186 resultados para general regression model


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Aim: To describe the geographical pattern of mean body size of the non-volant mammals of the Nearctic and Neotropics and evaluate the influence of five environmental variables that are likely to affect body size gradients. Location: The Western Hemisphere. Methods: We calculated mean body size (average log mass) values in 110 × 110 km cells covering the continental Nearctic and Neotropics. We also generated cell averages for mean annual temperature, range in elevation, their interaction, actual evapotranspiration, and the global vegetation index and its coefficient of variation. Associations between mean body size and environmental variables were tested with simple correlations and ordinary least squares multiple regression, complemented with spatial autocorrelation analyses and split-line regression. We evaluated the relative support for each multiple-regression model using AIC. Results: Mean body size increases to the north in the Nearctic and is negatively correlated with temperature. In contrast, across the Neotropics mammals are largest in the tropical and subtropical lowlands and smaller in the Andes, generating a positive correlation with temperature. Finally, body size and temperature are nonlinearly related in both regions, and split-line linear regression found temperature thresholds marking clear shifts in these relationships (Nearctic 10.9 °C; Neotropics 12.6 °C). The increase in body sizes with decreasing temperature is strongest in the northern Nearctic, whereas a decrease in body size in mountains dominates the body size gradients in the warmer parts of both regions. Main conclusions: We confirm previous work finding strong broad-scale Bergmann trends in cold macroclimates but not in warmer areas. For the latter regions (i.e. the southern Nearctic and the Neotropics), our analyses also suggest that both local and broad-scale patterns of mammal body size variation are influenced in part by the strong mesoscale climatic gradients existing in mountainous areas. A likely explanation is that reduced habitat sizes in mountains limit the presence of larger-sized mammals.

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Background: Robot-mediated therapies offer entirely new approaches to neurorehabilitation. In this paper we present the results obtained from trialling the GENTLE/S neurorehabilitation system assessed using the upper limb section of the Fugl-Meyer ( FM) outcome measure. Methods: We demonstrate the design of our clinical trial and its results analysed using a novel statistical approach based on a multivariate analytical model. This paper provides the rational for using multivariate models in robot-mediated clinical trials and draws conclusions from the clinical data gathered during the GENTLE/S study. Results: The FM outcome measures recorded during the baseline ( 8 sessions), robot-mediated therapy ( 9 sessions) and sling-suspension ( 9 sessions) was analysed using a multiple regression model. The results indicate positive but modest recovery trends favouring both interventions used in GENTLE/S clinical trial. The modest recovery shown occurred at a time late after stroke when changes are not clinically anticipated. Conclusion: This study has applied a new method for analysing clinical data obtained from rehabilitation robotics studies. While the data obtained during the clinical trial is of multivariate nature, having multipoint and progressive nature, the multiple regression model used showed great potential for drawing conclusions from this study. An important conclusion to draw from this paper is that this study has shown that the intervention and control phase both caused changes over a period of 9 sessions in comparison to the baseline. This might indicate that use of new challenging and motivational therapies can influence the outcome of therapies at a point when clinical changes are not expected. Further work is required to investigate the effects arising from early intervention, longer exposure and intensity of the therapies. Finally, more function-oriented robot-mediated therapies or sling-suspension therapies are needed to clarify the effects resulting from each intervention for stroke recovery.

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Nonlinear system identification is considered using a generalized kernel regression model. Unlike the standard kernel model, which employs a fixed common variance for all the kernel regressors, each kernel regressor in the generalized kernel model has an individually tuned diagonal covariance matrix that is determined by maximizing the correlation between the training data and the regressor using a repeated guided random search based on boosting optimization. An efficient construction algorithm based on orthogonal forward regression with leave-one-out (LOO) test statistic and local regularization (LR) is then used to select a parsimonious generalized kernel regression model from the resulting full regression matrix. The proposed modeling algorithm is fully automatic and the user is not required to specify any criterion to terminate the construction procedure. Experimental results involving two real data sets demonstrate the effectiveness of the proposed nonlinear system identification approach.

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A poor representation of cloud structure in a general circulation model (GCM) is widely recognised as a potential source of error in the radiation budget. Here, we develop a new way of representing both horizontal and vertical cloud structure in a radiation scheme. This combines the ‘Tripleclouds’ parametrization, which introduces inhomogeneity by using two cloudy regions in each layer as opposed to one, each with different water content values, with ‘exponential-random’ overlap, in which clouds in adjacent layers are not overlapped maximally, but according to a vertical decorrelation scale. This paper, Part I of two, aims to parametrize the two effects such that they can be used in a GCM. To achieve this, we first review a number of studies for a globally applicable value of fractional standard deviation of water content for use in Tripleclouds. We obtain a value of 0.75 ± 0.18 from a variety of different types of observations, with no apparent dependence on cloud type or gridbox size. Then, through a second short review, we create a parametrization of decorrelation scale for use in exponential-random overlap, which varies the scale linearly with latitude from 2.9 km at the Equator to 0.4 km at the poles. When applied to radar data, both components are found to have radiative impacts capable of offsetting biases caused by cloud misrepresentation. Part II of this paper implements Tripleclouds and exponential-random overlap into a radiation code and examines both their individual and combined impacts on the global radiation budget using re-analysis data.

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Reliably representing both horizontal cloud inhomogeneity and vertical cloud overlap is fundamentally important for the radiation budget of a general circulation model. Here, we build on the work of Part One of this two-part paper by applying a pair of parameterisations that account for horizontal inhomogeneity and vertical overlap to global re-analysis data. These are applied both together and separately in an attempt to quantify the effects of poor representation of the two components on radiation budget. Horizontal inhomogeneity is accounted for using the “Tripleclouds” scheme, which uses two regions of cloud in each layer of a gridbox as opposed to one; vertical overlap is accounted for using “exponential-random” overlap, which aligns vertically continuous cloud according to a decorrelation height. These are applied to a sample of scenes from a year of ERA-40 data. The largest radiative effect of horizontal inhomogeneity is found to be in areas of marine stratocumulus; the effect of vertical overlap is found to be fairly uniform, but with larger individual short-wave and long-wave effects in areas of deep, tropical convection. The combined effect of the two parameterisations is found to reduce the magnitude of the net top-of-atmosphere cloud radiative forcing (CRF) by 2.25 W m−2, with shifts of up to 10 W m−2 in areas of marine stratocumulus. The effects of the uncertainty in our parameterisations on radiation budget is also investigated. It is found that the uncertainty in the impact of horizontal inhomogeneity is of order ±60%, while the uncertainty in the impact of vertical overlap is much smaller. This suggests an insensitivity of the radiation budget to the exact nature of the global decorrelation height distribution derived in Part One.

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The winter climate of Europe and the Mediterranean is dominated by the weather systems of the mid-latitude storm tracks. The behaviour of the storm tracks is highly variable, particularly in the eastern North Atlantic, and has a profound impact on the hydroclimate of the Mediterranean region. A deeper understanding of the storm tracks and the factors that drive them is therefore crucial for interpreting past changes in Mediterranean climate and the civilizations it has supported over the last 12 000 years (broadly the Holocene period). This paper presents a discussion of how changes in climate forcing (e.g. orbital variations, greenhouse gases, ice sheet cover) may have impacted on the ‘basic ingredients’ controlling the mid-latitude storm tracks over the North Atlantic and the Mediterranean on intermillennial time scales. Idealized simulations using the HadAM3 atmospheric general circulation model (GCM) are used to explore the basic processes, while a series of timeslice simulations from a similar atmospheric GCM coupled to a thermodynamic slab ocean (HadSM3) are examined to identify the impact these drivers have on the storm track during the Holocene. The results suggest that the North Atlantic storm track has moved northward and strengthened with time since the Early to Mid-Holocene. In contrast, the Mediterranean storm track may have weakened over the same period. It is, however, emphasized that much remains still to be understood about the evolution of the North Atlantic and Mediterranean storm tracks during the Holocene period.

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This paper describes the impact of changing the current imposed ozone climatology upon the tropical Quasi-Biennial Oscillation (QBO) in a high top climate configuration of the Met Office U.K. general circulation model. The aim is to help distinguish between QBO changes in chemistry climate models that result from temperature-ozone feedbacks and those that might be forced by differences in climatology between previously fixed and newly interactive ozone distributions. Different representations of zonal mean ozone climatology under present-day conditions are taken to represent the level of change expected between acceptable model realizations of the global ozone distribution and thus indicate whether more detailed investigation of such climatology issues might be required when assessing ozone feedbacks. Tropical stratospheric ozone concentrations are enhanced relative to the control climatology between 20–30 km, reduced from 30–40 km and enhanced above, impacting the model profile of clear-sky radiative heating, in particular warming the tropical stratosphere between 15–35 km. The outcome is consistent with a localized equilibrium response in the tropical stratosphere that generates increased upwelling between 100 and 4 hPa, sufficient to account for a 12 month increase of modeled mean QBO period. This response has implications for analysis of the tropical circulation in models with interactive ozone chemistry because it highlights the possibility that plausible changes in the ozone climatology could have a sizable impact upon the tropical upwelling and QBO period that ought to be distinguished from other dynamical responses such as ozone-temperature feedbacks.

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Little has so far been reported on the performance of the near-far resistant CDMA detectors in the presence of the synchronization errors. Starting with the general mathematical model of matched filters, this paper examines the effects of three classes of synchronization errors (i.e. time-delay errors, carrier phase errors, and carrier frequency errors) on the performance (bit error rate and near-far resistance) of an emerging type of near-far resistant coherent DS/SSMA detectors, i.e. the linear decorrelating detector (LDD). For comparison, the corresponding results for the conventional detector are also presented. It is shown that the LDD can still maintain a considerable performance advantage over the conventional detector even when some synchronization errors exist. Finally, several computer simulations are carried out to verify the theoretical conclusions.

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Little has been reported on the performance of near-far resistant CDMA detectors in the presence of system parameter estimation errors (SPEEs). Starting with the general mathematical model of matched filters, the paper examines the effects of three classes of SPEEs, i.e., time-delay, carrier phase, and carrier frequency errors, on the performance (BER) of an emerging type of near-far resistant coherent DS/SSMA detector, i.e., the linear decorrelating detector. For comparison, the corresponding results for the conventional detector are also presented. It is shown that the linear decorrelating detector can still maintain a considerable performance advantage over the conventional detector even when some SPEEs exist.

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A strong climatic warming is currently observed in the Caucasus mountains, which has profound impact on runoff generation in the glaciated Glavny (Main) Range and on water availability in the whole region. To assess future changes in the hydrological cycle, the output of a general circulation model was downscaled statistically. For the 21st century, a further warming by 4–7 °C and a slight precipitation increase is predicted. Measured and simulated meteorological variables were used as input into a runoff model to transfer climate signals into a hydrological response under both present and future climate forcings. Runoff scenarios for the mid and the end of the 21st century were generated for different steps of deglaciation. The results show a satisfactory model performance for periods with observed runoff. Future water availability strongly depends on the velocity of glacier retreat. In a first phase, a surplus of water will increase flood risk in hot years and after continuing glacier reduction, annual runoff will again approximate current values. However, the seasonal distribution of streamflow will change towards runoff increase in spring and lower flows in summer.

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The processes that govern the predictability of decadal variations in the North Atlantic meridional overturning circulation (MOC) are investigated in a long control simulation of the ECHO-G coupled atmosphere–ocean model. We elucidate the roles of local stochastic forcing by the atmosphere, and other potential ocean processes, and use our results to build a predictive regression model. The primary influence on MOC variability is found to come from air–sea heat fluxes over the Eastern Labrador Sea. The maximum correlation between such anomalies and the variations in the MOC occurs at a lead time of 2 years, but we demonstrate that the MOC integrates the heat flux variations over a period of 10 years. The corresponding univariate regression model accounts for 74.5% of the interannual variability in the MOC (after the Ekman component has been removed). Dense anomalies to the south of the Greenland-Scotland ridge are also shown to precede the overturning variations by 4–6 years, and provide a second predictor. With the inclusion of this second predictor the resulting regression model explains 82.8% of the total variance of the MOC. This final bivariate model is also tested during large rapid decadal overturning events. The sign of the rapid change is always well represented by the bivariate model, but the magnitude is usually underestimated, suggesting that other processes are also important for these large rapid decadal changes in the MOC.

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Enhanced release of CO2 to the atmosphere from soil organic carbon as a result of increased temperatures may lead to a positive feedback between climate change and the carbon cycle, resulting in much higher CO2 levels and accelerated lobal warming. However, the magnitude of this effect is uncertain and critically dependent on how the decomposition of soil organic C (heterotrophic respiration) responds to changes in climate. Previous studies with the Hadley Centre’s coupled climate–carbon cycle general circulation model (GCM) (HadCM3LC) used a simple, single-pool soil carbon model to simulate the response. Here we present results from numerical simulations that use the more sophisticated ‘RothC’ multipool soil carbon model, driven with the same climate data. The results show strong similarities in the behaviour of the two models, although RothC tends to simulate slightly smaller changes in global soil carbon stocks for the same forcing. RothC simulates global soil carbon stocks decreasing by 54 GtC by 2100 in a climate change simulation compared with an 80 GtC decrease in HadCM3LC. The multipool carbon dynamics of RothC cause it to exhibit a slower magnitude of transient response to both increased organic carbon inputs and changes in climate. We conclude that the projection of a positive feedback between climate and carbon cycle is robust, but the magnitude of the feedback is dependent on the structure of the soil carbon model.

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A time-dependent climate-change experiment with a coupled ocean–atmosphere general circulation model has been used to study changes in the occurrence of drought in summer in southern Europe and central North America. In both regions, precipitation and soil moisture are reduced in a climate of greater atmospheric carbon dioxide. A detailed investigation of the hydrology of the model shows that the drying of the soil comes about through an increase in evaporation in winter and spring, caused by higher temperatures and reduced snow cover, and a decrease in the net input of water in summer. Evaporation is reduced in summer because of the drier soil, but the reduction in precipitation is larger. Three extreme statistics are used to define drought, namely the frequency of low summer precipitation, the occurrence of long dry spells, and the probability of dry soil. The last of these is arguably of the greatest practical importance, but since it is based on soil moisture, of which there are very few observations, the authors’ simulation of it has the least confidence. Furthermore, long time series for daily observed precipitation are not readily available from a sufficient number of stations to enable a thorough evaluation of the model simulation, especially for the frequency of long dry spells, and this increases the systematic uncertainty of the model predictions. All three drought statistics show marked increases owing to the sensitivity of extreme statistics to changes in their distributions. However, the greater likelihood of long dry spells is caused by a tendency in the character of daily rainfall toward fewer events, rather than by the reduction in mean precipitation. The results should not be taken as firm predictions because extreme statistics for small regions cannot be calculated reliably from the output of the current generation of GCMs, but they point to the possibility of large increases in the severity of drought conditions as a consequence of climate change caused by increased CO2.

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In response to increasing atmospheric con- centrations of greenhouse gases, the rate of time- dependent climate change is determined jointly by the strength of climate feedbacks and the e�ciency of pro- cesses which remove heat from the surface into the deep ocean. This work examines the vertical heat transport processes in the ocean of the HADCM2 atmosphere± ocean general circulation model (AOGCM) in experi- ments with CO2 held constant (control) and increasing at 1% per year (anomaly). The control experiment shows that global average heat exchanges between the upper and lower ocean are dominated by the Southern Ocean, where heat is pumped downwards by the wind- driven circulation and di�uses upwards along sloping isopycnals. This is the reverse of the low-latitude balance used in upwelling±di�usion ocean models, the global average upward di�usive transport being against the temperature gradient. In the anomaly experiment, weakened convection at high latitudes leads to reduced diffusive and convective heat loss from the deep ocean, and hence to net heat uptake, since the advective heat input is less a�ected. Reduction of deep water produc- tion at high latitudes results in reduced upwelling of cold water at low latitudes, giving a further contribution to net heat uptake. On the global average, high-latitude processes thus have a controlling in¯uence. The impor- tant role of di�usion highlights the need to ensure that the schemes employed in AOGCMs give an accurate representation of the relevant sub-grid-scale processes.

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We extend the current immigration-enforcement literature by incorporating both the practice of people smuggling and a role for non-wage income into a two-country, dynamic general equilibrium model. We use the model economy to examine three questions. First, how does technological progress in the smuggling industry affect the level of migration and capital accumulation for a given level of enforcement? Second, do changes in border enforcement affect the level of migration, capital accumulation, and smuggling activity? Third, is the optimal level of enforcement sensitive to technological progress in the smuggling industry? We show that the government chooses to devote resources to border enforcement only if the deterrent effect on smugglers is large enough. Otherwise, it is not worth taxing host-country natives as the taxes paid will more than offset any income gain resulting from fewer migrants.