Institutional and matrix support and its relationship with primary healthcare

OBJECTIVE To analyze whether the level of institutional and matrix support is associated with better certification of primary healthcare teams.METHODS In this cross-sectional study, we evaluated two kinds of primary healthcare support – 14,489 teams received institutional support and 14,306 teams received matrix support. Logistic regression models were applied. In the institutional support model, the independent variable was “level of support” (as calculated by the sum of supporting activities for both modalities). In the matrix support model, in turn, the independent variables were the supporting activities. The multivariate analysis has considered variables with p < 0.20. The model was adjusted by the Hosmer-Lemeshow test.RESULTS The teams had institutional and matrix supporting activities (84.0% and 85.0%), respectively, with 55.0% of them performing between six and eight activities. For the institutional support, we have observed 1.96 and 3.77 chances for teams who had medium and high levels of support to have very good or good certification, respectively. For the matrix support, the chances of their having very good or good certification were 1.79 and 3.29, respectively. Regarding to the association between institutional support activities and the certification, the very good or good certification was positively associated with self-assessment (OR = 1.95), permanent education (OR = 1.43), shared evaluation (OR = 1.40), and supervision and evaluation of indicators (OR = 1.37). In regards to the matrix support, the very good or good certification was positively associated with permanent education (OR = 1.50), interventions in the territory (OR = 1.30), and discussion in the work processes (OR = 1.23).CONCLUSIONS In Brazil, supporting activities are being incorporated in primary healthcare, and there is an association between the level of support, both matrix and institutional, and the certification result.

Jamming detection in GNSS signals using the sample covariance matrix.

We propose a blind method to detect interference in GNSS signals whereby the algorithms do not require knowledge of the interference or channel noise features. A sample covariance matrix is constructed from the received signal and its eigenvalues are computed. The generalized likelihood ratio test (GLRT) and the condition number test (CNT) are developed and compared in the detection of sinusoidal and chirp jamming signals. A computationally-efficient decision threshold was proposed for the CNT.

Algorithm-oriented design of efficient many-core architectures applied to dense matrix multiplication

Recent integrated circuit technologies have opened the possibility to design parallel architectures with hundreds of cores on a single chip. The design space of these parallel architectures is huge with many architectural options. Exploring the design space gets even more difficult if, beyond performance and area, we also consider extra metrics like performance and area efficiency, where the designer tries to design the architecture with the best performance per chip area and the best sustainable performance. In this paper we present an algorithm-oriented approach to design a many-core architecture. Instead of doing the design space exploration of the many core architecture based on the experimental execution results of a particular benchmark of algorithms, our approach is to make a formal analysis of the algorithms considering the main architectural aspects and to determine how each particular architectural aspect is related to the performance of the architecture when running an algorithm or set of algorithms. The architectural aspects considered include the number of cores, the local memory available in each core, the communication bandwidth between the many-core architecture and the external memory and the memory hierarchy. To exemplify the approach we did a theoretical analysis of a dense matrix multiplication algorithm and determined an equation that relates the number of execution cycles with the architectural parameters. Based on this equation a many-core architecture has been designed. The results obtained indicate that a 100 mm(2) integrated circuit design of the proposed architecture, using a 65 nm technology, is able to achieve 464 GFLOPs (double precision floating-point) for a memory bandwidth of 16 GB/s. This corresponds to a performance efficiency of 71 %. Considering a 45 nm technology, a 100 mm(2) chip attains 833 GFLOPs which corresponds to 84 % of peak performance These figures are better than those obtained by previous many-core architectures, except for the area efficiency which is limited by the lower memory bandwidth considered. The results achieved are also better than those of previous state-of-the-art many-cores architectures designed specifically to achieve high performance for matrix multiplication.

Preliminary study on the production of functionally graded materials by friction stir processing

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

Matrix converter as unified power flow controller: design and implementation of decoupled direct power controllers

This paper presents the design and implementation of direct power controllers for three-phase matrix converters (MC) operating as Unified Power Flow Controllers (UPFC). Theoretical principles of the decoupled linear power controllers of the MC-UPFC to minimize the cross-coupling between active and reactive power control are established. From the matrix converter based UPFC model with a modified Venturini high frequency PWM modulator, decoupled controllers for the transmission line active (P) and reactive (Q) power direct control are synthesized. Simulation results, obtained from Matlab/Simulink, are presented in order to confirm the proposed approach. Results obtained show decoupled power control, zero error tracking, and fast responses with no overshoot and no steady-state error.

On derivatives and norms of generalized matrix functions and respective symmetric powers

In recent papers, the authors obtained formulas for directional derivatives of all orders, of the immanant and of the m-th xi-symmetric tensor power of an operator and a matrix, when xi is a character of the full symmetric group. The operator norm of these derivatives was also calculated. In this paper, similar results are established for generalized matrix functions and for every symmetric tensor power.

Sparse matrix multiplication on a reconfigurable many-core architecture

Sparse matrix-vector multiplication (SMVM) is a fundamental operation in many scientific and engineering applications. In many cases sparse matrices have thousands of rows and columns where most of the entries are zero, while non-zero data is spread over the matrix. This sparsity of data locality reduces the effectiveness of data cache in general-purpose processors quite reducing their performance efficiency when compared to what is achieved with dense matrix multiplication. In this paper, we propose a parallel processing solution for SMVM in a many-core architecture. The architecture is tested with known benchmarks using a ZYNQ-7020 FPGA. The architecture is scalable in the number of core elements and limited only by the available memory bandwidth. It achieves performance efficiencies up to almost 70% and better performances than previous FPGA designs.

The effect of water inorganic matrix in ibuprofen adsorption onto activated carbon for water and wastewater treatment

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Spatial neighborhood matrix computation: Inverse distance weighted versus binary contiguity

Paper presented at Geo-Spatial Crossroad GI_Forum, Salzburg, Austria.

Matrix fractional systems

This paper addresses the matrix representation of dynamical systems in the perspective of fractional calculus. Fractional elements and fractional systems are interpreted under the light of the classical Cole–Cole, Davidson–Cole, and Havriliak–Negami heuristic models. Numerical simulations for an electrical circuit enlighten the results for matrix based models and high fractional orders. The conclusions clarify the distinction between fractional elements and fractional systems.

Development and implementation of strategies for the incorporation of reinforcing elements in aluminium alloys by solid state processing

Dissertação para obtenção do Grau de Mestre em Engenharia Mecânica

Marcadores inflamatórios de instabilidade da placa aterosclerótica coronária : caraterização e potencial utilização clínica

RESUMO:Introdução: Reviu-se o conhecimento epidemiológico, fisiopatológico e clínico atual sobre a doença coronária, da sua génese até ao evento agudo, o Enfarte Agudo do Miocárdio (EAM). Valorizou-se, em especial, a teoria inflamatória da aterosclerose, que foi objeto de grandes desenvolvimentos na última década. Marcadores de instabilidade da placa aterosclerótica coronária: Aprofundou-se o conhecimento da placa aterosclerótica coronária instável. Descreveram-se detalhadamente os biomarcadores clínicos e laboratoriais associados à instabilidade da placa, com particular ênfase nos mecanismos inflamatórios. Objetivos:Estão divididos em dois pontos fundamentais:(1) Estudar em doentes com EAM a relação existente entre as moléculas inflamatórias: Interleucina-6 (IL-6), Fator de Necrose Tumoral-α (TNF-α) e Metaloproteinase de Matriz-3 (MMP3), não usados em contexto clínico, com um marcador inflamatório já em uso clínico: a Proteína C-Reativa ultrassensível (hs-CRP). Avaliar a relação de todas as moléculas inflamatórias com um biomarcador de lesão miocárdica: a Troponina Cardíaca I (cTnI). (2) Avaliar, no mesmo contexto de EAM, a Resposta de Fase Aguda (RFA) . Pretende-se demonstrar o impacto deste fenómeno, com repercussão clínica generalizada, no perfil lipídico e nos biomarcadores inflamatórios dos doentes. Métodos:(1) Estudo observacional prospetivo de doentes admitidos consecutivamente por EAM (grupo EAM) numa única unidade coronária, após exclusão de trauma ou infeção. Doseamento no sangue periférico, na admissão, de IL-6, TNF-α, MMP3, hs-CRP e cTnI. Este último biomarcador foi valorizado também nos valores séricos obtidos 6-9 horas depois. Procedeu-se a correlação linear (coeficiente de Pearson, de Rho-Spearman e determinação do R2) entre os 3 marcadores estudados com os valores de hs-CRP e de cTnI (valores da admissão e 6 a 9 horas após). Efetuou-se o cálculo dos coeficientes de regressão linear múltipla entre cTnI da admissão e cTnI 6-9h após, com o conjunto dos fatores inflamatórios estudados. (2) Estudo caso-controlo entre o grupo EAM e uma população aleatória de doentes seguidos em consulta de cardiologia, após exclusão de eventos cardiovasculares de qualquer território (grupo controlo) e também sem infeção ou trauma. Foram doseados os mesmos marcadores inflamatórios no grupo controlo e no grupo EAM. Nos dois grupos dosearam-se, ainda, as lipoproteínas: Colesterol total (CT), Colesterol HDL (HDLc), com as suas subfrações 2 e 3 (HDL 2 e HDL3), Colesterol LDL oxidado (LDLox),Triglicéridos (TG), Lipoproteína (a) [Lp(a)], Apolipoproteína A1 (ApoA1), Apolipoproteína B (ApoB) e Apolipoproteína E (ApoE). Definiram-se, em cada grupo, os dados demográficos, fatores de risco clássicos, terapêutica cardiovascular e o uso de anti-inflamatórios. Procedeu-se a análise multivariada em relação aos dados demográficos, fatores de risco e à terapêutica basal. Compararam-se as distribuições destas mesmas caraterísticas entre os dois grupos, assim como os valores séricos respetivos para as lipoproteínas estudadas. Procedeu-se à correlação entre as moléculas inflamatórias e as lipoproteínas, para todos os doentes estudados. Encontraram-se os coeficientes de regressão linear múltipla entre cada marcador inflamatório e o conjunto das moléculas lipídicas, por grupo. Finalmente, efetuou-se a comparação estatística entre os marcadores inflamatórios do grupo controlo e os marcadores inflamatórios do grupo EAM. Resultados: (1) Correlações encontradas, respetivamente, Pearson, Rho-Spearman e regressão-R2: IL-6/hs-CRP 0,549, p<0,001; 0,429, p=0,001; 0,302, p<0,001; MMP 3/hsCRP 0,325, p=0,014; 0,171, p=0,202; 0,106, p=0,014; TNF-α/hs-CRP 0,261, p=0,050; 0,315, p=0,017; 0,068, p=0.050; IL-6/cTnI admissão 0,486, p<0,001; 0,483, p<0,001; 0,236, p<0,001; MMP3/cTnI admissão 0,218, p=0,103; 0,146, p=0,278; 0,048, p=0,103; TNF-α/cTnI admissão 0,444, p=0,001; 0,380, p=0,004; 0,197, p=0,001; IL-6/cTnI 6-9h 0,676, p<0,001; 0,623, p<0,001; 0,456, p<0,01; MMP3/cTnI 6-9h 0,524, p=0,001; 0,149, p=0,270; 0,275, p<0,001; TNF-α/cTnI 6-9h 0,428, p=0,001, 0,452, p<0,001, 0,183, p<0,001. A regressão linear múltipla cTnI admissão/marcadores inflamatórios produziu: (R=0,638, R2=0,407) p<0,001 e cTnI 6-9h/marcadores inflamatórios (R=0,780, R2=0,609) p<0,001. (2) Significância da análise multivariada para idade (p=0,029), IMC>30 (p=0.070), AAS (p=0,040) e grupo (p=0,002). Diferenças importantes entre as distribuições dos dados basais entre os dois grupos (grupo controlo vs EAM): idade (47,95±11,55 vs 68,53±2,70 anos) p<0.001; sexo feminino (18,18 vs 22,80%) p=0,076; diabetes mellitus (9,09% vs 36,84%) p=0,012; AAS (18,18 vs 66,66%) p<0,001; clopidogrel (4,54% vs 66,66%) p=0,033; estatinas (31,81% vs 66,14%) p=0,078; beta-bloqueadores (18,18% vs 56,14%) p=0,011; anti-inflamatórios (4,54% vs 33,33%) p=0,009. Resultados da comparação entre os dois grupos quanto ao padrão lipídico (média±dp ou mediana/intervalo interquartil, grupo controlo vs EAM): CT (208,45±35,03 vs 171,05±41,63 mg/dl) p<0,001; HDLc (51,50/18,25 vs 42,00/16,00 mg/dl) p=0,007; HDL2 (8,50/3,25 vs 10,00/6,00 mg/dl) p=0,292; HDL3 (41,75±9,82 vs 31,75±9,41 mg/dl) p<0,001; LDLox (70,00/22,0 vs 43,50/21,00 U/L) p<0,001; TG (120,00/112,50 vs 107,00/86,00 mg/dl) p=0,527; Lp(a) (0,51/0,73 vs 0,51/0,50 g/L) p=0,854; ApoA1 (1,38±0,63 vs 1,19±0,21 g/L) p=0,002; ApoB (0,96±0,19 vs 0,78±0,28 g/L) p=0,004; ApoE (38,50/10,00 vs 38,00/17,00 mg/L) p=0,574. Nas correlações lineares entre as variáveis inflamatórias e as variáveis lipídicas para todos os doentes, encontrámos uma relação negativa entre IL-6 e CT, HDLc, HDL3, LDLox, ApoA1 e ApoB. A regressão múltipla marcadores inflamatórios/perfil lipídico (grupo controlo) foi: hs-CRP (R=0,883, R2=0,780) p=0,022; IL-6 (R=0,911, R2=0,830) p=0,007; MMP3 (R=0,498, R2=0,248) p=0,943; TNF-α (R=0,680, R2=0,462) p=0,524. A regressão múltipla marcadores inflamatórios/perfil lipídico (grupo EAM) foi: hs-CRP (R=0,647, R2=0,418) p=0,004; IL-6 (R=0,544, R2=0,300), p=0,073; MMP3 (R=0,539, R2=0,290) p=0,089; TNF-α (R=0,595; R2=0,354) p=0,022. Da comparação entre os marcadores inflamatórios dos dois grupos resultou (mediana/intervalo interquartil, grupo controlo vs EAM): hs-CRP (0,19/0,27 vs 0,42/2,53 mg/dl) p=0,001, IL-6 (4,90/5,48 vs 13,07/26,41 pg/ml) p<0,001, MMP3 (19,70/13,70 vs 10,10/10,40 ng/ml) p<0,001;TNF-α (8,67/6,71 vs 8,26/7,80 pg/dl) p=0,805. Conclusões: (1) Nos doentes com EAM, existe correlação entre as moléculas inflamatórias IL-6, MMP3 e TNF-α, quer com o marcador inflamatório hs-CRP, quer com o marcador de lesão miocárdica cTnI. Esta correlação reforça-se para os valores de cTnI 6-9 horas após admissão, especialmente na correlação múltipla com o grupo dos quatro marcadores inflamatórios. (2) IL-6 está inversamente ligada às lipoproteínas de colesterol; hs-CRP e IL-6 têm excelentes correlações com o perfil lipídico valorizado no seu conjunto. No grupo EAM encontram-se níveis séricos mais reduzidos para as lipoproteínas de colesterol. Para TNF-α não foram encontradas diferenças significativas entre os grupos, as quais foram observadas para a IL-6 e hs-CRP (mais elevadas no grupo EAM). Os valores de MMP3 no grupo controlo estão mais elevados. ABSTRACT: 0,524, p=0,001; 0,149, p=0,270; 0,275, p<0,001; TNF-α/cTnI 6-9h 0,428, p=0,001, 0,452, p<0,001, 0,183, p<0,001. A regressão linear múltipla cTnI admissão/marcadores inflamatórios produziu: (R=0,638, R2=0,407) p<0,001 e cTnI 6-9h/marcadores inflamatórios (R=0,780, R2=0,609) p<0,001. (2) Significância da análise multivariada para idade (p=0,029), IMC>30 (p=0.070), AAS (p=0,040) e grupo (p=0,002). Diferenças importantes entre as distribuições dos dados basais entre os dois grupos (grupo controlo vs EAM): idade (47,95±11,55 vs 68,53±2,70 anos) p<0.001; sexo feminino (18,18 vs 22,80%) p=0,076; diabetes mellitus (9,09% vs 36,84%) p=0,012; AAS (18,18 vs 66,66%) p<0,001; clopidogrel (4,54% vs 66,66%) p=0,033; estatinas (31,81% vs 66,14%) p=0,078; beta-bloqueadores (18,18% vs 56,14%) p=0,011; anti-inflamatórios (4,54% vs 33,33%) p=0,009. Resultados da comparação entre os dois grupos quanto ao padrão lipídico (média±dp ou mediana/intervalo interquartil, grupo controlo vs EAM): CT (208,45±35,03 vs 171,05±41,63 mg/dl) p<0,001; HDLc (51,50/18,25 vs 42,00/16,00 mg/dl) p=0,007; HDL2 (8,50/3,25 vs 10,00/6,00 mg/dl) p=0,292; HDL3 (41,75±9,82 vs 31,75±9,41 mg/dl) p<0,001; LDLox (70,00/22,0 vs 43,50/21,00 U/L) p<0,001; TG (120,00/112,50 vs 107,00/86,00 mg/dl) p=0,527; Lp(a) (0,51/0,73 vs 0,51/0,50 g/L) p=0,854; ApoA1 (1,38±0,63 vs 1,19±0,21 g/L) p=0,002; ApoB (0,96±0,19 vs 0,78±0,28 g/L) p=0,004; ApoE (38,50/10,00 vs 38,00/17,00 mg/L) p=0,574. Nas correlações lineares entre as variáveis inflamatórias e as variáveis lipídicas para todos os doentes, encontrámos uma relação negativa entre IL-6 e CT, HDLc, HDL3, LDLox, ApoA1 e ApoB. A regressão múltipla marcadores inflamatórios/perfil lipídico (grupo controlo) foi: hs-CRP (R=0,883, R2=0,780) p=0,022; IL-6 (R=0,911, R2=0,830) p=0,007; MMP3 (R=0,498, R2=0,248) p=0,943; TNF-α (R=0,680, R2=0,462) p=0,524. A regressão múltipla marcadores inflamatórios/perfil lipídico (grupo EAM) foi: hs-CRP (R=0,647, R2=0,418) p=0,004; IL-6 (R=0,544, R2=0,300), p=0,073; MMP3 (R=0,539, R2=0,290) p=0,089; TNF-α (R=0,595; R2=0,354) p=0,022. Da comparação entre os marcadores inflamatórios dos dois grupos resultou (mediana/intervalo interquartil, grupo controlo vs EAM): hs-CRP (0,19/0,27 vs 0,42/2,53 mg/dl) p=0,001, IL-6 (4,90/5,48 vs 13,07/26,41 pg/ml) p<0,001, MMP3 (19,70/13,70 vs 10,10/10,40 ng/ml) p<0,001;TNF-α (8,67/6,71 vs 8,26/7,80 pg/dl) p=0,805. Conclusões: (1) Nos doentes com EAM, existe correlação entre as moléculas inflamatórias IL-6, MMP3 e TNF-α, quer com o marcador inflamatório hs-CRP, quer com o marcador de lesão miocárdica cTnI. Esta correlação reforça-se para os valores de cTnI 6-9 horas após admissão, especialmente na correlação múltipla com o grupo dos quatro marcadores inflamatórios. (2) IL-6 está inversamente ligada às lipoproteínas de colesterol; hs-CRP e IL-6 têm excelentes correlações com o perfil lipídico valorizado no seu conjunto. No grupo EAM encontram-se níveis séricos mais reduzidos para as lipoproteínas de colesterol. Para TNF-α não foram encontradas diferenças significativas entre os grupos, as quais foram observadas para a IL-6 e hs-CRP (mais elevadas no grupo EAM). Os valores de MMP3 no grupo controlo estão mais elevados. ------------- ABSTRACT: Introduction: We reviewed the epidemiology, pathophysiology and current clinical knowledge about coronary heart disease, from its genesis to the acute myocardial infarction (AMI). The inflammatory theory for atherosclerosis, which has undergone considerable development in the last decade, was especially detailed. Markers of coronary atherosclerotic vulnerable plaque: The clinical and laboratory biomarkers associated with the unstable coronary atherosclerotic plaque vulnerable plaque are detailed. An emphasis was placed on the inflammatory mechanisms. Objectives: They are divided into two fundamental points: (1) To study in AMI patients, the relationship between the inflammatory molecules: Interleukin-6 (IL-6), Tumor Necrosis Factor-α (TNF-α) and Matrix metalloproteinase-3 (MMP3), unused in the clinical setting, with an inflammatory marker in clinical use: ultrasensitive C-reactive protein (hs-CRP), as well as a biomarker of myocardial injury: cardiac troponin I (cTnI). (2) To study, in the context of AMI, the Acute Phase Response (APR). We intend to demonstrate the impact of that clinical relevant phenomenon in the lipid profile and inflammatory biomarkers of our patients. Methods: (1) Prospective observational study of patients consecutively admitted for AMI (AMI group) in a single coronary care unit, after exclusion of trauma or infection. A peripheral assay at admission for IL-6, TNF-α, MMP3, hs-CRP and cTnI was performed. The latter was also valued in assays obtained 6-9 hours after admission. Linear correlation (Pearson's correlation coefficient, Spearman Rho's correlation coefficient and R2 regression) was performed between the three markers studied and the values of hs-CRP and cTnI (on admission and 6-9 hours after admission). Multiple linear regression was also obtained between cTnI on admission and 6-9h after, with all the inflammatory markers studied. (2) Case-control study between the AMI group and a random population of patients from an outpatient cardiology setting (control group). Cardiovascular events of any kind and infection or trauma were excluded in this group. The same inflammatory molecules were assayed in control and AMI groups. The following lipoproteins were also assayed: total cholesterol (TC), HDL cholesterol (HDLc) and subfractions 2 and 3 (HDL2 and HDL 3), oxidized LDL cholesterol (oxLDL), Triglycerides (TG), Lipoprotein (a) [Lp(a)], Apolipoprotein A1 (apoA1), Apolipoprotein B (ApoB) and Apolipoprotein E (ApoE). Demographics, classical risk factors, cardiovascular therapy and the use of anti-inflammatory drugs were appreciated in each group. The authors conducted a multivariate analysis with respect to demographics, risk factors and baseline therapy. The distribution of the same baseline characteristics was compared between the two groups, as well as the lipoprotein serum values. A correlation was performed between each inflammatory molecule and each of the lipoproteins, for all the patients studied. Multiple linear regression was determined between each inflammatory marker and all the lipid molecules per group. Finally, the statistical comparison between the inflammatory markers in the two groups was performed. Results: (1) The correlation coefficients recorded, respectively, Pearson, Spearman's Rho and regression-R2, were: IL-6/hs-CRP 0.549, p <0.001; 0.429, p=0.001; 0.302, p <0.001; MMP 3/hsCRP 0.325, p=0.014; 0.171, p=0.202; 0.106, p=0.014; TNF-α/hs-CRP 0.261, p=0.050; 0.315, p=0.017; 0.068, p=0.050; IL-6/admission cTnI 0.486, p<0.001; 0.483, p<0.001; 0.236, p<0.001; MMP3/admission cTnI 0.218, p=0.103; 0.146, p=0.278; 0.048, p=0.103; TNF-α/admission cTnI 0.444, p=0.001; 0.380, p=0.004; 0.197, p=0.001; IL-6/6-9 h cTnI 0.676, p<0.001; 0.149, p<0.001; 0.456, p <0.01; MMP3/6-9h cTnI 0.428, p=0.001; 0.149, p<0.001; 0.183, p=0.001; TNF-α/6-9 h cTnI 0.676, p<0,001; 0.452, p<0.001; 0.183, p<0,001. The multiple linear regression admission cTnI/inflammatory markers produced: (R=0.638, R2=0.407) p<0.001 and 6-9 h cTnI/inflammatory markers (R=0.780, R2=0.609) p<0.001. (2) Significances of the multivariate analysis were found for age (p=0.029), IMC>30 (p=0.070), Aspirin (p=0.040) and group (p=0.002). Important differences between the baseline data of the two groups (control group vs AMI): age (47.95 ± 11.55 vs 68.53±12.70 years) p<0.001; gender (18.18 vs 22.80%) p=0.076; diabetes mellitus (9.09% vs 36. 84%) p=0.012; Aspirin (18.18 vs. 66.66%) p<0.001; Clopidogrel (4, 54% vs 66.66%) p=0.033; Statins, 31.81% vs 66.14%, p=0.078, beta-blockers 18.18% vs 56.14%, p=0.011; anti-inflammatory drugs (4.54% vs 33.33%) p=0.009. Significant differences in the lipid pattern of the two groups (mean±SD or median/interquartile range, control group vs AMI): TC (208.45±35.03 vs 171.05±41.63 mg/dl) p<0.001; HDLc (51.50/18.25 vs 42.00/16.00 mg/dl) p=0.007; HDL2 (8.50/3.25 vs 10.00/6.00 mg/dl) p=0.292; HDL3 (41.75±9.82 vs 31.75±9.82 mg/dl) p<0.01; oxLDL (70.00/22.0 vs 43.50/21.00 U/L) p <0.001; TG (120.00/112.50 vs 107.00/86.00 mg/dl) p=0.527; Lp(a) (0.51/0.73 vs 0,51/0.50 g/L) p=0.854; apoA1 (1.38±0.63 vs 1.19±0.21 g/L) p=0.002; ApoB (0.96± 0.39 vs 0.78±0.28 g/L) p=0.004; ApoE (38.50/10,00 vs 38.00 /17,00 mg/L) p=0.574. In the linear correlations between inflammatory variables and lipid variables for all patients, we found a negative relationship between IL-6 and TC, HDLc, HDL3, ApoA1 and ApoB. The multiple linear regression inflammatory markers/lipid profile (control group) was: hs-CRP (R= 0.883, R2=0.780) p=0.022; IL6 (R=0.911, R2=0.830) p=0.007; MMP3 (R=0.498, R2=0.248) p=0.943; TNF-α (R=0.680, R2=0.462) p=0.524. For the linear regression inflammatory markers/lipid profile (AMI group) we found: hs-CRP (R=0.647, R2=0.418) p=0.004; IL-6 (R=0.544, R2=0.300) p=0.073; MMP3 (R=0.539, R2 =0.290) p=0.089; TNF-α (R=0.595, R2=0.354) p=0.022. The comparison between inflammatory markers in both groups (median/interquartile range, control group vs AMI) resulted as: hs-CRP (0.19/0.27 vs 0.42/2.53 mg/dl) p=0.001; IL-6 (4.90/5.48 vs 13.07/26.41 pg/ml) p<0.001; MMP3 (19.70/13.70 vs 10.10/10.40 ng/ml) p<0.001; TNF-α (8.67/6.71 vs 8.26/7.80 pg/dl) p=0.805. Conclusions: (1) In AMI patients there is a correlation between the inflammatory molecules IL-6, TNF-α and MMP3 with both the inflammatory marker hs-CRP and the ischemic marker cTnI. This correlation is strengthened for the cTnI at 6-9h post admission, particularly in the multiple linear regression to the four inflammatory markers studied. (2) IL-6 correlates negatively with the cholesterol lipoproteins. Hs-CRP and IL-6 are strongly correlated to the whole lipoprotein profile. AMI patients display reduced serum lipid levels. For the marker TNF-α no significant differences were found between groups, which were observed for IL-6 and hs-CRP (higher in the AMI group). MMP3 values are higher in the control group.

Development of mixed matrix membranes with metal - organic framework and ionic liquids for biogas upgrading

Dissertation presented to Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa for obtaining the master degree in Membrane Engineering

The additive effects in matrix dispersed liquid crystals

Dissertation presented at Faculdade de Ciências e Tecnologia from Universidade Nova de Lisboa to obtain the degree of Master in Chemical and Biochemical Engineering