An e-marketplace of healthcare and social care services: the perceived interest

Purpose – The health and social care sector is receiving growing attention due to the increased life expectancy and to the public demand for a better quality of life and better health services. New cost-efficient approaches are required, and the paper aims to present and discuss the main results of a study undertaken in a Portuguese municipality on the perceived relevance of an e-marketplace of social and healthcare services for the inhabitants in general, and for people with special needs in particular, and the identification of the most relevant services to be offered through this platform. Design/methodology/approach – A wide survey was undertaken to identify the needs of potential users and their expectancies with relation to the proposed platform. The results of the study are a support for the project promoters to understand the viability of the solution and the requirements to the deployment of the pilot experiment, as well as to drive the selection of domains of activities/classes of services to be offered by the platform. Findings – Services such as information about healthcare services, home monitoring/accompanying services 24 hours per day, and personal hygiene services provided at home are the ones recognized by the inquired citizens as the most important, which indicates that the potential users will be mostly people with special needs or their family or caregivers. Originality/value – While still at a preliminary development phase, the project represents a good opportunity to develop a totally innovative service with high potential impact for the senior population and for individuals with special needs.

An e-marketplace of healthcare and social care services: the perceived interest

The health and social care sector is receiving growing attention for the last years, due to the increased life expectancy, the public demand for a better quality of life and for better health services. These requirements can be met with more cost-efficient approaches and using new technology-based solutions for providing services. The paper presents and discusses some of the main results of a study undertaken in Guimarães, a Municipality at the North of Portugal, on the perceived relevance of an e-Marketplace of social and healthcare services for the inhabitants in general, and in particular for people with special needs; the study also included the identification of the most relevant services to be offered by this platform and allowed concluding that such an e-Marketplace is of recognized relevance and that it is expected a good adhesion from the population.

Association between tooth loss and obesity in Brazilian adults: a population-based study

OBJECTIVE: To examine the association between tooth loss and general and central obesity among adults. METHODS: Population-based cross-sectional study with 1,720 adults aged 20 to 59 years from Florianópolis, Southern Brazil. Home interviews were performed and anthropometric measures were taken. Information on sociodemographic data, self-reported diabetes, self-reported number of teeth, central obesity (waist circumference [WC] > 88 cm in women and > 102 cm in men) and general obesity (body mass index [BMI] ≥ 30 kg/m²) was collected. We used multivariable Poisson regression models to assess the association between general and central obesity and tooth loss after controlling for confounders. We also performed simple and multiple linear regressions by using BMI and WC as continuous variables. Interaction between age and tooth loss was also assessed. RESULTS: The mean BMI was 25.9 kg/m² (95%CI 25.6;26.2) in men and 25.4 kg/m2 (95%CI 25.0;25.7) in women. The mean WC was 79.3 cm (95%CI 78.4;80.1) in men and 88.4 cm (95%CI 87.6;89.2) in women. A positive association was found between the presence of less than 10 teeth in at least one arch and increased mean BMI and WC after adjusting for education level, self-reported diabetes, gender and monthly per capita income. However, this association was lost when the variable age was included in the model. The prevalence of general obesity was 50% higher in those with less than 10 teeth in at least one arch when compared with those with 10 or more teeth in both arches after adjusting for education level, self-reported diabetes and monthly per capita family income. However, the statistical significance was lost after controlling for age. CONCLUSIONS: Obesity was associated with number of teeth, though it depended on the participants' age groups.

An approach to health and safety in E.U. forestry operations – Hazards and preventive measures

Forestry in general and logging in particular continue to be among the three most hazardous sectors in European countries. The aim of this article is to characterize health and safety problems and solutions in E.U. forestry operations, and particularly in Portuguese operations. Forest types, production, employment and ownership are used to characterize the forest sector. Forestry accidents and health problems data are mentioned. Typical hazards associated to the nature of logging operations are systematized. Preventive measures, focused on a wide spectrum of measures, making safety considerations an integral feature of all operational activities from planning to organization to execution and supervision of work are emphasized in this article.

Gender differences in the association between tooth loss and obesity among older adults in Brazil

OBJECTIVE To analyze if differences according to gender exists in the association between tooth loss and obesity among older adults.METHODS We analyzed data on 1,704 older adults (60 years and over) from the baseline of a prospective cohort study conducted in Florianopolis, SC, Southern Brazil. Multivariable logistic regression models were used to assess the association between tooth loss and general and central obesity after adjustment for confounders (age, gender, skin color, educational attainment, income, smoking, physical activity, use of dentures, hypertension, and diabetes). Linear regressions were also assessed with body mass index and waist circumference as continuous outcomes. Interaction between gender and tooth loss was further assessed.RESULTS Overall mean body mass index was 28.0 kg/m2. Mean waist circumference was 96.8 cm for males and 92.6 cm for females. Increasing tooth loss was positively associated with increased body mass index and waist circumference after adjustment for confounders. Edentates had 1.4 (95%CI 1.1;1.9) times higher odds of being centrally obese than individuals with a higher number of teeth; however, the association lost significance after adjustment for confounders. In comparison with edentate males, edentate females presented a twofold higher adjusted prevalence of general and central obesity. In the joint effects model, edentate females had a 3.8 (95%CI 2.2;6.6) times higher odds to be centrally obese in comparison with males with more than 10 teeth present in both the arches. Similarly, females with less than 10 teeth in at least one arch had a 2.7 (95%CI 1.6;4.4) times higher odds ratio of having central obesity in comparison with males with more than 10 teeth present in both the arches.CONCLUSIONS Central obesity was more prevalent than general obesity among the older adults. We did not observe any association between general obesity and tooth loss. The association between central obesity and tooth loss depends on gender – females with tooth loss had greater probability of being obese.

LSP communication in a digital age: the outcomes of teaching and learning in tertiary education

This paper discusses the changes brought by the communication revolution in teaching and learning in the scope of LSP. Its aim is to provide an insight on how teaching which was bi-dimensional, turned into a multidimensional system, gathering other complementary resources that have transformed, in a incredibly short time, the ways we receive share and store information, for instance as professionals, and keep in touch with our peers. The increasing rise of electronic publications, the incredible boom of social and professional networks, search engines, blogs, list servs, forums, e-mail blasts, Facebook pages, YouTube contents, Tweets and Apps, have twisted the way information is conveyed. Classes ceased to be predictable and have been empowered by digital platforms, innumerous and different data repositories (TILDE, IATE, LINGUEE, and so many other terminological data banks) that have definitely transformed the academic world in general and tertiary education in particular. There is a bulk of information to be digested by students, who are no longer passive but instead responsible and active for their academic outcomes. The question is whether they possess the tools to select only what is accurate and important for a certain subject or assignment, due to that overflow? Due to the reduction of the number of course years in most degrees, after the implementation of Bologna and the shrinking of the curricula contents, have students the possibility of developing critical thinking? Both teaching and learning rely on digital resources to improve the speed of the spreading of knowledge. But have those changes been effective to promote really communication? Furthermore, with the increasing Apps that have already been developed and will continue to appear for learning foreign languages, for translation among others, will the students feel the need of learning them once they have those Apps. These are some the questions we would like to discuss in our paper.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Retrospective study of malaria prevalence and Anopheles genus in the area of influence of the binational Itaipu reservoir

The importance of hydroelectric dams beside the human interchange in the maintenance of malarious foci and the occurrence of the Anopheles genus on the Binational Itaipu Reservoir were the main points of this retrospective study. Data were collected from existing registrations at National, State and Municipal Health Departments and literature systematic overview, from January 1984 to December 2003. The occurrence of some outbreak of malaria, mainly by Plasmodium vivax, and the prevalence of species of the Anopheles genus different from Anopheles darlingi in the region are discussed. The malaria in the left bank of Paraná River is a focal problem, which must be approached locally through health, educational and social actions to prevent the continuity of outbreaks in the area. Concomitantly, it is necessary to plan and apply effective surveillance measures in the influence area of the Itaipu Reservoir.

Two divergent ways to manage HR and to get to the top: an exploratory study in micro firms

Aim of the paper: The purpose of this paper is to examine human resources management practices (HRM practices) in small firms and to improve the understanding of the relationship between this kind of practices and business growth. This exploratory study is based on the resource-based view of the firm and empirical work carried out in two small firms by relating HRM practices with the firms’ results. Contribution to the literature: This is an in-depth study of HRM practices and its impact on performance growth in micro firms, isolating and controlling for most of the contextual and internal variables considered in the literature that relate HRM to growth. Firm growth analysis was broadened by the use of several dependent variables: employment growth and operational and financial performance growth. Some hypotheses for further research in identifying HRM practices in small business and its relation with firm growth are suggested. Methodology: Case study methodology was used to study two firms. The techniques used to collect data were semi-structured interviews to the owner and all the employees, unstructured observation at the firms’ facilities (during two days), entrepreneur profile definition (survey answer) and document data collection (on demographic characterization and performance results). Data was analyzed through content analysis methodology, and categories derived from the interviews’ protocols and literature. Results and implications: Results revealed that despite the firms’ organizational characteristics similarities, they differ significantly in owners’ motivation to grow, HRM practices and organizational performance and growth. Future studies should pay special attention to owner willingness to grow, to firms’ years of experience in business, to staff’s years of experience in their field of work and turnover. HRM practices in micro/small firms should be better defined and characterized. The external image of management posture relating to longitudinal financial results and growth should also be explored.

On the analysis of data emerging in non-linear and complex systemscomparison of two X-Ray prony spectra

New arguments proving that successive (repeated) measurements have a memory and actually remember each other are presented. The recognition of this peculiarity can change essentially the existing paradigm associated with conventional observation in behavior of different complex systems and lead towards the application of an intermediate model (IM). This IM can provide a very accurate fit of the measured data in terms of the Prony's decomposition. This decomposition, in turn, contains a small set of the fitting parameters relatively to the number of initial data points and allows comparing the measured data in cases where the “best fit” model based on some specific physical principles is absent. As an example, we consider two X-ray diffractometers (defined in paper as A- (“cheap”) and B- (“expensive”) that are used after their proper calibration for the measuring of the same substance (corundum a-Al2O3). The amplitude-frequency response (AFR) obtained in the frame of the Prony's decomposition can be used for comparison of the spectra recorded from (A) and (B) - X-ray diffractometers (XRDs) for calibration and other practical purposes. We prove also that the Fourier decomposition can be adapted to “ideal” experiment without memory while the Prony's decomposition corresponds to real measurement and can be fitted in the frame of the IM in this case. New statistical parameters describing the properties of experimental equipment (irrespective to their internal “filling”) are found. The suggested approach is rather general and can be used for calibration and comparison of different complex dynamical systems in practical purposes.

New strategies to detect and understand genotype-by-environment interactions and QTL-by-environment interactions

Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco, especialidade em Estatística

Effects of an exercise program on blood pressure in patients with treated hypertension and chronic Chagas' heart disease

INTRODUCTION: Previous studies describe an imbalance of the autonomic nervous system in Chagas' disease causing increased sympathetic activity, which could influence the genesis of hypertension. However, patients undergoing regular physical exercise could counteract this condition, considering that exercise causes physiological responses through autonomic and hemodynamic changes that positively affect the cardiovascular system. This study aimed to evaluate the effects of an exercise program on blood pressure in hypertensive patients with chronic Chagas' heart disease. METHODS: We recruited 17 patients to a 24-week regular exercise program and used ambulatory blood pressure monitoring before and after training. We determined the differences in the systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean blood pressure (MBP) from the beginning to the end of the study. RESULTS: The blood pressures were evaluated in general and during periods of wakefulness and sleep, respectively: SBP (p = 0.34; 0.23; 0.85), DBP (p = 0.46; 0.44; 0.94) and MBP (p = 0.41; 0.30; 0.97). CONCLUSIONS: There was no statistically significant change in blood pressure after the 24-week exercise program; however, we concluded that physical training is safe for patients with chronic Chagas' disease, with no incidence of increase in blood pressure.

Mechanism of extracellular silver nanoparticles synthesis by Stereum hirsutum and Fusarium oxysporum

The increasing interest for greener and biological methods of synthesis has led to the development of non-toxic and comparatively more bioactive nanoparticles. Unlike physical and chemical methods of nanoparticle synthesis, microbial synthesis in general and mycosynthesis in particular is cost-effective and environment-friendly. However, different aspects, such as the rate of synthesis, monodispersity and downstream processing, need to be improved. Many fungal-based mechanisms have been proposed for the formation of silver nanoparticles (AgNPs), mainly those involving the presence of nitrate reductase, which has been detected in filtered fungus cell used for AgNPs production. There is a general acceptance that nitrate reductase is the main responsible for the reduction of Ag ions for the formation of AgNPs. However, this generally accepted mechanism for fungal AgNPs production is not totally understood. In order to elucidate the molecules participating in the mechanistic formation of metal nanoparticles, the current study is focused on the enzymes and other organic compounds involved in the biosynthesis of AgNPs. The use of each free fungal mycelium of both Stereum hirsutum and Fusarium oxysporum will be assessed. In order to identify defective mutants on the nitrate reductase structural gene niaD, fungal cultures of S.hirsutum and F.oxysporum will be selected by chlorate resistance. In addition, in order to verify if each compound identified as key-molecule influenced on the production of nanoparticles, an in vitro assay using different nitrogen sources will be developed. Lately, fungal extracellular enzymes will be measured and an in vitro assay will be done. Finally, The nanoparticle formation and its characterization will be evaluated by UV-visible spectroscopy, electron microscopy (TEM), X-ray diffraction analysis (XRD), Fourier transforms infrared spectroscopy (FTIR), and LC-MS/MS.