An analysis of the perceived service quality of hospitality industry in Rio de Janeiro through the SERVQUAL model: a multiple case study

Brazil is under political and financial crises where the end seems far away. Because of that, researchers argue that the hotel rooms offered by Rio de Janeiro, built to host the Olympic Games 2016, will be difficult to occupy after the event. It is then necessary for the hotels to understand how guests perceive the service quality in order to adapt to this new era. If guests’ perceptions meet or exceed their expectations, they will be satisfied and will probably return. Thus based on the SERVQUAL approach, this paper aims to study the impact of the service dimensions on the guests’ overall satisfaction at hotels of Rio de Janeiro. Two hotels were considered representative of the city in terms of service quality and customers’ profile. Interviews to the hotel managers were performed, and questionnaires to the guests were administered. Among the five SERVQUAL dimensions – Reliability, Tangibles, Responsiveness, Assurance, and Empathy – the Empathy dimension appears to be the only one that affects the guests’ overall satisfaction. The study could also identify that gender, country of residence, home country and family income have an impact on guests’ satisfaction. This study has no intention of generalization, but rather of refining the theory about services and the SERVQUAL model.

Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.

Ingredient classification according to the digestible amino acid profile: an exploratory analysis

This study aimed: 1) to classify ingredients according to the digestible amino acid (AA) profile; 2) to determine ingredients with AA profile closer to the ideal for broiler chickens; and 3) to compare digestible AA profiles from simulated diets with the ideal protein profile. The digestible AA levels of 30 ingredients were compiled from the literature and presented as percentages of lysine according to the ideal protein concept. Cluster and principal component analyses (exploratory analyses) were used to compose and describe groups of ingredients according to AA profiles. Four ingredient groups were identified by cluster analysis, and the classification of the ingredients within each of these groups was obtained from a principal component analysis, showing 11 classes of ingredients with similar digestible AA profiles. The ingredients with AA profiles closer to the ideal protein were meat and bone meal 45, fish meal 60 and wheat germ meal, all of them constituting Class 1; the ingredients from the other classes gradually diverged from the ideal protein. Soybean meal, which is the main protein source for poultry, showed good AA balance since it was included in Class 3. on the contrary, corn, which is the main energy source in poultry diets, was classified in Class 8. Dietary AA profiles were improved when corn and/or soybean meal were partially or totally replaced in the simulations by ingredients with better AA balance.

Efficient supervised optimum-path forest classification for large datasets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Critical analysis of the international classification of headache disorders diagnostic criteria (ICHD I-1988) and (ICHD II-2004), for migraine in children and adolescents

The present study analyzed the (ICHD I-1988) and ( ICHD II-2004) diagnostic criteria in children and adolescents. Our population consisted of 496 patients of the Headache Outpatient Ward for Children and Adolescents retrospectively studied from 1992 to 2002. Individuals were classified according to three diagnostic groups: Intuitive Clinical Diagnosis ( Gold Standard), ICHD I-1988 and ICHD II-2004. They were statistically compared using the variables: Sensitivity ( S), Specificity (Sp), Positive Predictive Value (PPV), Negative Predictive Value (NPV). When ICHD I-1988 was used, the sensitivity of migraine without and with aura was 21% and 27%, respectively, whereas in ICHD II-2004 it changed to 53% and 71% without affecting specificity. As a conclusion, the current classification criteria ( ICHD II-2004) showed greater sensitivity and high specificity for migraine than ICHD I-1988, although it improved migraine diagnosis in children and adolescents, the sensitivity remains poor.

Independent clonal origin of multiple uterine leiomyomas that was determined by X chromosome inactivation and microsatellite analysis

Objective: In an attempt to clarify the clonality and genetic relationships that are involved in the tumorigenesis of uterine leiomyomas, we used a total of 43 multiple leiomyomas from 14 patients and analyzed the allelic status with 15 microsatellite markers and X chromosome inactivation analysis.Study design: We have used a set of 15 microsatellite polymorphism markers mapped on 3q, 7p, 11, and 15q by automated analysis. The X chromosome inactivation was evaluated by the methylation status of the X-linked androgen receptor gene.Results: Loss of heterozygosity analysis showed a different pattern in 7 of the 8 cases with allelic loss for at least 1 of 15 microsatellite markers that were analyzed. A similar loss of heterozygosity findings at 7p22-15 was detected in 3 samples from the same patient. X chromosome inactivation analysis demonstrated the same inactivated allele in all tumors of the 9 of 12 informative patients;. different inactivation patterns were observed in 3 cases.Conclusion: Our data support the concept that uterine leiomyomas are derived from a single cell but are generated independently in the uterus. Loss of heterozygosity findings at 7p22-15 are consistent with previous data that suggested the relevance of chromosomal aberrations at 7p that were involved in individual uterine leiomyomas. (C) 2005 Mosby, Inc. All rights reserved.

Photoelastic Analysis of Biomechanical Behavior of Single and Multiple Fixed Partial Prostheses With Different Prosthetic Connections

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Finite Element Stress Analysis of Edentulous Mandibles with Different Bone Types Supporting Multiple-Implant Superstructures

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mapping soil pollution by spatial analysis and fuzzy classification

Spatial analysis and fuzzy classification techniques were used to estimate the spatial distributions of heavy metals in soil. The work was applied to soils in a coastal region that is characterized by intense urban occupation and large numbers of different industries. Concentrations of heavy metals were determined using geostatistical techniques and classes of risk were defined using fuzzy classification. The resulting prediction mappings identify the locations of high concentrations of Pb, Zn, Ni, and Cu in topsoils of the study area. The maps show that areas of high pollution of Ni and Cu are located at the northeast, where there is a predominance of industrial and agricultural activities; Pb and Zn also occur in high concentrations in the northeast, but the maps also show significant concentrations of Pb and Zn in other areas, mainly in the central and southeastern parts, where there are urban leisure activities and trade centers. Maps were also prepared showing levels of pollution risk. These maps show that (1) Cu presents a large pollution risk in the north-northwest, midwest, and southeast sectors, (2) Pb represents a moderate risk in most areas, (3) Zn generally exhibits low risk, and (4) Ni represents either low risk or no risk in the studied area. This study shows that combining geostatistics with fuzzy theory can provide results that offer insight into risk assessment for environmental pollution.

Thermistor behaviour and electric conduction analysis of Ni-doped niobate ferroelectric: the role of multiple beta parameters

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multiple-time higher-order perturbation analysis of the regularized long-wavelength equation

By considering the long-wavelength limit of the regularized long wave (RLW) equation, we study its multiple-time higher-order evolution equations. As a first result, the equations of the Korteweg-de Vries hierarchy are shown to play a crucial role in providing a secularity-free perturbation theory in the specific case of a solitary-wave solution. Then, as a consequence, we show that the related perturbative series can be summed and gives exactly the solitary-wave solution of the RLW equation. Finally, some comments and considerations are made on the N-soliton solution, as well as on the limitations of applicability of the multiple-scale method in obtaining uniform perturbative series.

Automatic segmentation and classification of human intestinal parasites from microscopy images

Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.

Comparative analysis of different meat traceability systems using multiple criteria and a social network approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)