Dimensionamento de um secador em leito fluidizado para secagem de cereais

O objectivo desta tese é dimensionar um secador em leito fluidizado para secagem de cereais, nomeadamente, secagem de sementes de trigo. Inicialmente determinaram-se as condições de hidrodinâmica (velocidade de fluidização, TDH, condições mínimas de “slugging”, expansão do leito, dimensionamento do distribuidor e queda de pressão). Com as condições de hidrodinâmica definidas, foi possível estimar as dimensões físicas do secador. Neste ponto, foram realizados estudos relativamente à cinética da secagem e à própria secagem. Foi também estudado o transporte pneumático das sementes. Deste modo, determinaram-se as velocidades necessárias ao transporte pneumático e respectivas quedas de pressão. Por fim, foi realizada uma análise custos para que se soubesse o custo deste sistema de secagem. O estudo da secagem foi feito para uma temperatura de operação de 50ºC, tendo a ressalva que no limite se poderia trabalhar com 60ºC. A velocidade de operação é de 2,43 m/s, a altura do leito fixo é de 0,4 m, a qual sofre uma expansão durante a fluidização, assumindo o valor de 0,79 m. O valor do TDH obtido foi de 1,97 m, que somado à expansão do leito permite obter uma altura total da coluna de 2,76 m. A altura do leito fixo permite retirar o valor do diâmetro que é de 0,52 m. Verifica-se que a altura do leito expandido é inferior à altura mínima de “slugging” (1,20 m), no entanto, a velocidade de operação é superior à velocidade mínima de “slugging” (1,13 m/s). Como só uma das condições mínimas é cumprida, existe a possibilidade da ocorrência de “slugging”. Finalmente, foi necessário dimensionar o distribuidor, que com o diâmetro de orifício de 3 mm, valor inferior ao da partícula (3,48 mm), permite a distruibuição do fluido de secagem na coluna através dos seus 3061 orifícios. O inicio do estudo da secagem centrou-se na determinação do tempo de secagem. Além das duas temperaturas atrás referidas, foram igualmente consideradas duas humidades iniciais para os cereais (21,33% e 18,91%). Temperaturas superiores traduzem-se em tempos de secagem inferiores, paralelamente, teores de humidade inicial inferiores indicam tempos menores. Para a temperatura de 50ºC, os tempos de secagem assumiram os valores de 2,8 horas para a 21,33% de humidade e 2,7 horas para 18,91% de humidade. Foram também tidas em conta três alturas do ano para a captação do ar de secagem, Verão e Inverno representando os extremos, e a Meia- Estação. Para estes três casos, foi possível verificar que a humidade específica do ar não apresenta alterações significativas entre a entrada no secador e a corrente de saída do mesmo equipamento, do mesmo modo que a temperatura de saída pouco difere da de entrada. Este desvio de cerca de 1% para as humidades e para as temperaturas é explicado pela ausência de humidade externa nas sementes e na pouca quantidade de humidade interna. Desta forma, estes desvios de 1% permitem a utilização de uma razão de reciclagem na ordem dos 100% sem que o comportamento da secagem se altere significativamente. O uso de 100% de reciclagem permite uma poupança energética de cerca de 98% no Inverno e na Meia-Estação e de cerca de 93% no Verão. Caso não fosse realizada reciclagem, seria necessário fornecer à corrente de ar cerca de 18,81 kW para elevar a sua temperatura de 20ºC para 50ºC (Meia-Estação), cerca de 24,67 kW para elevar a sua temperatura de 10ºC para 50ºC (Inverno) e na ordem dos 8,90 kW para elevar a sua temperatura dos 35ºC para 50ºC (Verão). No caso do transporte pneumático, existem duas linhas, uma horizontal e uma vertical, logo foi necessário estimar o valor da velocidade das partículas para estes dois casos. Na linha vertical, a velocidade da partícula é cerca de 25,03 m/s e cerca de 35,95 m/s na linha horizontal. O menor valor para a linha vertical prende-se com o facto de nesta zona ter que se vencer a força gravítica. Em ambos os circuitos a velocidade do fluido é cerca de 47,17 m/s. No interior da coluna, a velocidade do fluido tem o valor de 10,90 m/s e a velocidade das partículas é de 1,04 m/s. A queda de pressão total no sistema é cerca de 2408 Pa. A análise de custos ao sistema de secagem indicou que este sistema irá acarretar um custo total (fabrico mais transporte) de cerca de 153035€. Este sistema necessita de electricidade para funcionar, e esta irá acarretar um custo anual de cerca de 7951,4€. Embora este sistema de secagem apresente a possibilidade de se realizar uma razão de reciclagem na ordem dos 100% e também seja possível adaptar o mesmo para diferentes tipos de cereais, e até outros tipos de materiais, desde que possam ser fluidizados, o seu custo impede que a realização deste investimento não seja atractiva, especialmente tendo em consideração que se trata de uma instalação à escala piloto com uma capacidade de 45 kgs.

Produção de hidrogénio através da gasificação da biomassa

A procura de uma forma limpa de combustível, aliada à crescente instabilidade de preços dos combustíveis fósseis verificada nos mercados faz com que o hidrogénio se torne num combustível a considerar devido a não resultar qualquer produto poluente da sua queima e de se poder utilizar, por exemplo, desperdícios florestais cujo valor de mercado não está inflacionado por não pertencer à cadeia alimentar humana. Este trabalho tem como objetivo simular o processo de gasificação de biomassa para produção de hidrogénio utilizando um gasificador de leito fluidizado circulante. O oxigénio e vapor de água funcionam como agentes gasificantes. Para o efeito usou-se o simulador de processos químicos ASPEN Plus. A simulação desenvolvida compreende três etapas que ocorrem no interior do gasificador: pirólise, que foi simulada por um bloco RYIELD, combustão de parte dos compostos voláteis, simulada por um bloco RSTOIC e, por fim, as reações de oxidação e gasificação do carbonizado “char”, simuladas por um bloco RPLUG. Os valores de rendimento dos compostos após a pirólise, obtidos por uma correlação proposta por Gomez-Barea, et al. (2010), foram os seguintes: 20,33% “char”, 22,59% alcatrão, 36,90% monóxido de carbono, 16,05%m/m dióxido de carbono, 3,33% metano e 0,79% hidrogénio (% em massa). Como não foi possível encontrar valores da variação da composição do gás à saída do gasificador com a variação da temperatura, para o caso de vapor de água e oxigénio, optou-se por utilizar apenas vapor na simulação de forma a comparar os seus valores com os da literatura. Às temperaturas de 700, 770 e 820ºC, para um “steam-to-biomass ratio”, (SBR) igual a 0,5, os valores da percentagem molar de monóxido de carbono foram, respetivamente, 56,60%, 55,84% e 53,85%, os valores de hidrogénio foram, respetivamente, 17,83%, 18,25% e 19,31%, os valores de dióxido de carbono foram, respetivamente, 16,40%, 16,85% e 17,93% e os valores de metano foram, respetivamente, 9,00%, 8,95% e 8,83%. Os valores da composição à saída do gasificador, à temperatura de 820ºC, para um SBR de 0,5 foram: 53,85% de monóxido de carbono, 19,31% de hidrogénio, 17,93% de dióxido de carbono e 8,83% de metano (% em moles). Para um SBR de 0,7 a composição à saída foi de 54,45% de monóxido de carbono, 19,01% de hidrogénio, 17,59% de dióxido de carbono e 8,87% de metano. Por fim, quando SBR foi igual a 1 a composição do gás à saída foi de 55,08% de monóxido de carbono, 18,69% de hidrogénio, 17,24% de dióxido de carbono e 8,90% de metano. Os valores da composição obtidos através da simulação, para uma mistura de ar e vapor de água, ER igual a 0,26 e SBR igual a 1, foram: 34,00% de monóxido de carbono, 14,65% de hidrogénio, 45,81% de dióxido de carbono e 5,41% de metano. A simulação permitiu-nos ainda dimensionar o gasificador e determinar alguns parâmetros hidrodinâmicos do gasificador, considerando que a reação “water-gas shift” era a limitante, e que se pretendia obter uma conversão de 95%. A velocidade de operação do gasificador foi de 4,7m/s e a sua altura igual a 0,73m, para um diâmetro de 0,20m.

Biofiltration of Air/Styrene and Air/Styrene/Acetone mixtures in a bubble column reactor

The goal of this work was the treatment of polluted waste gases in a bubble column reactor (BCR), in order to determinate the maximum value of reactor’s efficiency (RE), varying the inlet concentration (C in) of the pollutants. The gaseous mixtures studied were: (i) air with styrene and (ii) air with styrene and acetone. The liquid phase used to contain the biomass in the reactor was a basal salt medium (BSM), fundamental for the microorganisms’ development. The reactor used in this project consists of a glass column of 620mm height and inside diameter 75mm. In all essays there were continually measured: pH, dissolved oxygen and liquid’s temperature. Temperature and pH were controlled (T=24ºC, 7.0 ≤ pH ≤ 7.7). In all experiments the liquid volume (including the biomass) used in the reactor was kept constant (1.5L) as well as the total gas flowrate (1 L/min). Concerning the goal of the work, some parameters were calculated: the organic load (OL), removal efficiency (RE), elimination capacity (EC), biomass concentration (xf) and dry biomass concentration (Xdw). In a first series of experiments, the gas mixture used was air with styrene, varying its concentration from 191 mg.m-3 to 6500 mg.m-3.It was concluded that the RE maximum value (97%) was obtained for C in Sty = 4200 mg.m-3. For the maximum tested value of C in Sty, RE obtained was 20%. In a second step, the gaseous mixture included acetone, varying C in Sty between 225 mg.m-3 and 2659 mg.m-3 and C in Ac between 153mg.m-3 and 1389 mg.m-3. The aim of these tests was the determination of C in Ac for which RE was maximum, obtaining C in Ac = 750 mg.m-3. A third series of experiments was performed, in which C in Ac was maintained equal to that value and C in Sty was varied until higher values (5422 mg.m-3). RE maximum values obtained in this last series were 100% for styrene and 40% for acetone. One important conclusion is the fact that the microorganisms available degrade better styrene than acetone. On the ambit of this study, it was possible to identify the species available in biomass: Xanthobacter antotrophicus py2, Enterobacter aerogenes, Nocardia, Corynebacterium Spp., Rhodococcus rhodochrous e Pseudomonas Sp.

Learner’s satisfaction within a breast imaging eLearning course for radiographers

Background: An asynchronous eLearning system was developed for radiographers in order to promote a better knowledge about senology and mammography. Objectives: to assess the learners’ satisfaction. Methods: Target population included radiographers and radiogr aphy students, in order to assess eLearning satisfaction according to different experience levels in breast imaging. Satisfaction was measured through a questionnaire developed especially for eLearning systems, using a seven - point Likert scale. Main topics related are content, interface, personalization and learning community. Results: Overall, 85% of learners were satisfied with the course and 87,5% considered that the course is successful. Main areas that were evaluated by most learners in a positive way were interface and content (between six and seven - point); on the other hand, learning community presented a wider distribution of answers . Conclusions: The course provides an overall high degree of learner satisfaction, thus providing more effective knowle dge gain on breast imaging for radiographers.

Food consumption, physical activity and socio-economic status related to BMI, waist circumference and waist-to-height ratio in adolescents

Objective: To examine the association between obesity and food group intakes, physical activity and socio-economic status in adolescents. Design: A cross-sectional study was carried out in 2008. Cole’s cut-off points were used to categorize BMI. Abdominal obesity was defined by a waist circumference at or above the 90th percentile, as well as a waist-to-height ratio at or above 0?500. Diet was evaluated using an FFQ, and the food group consumption was categorized using sex-specific tertiles of each food group amount. Physical activity was assessed via a self-report questionnaire. Socio-economic status was assessed referring to parental education and employment status. Data were analysed separately for girls and boys and the associations among food consumption, physical activity, socio-economic status and BMI, waist circumference and waist-to-height ratio were evaluated using logistic regression analysis, adjusting the results for potential confounders. Setting: Public schools in the Azorean Archipelago, Portugal. Subjects: Adolescents (n 1209) aged 15–18 years. Results: After adjustment, in boys, higher intake of ready-to-eat cereals was a negative predictor while vegetables were a positive predictor of overweight/ obesity and abdominal obesity. Active boys had lower odds of abdominal obesity compared with inactive boys. Boys whose mother showed a low education level had higher odds of abdominal obesity compared with boys whose mother presented a high education level. Concerning girls, higher intake of sweets and pastries was a negative predictor of overweight/obesity and abdominal obesity. Girls in tertile 2 of milk intake had lower odds of abdominal obesity than those in tertile 1. Girls whose father had no relationship with employment displayed higher odds of abdominal obesity compared with girls whose father had high employment status. Conclusions: We have found that different measures of obesity have distinct associations with food group intakes, physical activity and socio-economic status.

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).

Development and Assessment of an E-Learning Course on Breast Imaging for Radiographers: A Stratified Randomized Controlled Trial

Background: Mammography is considered the best imaging technique for breast cancer screening, and the radiographer plays an important role in its performance. Therefore, continuing education is critical to improving the performance of these professionals and thus providing better health care services. Objective: Our goal was to develop an e-learning course on breast imaging for radiographers, assessing its efficacy , effectiveness, and user satisfaction. Methods: A stratified randomized controlled trial was performed with radiographers and radiology students who already had mammography training, using pre- and post-knowledge tests, and satisfaction questionnaires. The primary outcome was the improvement in test results (percentage of correct answers), using intention-to-treat and per-protocol analysis. Results: A total of 54 participants were assigned to the intervention (20 students plus 34 radiographers) with 53 controls (19+34). The intervention was completed by 40 participants (11+29), with 4 (2+2) discontinued interventions, and 10 (7+3) lost to follow-up. Differences in the primary outcome were found between intervention and control: 21 versus 4 percentage points (pp), P<.001. Stratified analysis showed effect in radiographers (23 pp vs 4 pp; P=.004) but was unclear in students (18 pp vs 5 pp; P=.098). Nonetheless, differences in students’ posttest results were found (88% vs 63%; P=.003), which were absent in pretest (63% vs 63%; P=.106). The per-protocol analysis showed a higher effect (26 pp vs 2 pp; P<.001), both in students (25 pp vs 3 pp; P=.004) and radiographers (27 pp vs 2 pp; P<.001). Overall, 85% were satisfied with the course, and 88% considered it successful. Conclusions: This e-learning course is effective, especially for radiographers, which highlights the need for continuing education.

Using data mining techniques to support breast cancer diagnosis

More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

A novel antibody-like material for breast cancer antigen CA15-3, used to track breast cancer by potentiometric transduction

This work presents the development of a low cost sensor device for the diagnosis of breast cancer in point-of-care, made with new synthetic biomimetic materials inside plasticized poly(vinyl chloride), PVC, membranes, for subsequent potentiometric detection. This concept was applied to target a conventional biomarker in breast cancer: Breast Cancer Antigen (CA15-3). The new biomimetic material was obtained by molecularly-imprinted technology. In this, a plastic antibody was obtained by polymerizing around the biomarker that acted as an obstacle to the growth of the polymeric matrix. The imprinted polymer was specifically synthetized by electropolymerization on an FTO conductive glass, by using cyclic voltammetry, including 40 cycles within -0.2 and 1.0 V. The reaction used for the polymerization included monomer (pyrrol, 5.0×10-3 mol/L) and protein (CA15-3, 100U/mL), all prepared in phosphate buffer saline (PBS), with a pH of 7.2 and 1% of ethylene glycol. The biomarker was removed from the imprinted sites by proteolytic action of proteinase K. The biomimetic material was employed in the construction of potentiometric sensors and tested with regard to its affinity and selectivity for binding CA15-3, by checking the analytical performance of the obtained electrodes. For this purpose, the biomimetic material was dispersed in plasticized PVC membranes, including or not a lipophilic ionic additive, and applied on a solid conductive support of graphite. The analytical behaviour was evaluated in buffer and in synthetic serum, with regard to linear range, limit of detection, repeatability, and reproducibility. This antibody-like material was tested in synthetic serum, and good results were obtained. The best devices were able to detect 5 times less CA15-3 than that required in clinical use. Selectivity assays were also performed, showing that the various serum components did not interfere with this biomarker. Overall, the potentiometric-based methods showed several advantages compared to other methods reported in the literature. The analytical process was simple, providing fast responses for a reduced amount of analyte, with low cost and feasible miniaturization. It also allowed the detection of a wide range of concentrations, diminishing the required efforts in previous sample pre-treating stages.

Effects of Environmental Organochlorine Pesticides on Human Breast Cancer: Putative Involvement on Invasive Cell Ability

Human exposure to persistent organic pollutants (POPs) is a certainty, even to long banned pesticides like o,p′-dichlorodiphenyltrichloroethane (o,p′-DDT), and its metabolites p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE), and p,p′-dichlorodiphenyldichloroethane (p,p′-DDD). POPs are known to be particularly toxic and have been associated with endocrine-disrupting effects in several mammals, including humans even at very low doses. As environmental estrogens, they could play a critical role in carcinogenesis, such as in breast cancer. With the purpose of evaluating their effect on breast cancer biology, o,p′-DDT, p,p′-DDE, and p,p′-DDD (50–1000 nM) were tested on two human breast adenocarcinoma cell lines: MCF-7 expressing estrogen receptor (ER) α and MDA-MB-231 negative for ERα, regarding cell proliferation and viability in addition to their invasive potential. Cell proliferation and viability were not equally affected by these compounds. In MCF-7 cells, the compounds were able to decrease cell proliferation and viability. On the other hand, no evident response was observed in treated MDA-MB-231 cells. Concerning the invasive potential, the less invasive cell line, MCF-7, had its invasion potential significantly induced, while the more invasive cell line MDA-MB-231, had its invasion potential dramatically reduced in the presence of the tested compounds. Altogether, the results showed that these compounds were able to modulate several cancer-related processes, namely in breast cancer cell lines, and underline the relevance of POP exposure to the risk of cancer development and progression, unraveling distinct pathways of action of these compounds on tumor cell biology.

Longitudinal analysis of tumor marker CEA of breast cancer patients from Braga's hospital

Allied to an epidemiological study of population of the Senology Unit of Braga’s Hospital that have been diagnosed with malignant breast cancer, we describe the progression in time of repeated measurements of tumor marker Carcinoembryonic antigen (CEA). Our main purpose is to describe the progression of this tumor marker as a function of possible risk factors and, hence, to understand how these risk factors influences that progression. The response variable, values of CEA, was analyzed making use of longitudinal models, testing for different correlation structures. The same covariates used in a previous survival analysis were considered in the longitudinal model. The reference time used was time from diagnose until death from breast cancer. For diagnostic of the models fitted we have used empirical and theoretical variograms. To evaluate the fixed term of the longitudinal model we have tested for a changing point on the effect of time on the tumor marker progression. A longitudinal model was also fitted only to the subset of patients that died from breast cancer, using the reference time as time from date of death until blood test.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.