965 resultados para dementia case-finding
Resumo:
Performance evaluation increasingly assumes a more important role in any organizational environment. In the transport area, the drivers are the company’s image and for this reason it is important to develop and increase their performance and commitment to the company goals. This evaluation can be used to motivate driver to improve their performance and to discover training needs. This work aims to create a performance appraisal evaluation model of the drivers based on the multi-criteria decision aid methodology. The MMASSI (Multicriteria Methodology to Support Selection of Information Systems) methodology was adapted by using a template supporting the evaluation according to the freight transportation company in study. The evaluation process involved all drivers (collaborators being evaluated), their supervisors and the company management. The final output is a ranking of the drivers, based on their performance, for each one of the scenarios used.
Resumo:
This project aims to study the implementation of Lean principles and tools in several levels of logistics, from internal logistics to interface with distribution center and suppliers, in an industrial plant. The main focus of all efforts is to create the conditions to approach the continuous flow scenario in the manufacturing processes. The subject of improvement actions is a company whose core activity is car seat production, more specifically the car seat cover production and assembly. This focuses the assembly process, which requires the usage of a considerable variety of components and therefore is an important obstacle to the implementation of continuous flow. The most salient issues are related with inefficient interaction between sections and late supply of components in assembly lines, forcing the operator to abandon his work station and leading to production interruption. As an operational methodology, actions from Lean philosophy and optimization were implemented according to project management principles.
Resumo:
Multi-criteria decision analysis(MCDA) has been one of the fastest-growing areas of operations research during the last decades. The academic attention devoted to MCDA motivated the development of a great variety of approaches and methods within the field. These methods distinguish themselves in terms of procedures, theoretical assumptions and type of decision addressed. This diversity poses challenges to the process of selecting the most suited method for a specific real-world decision problem. In this paper we present a case study in a real-world decision problem arising in the painting sector of an automobile plant. We tackle the problem by resorting to the well-known AHP method and to the MCDA method proposed by Pereira and Fontes (2012) (MMASSI). By relying on two, rather than one, MCDA methods we expect to improve the confidence and robustness of the obtained results. The contributions of this paper are twofold: first, we intend to investigate the contrasts and similarities of the results obtained by distinct MCDA approaches (AHP and MMASSI); secondly, we expect to enrich the literature of the field with a real-world MCDA case study on a complex decision making problem since there is a paucity of applied research work addressing real decision problems faced by organizations.
Resumo:
Multi-criteria decision analysis (MCDA) has been one of the fastest-growing areas of operations research during the last decades. The academic attention devoted to MCDA motivated the development of a great variety of approaches and methods within the field. These methods distinguish themselves in terms of procedures, theoretical assumptions and type of decision addressed. This diversity poses challenges to the process of selecting the most suited method for a specific real-world decision problem. In this paper we present a case study in a real-world decision problem arising in the painting sector of an automobile plant. We tackle the problem by resorting to the well-known AHP method and to the MCDA method proposed by Pereira and Fontes (2012) (MMASSI). By relying on two, rather than one, MCDA methods we expect to improve the confidence and robustness of the obtained results. The contributions of this paper are twofold: first, we intend to investigate the contrasts and similarities of the results obtained by distinct MCDA approaches (AHP and MMASSI); secondly, we expect to enrich the literature of the field with a real-world MCDA case study on a complex decision making problem since there is a paucity of applied research work addressing real decision problems faced by organizations.
Resumo:
This paper reports the first case of human infection caused by Ttrichophyton vanbreuseghemii in Brazil.
Resumo:
It is presented a case of auricular chromoblastomycosis mimicking an eczematous lesion. The authors refer the rarity of this localization. All reported cases of auricular chromoblastomycosis have been caused by Fonsecaea pedrosoi but in the present case the etiologic agent was Phialophora verrucosa.
Resumo:
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.
Resumo:
This is a case report that describe an association of AIDS, visceral leishmaniasis and probable disseminated tuberculosis. Due to the spread of AIDS in developing areas worldwide this association would be more frequently, seen on subjects from endemic areas where this protozoonosis is prevalent. More than one opportunistic infection related with the endemic diseases of the developing regions can be associated with those immunocompromised patients.
Resumo:
The curricular movement known as Modern Mathematics aimed at the transformation of representations and practices in school mathematics. Its study provides us with ways of understanding how these changes came about. The purpose of this paper is to contribute to the understanding of the ways in which representations of school mathematics gradually were influenced by ideas from the Modern Mathematics movement, how these new ideas merged into local educational traditions, and how they were transformed into meaningful practice. This work is centred on the Portuguese context from the middle 1950s to the middle 1960s, and builds on Chervel’s notion of school culture and Gruzinski’s discussion of connected histories.
Resumo:
A 36-year-old black man, without history of systemic disease or ocular trauma developed a corneal infection in his left eye. He was treated with antibacterial antibiotic and corticosteroids for one month prior to diagnosis. Fungal hyphae and chlamydospores were found in a KOH preparation of the corneal scrapings, and positive cultures for Fusarium solani were obtained in Sabouraud dextrose agar. It is emphasized the cautious use of antibiotics and steroids in corneal diseases, and the need of considering the involvement of opportunistic fungi in the etiology of these infections.
Resumo:
We present a case of subcutaneous hyalohyphomycosis due to Acremonium recifei, a species whose habitat is probably the soil, first identified in 1934 by Arêa Leão and Lobo in a case of podal eumycetoma with white-yellowish grains and initially named Cephalosporium recifei. A white immunocompetent female patient from the state of Bahia, Brazil, with a history of traumatic injury to the right hand is reported. The lesion was painless, with edema, inflammation and the presence of fistulae. Seropurulent secretion with the absence of grains was present. Histopathological examination of material stained with hematoxylin-eosin showed hyaline septate hyphae. A culture was positive for Acremonium recifei. Treatment with itraconazole, 200 mg/day, for two months led to a favorable course and cure of the process. We report for the first time in the literature a case of subcutaneous hyalohyphomycosis due to Acremonium recifei in a immunocompetent woman. Treatment with itraconazole 200 mg/day, for two months, resulted in cure.
Resumo:
An adult patient with chronic schistosomiasis from an endemic area, complained about a seven day fever, along with jaundice and lumbar backache on the right side. Image exams showed multiple pyogenic liver abscesses. All the classic etiologies were discarded through clinical, radiological and laboratorial criteria. Schistosomiasis can cause pylephlebitis as a complication, along with immunesuppression, granulomatous reaction with central lobular liver necrosis and a greater risk of infection. The authors suggest that schistosomiasis in its chronic form may be the predisposing cause of multiple pyogenic liver abscesses, especially in endemic areas.
Resumo:
In the present study we report the results of an analysis, based on ribotyping of Corynebacterium diphtheriae intermedius strains isolated from a 9 years old child with clinical diphtheria and his 5 contacts. Quantitative analysis of RFLPs of rRNA was used to determine relatedness of these 7 C.diphtheriae strains providing support data in the diphtheria epidemiology. We have also tested those strains for toxigenicity in vitro by using the Elek's gel diffusion method and in vivo by using cell culture method on cultured monkey kidney cell (VERO cells). The hybridization results revealed that the 5 C.diphtheriae strains isolated from contacts and one isolated from the clinical case (nose case strain) had identical RFLP patterns with all 4 restriction endonucleases used, ribotype B. The genetic distance from this ribotype and ribotype A (throat case strain), that we initially assumed to be responsible for the illness of the patient, was of 0.450 showing poor genetic correlation among these two ribotypes. We found no significant differences concerned to the toxin production by using the cell culture method. In conclusion, the use of RFLPs of rRNA gene was successful in detecting minor differences in closely related toxigenic C.diphtheriae intermedius strains and providing information about genetic relationships among them.
Resumo:
The authors report the clinical, laboratorial and epidemiological aspects of a human case of jungle yellow fever. The patient suffered from fever, chills, sweating, headaches, backaches, myalgia, epigastric pains, nausea, vomiting, diarrhea and prostration. He was unvaccinated and had been working in areas where cases of jungle yellow fever had been confirmed. Investigations concerning the yellow fever virus were performed. Blood samples were collected on several days in the course of the illness. Three of these samples (those obtained on days 5,7 and 10) were inoculated into suckling mice in attempt to isolate virus and to titrate the viremia level. Serological surveys were carried out by using the IgM Antibodies Capture Enzyme Linked Immunosorbent Assay (MAC-ELISA), Complement Fixation (CF), Hemagglulinalion Inhibition (HI) and Neutralization (N) tests. The yellow fever virus, recovered from the two first samples and the virus titration, showed high level of viremia. After that, specific antibodies appeared in all samples. The interval between the end of the viremia and the appearance of the antibodies was associated with the worsening of clinical symptoms, including bleeding of the mucous membrane. One must be aware of the risk of having a urban epidemics in areas where Aedes aegypti is found in high infestation indexes.