Atitude relativamente à máquina de café em cápsula: estudo sobre razões de compra

O café é uma das bebidas preferidas dos portugueses. Desde o ano 2010 que assistimos a uma tendência de crescimento no consumo de café no lar, nomeadamente desde o aparecimento de uma maior variedade de máquinas de café em cápsula. A presente dissertação procurou compreender “que aspetos valoriza o comprador de máquina de café em cápsula maior de 18 anos, da cidade de Lisboa, na sua compra?”. As respostas obtidas com este trabalho vão permitir aos profissionais de marketing das empresas comercializadoras das máquinas de café em cápsula conhecer o seu comprador e definir novas estratégias que contribuirão para o sucesso deste produto. Recorrendo a uma abordagem metodológica quantitativa, foi realizado um inquérito por questionário a possuidores de máquina de café em cápsula. Esta investigação aborda o comportamento de compra deste eletrodoméstico, incidindo sobre alguns dos aspetos que influenciam uma atitude favorável na sua compra.

A influência da marca Nespresso no comportamento de compra da máquina e cápsulas de café

Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

A user-friendly web portal for T-Coffee on supercomputers

Background: Parallel T-Coffee (PTC) was the first parallel implementation of the T-Coffee multiple sequence alignment tool. It is based on MPI and RMA mechanisms. Its purpose is to reduce the execution time of the large-scale sequence alignments. It can be run on distributed memory clusters allowing users to align data sets consisting of hundreds of proteins within a reasonable time. However, most of the potential users of this tool are not familiar with the use of grids or supercomputers. Results: In this paper we show how PTC can be easily deployed and controlled on a super computer architecture using a web portal developed using Rapid. Rapid is a tool for efficiently generating standardized portlets for a wide range of applications and the approach described here is generic enough to be applied to other applications, or to deploy PTC on different HPC environments. Conclusions: The PTC portal allows users to upload a large number of sequences to be aligned by the parallel version of TC that cannot be aligned by a single machine due to memory and execution time constraints. The web portal provides a user-friendly solution.

Using fraction images derived from modis data for coffee crop mapping

Coffee production was closely linked to the economic development of Brazil and, even today, coffee is an important product of the national agriculture. The State of Minas Gerais currently accounts for 52% of the whole coffee area in Brazil. Remote sensing data can provide information for monitoring and mapping of coffee crops, faster and cheaper than conventional methods. In this context, the objective of this study was to assess the effectiveness of coffee crop mapping in Monte Santo de Minas municipality, Minas Gerais State, Brazil, from fraction images derived from MODIS data, in both dry and rainy seasons. The Spectral Linear Mixing Model was used to derive fraction images of soil, coffee, and water/shade. These fraction images served as input data for the supervised automatic classification using the SVM - Support Vector Machine approach. The best results concerning Overall Accuracy and Kappa Index were obtained in the classification of the dry season, with 67% and 0.41, respectively.

Impact Of Chemical Changes On The Sensory Characteristics Of Coffee Beans During Storage.

Sensory changes during the storage of coffee beans occur mainly due to lipid oxidation and are responsible for the loss of commercial value. This work aimed to verify how sensory changes of natural coffee and pulped natural coffee are related to the oxidative processes during 15 months of storage. During this period, changes in the content of free fatty acids (1.4-3.8 mg/g oil), TBARS values (8.8-10.2 nmol MDA/g), and carbonyl groups (2.6-3.5 nmol/mg of protein) occurred. The intensity of rested coffee flavour in the coffee brew increased (2.1-6.7) and 5-caffeoylquinic acid concentration decreased (5.2-4.6g/100g). Losses were also observed in seed viability, colour of the beans and cellular structure. All the results of the chemical analyses are coherent with the oxidative process that occurred in the grains during storage. Therefore, oxidation would be also responsible for the loss of cellular structure, seed viability and sensory changes.

Evaluation Of The Location Of Capsules Swallowed With Food During The Pharyngeal Phase Triggering In Asymptomatic Adults.

To assess the location of hard gelatin capsules in the pharyngeal phase triggering among asymptomatic adults. The location of the bolus during the pharyngeal phase triggering provides information about the sensorimotor model of the beginning of deglutition onset. To evaluate the location of hard gelatin capsules in the pharyngeal phase triggering among asymptomatic adults. A videofluoroscopy swallowing study was carried out in 60 subjects (14 male and 46 female participants) aged between 27 and 55 years, who were evaluated with hard gelatin capsules #00 and #3 containing barium sulfate, swallowed with liquid food and pudding, in free volume. The first laryngeal elevation movement was the criterion to locate the pharyngeal phase triggering. Statistical analysis was based on the McNemar test. Capsule #3 presented higher percentage of location in the tongue dorsum compared to capsule #00, and capsule #00 presented higher percentage of location in the tongue base and vallecula compared to capsule #3. There was a difference between different capsules swallowed with liquid (p=0.016) and pudding (p=0.037). The capsule size influenced the location of the pharyngeal phase triggering. Smaller capsules started pharyngeal phase in the most anterior region (tongue dorsum) compared to larger capsules.

Supercritical CO2 recovery of caffeine from green coffee oil: new experimental solubility data and modeling

The caffeine solubility in supercritical CO2 was studied by assessing the effects of pressure and temperature on the extraction of green coffee oil (GCO). The Peng-Robinson¹ equation of state was used to correlate the solubility of caffeine with a thermodynamic model and two mixing rules were evaluated: the classical mixing rule of van der Waals with two adjustable parameters (PR-VDW) and a density dependent one, proposed by Mohamed and Holder² with two (PR-MH, two parameters adjusted to the attractive term) and three (PR-MH3 two parameters adjusted to the attractive and one to the repulsive term) adjustable parameters. The best results were obtained with the mixing rule of Mohamed and Holder² with three parameters.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Bone quality associated with daily intake of coffee: a biochemical, radiographic and histometric study

Caffeine induces loss of calcium and influences the normal development of bone. This study investigated the effects of coffee on bone metabolism in rats by biochemical measurement of calcium, bone densitometry and histometry. Male rats, born of female treated daily with coffee and with coffee intake since born, were anesthetized, subjected to extraction of the upper right incisor, and sacrificed 7, 21 and 42 days after surgery. Blood and urine samples were taken, and their maxilla radiographed and processed to obtain 5-µm-thick semi-serial sections stained with hematoxylin and eosin. The volume and bone quality were estimated using an image-analysis software. The results showed significantly greater amount of calcium in the plasma (9.40 ± 1.73 versus 9.80 ± 2.05 mg%) and urine (1.00 ± 0.50 versus 1.25 ± 0.70 mg/24 h) and significantly less amount in bone (90.0 ± 1.94 versus 86.0 ± 2.12 mg/mg bone), reduced bone mineral density (1.05 ± 0.11 versus 0.65 ± 0.15 mmAL), and lower amount of bone (76.19 ± 1.6 versus 53.41 ± 2.1 %) (ANOVA; p≤0.01) in animals treated with coffee sacrificed after 42 days. It may be concluded that coffee/caffeine intake caused serious adverse effects on calcium metabolism in rats, including increased levels of calcium in the urine and plasma, decreased bone mineral density and lower volume of bone, thus delaying the bone repair process.

Sensory evaluation of black instant coffee beverage with some volatile compounds present in aromatic oil from roasted coffee

The oil obtained from Brazilian roasted coffee by supercritical CO2 extraction shows considerable aromatic properties, mainly composed by five aromatic compounds, 2-methylpyrazine; 2-furfurylalcohol, 2,5-dimethylpyrazine; γ-butyrolactone and 2-furfurylacetate. Sensory analyses were used to verify the influence of a mixture of these important classes of aromatic coffee compounds (pyrazines, furans and lactones) and of the roasted coffee aromatic oil on the coffee aroma and flavour of black instant freeze and spray-dried coffee beverages. In the acceptance evaluation of the aroma, the samples prepared with freeze-dried instant coffee without the mixture of volatile compounds (sample 4) were not significantly different from the freeze-dried instant coffee in which the aromatic coffee oil was added (sample 5) and from the sample prepared with freeze-dried coffee in which the mixture of the five volatile was added (sample 3), coincidentally from the same drying process. Therefore, sample (3) did not differ from samples prepared with spray dried instant coffee without (sample 1) and to which (sample 2) the mixture of volatile was added. Therefore, with respect to this attribute, the addition of this mixture did not interfere in this drink acceptance. Taking into consideration the flavor, samples prepared with freeze-dried instant coffee in which the aromatic coffee oil was added (5) and the samples with (3) and without (4) the mixture of the five volatile was added did not differ significantly, however sample (4) did not differ from samples (1) and (2). Regarding this attribute, the addition of the aromatic oil of roasted coffee or a mixture of volatile in samples of freeze-dried instant coffee had a better acceptance than those dried by spray dryer (1) and (2). Thus, the enrichment of drinks with the aromatic oil of roasted coffee, or even with the mixture of the five components did not influence the consumer acceptance with respect to the aroma, but exerts influence with respect to flavour.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Collimated scanning LS-INAA for testing trace elements homogeneity in Brazilian coffee beans

The degree of homogeneity is normally assessed by the variability of the results of independent analyses of several (e.g., 15) normal-scale replicates. Large sample instrumental neutron activation analysis (LS-INAA) with a collimated Ge detector allows inspecting the degree of homogeneity of the initial batch material, using a kilogram-size sample. The test is based on the spatial distributions of induced radioactivity. Such test was applied to samples of Brazilian whole (green) coffee beans (Coffea arabica and Coffea canephora) of approximately I kg in the frame of development of a coffee reference material. Results indicated that the material do not contain significant element composition inhomogeneities between batches of approximately 30-50 g, masses typically forming the starting base of a reference material.

A study on chemical constituents and sugars extraction from spent coffee grounds

Spent coffee grounds (SCG) the residual materials obtained during the processing of raw coffee powder to prepare instant coffee are the main coffee Industry residues In the present work this material was chemically characterized and subsequently submitted to a dilute acid hydrolysis aiming to recover the hemicellulose sugars Reactions were performed according to experimental designs to verify the effects of the variables H(2)SO(4) concentration liquid-to-solid ratio temperature and reaction time on the efficiency of hydrolysis SCG was found to be rich in sugars (45 3% w/w) among of which hemicellulose (constituted by mannose galactose and arabinose) and cellulose (glucose homopolymer) correspond to 367% (w/w) and 8 6% (w/w) respectively Optimal conditions for hemicellulose sugars extraction consisted in using 100 mg acid/g dry matter 10g liquid/g solid at 163 degrees C for 45 min Under these conditions hydrolysis efficiencies of 100% 774% and 895% may be achieved for galactan mannan and arabinan respectively corresponding to a hemicellulose hydrolysis efficiency of 874% (C) 2010 Elsevier Ltd All rights reserved

Thermal error evaluation and modelling of a CNC cylindrical grinding machine

With the relentless quest for improved performance driving ever tighter tolerances for manufacturing, machine tools are sometimes unable to meet the desired requirements. One option to improve the tolerances of machine tools is to compensate for their errors. Among all possible sources of machine tool error, thermally induced errors are, in general for newer machines, the most important. The present work demonstrates the evaluation and modelling of the behaviour of the thermal errors of a CNC cylindrical grinding machine during its warm-up period.