The relationship between non-orthographic language abilities and reading performance: An exploration of the primary systems hypothesis in chronic aphasia

Thesis (Ph.D.)--University of Washington, 2016-06

Process, performance, and pollution potential: A review of septic tank-soil absorption systems

On-site wastewater treatment and dispersal systems (OWTS) are used in non-sewered populated areas in Australia to treat and dispose of household wastewater. The most common OWTS in Australia is the septic tank-soil absorption system (SAS) - which relies on the soil to treat and disperse effluent. The mechanisms governing purification and hydraulic performance of a SAS are complex and have been shown to be highly influenced by the biological zone (biomat) which develops on the soil surface within the trench or bed. Studies suggest that removal mechanisms in the biomat zone, primarily adsorption and filtering, are important processes in the overall purification abilities of a SAS. There is growing concern that poorly functioning OWTS are impacting upon the environment, although to date, only a few investigations have been able to demonstrate pollution of waterways by on-site systems. In this paper we review some key hydrological and biogeochemical mechanisms in SAS, and the processes leading to hydraulic failure. The nutrient and pathogen removal efficiencies in soil absorption systems are also reviewed, and a critical discussion of the evidence of failure and environmental and public health impacts arising from SAS operation is presented. Future research areas identified from the review include the interactions between hydraulic and treatment mechanisms, and the biomat and sub-biomat zone gas composition and its role in effluent treatment.

Competition between polyphosphate and glycogen accumulating organisms in enhanced biological phosphorus removal systems with acetate and propionate as carbon sources

Enhanced biological phosphorus removal (EBPR) is a widely used process for achieving phosphorus removal from wastewater. A potential reason for EBPR failure is the undesirable growth of glycogen accumulating organisms (GAOs), which can compete for carbon sources with the bacterial group responsible for phosphorus removal from wastewater: the polyphosphate accumulating organisms (PAOs). This study investigates the impact of carbon source on EBPR performance and the competition between PAOs and GAOs. Two sequencing batch reactors (SBRs) were operated during a 4-6 month period and fed with a media containing acetate or propionate, respectively, as the sole carbon source. It was found that the acetate fed SBR rarely achieved a high level of phosphorus removal, and that a large portion of the microbial community was comprised of Candidatus Competibacter phosphatis, a known GAO. The propionate fed SBR, however, achieved stable phosphorus removal throughout the study, apart from one brief disturbance. The bacterial community of the propionate fed SBR was dominated by Candidatus Accumulibacter phosphatis, a known PAO, and did not contain Competibacter In a separate experiment, another SBR was seeded with a mixture of PAOs and a group of alphaproteobacterial GAOs, both enriched with propionate as the sole carbon source. Stable EBPR was achieved and the PAO population increased while the GAOs appeared to be out-competed. The results of this paper suggest that propionate may provide PAOs with a selective advantage over GAOs in the PAO-GAO competition, particularly through the minimisation of Competibacter Propionate may be a more suitable substrate than acetate for enhancing phosphorus removal in EBPR systems. (c) 2005 Elsevier B.V. All rights reserved.

Investigating the performance of MIMO systems from an electromagnetic perspective

Multiple input multiple output (MIMO) wireless systems use multiple element antennas (MEAs) tit the transmitter (TX) and the receiver (RX) in order to offer improved information rates (capacity) over conventional single antenna systems in rich scattering environments. In this paper, an example of a simple MIMO system is considered in which both antennas and scattering objects is are formed by wire dipoles. Such it system can be analyzed in the strict electromagnetic (EM) sense and its capacity can be determined for varying array size, interelement spacing, and distributions of scatterers. The EM model of this MIMO system can be used to assess the validity of single- or double-bounce scattering models for mixed line of sight (LOS) and non-line of sight (NLOS) signal-propagation conditions. (c) 2006 Wiley Periodicals, Inc.

Summarizing level-two topological relations in large spatial datasets

Summarizing topological relations is fundamental to many spatial applications including spatial query optimization. In this article, we present several novel techniques to effectively construct cell density based spatial histograms for range (window) summarizations restricted to the four most important level-two topological relations: contains, contained, overlap, and disjoint. We first present a novel framework to construct a multiscale Euler histogram in 2D space with the guarantee of the exact summarization results for aligned windows in constant time. To minimize the storage space in such a multiscale Euler histogram, an approximate algorithm with the approximate ratio 19/12 is presented, while the problem is shown NP-hard generally. To conform to a limited storage space where a multiscale histogram may be allowed to have only k Euler histograms, an effective algorithm is presented to construct multiscale histograms to achieve high accuracy in approximately summarizing aligned windows. Then, we present a new approximate algorithm to query an Euler histogram that cannot guarantee the exact answers; it runs in constant time. We also investigate the problem of nonaligned windows and the problem of effectively partitioning the data space to support nonaligned window queries. Finally, we extend our techniques to 3D space. Our extensive experiments against both synthetic and real world datasets demonstrate that the approximate multiscale histogram techniques may improve the accuracy of the existing techniques by several orders of magnitude while retaining the cost efficiency, and the exact multiscale histogram technique requires only a storage space linearly proportional to the number of cells for many popular real datasets.

Toddler subtraction with large sets: further evidence for an analog-magnitude representation of number

Two experiments were conducted to test the hypothesis that toddlers have access to an analog-magnitude number representation that supports numerical reasoning about relatively large numbers. Three-year-olds were presented with subtraction problems in which initial set size and proportions subtracted were systematically varied. Two sets of cookies were presented and then covered The experimenter visibly subtracted cookies from the hidden sets, and the children were asked to choose which of the resulting sets had more. In Experiment 1, performance was above chance when high proportions of objects (3 versus 6) were subtracted from large sets (of 9) and for the subset of older participants (older than 3 years, 5 months; n = 15), performance was also above chance when high proportions (10 versus 20) were subtracted from the very large sets (of 30). In Experiment 2, which was conducted exclusively with older 3-year-olds and incorporated an important methodological control, the pattern of results for the subtraction tasks was replicated In both experiments, success on the tasks was not related to counting ability. The results of these experiments support the hypothesis that young children have access to an analog-magnitude system for representing large approximate quantities, as performance on these subtraction tasks showed a Webers Law signature, and was independent of conventional number knowledge.

Anisotropy-based robust performance analysis of finite horizon linear discrete time varying systems

We consider a problem of robust performance analysis of linear discrete time varying systems on a bounded time interval. The system is represented in the state-space form. It is driven by a random input disturbance with imprecisely known probability distribution; this distributional uncertainty is described in terms of entropy. The worst-case performance of the system is quantified by its a-anisotropic norm. Computing the anisotropic norm is reduced to solving a set of difference Riccati and Lyapunov equations and a special form equation.

Advanced computing for systems biology

Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.

Performance comparisons between greedy and lagrange algorithms in adaptive MIMO MC-CDMA systems

This paper describes two algorithms for adaptive power and bit allocations in a multiple input multiple output multiple-carrier code division multiple access (MIMO MC-CDMA) system. The first is the greedy algorithm, which has already been presented in the literature. The other one, which is proposed by the authors, is based on the use of the Lagrange multiplier method. The performances of the two algorithms are compared via Monte Carlo simulations. At present stage, the simulations are restricted to a single user MIMO MC-CDMA system, which is equivalent to a MIMO OFDM system. It is assumed that the system operates in a frequency selective fading environment. The transmitter has a partial knowledge of the channel whose properties are measured at the receiver. The use of the two algorithms results in similar system performances. The advantage of the Lagrange algorithm is that is much faster than the greedy algorithm. ©2005 IEEE