996 resultados para signal loss


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Recent literature has suggested that macroeconomic forecasters may have asymmetric loss functions, and that there may be heterogeneity across forecasters in the degree to which they weigh under- and over-predictions. Using an individual-level analysis that exploits the Survey of Professional Forecasters respondents’ histogram forecasts, we find little evidence of asymmetric loss for the inflation forecasters

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This paper presents an in-depth critical discussion and derivation of a detailed small-signal analysis of the Phase-Shifted Full-Bridge (PSFB) converter. Circuit parasitics, resonant inductance and transformer turns ratio have all been taken into account in the evaluation of this topology’s open-loop control-to-output, line-to-output and load-to-output transfer functions. Accordingly, the significant impact of losses and resonant inductance on the converter’s transfer functions is highlighted. The enhanced dynamic model proposed in this paper enables the correct design of the converter compensator, including the effect of parasitics on the dynamic behavior of the PSFB converter. Detailed experimental results for a real-life 36V-to-14V/10A PSFB industrial application show excellent agreement with the predictions from the model proposed herein.1

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The observed depletion of the ozone layer from the 1980s onwards is attributed to halogen source gases emitted by human activities. However, the precision of this attribution is complicated by year-to-year variations in meteorology, that is, dynamical variability, and by changes in tropospheric ozone concentrations. As such, key aspects of the total-column ozone record, which combines changes in both tropospheric and stratospheric ozone, remain unexplained, such as the apparent absence of a decline in total-column ozone levels before 1980, and of any long-term decline in total-column ozone levels in the tropics. Here we use a chemistry–climate model to estimate changes in halogen-induced ozone loss between 1960 and 2010; the model is constrained by observed meteorology to remove the effects of dynamical variability, and driven by emissions of tropospheric ozone precursors to separate out changes in tropospheric ozone. We show that halogen-induced ozone loss closely followed stratospheric halogen loading over the studied period. Pronounced enhancements in ozone loss were apparent in both hemispheres following the volcanic eruptions of El Chichon and, in particular, Mount Pinatubo, which significantly enhanced stratospheric aerosol loads. We further show that approximately 40% of the long-term non-volcanic ozone loss occurred before 1980, and that long-term ozone loss also occurred in the tropical stratosphere. Finally, we show that halogen-induced ozone loss has declined by over 10% since stratospheric halogen loading peaked in the late 1990s, indicating that the recovery of the ozone layer is well underway.

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Policy-makers are creating mechanisms to help developing countries cope with loss and damage from climate change, but the negotiations are largely neglecting scientific questions about what the impacts of climate change actually are. Mitigation efforts have failed to prevent the continued increase of anthropogenic greenhouse gas (GHG) emissions. Adaptation is now unlikely to be sufficient to prevent negative impacts from current and future climate change1. In this context, vulnerable nations argue that existing frameworks to promote mitigation and adaptation are inadequate, and have called for a third international mechanism to deal with residual climate change impacts, or “loss and damage”2. In 2013, the United Nations Framework Convention on Climate Change (UNFCCC) responded to these calls and established the Warsaw International Mechanism (WIM) to address loss and damage from the impacts of climate change in developing countries3. An interim Executive Committee of party representatives has been set up, and is currently drafting a two-year workplan comprising meetings, reports, and expert groups; and aiming to enhance knowledge and understanding of loss and damage, strengthen dialogue among stakeholders, and promote enhanced action and support. Issues identified as priorities for the WIM thus far include: how to deal with non-economic losses, such as loss of life, livelihood, and cultural heritage; and linkages between loss and damage and patterns of migration and displacement2. In all this, one fundamental issue still demands our attention: which losses and damages are relevant to the WIM? What counts as loss and damage from climate change?

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During the last decades, several windstorm series hit Europe leading to large aggregated losses. Such storm series are examples of serial clustering of extreme cyclones, presenting a considerable risk for the insurance industry. Clustering of events and return periods of storm series for Germany are quantified based on potential losses using empirical models. Two reanalysis data sets and observations from German weather stations are considered for 30 winters. Histograms of events exceeding selected return levels (1-, 2- and 5-year) are derived. Return periods of historical storm series are estimated based on the Poisson and the negative binomial distributions. Over 4000 years of general circulation model (GCM) simulations forced with current climate conditions are analysed to provide a better assessment of historical return periods. Estimations differ between distributions, for example 40 to 65 years for the 1990 series. For such less frequent series, estimates obtained with the Poisson distribution clearly deviate from empirical data. The negative binomial distribution provides better estimates, even though a sensitivity to return level and data set is identified. The consideration of GCM data permits a strong reduction of uncertainties. The present results support the importance of considering explicitly clustering of losses for an adequate risk assessment for economical applications.

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This paper discusses ECG signal classification after parametrizing the ECG waveforms in the wavelet domain. Signal decomposition using perfect reconstruction quadrature mirror filter banks can provide a very parsimonious representation of ECG signals. In the current work, the filter parameters are adjusted by a numerical optimization algorithm in order to minimize a cost function associated to the filter cut-off sharpness. The goal consists of achieving a better compromise between frequency selectivity and time resolution at each decomposition level than standard orthogonal filter banks such as those of the Daubechies and Coiflet families. Our aim is to optimally decompose the signals in the wavelet domain so that they can be subsequently used as inputs for training to a neural network classifier.

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A variety of operational systems are vulnerable to disruption by solar disturbances brought to the Earth by the solar wind. Of particular importance to navigation systems are energetic charged particles which can generate temporary malfunctions and permanent damage in satellites. Modern spacecraft technology may prove to be particularly at risk during the next maximum of the solar cycle. In addition, the associated ionospheric disturbances cause phase shifts of transionospheric and ionosphere-reflected signals, giving positioning errors and loss of signal for GPS and Loran-C positioning systems and for over-the-horizon radars. We now have sufficient understanding of the solar wind, and how it interacts with the Earth's magnetic field, to predict statistically the likely effects on operational systems over the next solar cycle. We also have a number of advanced ways of detecting and tracking these disturbances through space but we cannot, as yet, provide accurate forecasts of individual disturbances that could be used to protect satellites and to correct errors. In addition, we have recently discovered long-term changes in the Sun, which mean that the number and severity of the disturbances to operational systems are increasing.

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Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed.

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The susceptibility of a catchment to flooding is affected by its soil moisture prior to an extreme rainfall event. While soil moisture is routinely observed by satellite instruments, results from previous work on the assimilation of remotely sensed soil moisture into hydrologic models have been mixed. This may have been due in part to the low spatial resolution of the observations used. In this study, the remote sensing aspects of a project attempting to improve flow predictions from a distributed hydrologic model by assimilating soil moisture measurements are described. Advanced Synthetic Aperture Radar (ASAR) Wide Swath data were used to measure soil moisture as, unlike low resolution microwave data, they have sufficient resolution to allow soil moisture variations due to local topography to be detected, which may help to take into account the spatial heterogeneity of hydrological processes. Surface soil moisture content (SSMC) was measured over the catchments of the Severn and Avon rivers in the South West UK. To reduce the influence of vegetation, measurements were made only over homogeneous pixels of improved grassland determined from a land cover map. Radar backscatter was corrected for terrain variations and normalized to a common incidence angle. SSMC was calculated using change detection. To search for evidence of a topographic signal, the mean SSMC from improved grassland pixels on low slopes near rivers was compared to that on higher slopes. When the mean SSMC on low slopes was 30–90%, the higher slopes were slightly drier than the low slopes. The effect was reversed for lower SSMC values. It was also more pronounced during a drying event. These findings contribute to the scant information in the literature on the use of high resolution SAR soil moisture measurement to improve hydrologic models.

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The detection of physiological signals from the motor system (electromyographic signals) is being utilized in the practice clinic to guide the therapist in a more precise and accurate diagnosis of motor disorders. In this context, the process of decomposition of EMG (electromyographic) signals that includes the identification and classification of MUAP (Motor Unit Action Potential) of a EMG signal, is very important to help the therapist in the evaluation of motor disorders. The EMG decomposition is a complex task due to EMG features depend on the electrode type (needle or surface), its placement related to the muscle, the contraction level and the health of the Neuromuscular System. To date, the majority of researches on EMG decomposition utilize EMG signals acquired by needle electrodes, due to their advantages in processing this type of signal. However, relatively few researches have been conducted using surface EMG signals. Thus, this article aims to contribute to the clinical practice by presenting a technique that permit the decomposition of surface EMG signal via the use of Hidden Markov Models. This process is supported by the use of differential evolution and spectral clustering techniques. The developed system presented coherent results in: (1) identification of the number of Motor Units actives in the EMG signal; (2) presentation of the morphological patterns of MUAPs in the EMG signal; (3) identification of the firing sequence of the Motor Units. The model proposed in this work is an advance in the research area of decomposition of surface EMG signals.

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Studiesthat use prolonged periods of sensory stimulation report associations between regional reductions in neural activity and negative blood oxygenation level-dependent (BOLD) signaling. However, the neural generators of the negative BOLD response remain to be characterized. Here, we use single-impulse electrical stimulation of the whisker pad in the anesthetized rat to identify components of the neural response that are related to “negative” hemodynamic changes in the brain. Laminar multiunit activity and local field potential recordings of neural activity were performed concurrently withtwo-dimensional optical imaging spectroscopy measuring hemodynamic changes. Repeated measurements over multiple stimulation trials revealed significant variations in neural responses across session and animal datasets. Within this variation, we found robust long-latency decreases (300 and 2000 ms after stimulus presentation) in gammaband power (30 – 80 Hz) in the middle-superficial cortical layers in regions surrounding the activated whisker barrel cortex. This reduction in gamma frequency activity was associated with corresponding decreases in the hemodynamic responses that drive the negative BOLD signal. These findings suggest a close relationship between BOLD responses and neural events that operate over time scales that outlast the initiating sensory stimulus, and provide important insights into the neurophysiological basis of negative neuroimaging signals.

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The United Nations Framework Convention on Climate Change (UNFCCC) has established the Warsaw International Mechanism (WIM) to deal with loss and damage associated with climate change impacts, including extreme events, in developing countries. It is not yet known whether events will need to be attributed to anthropogenic climate change to be considered under the WIM. Attribution is possible for some extreme events- a climate model assessment can estimate how greenhouse gas emissions have affected the likelihood of their occurrence. Dialogue between scientists and stakeholders is required to establish whether, and how, this science could play a role in the WIM.

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Presents an interview with Elizabeth Nunez, author and professor. Nunez discusses the issues on migration, family, and intimacy which are the topics of her novel "Anna In-Between." She explains the demands of the publishing industry that cast a shadow in the world of the novel and the real world of Caribbean writers. This interview was translated by Maria Lusia Ruiz.

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Background: Podosphaera aphanis, the causal agent of strawberry powdery mildew causes significant economic loss worldwide. Methods: We used the diploid strawberry species Fragaria vesca as a model to study plant pathogen interactions. RNA-seq was employed to generate a transcriptome dataset from two accessions, F. vesca ssp. vesca Hawaii 4 (HW) and F. vesca f. semperflorens Yellow Wonder 5AF7 (YW) at 1 d (1 DAI) and 8 d (8 DAI) after infection. Results: Of the total reads identified about 999 million (92%) mapped to the F. vesca genome. These transcripts were derived from a total of 23,470 and 23,464 genes in HW and YW, respectively from the three time points (control, 1 and 8 DAI). Analysis identified 1,567, 1,846 and 1,145 up-regulated genes between control and 1 DAI, control and 8 DAI, and 1 and 8 DAI, respectively in HW. Similarly, 1,336, 1,619 and 968 genes were up-regulated in YW. Also 646, 1,098 and 624 down-regulated genes were identified in HW, while 571, 754 and 627 genes were down-regulated in YW between all three time points, respectively. Conclusion: Investigation of differentially expressed genes (log2 fold changes �5) between control and 1 DAI in both HW and YW identified a large number of genes related to secondary metabolism, signal transduction; transcriptional regulation and disease resistance were highly expressed. These included flavonoid 3´-monooxygenase, peroxidase 15, glucan endo-1,3-β-glucosidase 2, receptor-like kinases, transcription factors, germin-like proteins, F-box proteins, NB-ARC and NBS-LRR proteins. This is the first application of RNA-seq to any pathogen interaction in strawberry

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Considerable progress has been made in understanding the present and future regional and global sea level in the 2 years since the publication of the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change. Here, we evaluate how the new results affect the AR5’s assessment of (i) historical sea level rise, including attribution of that rise and implications for the sea level budget, (ii) projections of the components and of total global mean sea level (GMSL), and (iii) projections of regional variability and emergence of the anthropogenic signal. In each of these cases, new work largely provides additional evidence in support of the AR5 assessment, providing greater confidence in those findings. Recent analyses confirm the twentieth century sea level rise, with some analyses showing a slightly smaller rate before 1990 and some a slightly larger value than reported in the AR5. There is now more evidence of an acceleration in the rate of rise. Ongoing ocean heat uptake and associated thermal expansion have continued since 2000, and are consistent with ocean thermal expansion reported in the AR5. A significant amount of heat is being stored deeper in the water column, with a larger rate of heat uptake since 2000 compared to the previous decades and with the largest storage in the Southern Ocean. The first formal detection studies for ocean thermal expansion and glacier mass loss since the AR5 have confirmed the AR5 finding of a significant anthropogenic contribution to sea level rise over the last 50 years. New projections of glacier loss from two regions suggest smaller contributions to GMSL rise from these regions than in studies assessed by the AR5; additional regional studies are required to further assess whether there are broader implications of these results. Mass loss from the Greenland Ice Sheet, primarily as a result of increased surface melting, and from the Antarctic Ice Sheet, primarily as a result of increased ice discharge, has accelerated. The largest estimates of acceleration in mass loss from the two ice sheets for 2003–2013 equal or exceed the acceleration of GMSL rise calculated from the satellite altimeter sea level record over the longer period of 1993–2014. However, when increased mass gain in land water storage and parts of East Antarctica, and decreased mass loss from glaciers in Alaska and some other regions are taken into account, the net acceleration in the ocean mass gain is consistent with the satellite altimeter record. New studies suggest that a marine ice sheet instability (MISI) may have been initiated in parts of the West Antarctic Ice Sheet (WAIS), but that it will affect only a limited number of ice streams in the twenty-first century. New projections of mass loss from the Greenland and Antarctic Ice Sheets by 2100, including a contribution from parts of WAIS undergoing unstable retreat, suggest a contribution that falls largely within the likely range (i.e., two thirds probability) of the AR5. These new results increase confidence in the AR5 likely range, indicating that there is a greater probability that sea level rise by 2100 will lie in this range with a corresponding decrease in the likelihood of an additional contribution of several tens of centimeters above the likely range. In view of the comparatively limited state of knowledge and understanding of rapid ice sheet dynamics, we continue to think that it is not yet possible to make reliable quantitative estimates of future GMSL rise outside the likely range. Projections of twenty-first century GMSL rise published since the AR5 depend on results from expert elicitation, but we have low confidence in conclusions based on these approaches. New work on regional projections and emergence of the anthropogenic signal suggests that the two commonly predicted features of future regional sea level change (the increasing tilt across the Antarctic Circumpolar Current and the dipole in the North Atlantic) are related to regional changes in wind stress and surface heat flux. Moreover, it is expected that sea level change in response to anthropogenic forcing, particularly in regions of relatively low unforced variability such as the low-latitude Atlantic, will be detectable over most of the ocean by 2040. The east-west contrast of sea level trends in the Pacific observed since the early 1990s cannot be satisfactorily accounted for by climate models, nor yet definitively attributed either to unforced variability or forced climate change.