855 resultados para Heterogeneous azeotropic distillation


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The Everglades freshwater marl prairie is a dynamic and spatially heterogeneous landscape, containing thousands of tree islands nested within a marsh matrix. Spatial processes underlie population and community dynamics across the mosaic, especially the balance between woody and graminoid components, and landscape patterns reflect interactions among multiple biotic and abiotic drivers. To better understand these complex, multi-scaled relationships we employed a three-tiered hierarchical design to investigate the effects of seed source, hydrology, and more indirectly fire on the establishment of new woody recruits in the marsh, and to assess current tree island patterning across the landscape. Our analyses were conducted at the ground level at two scales, which we term the micro- and meso-scapes, and results were related to remotely detected tree island distributions assessed in the broader landscape, that is, the macro-scape. Seed source and hydrologic effects on recruitment in the micro- and meso-scapes were analyzed via logistic regression, and spatial aggregation in the macro-scape was evaluated using a grid-based univariate O-ring function. Results varied among regions and scales but several general trends were observed. The patterning of adult populations was the strongest driver of recruitment in the micro- and meso-scape prairies, with recruits frequently aggregating around adults or tree islands. However in the macro-scape biologically associated (second order) aggregation was rare, suggesting that emergent woody patches are heavily controlled by underlying physical and environmental factors such as topography, hydrology, and fire.

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Habitat selection decisions by consumers has the potential to shape ecosystems. Understanding the factors that influence habitat selection is therefore critical to understanding ecosystem function. This is especially true of mesoconsumers because they provide the link between upper and lower tropic levels. We examined the factors influencing microhabitat selection of marine mesoconsumers – juvenile giant shovelnose rays (Glaucostegus typus), reticulate whiprays (Himantura uarnak), and pink whiprays (H. fai) – in a coastal ecosystem with intact predator and prey populations and marked spatial and temporal thermal heterogeneity. Using a combination of belt transects and data on water temperature, tidal height, prey abundance, predator abundance and ray behavior, we found that giant shovelnose rays and reticulate whiprays were most often found resting in nearshore microhabitats, especially at low tidal heights during the warm season. Microhabitat selection did not match predictions derived from distributions of prey. Although at a course scale, ray distributions appeared to match predictions of behavioral thermoregulation theory, fine-scale examination revealed a mismatch. The selection of the shallow nearshore microhabitat at low tidal heights during periods of high predator abundance (warm season) suggests that this microhabitat may serve as a refuge, although it may come with metabolic costs due to higher temperatures. The results of this study highlight the importance of predators in the habitat selection decisions of mesoconsumers and that within thermal gradients, factors, such as predation risk, must be considered in addition to behavioral thermoregulation to explain habitat selection decisions. Furthermore, increasing water temperatures predicted by climate change may result in complex trade-offs that might have important implications for ecosystem dynamics.

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This study investigated the efficacy of Group Cognitive-Behavioral Therapy (GCBT) in the treatment of heterogeneous anxiety disorders in children. A partially nonconcurrent multiple baseline across groups design was used to assess the effects of the treatment on 12 clinically referred children and adolescents between 6 and 16 years of age who met DSM-IV criteria for an anxiety disorder. Targeted diagnoses included Obsessive Compulsive Disorder, Simple Phobia, Separation Anxiety Disorder, Social Phobia, and Generalized Anxiety Disorder, with three of the children also presenting with school refusal behavior. Duration of baseline for each of the three groups varied and ran for one, two, or three weeks. Dependent measures included diagnostic status, child and parent-completed reports, and daily child and parent ratings of child anxiety severity. Results indicated that GCBT was efficacious in reducing anxious symptoms in children and adolescents treated in diagnostically heterogeneous groups, and that gains were generally maintained at 6 and 12 month follow-ups. Findings are discussed in terms of their theoretical and practical implications for the efficient treatment of children and adolescents with anxiety disorders. ^

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Current technology permits connecting local networks via high-bandwidth telephone lines. Central coordinator nodes may use Intelligent Networks to manage data flow over dialed data lines, e.g. ISDN, and to establish connections between LANs. This dissertation focuses on cost minimization and on establishing operational policies for query distribution over heterogeneous, geographically distributed databases. Based on our study of query distribution strategies, public network tariff policies, and database interface standards we propose methods for communication cost estimation, strategies for the reduction of bandwidth allocation, and guidelines for central to node communication protocols. Our conclusion is that dialed data lines offer a cost effective alternative for the implementation of distributed database query systems, and that existing commercial software may be adapted to support query processing in heterogeneous distributed database systems. ^

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In finance literature many economic theories and models have been proposed to explain and estimate the relationship between risk and return. Assuming risk averseness and rational behavior on part of the investor, the models are developed which are supposed to help in forming efficient portfolios that either maximize (minimize) the expected rate of return (risk) for a given level of risk (rates of return). One of the most used models to form these efficient portfolios is the Sharpe's Capital Asset Pricing Model (CAPM). In the development of this model it is assumed that the investors have homogeneous expectations about the future probability distribution of the rates of return. That is, every investor assumes the same values of the parameters of the probability distribution. Likewise financial volatility homogeneity is commonly assumed, where volatility is taken as investment risk which is usually measured by the variance of the rates of return. Typically the square root of the variance is used to define financial volatility, furthermore it is also often assumed that the data generating process is made of independent and identically distributed random variables. This again implies that financial volatility is measured from homogeneous time series with stationary parameters. In this dissertation, we investigate the assumptions of homogeneity of market agents and provide evidence for the case of heterogeneity in market participants' information, objectives, and expectations about the parameters of the probability distribution of prices as given by the differences in the empirical distributions corresponding to different time scales, which in this study are associated with different classes of investors, as well as demonstrate that statistical properties of the underlying data generating processes including the volatility in the rates of return are quite heterogeneous. In other words, we provide empirical evidence against the traditional views about homogeneity using non-parametric wavelet analysis on trading data, The results show heterogeneity of financial volatility at different time scales, and time-scale is one of the most important aspects in which trading behavior differs. In fact we conclude that heterogeneity as posited by the Heterogeneous Markets Hypothesis is the norm and not the exception.

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In this paper, a heterogeneous network composed of femtocells deployed within a macrocell network is considered, and a quality-of-service (QoS)-oriented fairness metric which captures important characteristics of tiered network architectures is proposed. Using homogeneous Poisson processes, the sum capacities in such networks are expressed in closed form for co-channel, dedicated channel, and hybrid resource allocation methods. Then a resource splitting strategy that simultaneously considers capacity maximization, fairness constraints, and QoS constraints is proposed. Detailed computer simulations utilizing 3GPP simulation assumptions show that a hybrid allocation strategy with a well-designed resource split ratio enjoys the best cell-edge user performance, with minimal degradation in the sum throughput of macrocell users when compared with that of co-channel operation.

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The mediator software architecture design has been developed to provide data integration and retrieval in distributed, heterogeneous environments. Since the initial conceptualization of this architecture, many new technologies have emerged that can facilitate the implementation of this design. The purpose of this thesis was to show that a mediator framework supporting users of mobile devices could be implemented using common software technologies available today. In addition, the prototype was developed with a view to providing a better understanding of what a mediator is and to expose issues that will have to be addressed in full, more robust designs. The prototype developed for this thesis was implemented using various technologies including: Java, XML, and Simple Object Access Protocol (SOAP) among others. SOAP was used to accomplish inter-process communication. In the end, it is expected that more data intensive software applications will be possible in a world with ever-increasing demands for information.

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The purpose of this study was to examine the relation between classroom environmental quality and early literacy outcomes amongst a sample of Latino children from various Latin-American countries. Participants included 116 preschoolers that attended various childcare centers in Southeast Florida. Participant’s literacy knowledge was assessed using the Test of Preschool Early Literacy. Classrooms were assessed on environmental quality using the Early Childhood Environmental Rating Scale-Revised. A regression analysis revealed that classroom environmental quality did not account for Latino children’s early literacy outcomes. However, a multiple regression analysis was significant (R2= .15, F(5, 115) = 3.86, p< .05) indicating that quality has a varying impact on children’s early literacy skills based on children’s region of origin. Findings suggest that high classroom environmental quality does not necessarily mean better literacy development for Latino children. Additionally, Latino children should not be viewed as a homogeneous group, particularly in relation to their development of literacy skills in English.

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Today, databases have become an integral part of information systems. In the past two decades, we have seen different database systems being developed independently and used in different applications domains. Today's interconnected networks and advanced applications, such as data warehousing, data mining & knowledge discovery and intelligent data access to information on the Web, have created a need for integrated access to such heterogeneous, autonomous, distributed database systems. Heterogeneous/multidatabase research has focused on this issue resulting in many different approaches. However, a single, generally accepted methodology in academia or industry has not emerged providing ubiquitous intelligent data access from heterogeneous, autonomous, distributed information sources. This thesis describes a heterogeneous database system being developed at Highperformance Database Research Center (HPDRC). A major impediment to ubiquitous deployment of multidatabase technology is the difficulty in resolving semantic heterogeneity. That is, identifying related information sources for integration and querying purposes. Our approach considers the semantics of the meta-data constructs in resolving this issue. The major contributions of the thesis work include: (i.) providing a scalable, easy-to-implement architecture for developing a heterogeneous multidatabase system, utilizing Semantic Binary Object-oriented Data Model (Sem-ODM) and Semantic SQL query language to capture the semantics of the data sources being integrated and to provide an easy-to-use query facility; (ii.) a methodology for semantic heterogeneity resolution by investigating into the extents of the meta-data constructs of component schemas. This methodology is shown to be correct, complete and unambiguous; (iii.) a semi-automated technique for identifying semantic relations, which is the basis of semantic knowledge for integration and querying, using shared ontologies for context-mediation; (iv.) resolutions for schematic conflicts and a language for defining global views from a set of component Sem-ODM schemas; (v.) design of a knowledge base for storing and manipulating meta-data and knowledge acquired during the integration process. This knowledge base acts as the interface between integration and query processing modules; (vi.) techniques for Semantic SQL query processing and optimization based on semantic knowledge in a heterogeneous database environment; and (vii.) a framework for intelligent computing and communication on the Internet applying the concepts of our work.