its concentration is measurable in the serum fraction of blood. In this work an electrochemical immunosensor for the analysis of HER2 ECD in human serum samples was developed. To achieve this goal a screen-printed carbon electrode, modified with gold nanoparticles, was used as transducer surface. A sandwich immunoassay, using two monoclonal antibodies, was employed and the detection of the antibody–antigen interaction was performed through the analysis of an enzymatic reaction product by linear sweep voltammetry. Using the optimized experimental conditions the calibration curve (ip vs. log[HER2 ECD]) was established between 15 and 100 ng/mL and a limit of detection (LOD) of 4.4 ng/mL was achieved. These results indicate that the developed immunosensor could be a promising tool in breast cancer diagnostics, patient follow-up and monitoring of metastatic breast cancer since it allows quantification in a useful concentration range and has an LOD below the established cut-off value (15 ng/mL).

Malaria serology: performance of six Plasmodium falciparum antigen extracts and of three ways of determining serum titers in IgG and IgM-ELISA

The study evaluated six Plasmodium falciparum antigen extracts to be used in the IgG and IgM enzyme-linked immunosorbent assays (ELISA), for malaria diagnosis and epidemiological studies. Results obtained with eighteen positive and nine negative control sera indicated that there were statistically significant differences among these antigen extracts (Multifactor ANOVA, p< 0.0001). Urea, sodium deoxycholate and Zwittergent antigen extracts performed better than did the three others, their features being very similar for the detection of IgG antibodies. Urea, alkaline and sodium deoxycholate antigen extracts proved to be better than the others for the detection of IgM antibodies. A straight line relationship was found between the optical densities (or their respective log 10) and the log 10 of antibody dilutions, with a very constant slope. Thus serum titers could be determined by direct titration and by two different equations, needing only one serum dilution. For IgM antibody detections, log 10 expression gave results that better correlated with direct titration (95% Bonferroni). For IgG antibody detections, the titer differences were not significant. The reproducibility of antibody titers and antigen batches was also evaluated, giving satisfactory results.

Prognostic modelling of breast cancer patients: a benchmark of predictive models with external validation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores – Sistemas Digitais e Percepcionais pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Implementação do método de suspensão quantitativa para avaliar a actividade bactericida de desinfectantes químicos, de acordo com a Norma Europeia EN 1040

As bactérias patogénicas presentes nos sistemas de processamento de alimentos podem ser potencialmente causadoras de doenças alimentares graves, quando sobrevivem à acção bactericida de desinfectantes. Esta acção depende da eficácia das substâncias activas que fazem parte da formulação do desinfectante e das condições ambientais onde se processa a interacção desinfectante – bactéria, sendo ainda específica para cada estirpe bacteriana. Este trabalho teve, como propósito, a implementação de um método que permita avaliar, in vitro, a eficácia bactericida de desinfectantes comerciais contra estirpes bacterianas que são potencialmente causadores de doenças de origem alimentar. A eficácia do desinfectante foi avaliada seguindo a Norma EN1040 e aplicando o método de diluição-neutralização. Para além das estirpes recomendadas naquele documento normativo, nomeadamente, Pseudomonas aeruginosa e Staphylococcus aureus, foram também utilizadas Escherichia coli, Enterococcus faecalis, Salmonella Typhimurium e Listeria monocytogenes. Os desinfectantes foram seleccionados com base nas suas formulações, tendo sido escolhidos desinfectantes cujos princípios activos são, respectivamente: tensioactivos aniónicos; alcalis inorgânicos; hidrocloreto de biguanida polimérica; álcool etoxilado ou cloreto benzalcónio. Foram seleccionados como neutralizantes: tampão fosfato, tiosulfato de sódio, gema de ovo fresca e polisorbato 80 com histidina. Após cada ensaio, o número de bactérias sobreviventes foi obtido pelo cálculo da redução logarítmica decimal, a partir do número de unidades formadoras de colónia presentes em cada placa. A eficácia do desinfectante, na inactivação de cada estirpe alvo, foi classificada numa escala de redução logarítmica à qual 5 log corresponde a redução mínima aceitável do número de colónias quando o tempo de contacto é de 5 minutos, e a temperatura do ensaio é 20ºC. Conclui-se que o método de diluição-neutralização é sensível para todas as estirpes testadas. A gema de ovo fresca revelou ser o melhor neutralizante para desinfectantes contendo tensioactivos aniónicos, enquanto o tampão fosfato é mais adequado para neutralizar desinfectantes contendo alcalis inorgânicos. Porém, nenhum dos neutralizantes testados mostrou ser adequado para os desinfectantes contendo cloreto de benzalcónio ou hidrocloreto biguanida polimérica ou álcool etoxilado. Conclui-se também que as condições laboratoriais implementadas são as adequadas para testar a acção bactericida de desinfectantes utilizados em sistemas de processamento de alimentos.

Immunological status of ENL (Erythema Nodosum Leprosum) patients: its relationship to bacterial load and levels of circulanting IL-2R

Recent data suggest that the clinical course of reactional states in leprosy is closely related to the cytokine profile released locally or systemically by the patients. In the present study, patients with erythema nodosum leprosum (ENL) were grouped according to the intensity of their clinical symptoms. Clinical and immunological aspects of ENL and the impact of these parameters on bacterial load were assessed in conjunction with patients' in vitro immune response to mycobacterial antigens. In 10 out of the 17 patients tested, BI (bacterial index) was reduced by at least 1 log from leprosy diagnosis to the onset of their first reactional episode (ENL), as compared to an expected 0.3 log reduction in the unreactional group for the same MDT (multidrug therapy) period. However, no difference in the rate of BI reduction was noted at the end of MDT among ENL and unreactional lepromatous patients. Accordingly, although TNF-alpha (tumor necrosis factor) levels were enhanced in the sera of 70.6% of the ENL patients tested, no relationship was noted between circulating TNF-alpha levels and the decrease in BI detected at the onset of the reactional episode. Evaluation of bacterial viability of M. leprae isolated from the reactional lesions showed no growth in the mouse footpads. Only 20% of the patients demonstrated specific immune response to M. leprae during ENL. Moreover, high levels of soluble IL-2R (interleukin-2 receptor) were present in 78% of the patients. Circulating anti-neural (anti-ceramide and anti-galactocerebroside antibodies) and anti-mycobacterial antibodies were detected in ENL patients' sera as well, which were not related to the clinical course of disease. Our data suggest that bacterial killing is enhanced during reactions. Emergence of specific immune response to M. leprae and the effective role of TNF-alpha in mediating fragmentation of bacteria still need to be clarified.

In vivo and in vitro Plasmodium falciparum Resistance to Chloroquine, Amodiaquine and Quinine in the Brazilian Amazon

In order to study the chemoresistance of Plasmodium falciparum to commonly used antimalarial drugs in Brazil the authors have studied ten patients with falciparum malaria, acquired in the Brazilian Amazon region. Patients were submitted to in vivo study of drug sensitivity, after chemotherapy with either 4-aminoquinolines (chloroquine or amodiaquine) or quinine. Adequate drug absorption was confirmed by standard urine excretion tests for antimalarials. Eight patients could be followed up to 28 days. Among these in vivo resistance (R I and R II responses) was seen in all patients who received 4-amino-quinolines. One patient treated with quinine exhibited a R III response. Peripheral blood samples of the same patients were submitted to in vitro microtests for sensitivity to antimalarials. Out of nine successful tests, resistance to chloroquine and amodiaquine was found in 100% and resistance to quinine in 11.11% of isolates. Probit analysis of log dose-response was used to determine effective concentrations EC50, EC90 and EC99 to the studied drugs. Good correlation between in vivo and in vitro results was seen in six patients. The results emphasize high levels of P. falciparum resistance to 4- aminoquinolines and suggest an increase in resistance to quinine in the Brazilian Amazon region, reinforcing the need for continuous monitoring of drug sensitivity to adequate chemotherapy according to the most efficacious drug regimens