A Quantitative analysis of pulsed signals emitted by wild bottlenose dolphins

Common bottlenose dolphins (Tursiops truncatus), produce a wide variety of vocal emissions for communication and echolocation, of which the pulsed repertoire has been the most difficult to categorize. Packets of high repetition, broadband pulses are still largely reported under a general designation of burst-pulses, and traditional attempts to classify these emissions rely mainly in their aural characteristics and in graphical aspects of spectrograms. Here, we present a quantitative analysis of pulsed signals emitted by wild bottlenose dolphins, in the Sado estuary, Portugal (2011-2014), and test the reliability of a traditional classification approach. Acoustic parameters (minimum frequency, maximum frequency, peak frequency, duration, repetition rate and inter-click-interval) were extracted from 930 pulsed signals, previously categorized using a traditional approach. Discriminant function analysis revealed a high reliability of the traditional classification approach (93.5% of pulsed signals were consistently assigned to their aurally based categories). According to the discriminant function analysis (Wilk's Λ = 0.11, F3, 2.41 = 282.75, P < 0.001), repetition rate is the feature that best enables the discrimination of different pulsed signals (structure coefficient = 0.98). Classification using hierarchical cluster analysis led to a similar categorization pattern: two main signal types with distinct magnitudes of repetition rate were clustered into five groups. The pulsed signals, here described, present significant differences in their time-frequency features, especially repetition rate (P < 0.001), inter-click-interval (P < 0.001) and duration (P < 0.001). We document the occurrence of a distinct signal type-short burst-pulses, and highlight the existence of a diverse repertoire of pulsed vocalizations emitted in graded sequences. The use of quantitative analysis of pulsed signals is essential to improve classifications and to better assess the contexts of emission, geographic variation and the functional significance of pulsed signals.

A new approach for computing a flood vulnerability index using cluster analysis

A Flood Vulnerability Index (FloodVI) was developed using Principal Component Analysis (PCA) and a new aggregation method based on Cluster Analysis (CA). PCA simplifies a large number of variables into a few uncorrelated factors representing the social, economic, physical and environmental dimensions of vulnerability. CA groups areas that have the same characteristics in terms of vulnerability into vulnerability classes. The grouping of the areas determines their classification contrary to other aggregation methods in which the areas' classification determines their grouping. While other aggregation methods distribute the areas into classes, in an artificial manner, by imposing a certain probability for an area to belong to a certain class, as determined by the assumption that the aggregation measure used is normally distributed, CA does not constrain the distribution of the areas by the classes. FloodVI was designed at the neighbourhood level and was applied to the Portuguese municipality of Vila Nova de Gaia where several flood events have taken place in the recent past. The FloodVI sensitivity was assessed using three different aggregation methods: the sum of component scores, the first component score and the weighted sum of component scores. The results highlight the sensitivity of the FloodVI to different aggregation methods. Both sum of component scores and weighted sum of component scores have shown similar results. The first component score aggregation method classifies almost all areas as having medium vulnerability and finally the results obtained using the CA show a distinct differentiation of the vulnerability where hot spots can be clearly identified. The information provided by records of previous flood events corroborate the results obtained with CA, because the inundated areas with greater damages are those that are identified as high and very high vulnerability areas by CA. This supports the fact that CA provides a reliable FloodVI.

Preference Mapping Of Dulce De Leche Commercialized In Brazilian Markets.

Dulce de leche samples available in the Brazilian market were submitted to sensory profiling by quantitative descriptive analysis and acceptance test, as well sensory evaluation using the just-about-right scale and purchase intent. External preference mapping and the ideal sensory characteristics of dulce de leche were determined. The results were also evaluated by principal component analysis, hierarchical cluster analysis, partial least squares regression, artificial neural networks, and logistic regression. Overall, significant product acceptance was related to intermediate scores of the sensory attributes in the descriptive test, and this trend was observed even after consumer segmentation. The results obtained by sensometric techniques showed that optimizing an ideal dulce de leche from the sensory standpoint is a multidimensional process, with necessary adjustments on the appearance, aroma, taste, and texture attributes of the product for better consumer acceptance and purchase. The optimum dulce de leche was characterized by high scores for the attributes sweet taste, caramel taste, brightness, color, and caramel aroma in accordance with the preference mapping findings. In industrial terms, this means changing the parameters used in the thermal treatment and quantitative changes in the ingredients used in formulations.

Classificação de água de coco processada e natural por meio de HCA, PCA e teores de íons metálicos determinados por ICP OES

Inductively Coupled Plasma Optical Emission Spectrometry was used to determine Ca, Mg, Mn, Fe, Zn and Cu in samples of processed and natural coconut water. The sample preparation consisted in a filtration step followed by a dilution. The analysis was made employing optimized instrumental parameters and the results were evaluated using methods of Pattern Recognition. The data showed common concentration values for the analytes present in processed and natural samples. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) indicated that the samples of different kinds were statistically different when the concentrations of all the analytes were considered simultaneously.

Avaliação sensorial de cachaça

The hedonic level of commercial cachaças, was evaluated by consumers and by a tasters. The results of sensorial methods analyzed trough Principal Components Analysis, Hierarchical Cluster Analysis and the Pearson linear correlation indicated that the best classified cachaças were produced in copper stills and aged in oak casks. By contrast the worst classified exhibited as the main features be not aged and high alcohol percentage. The index of preference is positively correlated with the intensity of yellow color, wood flavor, sweetness and fruit aroma. There is a negative preference correlation with the acidity, the taste of alcohol and bitterness.

Assessing the association between phenolic compounds and the antioxidant activity of Brazilian red wines using chemometrics

The objective of this study was to evaluate the association among chemical parameters, the commercial value, and the antioxidant activity of Brazilian red wines using chemometric techniques. Twenty-nine samples from five different varieties were assessed. Samples were separated into three groups using hierarchical cluster analysis: cluster 1 presented the highest antioxidant activity towards DPPH (68.51% of inhibition) and ORAC (30,918.64 mu mol Trolox Equivalents/L), followed by cluster 3 (DPPH = 59.36% of inhibition: ORAC = 25,255.02 mu mol Trolox Equivalents/L) and then cluster 2 (DPPH = 46.67% of inhibition; ORAC = 19,395.74 gmol Trolox Equivalents/L). Although the correlation between the commercial value and the antioxidant activity on DPPH and ORAC was not statistically significant (P = 0.13 and P = 0.06, respectively), cluster 1 grouped the samples with higher commercial values. Cluster analysis applied to the variables suggested that non-anthocyanin flavonoids were the main phenolic class exerting antioxidant activity on Brazilian red wines. (C) 2010 Elsevier Ltd. All rights reserved.

Novel benzofuroxan derivatives against multidrug-resistant Staphylococcus aureus strains: Design using Topliss` decision tree, synthesis and biological assay

The aim of this study was the design of a set of benzofuroxan derivatives as antimicrobial agents exploring the physicochemical properties of the related substituents. Topliss` decision tree approach was applied to select the substituent groups. Hierarchical cluster analysis was also performed to emphasize natural clusters and patterns. The compounds were obtained using two synthetic approaches for reducing the synthetic steps as well as improving the yield. The minimal inhibitory concentration method was employed to evaluate the activity against multidrug-resistant Staphylococcus aureus strains. The most active compound was 4-nitro-3-(trifluoromethyl)[N`-(benzofuroxan-5-yl) methylene] benzhydrazide (MIC range 12.7-11.4 mu g/mL), pointing out that the antimicrobial activity was indeed influenced by the hydrophobic and electron-withdrawing property of the substituent groups 3-CF(3) and 4-NO(2), respectively. (C) 2011 Elsevier Ltd. All rights reserved.

Monitoring the authenticity of Brazilian UHT milk: A chemometric approach

In this work, chemometric methods are reported as potential tools for monitoring the authenticity of Brazilian ultra-high temperature (UHT) milk processed in industrial plants located in different regions of the country. A total of 100 samples were submitted to the qualitative analysis of adulterants such as starch, chlorine, formal. hydrogen peroxide and urine. Except for starch, all the samples reported, at least, the presence of one adulterant. The use of chemometric methodologies such as the Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) enabled the verification of the occurrence of certain adulterations in specific regions. The proposed multivariate approaches may allow the sanitary agency authorities to optimise materials, human and financial resources, as they associate the occurrence of adulterations to the geographical location of the industrial plants. (c) 2010 Elsevier Ltd. All rights reserved.

A chemometric study on the analgesic activity of cannabinoid compounds using SDA, KNN and SIMCA methods

The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.

Probabilistic approach for comparing partitions

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon, Portugal.

Dentistry and HIV/AIDS related stigma

OBJECTIVE To analyze HIV/AIDS positive individual’s perception and attitudes regarding dental services.METHODS One hundred and thirty-four subjects (30.0% of women and 70.0% of men) from Nuevo León, Mexico, took part in the study (2014). They filled out structured, analytical, self-administered, anonymous questionnaires. Besides the sociodemographic variables, the perception regarding public and private dental services and related professionals was evaluated, as well as the perceived stigma associated with HIV/AIDS, through a Likert-type scale. The statistical evaluation included a factorial and a non-hierarchical cluster analysis.RESULTS Social inequalities were found regarding the search for public and private dental professionals and services. Most subjects reported omitting their HIV serodiagnosis and agreed that dentists must be trained and qualified to treat patients with HIV/AIDS. The factorial analysis revealed two elements: experiences of stigma and discrimination in dental appointments and feelings of concern regarding the attitudes of professionals or their teams concerning patients’ HIV serodiagnosis. The cluster analysis identified three groups: users who have not experienced stigma or discrimination (85.0%); the ones who have not had those experiences, but feel somewhat concerned (12.7%); and the ones who underwent stigma and discrimination and feel concerned (2.3%).CONCLUSIONS We observed a low percentage of stigma and discrimination in dental appointments; however, most HIV/AIDS patients do not reveal their serodiagnosis to dentists out of fear of being rejected. Such fact implies a workplace hazard to dental professionals, but especially to the very own health of HIV/AIDS patients, as dentists will not be able to provide them a proper clinical and pharmaceutical treatment.

Estimação de Modelos de Adopção e Difusão de Tecnologias de Informação e Comunicação em Portugal

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Exploraty Multivariate Statistical Methods Applied to Pharmaceutical Industry CRM Data

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

A novel tool for the assessment of pain: validation in low back pain.

BACKGROUND: Adequate pain assessment is critical for evaluating the efficacy of analgesic treatment in clinical practice and during the development of new therapies. Yet the currently used scores of global pain intensity fail to reflect the diversity of pain manifestations and the complexity of underlying biological mechanisms. We have developed a tool for a standardized assessment of pain-related symptoms and signs that differentiates pain phenotypes independent of etiology. METHODS AND FINDINGS: Using a structured interview (16 questions) and a standardized bedside examination (23 tests), we prospectively assessed symptoms and signs in 130 patients with peripheral neuropathic pain caused by diabetic polyneuropathy, postherpetic neuralgia, or radicular low back pain (LBP), and in 57 patients with non-neuropathic (axial) LBP. A hierarchical cluster analysis revealed distinct association patterns of symptoms and signs (pain subtypes) that characterized six subgroups of patients with neuropathic pain and two subgroups of patients with non-neuropathic pain. Using a classification tree analysis, we identified the most discriminatory assessment items for the identification of pain subtypes. We combined these six interview questions and ten physical tests in a pain assessment tool that we named Standardized Evaluation of Pain (StEP). We validated StEP for the distinction between radicular and axial LBP in an independent group of 137 patients. StEP identified patients with radicular pain with high sensitivity (92%; 95% confidence interval [CI] 83%-97%) and specificity (97%; 95% CI 89%-100%). The diagnostic accuracy of StEP exceeded that of a dedicated screening tool for neuropathic pain and spinal magnetic resonance imaging. In addition, we were able to reproduce subtypes of radicular and axial LBP, underscoring the utility of StEP for discerning distinct constellations of symptoms and signs. CONCLUSIONS: We present a novel method of identifying pain subtypes that we believe reflect underlying pain mechanisms. We demonstrate that this new approach to pain assessment helps separate radicular from axial back pain. Beyond diagnostic utility, a standardized differentiation of pain subtypes that is independent of disease etiology may offer a unique opportunity to improve targeted analgesic treatment.