153 resultados para Complexity measurement


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Traditionally functional magnetic resonance imaging (fMRI) has been used to map activity in the human brain by measuring increases in the Blood Oxygenation Level Dependent (BOLD) signal. Often accompanying positive BOLD fMRI signal changes are sustained negative signal changes. Previous studies investigating the neurovascular coupling mechanisms of the negative BOLD phenomenon have used concurrent 2D-optical imaging spectroscopy (2D-OIS) and electrophysiology (Boorman et al., 2010). These experiments suggested that the negative BOLD signal in response to whisker stimulation was a result of an increase in deoxy-haemoglobin and reduced multi-unit activity in the deep cortical layers. However, Boorman et al. (2010) did not measure the BOLD and haemodynamic response concurrently and so could not quantitatively compare either the spatial maps or the 2D-OIS and fMRI time series directly. Furthermore their study utilised a homogeneous tissue model in which is predominantly sensitive to haemodynamic changes in more superficial layers. Here we test whether the 2D-OIS technique is appropriate for studies of negative BOLD. We used concurrent fMRI with 2D-OIS techniques for the investigation of the haemodynamics underlying the negative BOLD at 7 Tesla. We investigated whether optical methods could be used to accurately map and measure the negative BOLD phenomenon by using 2D-OIS haemodynamic data to derive predictions from a biophysical model of BOLD signal changes. We showed that despite the deep cortical origin of the negative BOLD response, if an appropriate heterogeneous tissue model is used in the spectroscopic analysis then 2D-OIS can be used to investigate the negative BOLD phenomenon.

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Prism is a modular classification rule generation method based on the ‘separate and conquer’ approach that is alternative to the rule induction approach using decision trees also known as ‘divide and conquer’. Prism often achieves a similar level of classification accuracy compared with decision trees, but tends to produce a more compact noise tolerant set of classification rules. As with other classification rule generation methods, a principle problem arising with Prism is that of overfitting due to over-specialised rules. In addition, over-specialised rules increase the associated computational complexity. These problems can be solved by pruning methods. For the Prism method, two pruning algorithms have been introduced recently for reducing overfitting of classification rules - J-pruning and Jmax-pruning. Both algorithms are based on the J-measure, an information theoretic means for quantifying the theoretical information content of a rule. Jmax-pruning attempts to exploit the J-measure to its full potential because J-pruning does not actually achieve this and may even lead to underfitting. A series of experiments have proved that Jmax-pruning may outperform J-pruning in reducing overfitting. However, Jmax-pruning is computationally relatively expensive and may also lead to underfitting. This paper reviews the Prism method and the two existing pruning algorithms above. It also proposes a novel pruning algorithm called Jmid-pruning. The latter is based on the J-measure and it reduces overfitting to a similar level as the other two algorithms but is better in avoiding underfitting and unnecessary computational effort. The authors conduct an experimental study on the performance of the Jmid-pruning algorithm in terms of classification accuracy and computational efficiency. The algorithm is also evaluated comparatively with the J-pruning and Jmax-pruning algorithms.

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An extensive off-line evaluation of the Noah/Single Layer Urban Canopy Model (Noah/SLUCM) urban land-surface model is presented using data from 15 sites to assess (1) the ability of the scheme to reproduce the surface energy balance observed in a range of urban environments, including seasonal changes, and (2) the impact of increasing complexity of input parameter information. Model performance is found to be most dependent on representation of vegetated surface area cover; refinement of other parameter values leads to smaller improvements. Model biases in net all-wave radiation and trade-offs between turbulent heat fluxes are highlighted using an optimization algorithm. Here we use the Urban Zones to characterize Energy partitioning (UZE) as the basis to assign default SLUCM parameter values. A methodology (FRAISE) to assign sites (or areas) to one of these categories based on surface characteristics is evaluated. Using three urban sites from the Basel Urban Boundary Layer Experiment (BUBBLE) dataset, an independent evaluation of the model performance with the parameter values representative of each class is performed. The scheme copes well with both seasonal changes in the surface characteristics and intra-urban heterogeneities in energy flux partitioning, with RMSE performance comparable to similar state-of-the-art models for all fluxes, sites and seasons. The potential of the methodology for high-resolution atmospheric modelling application using the Weather Research and Forecasting (WRF) model is highlighted. This analysis supports the recommendations that (1) three classes are appropriate to characterize the urban environment, and (2) that the parameter values identified should be adopted as default values in WRF.

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Aerosols affect the Earth's energy budget directly by scattering and absorbing radiation and indirectly by acting as cloud condensation nuclei and, thereby, affecting cloud properties. However, large uncertainties exist in current estimates of aerosol forcing because of incomplete knowledge concerning the distribution and the physical and chemical properties of aerosols as well as aerosol-cloud interactions. In recent years, a great deal of effort has gone into improving measurements and datasets. It is thus feasible to shift the estimates of aerosol forcing from largely model-based to increasingly measurement-based. Our goal is to assess current observational capabilities and identify uncertainties in the aerosol direct forcing through comparisons of different methods with independent sources of uncertainties. Here we assess the aerosol optical depth (τ), direct radiative effect (DRE) by natural and anthropogenic aerosols, and direct climate forcing (DCF) by anthropogenic aerosols, focusing on satellite and ground-based measurements supplemented by global chemical transport model (CTM) simulations. The multi-spectral MODIS measures global distributions of aerosol optical depth (τ) on a daily scale, with a high accuracy of ±0.03±0.05τ over ocean. The annual average τ is about 0.14 over global ocean, of which about 21%±7% is contributed by human activities, as estimated by MODIS fine-mode fraction. The multi-angle MISR derives an annual average AOD of 0.23 over global land with an uncertainty of ~20% or ±0.05. These high-accuracy aerosol products and broadband flux measurements from CERES make it feasible to obtain observational constraints for the aerosol direct effect, especially over global the ocean. A number of measurement-based approaches estimate the clear-sky DRE (on solar radiation) at the top-of-atmosphere (TOA) to be about -5.5±0.2 Wm-2 (median ± standard error from various methods) over the global ocean. Accounting for thin cirrus contamination of the satellite derived aerosol field will reduce the TOA DRE to -5.0 Wm-2. Because of a lack of measurements of aerosol absorption and difficulty in characterizing land surface reflection, estimates of DRE over land and at the ocean surface are currently realized through a combination of satellite retrievals, surface measurements, and model simulations, and are less constrained. Over the oceans the surface DRE is estimated to be -8.8±0.7 Wm-2. Over land, an integration of satellite retrievals and model simulations derives a DRE of -4.9±0.7 Wm-2 and -11.8±1.9 Wm-2 at the TOA and surface, respectively. CTM simulations derive a wide range of DRE estimates that on average are smaller than the measurement-based DRE by about 30-40%, even after accounting for thin cirrus and cloud contamination. A number of issues remain. Current estimates of the aerosol direct effect over land are poorly constrained. Uncertainties of DRE estimates are also larger on regional scales than on a global scale and large discrepancies exist between different approaches. The characterization of aerosol absorption and vertical distribution remains challenging. The aerosol direct effect in the thermal infrared range and in cloudy conditions remains relatively unexplored and quite uncertain, because of a lack of global systematic aerosol vertical profile measurements. A coordinated research strategy needs to be developed for integration and assimilation of satellite measurements into models to constrain model simulations. Enhanced measurement capabilities in the next few years and high-level scientific cooperation will further advance our knowledge.

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The authors identified several specific problems with the measurement of achievement goals in the current literature and illustrated these problems, focusing primarily on A. J. Elliot and H. A. McGregor's (2001) Achievement Goal Questionnaire (AGQ). They attended to these problems by creating the AGQ-Revised and conducting a study that examined the measure's structural validity and predictive utility with 229 (76 male, 150 female, 3 unspecified) undergraduates. The hypothesized factor and dimensional structures of the measure were confirmed and shown to be superior to a host of alternatives. The predictions were nearly uniformly supported with regard to both the antecedents (need for achievement and fear of failure) and consequences (intrinsic motivation and exam performance) of the 4 achievement goals. In discussing their work, the authors highlight the importance and value of additional precision in the area of achievement goal measurement. (PsycINFO Database Record (c) 2012 APA, all rights reserved)(journal abstract)

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Using a simple and accessible Teflon AF-2400 based tube-intube reactor, a series of pyrroles were synthesised in flow using the Paal–Knorr reaction of 1,4-diketones with gaseous ammonia. An inline flow titration technique allowed measurement of the ammonia concentration and its relationship to residence time and temperature.

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Beginning with an extensive literature review, this new research summary report analyses the process of rental depreciation, its effect on the performance of rents, and the impacts of capital expenditure on depreciation. It is based on an analysis of more than 700 commercial and industrial properties and newer property types and it is the most comprehensive national study of rental depreciation since the 1986 CALUS report. The report will be of interest to valuers, fund managers, institutional investors and their advisors and researchers.

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The centre of cities, characterised by spatial and temporal complexity, are challenging environments for micrometeorological research. This paper considers the impact of sensor location and heterogeneity of the urban surface on flux observations in the dense city centre of London, UK. Data gathered at two sites in close vicinity, but with different measurement heights, were analysed to investigate the influence of source area characteristics on long-term radiation and turbulent heat fluxes. Combining consideration of diffuse radiation and effects of specular reflections, the non-Lambertian urban surface is found to impact the measurements of surface albedo. Comparisons of observations from the two sites reveal that turbulent heat fluxes are similar under some flow conditions. However, they mostly observe processes at different scales due to their differing measurement heights, highlighting the critical impact of siting sensors in urban areas. A detailed source area analysis is presented to investigate the surface controls influencing the energy exchanges at the different scales

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In this article we review the evolution of economic theory on decision making under uncertainty. After a brief reference to Expected Utility Theory, we refer to behavioural paradoxes, forcing the theorists to adopt less restrictive approaches, allowing us to explain a broader spectrum of phenomena. The complexity entailed in the new theories requires a multidimensional description of human attitudes towards risk. Nevertheless, measurement of this attitudes has not followed the desired path, with most elicitation methods remaining uni-dimensional.

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A flood warning system incorporates telemetered rainfall and flow/water level data measured at various locations in the catchment area. Real-time accurate data collection is required for this use, and sensor networks improve the system capabilities. However, existing sensor nodes struggle to satisfy the hydrological requirements in terms of autonomy, sensor hardware compatibility, reliability and long-range communication. We describe the design and development of a real-time measurement system for flood monitoring, and its deployment in a flash-flood prone 650 km2 semiarid watershed in Southern Spain. A developed low-power and long-range communication device, so-called DatalogV1, provides automatic data gathering and reliable transmission. DatalogV1 incorporates self-monitoring for adapting measurement schedules for consumption management and to capture events of interest. Two tests are used to assess the success of the development. The results show an autonomous and robust monitoring system for long-term collection of water level data in many sparse locations during flood events.

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Chongqing is the largest central-government-controlled municipality in China, which is now under going a rapid urbanization. The question remains open: What are the consequences of such rapid urbanization in Chongqing in terms of urban microclimates? An integrated study comprising three different research approaches is adopted in the present paper. By analyzing the observed annual climate data, an average rising trend of 0.10◦C/decade was found for the annual mean temperature from 1951 to 2010 in Chongqing,indicating a higher degree of urban warming in Chongqing. In addition, two complementary types of field measurements were conducted: fixed weather stations and mobile transverse measurement. Numerical simulations using a house-developed program are able to predict the urban air temperature in Chongqing.The urban heat island intensity in Chongqing is stronger in summer compared to autumn and winter.The maximum urban heat island intensity occurs at around midnight, and can be as high as 2.5◦C. In the day time, an urban cool island exists. Local greenery has a great impact on the local thermal environment.Urban green spaces can reduce urban air temperature and therefore mitigate the urban heat island. The cooling effect of an urban river is limited in Chongqing, as both sides of the river are the most developed areas, but the relative humidity is much higher near the river compared with the places far from it.

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The synthesis and characterization of five new indium selenides, [C9H17N2]3[In5Se8+x(Se2)1−x] (1–2), [C6H12N2]4[C6H14N2]3[In10Se15(Se2)3] (3), [C6H14N2][(C6H12N2)2NaIn5Se9] (4) and [enH2][NH4][In7Se12] (5), are described. These materials were prepared under solvothermal conditions, using 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU) and 1,4-diazabicyclo[2.2.2]octane (DABCO) as structure-directing agents. Compounds 1–4 represent the first examples of ribbons in indium selenides, and 4 is the first example of incorporation of an alkali metal complex. Compounds 1, 2 and 4 contain closely related [In5Se8+x(Se2)1−x]3− ribbons which differ only in their content of (Se2)2− anions. These ribbons are interspaced by organic countercations in 1 and 2, while in 4 they are linked by highly unusual [Na(DABCO)2]+ units into a three-dimensional framework. Compound 3 contains complex ribbons, with a long repeating sequence of ca. 36 Å, and 4 is a non-centrosymmetric three-dimensional framework, formed as a consequence of the decomposition of DABCO into ethylenediamine (en) and ammonia.

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Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.