939 resultados para Non-gaussian Random Functions
Resumo:
Background: Worldwide distribution of surgical interventions is unequal. Developed countries account for the majority of surgeries and information about non-cardiac operations in developing countries is scarce. The purpose of our study was to describe the epidemiological data of non-cardiac surgeries performed in Brazil in the last years. Methods and Findings: This is a retrospective cohort study that investigated the time window from 1995 to 2007. We collected information from DATASUS, a national public health system database. The following variables were studied: number of surgeries, in-hospital expenses, blood transfusion related costs, length of stay and case fatality rates. The results were presented as sum, average and percentage. The trend analysis was performed by linear regression model. There were 32,659,513 non-cardiac surgeries performed in Brazil in thirteen years. An increment of 20.42% was observed in the number of surgeries in this period and nowadays nearly 3 million operations are performed annually. The cost of these procedures has increased tremendously in the last years. The increment of surgical cost was almost 200%. The total expenses related to surgical hospitalizations were more than $10 billion in all these years. The yearly cost of surgical procedures to public health system was more than $1.27 billion for all surgical hospitalizations, and in average, U$445.24 per surgical procedure. The total cost of blood transfusion was near $98 million in all years and annually approximately $10 million were spent in perioperative transfusion. The surgical mortality had an increment of 31.11% in the period. Actually, in 2007, the surgical mortality in Brazil was 1.77%. All the variables had a significant increment along the studied period: r square (r(2)) = 0.447 for the number of surgeries (P = 0.012), r(2) = 0.439 for in-hospital expenses (P = 0.014) and r(2) = 0.907 for surgical mortality (P = 0.0055). Conclusion: The volume of surgical procedures has increased substantially in Brazil through the past years. The expenditure related to these procedures and its mortality has also increased as the number of operations. Better planning of public health resource and strategies of investment are needed to supply the crescent demand of surgery in Brazil.
Resumo:
We consider the problem of interaction neighborhood estimation from the partial observation of a finite number of realizations of a random field. We introduce a model selection rule to choose estimators of conditional probabilities among natural candidates. Our main result is an oracle inequality satisfied by the resulting estimator. We use then this selection rule in a two-step procedure to evaluate the interacting neighborhoods. The selection rule selects a small prior set of possible interacting points and a cutting step remove from this prior set the irrelevant points. We also prove that the Ising models satisfy the assumptions of the main theorems, without restrictions on the temperature, on the structure of the interacting graph or on the range of the interactions. It provides therefore a large class of applications for our results. We give a computationally efficient procedure in these models. We finally show the practical efficiency of our approach in a simulation study.
Resumo:
Background: Myelodysplastic syndromes (MDS) are a group of clonal hematological disorders characterized by ineffective hematopoiesis with morphological evidence of marrow cell dysplasia resulting in peripheral blood cytopenia. Microarray technology has permitted a refined high-throughput mapping of the transcriptional activity in the human genome. Non-coding RNAs (ncRNAs) transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression, and in the regulation of exon-skipping and intron retention. Characterization of ncRNAs in progenitor cells and stromal cells of MDS patients could be strategic for understanding gene expression regulation in this disease. Methods: In this study, gene expression profiles of CD34(+) cells of 4 patients with MDS of refractory anemia with ringed sideroblasts (RARS) subgroup and stromal cells of 3 patients with MDS-RARS were compared with healthy individuals using 44 k combined intron-exon oligoarrays, which included probes for exons of protein-coding genes, and for non-coding RNAs transcribed from intronic regions in either the sense or antisense strands. Real-time RT-PCR was performed to confirm the expression levels of selected transcripts. Results: In CD34(+) cells of MDS-RARS patients, 216 genes were significantly differentially expressed (q-value <= 0.01) in comparison to healthy individuals, of which 65 (30%) were non-coding transcripts. In stromal cells of MDS-RARS, 12 genes were significantly differentially expressed (q-value <= 0.05) in comparison to healthy individuals, of which 3 (25%) were non-coding transcripts. Conclusions: These results demonstrated, for the first time, the differential ncRNA expression profile between MDS-RARS and healthy individuals, in CD34(+) cells and stromal cells, suggesting that ncRNAs may play an important role during the development of myelodysplastic syndromes.
Resumo:
The doubly positively charged gas-phase molecules BrO(2+) and NBr(2+) have been produced by prolonged high-current energetic oxygen (17 keV (16)O(-)) ion surface bombardment (ion beam sputtering) of rubidium bromide (RbBr) and of ammonium bromide (NH(4)Br) powdered ionic salt samples, respectively, pressed into indium foil. These novel species were observed at half-integer m/z values in positive ion mass spectra for ion flight times of roughly similar to 12 mu s through a magnetic-sector secondary ion mass spectrometer. Here we present these experimental results and combine them with a detailed theoretical investigation using high level ab initio calculations of the ground states of BrO(2+) and NBr(2+), and a manifold of excited electronic states. NBr(2+) and BrO(2+), in their ground states, are long-lived metastable gas-phase molecules with well depths of 2.73 x 10(4) cm(-1) (3.38 eV) and 1.62 x 10(4) cm(-1) (2.01 eV); their fragmentation channels into two monocations lie 2.31 x 10(3) cm(-1) (0.29 eV) and 2.14 x 10(4) cm(-1) (2.65 eV) below the ground state minimum. The calculated lifetimes for NBr(2+) (v '' < 35) and BrO(2+) (v '' < 18) are large enough to be considered stable against tunneling. For NBr(2+), we predicted R(e) = 3.051 a(0) and omega(e) = 984 cm(-1); for BrO(2+), we obtained 3.033 a(0) and 916 cm(-1), respectively. The adiabatic double ionization energies of BrO and NBr to form metastable BrO(2+) and NBr(2+) are calculated to be 30.73 and 29.08 eV, respectively. The effect of spin-orbit interactions on the low-lying (Lambda + S) states is also discussed. (C) 2011 American Institute of Physics. [doi:10.1063/1.3562121]
Resumo:
The low-lying doublet and quartet electronic states of the species SeF correlating with the first dissociation channel are investigated theoretically at a high-level of electronic correlation treatment, namely, the complete active space self-consistent field/multireference single and double excitations configuration interaction (CASSCF/MRSDCI) using a quintuple-zeta quality basis set including a relativistic effective core potential for the selenium atom. Potential energy curves for (Lambda+S) states and the corresponding spectroscopic properties are derived that allows for an unambiguous assignment of the only spectrum known experimentally as due to a spin-forbidden X (2)Pi-a (4)Sigma(-) transition, and not a A (2)Pi-X (2)Pi transition as assumed so far. For the bound excited doublets, yet unknown experimentally, this study is the first theoretical characterization of their spectroscopic properties. Also the spin-orbit coupling constant function for the X (2)Pi state is derived as well as the spin-orbit coupling matrix element between the X (2)Pi and a (4)Sigma(-) states. Dipole moment functions and vibrationally averaged dipole moments show SeF to be a very polar species. An overview of the lowest-lying spin-orbit (Omega) states completes this description. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3426315]
Resumo:
P>Soil bulk density values are needed to convert organic carbon content to mass of organic carbon per unit area. However, field sampling and measurement of soil bulk density are labour-intensive, costly and tedious. Near-infrared reflectance spectroscopy (NIRS) is a physically non-destructive, rapid, reproducible and low-cost method that characterizes materials according to their reflectance in the near-infrared spectral region. The aim of this paper was to investigate the ability of NIRS to predict soil bulk density and to compare its performance with published pedotransfer functions. The study was carried out on a dataset of 1184 soil samples originating from a reforestation area in the Brazilian Amazon basin, and conventional soil bulk density values were obtained with metallic ""core cylinders"". The results indicate that the modified partial least squares regression used on spectral data is an alternative method for soil bulk density predictions to the published pedotransfer functions tested in this study. The NIRS method presented the closest-to-zero accuracy error (-0.002 g cm-3) and the lowest prediction error (0.13 g cm-3) and the coefficient of variation of the validation sets ranged from 8.1 to 8.9% of the mean reference values. Nevertheless, further research is required to assess the limits and specificities of the NIRS method, but it may have advantages for soil bulk density predictions, especially in environments such as the Amazon forest.
Resumo:
P>During the lifetime of an angiosperm plant various important processes such as floral transition, specification of floral organ identity and floral determinacy, are controlled by members of the MADS domain transcription factor family. To investigate the possible non-cell-autonomous function of MADS domain proteins, we expressed GFP-tagged clones of AGAMOUS (AG), APETALA3 (AP3), PISTILLATA (PI) and SEPALLATA3 (SEP3) under the control of the MERISTEMLAYER1 promoter in Arabidopsis thaliana plants. Morphological analyses revealed that epidermal overexpression was sufficient for homeotic changes in floral organs, but that it did not result in early flowering or terminal flower phenotypes that are associated with constitutive overexpression of these proteins. Localisations of the tagged proteins in these plants were analysed with confocal laser scanning microscopy in leaf tissue, inflorescence meristems and floral meristems. We demonstrated that only AG is able to move via secondary plasmodesmata from the epidermal cell layer to the subepidermal cell layer in the floral meristem and to a lesser extent in the inflorescence meristem. To study the homeotic effects in more detail, the capacity of trafficking AG to complement the ag mutant phenotype was compared with the capacity of the non-inwards-moving AP3 protein to complement the ap3 mutant phenotype. While epidermal expression of AG gave full complementation, AP3 appeared not to be able to drive all homeotic functions from the epidermis, perhaps reflecting the difference in mobility of these proteins.
Resumo:
Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.