902 resultados para distribution system operator


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The application of nonlocal density functional theory (NLDFT) to determine pore size distribution (PSD) of activated carbons using a nongraphitized carbon black, instead of graphitized thermal carbon black, as a reference system is explored. We show that in this case nitrogen and argon adsorption isotherms in activated carbons are precisely correlated by the theory, and such an excellent correlation would never be possible if the pore wall surface was assumed to be identical to that of graphitized carbon black. It suggests that pore wall surfaces of activated carbon are closer to that of amorphous solids because of defects of crystalline lattice, finite pore length, and the presence of active centers.. etc. Application of the NLDFT adapted to amorphous solids resulted in quantitative description of N-2 and Ar adsorption isotherms on nongraphitized carbon black BP280 at their respective boiling points. In the present paper we determined solid-fluid potentials from experimental adsorption isotherms on nongraphitized carbon black and subsequently used those potentials to model adsorption in slit pores and generate a corresponding set of local isotherms, which we used to determine the PSD functions of different activated carbons. (c) 2005 Elsevier Ltd. All rights reserved.

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OBJECTIVE: To determine the distribution of the pathological changes in the neocortex in multiple-system atrophy (MSA). METHOD: The vertical distribution of the abnormal neurons (neurons with enlarged or atrophic perikarya), surviving neurons, glial cytoplasmic inclusions (GCI) and neuronal cytoplasmic inclusions (NI) were studied in alpha-synuclein-stained material of frontal and temporal cortex in ten cases of MSA. RESULTS: Abnormal neurons exhibited two common patterns of distribution, viz., density was either maximal in the upper cortex or a bimodal distribution was present with a density peak in the upper and lower cortex. The NI were either located in the lower cortex or were more uniformly distributed down the cortical profile. The distribution of the GCI varied considerably between gyri and cases. The density of the glial cell nuclei was maximal in the lower cortex in the majority of gyri. In a number of gyri, there was a positive correlation between the vertical densities of the abnormal neurons, the total number of surviving neurons, and the glial cell nuclei. The vertical densities of the GCI were not correlated with those of the surviving neurons or glial cells but the GCI and NI were positively correlated in a small number of gyri. CONCLUSION: The data suggest that there is significant degeneration of the frontal and temporal lobes in MSA, the lower laminae being affected more significantly than the upper laminae. Cortical degeneration in MSA is likely to be secondary to pathological changes occurring within subcortical areas.

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To study the topographic distribution of the pathology in multiple system atrophy (MSA). Pattern analysis was carried out using a-synuclein immunohistochemistry in 10 MSA cases. The glial cytoplasmic inclusions (GCI) were distributed randomly or in large clusters. The neuronal inclusions (NI) and abnormal neurons were distributed in regular clusters. Clusters of the NI and abnormal neurons were spatially correlated whereas the GCI were not spatially correlated with either the NI or the abnormal neurons. The data suggest that the GCI represent the primary change in MSA and the neuronal pathology develops secondary to the glial pathology.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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Mobile WiFi devices are becoming increasingly popular in non-seamless and user-controlled mobile traffic offloading alongside the standard WiFi hotspots. Unlike the operator-controlled hotspots, a mobile WiFi device relies on the capacity of the macro-cell for the data rate allocated to it. This type of devices can help offloading data traffic from the macro-cell base station and serve the end users within a closer range, but will change the pattern of resource distributions operated by the base station. We propose a resource allocation scheme that aims to optimize user quality of experience (QoE) when accessing video services in the environment where traffic offloading is taking place through interworking between a mobile communication system and low range wireless LANs. In this scheme, a rate redistribution algorithm is derived to perform scheduling which is controlled by a no-reference quality assessment metric in order to achieve the desired trade-offs between efficiency and fairness. We show the performance of this algorithm in terms of the distribution of the allocated data rates throughout the macro-cell investigated and the service coverage offered by the WiFi access point.

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Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.