999 resultados para basic density


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This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

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In mammals, many aspects of metabolism are under circadian control. At least in part, this regulation is achieved by core-clock or clock-controlled transcription factors whose abundance and/or activity oscillate during the day. The clock-controlled proline- and acidic amino acid-rich domain basic leucine zipper proteins D-site-binding protein, thyrotroph embryonic factor, and hepatic leukemia factor have previously been shown to participate in the circadian control of xenobiotic detoxification in liver and other peripheral organs. Here we present genetic and biochemical evidence that the three proline- and acidic amino acid-rich basic leucine zipper proteins also play a key role in circadian lipid metabolism by influencing the rhythmic expression and activity of the nuclear receptor peroxisome proliferator-activated receptor α (PPARα). Our results suggest that, in liver, D-site-binding protein, hepatic leukemia factor, and thyrotroph embryonic factor contribute to the circadian transcription of genes specifying acyl-CoA thioesterases, leading to a cyclic release of fatty acids from thioesters. In turn, the fatty acids act as ligands for PPARα, and the activated PPARα receptor then stimulates the transcription of genes encoding proteins involved in the uptake and/or metabolism of lipids, cholesterol, and glucose metabolism.

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Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.

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We have previously reported (Dobreva, I., Waeber, G., Mooser, V., James, R. W., and Widmann, C. (2003) J. Lipid Res. 44, 2382-2390) that low density lipoproteins (LDLs) induce activation of the p38 MAPK pathway, resulting in fibroblast spreading and lamellipodia formation. Here, we show that LDL-stimulated fibroblast spreading and wound sealing are due to secretion of a soluble factor. Using an antibody-based human protein array, interleukin-8 (IL-8) was identified as the main cytokine whose concentration was increased in supernatants from LDL-stimulated cells. Incubation of supernatants from LDL-treated cells with an anti-IL-8 blocking antibody completely abolished their ability to induce cell spreading and mediate wound closure. In addition, fibroblasts treated with recombinant IL-8 spread to the same extent as cells incubated with LDL or supernatants from LDL-treated cells. The ability of LDL and IL-8 to induce fibroblast spreading was mediated by the IL-8 receptor type II (CXCR-2). Furthermore, LDL-induced IL-8 production and subsequent wound closure required the activation of the p38 MAPK pathway, because both processes were abrogated by a specific p38 inhibitor. Therefore, the capacity of LDLs to induce fibroblast spreading and accelerate wound closure relies on their ability to stimulate IL-8 secretion in a p38 MAPK-dependent manner. Regulation of fibroblast shape and migration by lipoproteins may be relevant to atherosclerosis that is characterized by increased LDL cholesterol levels, IL-8 production, and extensive remodeling of the vessel wall.

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A video summary by Catherine Comiskey

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The quantity of interest for high-energy photon beam therapy recommended by most dosimetric protocols is the absorbed dose to water. Thus, ionization chambers are calibrated in absorbed dose to water, which is the same quantity as what is calculated by most treatment planning systems (TPS). However, when measurements are performed in a low-density medium, the presence of the ionization chamber generates a perturbation at the level of the secondary particle range. Therefore, the measured quantity is close to the absorbed dose to a volume of water equivalent to the chamber volume. This quantity is not equivalent to the dose calculated by a TPS, which is the absorbed dose to an infinitesimally small volume of water. This phenomenon can lead to an overestimation of the absorbed dose measured with an ionization chamber of up to 40% in extreme cases. In this paper, we propose a method to calculate correction factors based on the Monte Carlo simulations. These correction factors are obtained by the ratio of the absorbed dose to water in a low-density medium □D(w,Q,V1)(low) averaged over a scoring volume V₁ for a geometry where V₁ is filled with the low-density medium and the absorbed dose to water □D(w,QV2)(low) averaged over a volume V₂ for a geometry where V₂ is filled with water. In the Monte Carlo simulations, □D(w,QV2)(low) is obtained by replacing the volume of the ionization chamber by an equivalent volume of water, according to the definition of the absorbed dose to water. The method is validated in two different configurations which allowed us to study the behavior of this correction factor as a function of depth in phantom, photon beam energy, phantom density and field size.

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Basic aspects of cell biology of Pneumocystis carinii are reviewed with major emphasis on its life cycle and the structural organization of the trophozoites and cyst forms. Initially considered as a protozoan it is now established that Pneumocystis belongs to the Fungi Kingdom. Its life cycle includes two basic forms: (a) trophozoites, which are haploid cells that divide by binary fission and may conjugate with each other forming an early procyst and (b) cysts where division takes place through a meiotic process with the formation of eight nuclei followed by cytoplasmic delimitation and formation of intracystic bodies which are subsequently released and transformed into trophozoites. Basic aspects of the structure of the two developmental stages of P. carinii are reviewed.

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Purpose: EEG is mandatory in the diagnosis of the epilepsy syndrome. However, its potential as imaging tool is still under estimated. In the present study, we aim to determine the prerequisites of maximal benefit of electric source imaging (ESI) to localize the irritative zone in patients with focal epilepsy. Methods: One hundred fifty patients suffering from focal epilepsy and with minimum 1 year postoperative follow-up were studied prospectively and blinded to the underlying diagnosis. We evaluated the influence of two important factors on sensitivity and specificity of ESI: the number of electrodes (low resolution, LR-ESI: <30 versus high resolution, HR-ESI: 128-256 electrodes), and the use of individual MRI (i-MRI) versus template MRI (t-MRI) as the head model. Findings: ESI had a sensitivity of 85% and a specificity of 87% when HR-ESI with i-MRI was used. Using LR-ESI, sensitivity decreased to 68%, or even 57% when only t-MRI was available. The sensitivity of HR-ESI/i-MRI compared favorably with those of MRI (76%), PET (69%) and ictal/interictal SPECT (64%). Interpretation: This study on a large patient group shows excellent sensitivity and specificity of ESI if 128 EEG channels or more are used for ESI and if the results are coregistered to the patient's individual MRI. Localization precision is as high as or even higher than established brain imagery techniques. HR-ESI appears to be a valuable additional imaging tool, given that larger electrode arrays are easily and rapidly applied with modern EEG equipment and that structural MRI is nearly always available for these patients.

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Background: The prevalence of a low bone mineral density (T-score <-1 SD) in postmenopausal women with a fragility fracture may vary from 70% to less than 50%. In one study (Siris ES. Arch Intern Med. 2004;164:1108-12), the prevalence of osteoporosis was very low at 6.4%. The corresponding values in men are rarely reported. Methods: In a nationwide Swiss survey, all consecutive patients aged 50+ presenting with one or more fractures to the emergency ward, were recruited by 8 participating hospitals (University Hospitals: Basel, Bern, and Lausanne; cantonal hospitals: Fribourg, Luzern, and St Gallen; regional hospitals: Estavayer and Riaz) between 2004 and 2006. Diagnostic workup was collected for descriptive analysis. Results: 3667 consecutive patients with a fragility fracture, 2797 women (73.8 ± 11.6 years) and 870 men (70.0 ± 12.1 years), were included. DXA measurement was performed in 1152 (44%) patients. The mean of the lowest T-score values was -2.34 SD in women and -2.16 SD in men. In the 908 women, the prevalence of osteoporosis and osteopenia according to the fracture type was: sacrum (100%, 0%), rib (100%, 0%), thoracic vertebral (78%, 22%), femur trochanter (67%, 26%), pelvis (66%, 32%), lumbar vertebral (63%, 28%), femoral neck (53%, 34%), femur shaft (50%, 50%), proximal humerus (50%, 34%), distal forearm (41%, 45%), tibia proximal (41%, 31%), malleolar lateral (28%, 46%), malleolar median (13%, 47%). The corresponding percentages in the 244 men were: distal forearm (70%, 19%), rib (63%, 11%), pelvis (60%, 20%), malleolar median (60%, 32%), femur trochanter (48%, 31%), thoracic vertebral (47%, 53%), lumbar vertebral (43%, 36%), proximal humerus (40%, 43%), femoral neck (28%, 55%), tibia proximal (26%, 36%), malleolar lateral (18%, 56%). Conclusion: The probability of underlying osteoporosis or osteopenia in men and women aged 50+ who experienced a fragility fracture was beyond 75% in fractures of the sacrum, pelvis, spine, femur, proximal humerus and distal forearm. The medial and lateral malleolar fractures had the lowest predictive value in women, not in men.

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Reseña del congreso WePreserve 2009 que tuvo lugar los pasados 23 al 27 de marzo en Barcelona, organizadopor la Facultad de Biblioteconomía y Documentación de la Universitat de Barcelona, con la colaboración del Institut d'Estudis Catalans, la Biblioteca de Catalunya y el Consorci de Biblioteques de Barcelona. El seminario 2009 WePreserve se celebra anualmente desde el año 2007 y participan todas las figuras de referencia europeas en materia de investigación en sistemas y metodologías que garantizan la preservación digital de los documentos: Digital Preservation Europe (DPE), Preservation and Long-term Access Through Networked Services (Planets), Cultural Artistic and Scientific Knowledge for Preservation, Access and Retrieval (CASPAR), y Network of expertise in Digital long-term preservation (nestor).

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Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individual. A particular case of FDA is when the observed functions are densityfunctions, that are also an example of infinite dimensional compositional data. In thiswork we compare several methods for dimensionality reduction for this particular typeof data: functional principal components analysis (PCA) with or without a previousdata transformation and multidimensional scaling (MDS) for diferent inter-densitiesdistances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (householdsincome distributions)

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Bihar, India has been in the grip of kala-azar for many years. Its rampant and severe spread has made life miserable in most parts of the state. Such conditions require a comprehensive understanding of this affliction. The numbers coming out of the districts prone to the disease in the north and south Ganges have provided us with several startling revelations, as there are striking uniformities on both sides, including similar vegetation, water storage facilities, house construction and little change in risk factors. The northern areas have been regularly sprayed with DDT since 1977, but eradication of the disease appears to be a distant dream. In 2007 alone, there were as many as 37,738 cases in that region. In contrast, the southern districts of Patna and Nalanda have never had the disease in its epidemic form and endemic disease has been present in only some pockets of the two districts. In those cases, two rounds of spraying with DDT had very positive results, with successful control and no new established foci. In addition, an eleven-year longitudinal study of the man hour density and house index for the vector Phlebotomus argentipes demonstrated that they were quite high in Patna and Nalanda and quite low in north Bihar. Given these facts, an attempt has been made to unravel the role of P. argentipes saliva (salivary gland) in the epidemiology of kala-azar. It was determined that patchy DDT spraying should be avoided for effective control of kala-azar.

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In the present paper, we evaluate the relationship between climate variables and population density of Lutzomyia longipalpis in Montes Claros, an area of active transmission of American visceral leishmaniasis (AVL) in Brazil. Entomological captures were performed in 10 selected districts of the city, between September 2002-August 2003. A total of 773 specimens of L. longipalpiswere captured in the period and the population density could be associated with local climate variables (cumulative rainfall, average temperature and relative humidity) through a mathematical linear model with a determination coefficient (Rsqr) of 0.752. Although based on an oversimplified statistical analysis, as far as the vector is concerned, this approach showed to be potentially useful as a starting point to guide control measures for AVL in Montes Claros.