198 resultados para forecasting methods


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Question: When multiple observers record the same spatial units of alpine vegetation, how much variation is there in the records and what are the consequences of this variation for monitoring schemes to detect change? Location: One test summit in Switzerland (Alps) and one test summit in Scotland (Cairngorm Mountains). Method: Eight observers used the GLORIA protocols for species composition and visual cover estimates in percent on large summit sections (>100 m2) and species composition and frequency in nested quadrats (1 m2). Results: The multiple records from the same spatial unit for species composition and species cover showed considerable variation in the two countries. Estimates of pseudoturnover of composition and coefficients of variation of cover estimates for vascular plant species in 1m x 1m quadrats showed less variation than in previously published reports whereas our results in larger sections were broadly in line with previous reports. In Scotland, estimates for bryophytes and lichens were more variable than for vascular plants. Conclusions: Statistical power calculations indicated that, unless large numbers of plots were used, changes in cover or frequency were only likely to be detected for abundant species (exceeding 10% cover) or if relative changes were large (50% or more). Lower variation could be reached with the point methods and with larger numbers of small plots. However, as summits often strongly differ from each other, supplementary summits cannot be considered as a way of increasing statistical power without introducing a supplementary component of variance into the analysis and hence the power calculations.

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The relationship between electrophysiological and functional magnetic resonance imaging (fMRI) signals remains poorly understood. To date, studies have required invasive methods and have been limited to single functional regions and thus cannot account for possible variations across brain regions. Here we present a method that uses fMRI data and singe-trial electroencephalography (EEG) analyses to assess the spatial and spectral dependencies between the blood-oxygenation-level-dependent (BOLD) responses and the noninvasively estimated local field potentials (eLFPs) over a wide range of frequencies (0-256 Hz) throughout the entire brain volume. This method was applied in a study where human subjects completed separate fMRI and EEG sessions while performing a passive visual task. Intracranial LFPs were estimated from the scalp-recorded data using the ELECTRA source model. We compared statistical images from BOLD signals with statistical images of each frequency of the eLFPs. In agreement with previous studies in animals, we found a significant correspondence between LFP and BOLD statistical images in the gamma band (44-78 Hz) within primary visual cortices. In addition, significant correspondence was observed at low frequencies (<14 Hz) and also at very high frequencies (>100 Hz). Effects within extrastriate visual areas showed a different correspondence that not only included those frequency ranges observed in primary cortices but also additional frequencies. Results therefore suggest that the relationship between electrophysiological and hemodynamic signals thus might vary both as a function of frequency and anatomical region.

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As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

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Five years after the 2005 Pakistan earthquake that triggered multiple mass movements, landslides continue to pose a threat to the population of Azad Kashmir, especially during heavy monsoon rains. The thousands of landslides that were triggered by the 7.6 magnitude earthquake in 2005 were not just due to a natural phenomenon but largely induced by human activities, namely, road building, grazing, and deforestation. The damage caused by the landslides in the study area (381 km2) is estimated at 3.6 times the annual public works budget of Azad Kashmir for 2005 of US$ 1 million. In addition to human suffering, this cost constitutes a significant economic setback to the region that could have been reduced through improved land use and risk management. This article describes interdisciplinary research conducted 18 months after the earthquake to provide a more systemic approach to understanding risks posed by landslides, including the physical, environmental, and human contexts. The goal of this research is twofold: to present empirical data on the social, geological, and environmental contexts in which widespread landslides occurred following the 2005 earthquake; and, second, to describe straightforward methods that can be used for integrated landslide risk assessments in data-poor environments. The article analyzes limitations of the methodologies and challenges for conducting interdisciplinary research that integrates both social and physical data. This research concludes that reducing landslide risk is ultimately a management issue, based in land use decisions and governance.

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Ga(3+) is a semimetal element that competes for the iron-binding sites of transporters and enzymes. We investigated the activity of gallium maltolate (GaM), an organic gallium salt with high solubility, against laboratory and clinical strains of methicillin-susceptible Staphylococcus aureus (MSSA), methicillin-resistant S. aureus (MRSA), methicillin-susceptible Staphylococcus epidermidis (MSSE), and methicillin-resistant S. epidermidis (MRSE) in logarithmic or stationary phase and in biofilms. The MICs of GaM were higher for S. aureus (375 to 2000 microg/ml) than S. epidermidis (94 to 200 microg/ml). Minimal biofilm inhibitory concentrations were 3,000 to >or=6,000 microg/ml (S. aureus) and 94 to 3,000 microg/ml (S. epidermidis). In time-kill studies, GaM exhibited a slow and dose-dependent killing, with maximal action at 24 h against S. aureus of 1.9 log(10) CFU/ml (MSSA) and 3.3 log(10) CFU/ml (MRSA) at 3x MIC and 2.9 log(10) CFU/ml (MSSE) and 4.0 log(10) CFU/ml (MRSE) against S. epidermidis at 10x MIC. In calorimetric studies, growth-related heat production was inhibited by GaM at subinhibitory concentrations; and the minimal heat inhibition concentrations were 188 to 4,500 microg/ml (MSSA), 94 to 1,500 microg/ml (MRSA), and 94 to 375 microg/ml (MSSE and MRSE), which correlated well with the MICs. Thus, calorimetry was a fast, accurate, and simple method useful for investigation of antimicrobial activity at subinhibitory concentrations. In conclusion, GaM exhibited activity against staphylococci in different growth phases, including in stationary phase and biofilms, but high concentrations were required. These data support the potential topical use of GaM, including its use for the treatment of wound infections, MRSA decolonization, and coating of implants.

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BACKGROUND: The evidence for a "diabesity" epidemic is accumulating worldwide but population-based data are still scarce in the African region. We assessed the prevalence, awareness and control of diabetes (DM) in the Seychelles, a rapidly developing country in the African region. We also examined the relationship between body mass index, fasting serum insulin and DM. METHODS: Examination survey in a sample representative of the entire population aged 25-64 of the Seychelles, attended by 1255 persons (participation rate of 80.2%). An oral glucose tolerance test (OGTT) was performed in individuals with fasting blood glucose between 5.6 and 6.9 mmol/l. Diabetes mellitus (DM), impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) were defined along criteria of the ADA. Prevalence estimates were standardized for age. RESULTS: The prevalence of DM was 11.5% and 54% of persons with DM were aware of having DM. Less than a quarter of all diabetic persons under treatment were well controlled for glycemia (HbA1c), blood pressure or LDL-cholesterol. The prevalence of IGT and IFG were respectively 10.4% and 24.2%. The prevalence of excess weight (BMI > or = 25 kg/m2) and obesity (BMI > or = 30 kg/m2) was respectively 60.1% and 25.0%. Half of all DM cases in the population could be attributed to excess weight. CONCLUSION: We found a high prevalence of DM and pre-diabetes in a rapidly developing country in the African region. The strong association between overweight and DM emphasizes the importance of weight control measures to reduce the incidence of DM in the population. High rates of diabetic persons not aware of having DM in the population and insufficient cardiometabolic control among persons treated for DM stress the need for intensifying health care for diabetes.

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There has been relatively little change over recent decades in the methods used in research on self-reported delinquency. Face-to-face interviews and selfadministered interviews in the classroom are still the predominant alternatives envisaged. New methods have been brought into the picture by recent computer technology, the Internet, and an increasing availability of computer equipment and Internet access in schools. In the autumn of 2004, a controlled experiment was conducted with 1,203 students in Lausanne (Switzerland), where "paper-and-pencil" questionnaires were compared with computer-assisted interviews through the Internet. The experiment included a test of two different definitions of the (same) reference period. After the introductory question ("Did you ever..."), students were asked how many times they had done it (or experienced it), if ever, "over the last 12 months" or "since the October 2003 vacation". Few significant differences were found between the results obtained by the two methods and for the two definitions of the reference period, in the answers concerning victimisation, self-reported delinquency, drug use, failure to respond (missing data). Students were found to be more motivated to respond through the Internet, take less time for filling out the questionnaire, and were apparently more confident of privacy, while the school principals were less reluctant to allow classes to be interviewed through the Internet. The Internet method also involves considerable cost reductions, which is a critical advantage if self-reported delinquency surveys are to become a routinely applied method of evaluation, particularly so in countries with limited resources. On balance, the Internet may be instrumental in making research on self-reported delinquency far more feasible in situations where limited resources so far have prevented its implementation.

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The contribution of muscle biopsies to the diagnosis of neuromuscular disorders and the indications of various methods of examination are investigated by analysis of 889 biopsies from patients suffering from myopathic and/or neurogenic disorders. Histo-enzymatic studies performed on frozen material as well as immunohistochemistry and electron microscopy allowed to provide specific diagnoses in all the neurogenic disorders (polyneuropathies and motor neuron diseases), whereas one third of myopathies remained uncertain. Confrontation of neuropathological data with the clinical indications for histological investigations shows that muscle biopsies reveal the diagnosis in 25% of the cases (mainly in congenital and metabolic myopathies) and confirm and/or complete the clinical diagnosis in 50%. In the remaining cases with non specific abnormalities neuropathological investigations may help the clinician by excluding well defined neuromuscular disorders. Analysis of performed studies and results of investigations show the contribution and specificity of each method for the diagnosis. Statistical evaluation of this series indicates that cryostat sectioning for histo- and immunochemical and electron microscopy increases the rate of diagnoses of neuromuscular diseases: full investigation was necessary for the diagnosis in 30% of the cases. The interpretation of the wide range of pathological reactions in muscles requires a close cooperation with the clinician.

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This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

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Aims: Plasma concentrations of imatinib differ largely between patients despite same dosage, owing to large inter-individual variability in pharmacokinetic (PK) parameters. As the drug concentration at the end of the dosage interval (Cmin) correlates with treatment response and tolerability, monitoring of Cmin is suggested for therapeutic drug monitoring (TDM) of imatinib. Due to logistic difficulties, random sampling during the dosage interval is however often performed in clinical practice, thus rendering the respective results not informative regarding Cmin values.Objectives: (I) To extrapolate randomly measured imatinib concentrations to more informative Cmin using classical Bayesian forecasting. (II) To extend the classical Bayesian method to account for correlation between PK parameters. (III) To evaluate the predictive performance of both methods.Methods: 31 paired blood samples (random and trough levels) were obtained from 19 cancer patients under imatinib. Two Bayesian maximum a posteriori (MAP) methods were implemented: (A) a classical method ignoring correlation between PK parameters, and (B) an extended one accounting for correlation. Both methods were applied to estimate individual PK parameters, conditional on random observations and covariate-adjusted priors from a population PK model. The PK parameter estimates were used to calculate trough levels. Relative prediction errors (PE) were analyzed to evaluate accuracy (one-sample t-test) and to compare precision between the methods (F-test to compare variances).Results: Both Bayesian MAP methods allowed non-biased predictions of individual Cmin compared to observations: (A) - 7% mean PE (CI95% - 18 to 4 %, p = 0.15) and (B) - 4% mean PE (CI95% - 18 to 10 %, p = 0.69). Relative standard deviations of actual observations from predictions were 22% (A) and 30% (B), i.e. comparable to the intraindividual variability reported. Precision was not improved by taking into account correlation between PK parameters (p = 0.22).Conclusion: Clinical interpretation of randomly measured imatinib concentrations can be assisted by Bayesian extrapolation to maximum likelihood Cmin. Classical Bayesian estimation can be applied for TDM without the need to include correlation between PK parameters. Both methods could be adapted in the future to evaluate other individual pharmacokinetic measures correlated to clinical outcomes, such as area under the curve(AUC).