155 resultados para LABORATORY MODELS

em University of Queensland eSpace - Australia


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Durante las últimas tres décadas el interés y diversidad en el uso de canales escalonados han aumentado debido al desarrollo de nuevas técnicas y materiales que permiten su construcción de manera rápida y económica (Concreto compactado con rodillo CCR, Gaviones, etc.). Actualmente, los canales escalonados se usan como vertedores y/o canales para peces en presas y diques, como disipadores de energía en canales y ríos, o como aireadores en plantas de tratamiento y torrentes contaminados. Diversos investigadores han estudiado el flujo en vertedores escalonados, enfocándose en estructuras de gran pendiente (  45o) por lo que a la fecha, el comportamiento del flujo sobre vertedores con pendientes moderadas (  15 a 30o) no ha sido totalmente comprendido. El presente artículo comprende un estudio experimental de las propiedades físicas del flujo aire-agua sobre canales escalonados con pendientes moderadas, típicas en presas de materiales sueltos. Un extenso rango de gastos en condiciones de flujo rasante se investigó en dos modelos experimentales a gran escala (Le = 3 a 6): Un canal con pendiente 3.5H:1V (  16o) y dos alturas de escalón distintas (h = 0.1 y 0.05 m) y un canal con pendiente 2.5H:1V (  22o) y una altura de escalón de h = 0.1 m. Los resultados incluyen un análisis detallado de las propiedades del flujo en vertedores escalonados con pendientes moderadas y un nuevo criterio de diseño hidráulico, el cual está basado en los resultados experimentales obtenidos. English abstract: Stepped chutes have been used as hydraulic structures since antiquity, they can be found acting as spillways and fish ladders in dams and weirs, as energy dissipators in artificial channels, gutters and rivers, and as aeration enhancers in water treatment plants and polluted streams. In recent years, new construction techniques and materials (Roller Compacted Concrete RCC, rip-rap gabions, etc.) together with the development of the abovementioned new applications have allowed cheaper construction methods, increasing the interest in stepped chute design. During the last three decades, research in stepped spillways has been very active. However, studies prior to 1993 neglected the effect of free-surface aeration. A number of studies have focused since on steep stepped chutes (  45o) but the hydraulic performance of moderate-slope stepped channels is not yet totally understood. This study details an experimental investigation of physical air-water flow properties down moderate slope stepped spillways conducted in two laboratory models: the first model was a 3.15 m long stepped chute with a 15.9o slope comprising two interchangeable step heights (h = 0.1 m and h = 0.05 m); the second model was a 3.3 m long, stepped channel with a 21.8o slope (h = 0.1 m). A broad range of discharges within transition and skimming flow regimes was investigated. Measurements were conducted using a double tip conductivity probe. The study provides new, original insights into air-water stepped chute flows not foreseen in prior studies and presents a new design criterion for chutes with moderate slopes based on the experimental results.

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The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Laboratory-scale sequencing batch reactors (SBRs) as models for wastewater treatment processes were used to identify glycogen-accumulating organisms (GAOs), which are thought to be responsible for the deterioration of enhanced biological phosphorus removal (EBPR). The SBRs (called Q and T), operated under alternating anaerobic-aerobic conditions typical for EBPR, generated mixed microbial communities (sludges) demonstrating the GAO phenotype. Intracellular glycogen and poly-beta-hydroxyalkanoate (PHA) transformations typical of efficient EBPR occurred but polyphosphate was not bioaccumulated and the sludges contained 1.8% P (sludge Q) and 1.5% P (sludge T). 16S rDNA clone libraries were prepared from DNA extracted from the Q and T sludges. Clone inserts were grouped into operational taxonomic units (OTUs) by restriction fragment length polymorphism banding profiles. OTU representatives were sequenced and phylogenetically analysed. The Q sludge library comprised four OTUs and all six determined sequences were 99.7% identical, forming a cluster in the gamma-Proteobacteria radiation. The T sludge library comprised eight OTUs and the majority of clones were Acidobacteria subphylum 4 (49% of the library) and candidate phylum OPU (39% of the library). One OTU (two clones, of which one was sequenced) was in the gamma-Proteobacteria radiation with 95% sequence identity to the Q sludge clones. Oligonucleotide probes (called GAOQ431 and GAOQ989) were designed from the gamma-Proteobacteria clone sequences for use in fluorescence in situ hybridization (FISH); 92 % of the Q sludge bacteria and 28 % of the T sludge bacteria bound these probes in FISH. FISH and post-FISH chemical staining for PHA were used to determine that bacteria from a novel gamma-Proteobacteria cluster were phenotypically GAOs in one laboratory-scale SBR and two fullscale wastewater treatment plants. It is suggested that the GAOs from the novel cluster in the gamma-Proteobacteria radiation be named 'Candidatus Competibacter phosphatis'.

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Evaluation of the performance of the APACHE III (Acute Physiology and Chronic Health Evaluation) ICU (intensive care unit) and hospital mortality models at the Princess Alexandra Hospital, Brisbane is reported. Prospective collection of demographic, diagnostic, physiological, laboratory, admission and discharge data of 5681 consecutive eligible admissions (1 January 1995 to 1 January 2000) was conducted at the Princess Alexandra Hospital, a metropolitan Australian tertiary referral medical/surgical adult ICU. ROC (receiver operating characteristic) curve areas for the APACHE III ICU mortality and hospital mortality models demonstrated excellent discrimination. Observed ICU mortality (9.1%) was significantly overestimated by the APACHE III model adjusted for hospital characteristics (10.1%), but did not significantly differ from the prediction of the generic APACHE III model (8.6%). In contrast, observed hospital mortality (14.8%) agreed well with the prediction of the APACHE III model adjusted for hospital characteristics (14.6%), but was significantly underestimated by the unadjusted APACHE III model (13.2%). Calibration curves and goodness-of-fit analysis using Hosmer-Lemeshow statistics, demonstrated that calibration was good with the unadjusted APACHE III ICU mortality model, and the APACHE III hospital mortality model adjusted for hospital characteristics. Post hoc analysis revealed a declining annual SMR (standardized mortality rate) during the study period. This trend was present in each of the non-surgical, emergency and elective surgical diagnostic groups, and the change was temporally related to increased specialist staffing levels. This study demonstrates that the APACHE III model performs well on independent assessment in an Australian hospital. Changes observed in annual SMR using such a validated model support an hypothesis of improved survival outcomes 1995-1999.

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Enhanced biological phosphorus removal (EBPR) has been used at many wastewater treatment plants all over the world for many years. In this study a full-scale sludge with good EBPR was tested with P-release batch tests and combined FISH/MAR (fluorescence in situ hybridisation and microautoradiography). Proposed models of PAOs and GAOs (polyphosphate- and glycogen-accumulating organisms) and microbial methods suggested from studies of laboratory reactors were found to be applicable also on sludge from full-scale plants. Dependency of pH and the uptake of both acetate and propionate were studied and used for calculations for verifying the models and results from microbial methods. All rates found from the batch tests with acetate were higher than in the batch tests with propionate, which was explained by the finding that only those parts of the bacterial community that were able to take up acetate anaerobically were able to take up propionate anaerobically.

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Even when data repositories exhibit near perfect data quality, users may formulate queries that do not correspond to the information requested. Users’ poor information retrieval performance may arise from either problems understanding of the data models that represent the real world systems, or their query skills. This research focuses on users’ understanding of the data structures, i.e., their ability to map the information request and the data model. The Bunge-Wand-Weber ontology was used to formulate three sets of hypotheses. Two laboratory experiments (one using a small data model and one using a larger data model) tested the effect of ontological clarity on users’ performance when undertaking component, record, and aggregate level tasks. The results indicate for the hypotheses associated with different representations but equivalent semantics that parsimonious data model participants performed better for component level tasks but that ontologically clearer data model participants performed better for record and aggregate level tasks.

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Objective:To investigate the effects of bilateral, surgically induced functional inhibition of the subthalamic nucleus (STN) on general language, high level linguistic abilities, and semantic processing skills in a group of patients with Parkinson’s disease. Methods:Comprehensive linguistic profiles were obtained up to one month before and three months after bilateral implantation of electrodes in the STN during active deep brain stimulation (DBS) in five subjects with Parkinson’s disease (mean age, 63.2 years). Equivalent linguistic profiles were generated over a three month period for a non-surgical control cohort of 16 subjects with Parkinson’s disease (NSPD) (mean age, 64.4 years). Education and disease duration were similar in the two groups. Initial assessment and three month follow up performance profiles were compared within subjects by paired t tests. Reliability change indices (RCI), representing clinically significant alterations in performance over time, were calculated for each of the assessment scores achieved by the five STN-DBS cases and the 16 NSPD controls, relative to performance variability within a group of 16 non-neurologically impaired adults (mean age, 61.9 years). Proportions of reliable change were then compared between the STN-DBS and NSPD groups. Results:Paired comparisons within the STN-DBS group showed prolonged postoperative semantic processing reaction times for a range of word types coded for meanings and meaning relatedness. Case by case analyses of reliable change across language assessments and groups revealed differences in proportions of change over time within the STN-DBS and NSPD groups in the domains of high level linguistics and semantic processing. Specifically, when compared with the NSPD group, the STN-DBS group showed a proportionally significant (p

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Traditionally the basal ganglia have been implicated in motor behavior, as they are involved in both the execution of automatic actions and the modification of ongoing actions in novel contexts. Corresponding to cognition, the role of the basal ganglia has not been defined as explicitly. Relative to linguistic processes, contemporary theories of subcortical participation in language have endorsed a role for the globus pallidus internus (GPi) in the control of lexical-semantic operations. However, attempts to empirically validate these postulates have been largely limited to neuropsychological investigations of verbal fluency abilities subsequent to pallidotomy. We evaluated the impact of bilateral posteroventral pallidotomy (BPVP) on language function across a range of general and high-level linguistic abilities, and validated/extended working theories of pallidal participation in language. Comprehensive linguistic profiles were compiled up to 1 month before and 3 months after BPVP in 6 subjects with Parkinson's disease (PD). Commensurate linguistic profiles were also gathered over a 3-month period for a nonsurgical control cohort of 16 subjects with PD and a group of 16 non-neurologically impaired controls (NC). Nonparametric between-groups comparisons were conducted and reliable change indices calculated, relative to baseline/3-month follow-up difference scores. Group-wise statistical comparisons between the three groups failed to reveal significant postoperative changes in language performance. Case-by-case data analysis relative to clinically consequential change indices revealed reliable alterations in performance across several language variables as a consequence of BPVP. These findings lend support to models of subcortical participation in language, which promote a role for the GPi in lexical-semantic manipulation mechanisms. Concomitant improvements and decrements in postoperative performance were interpreted within the context of additive and subtractive postlesional effects. Relative to parkinsonian cohorts, clinically reliable versus statistically significant changes on a case by case basis may provide the most accurate method of characterizing the way in which pathophysiologically divergent basal ganglia linguistic circuits respond to BPVP.

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The Gaudin models based on the face-type elliptic quantum groups and the XYZ Gaudin models are studied. The Gaudin model Hamiltonians are constructed and are diagonalized by using the algebraic Bethe ansatz method. The corresponding face-type Knizhnik–Zamolodchikov equations and their solutions are given.

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In this review we demonstrate how the algebraic Bethe ansatz is used for the calculation of the-energy spectra and form factors (operator matrix elements in the basis of Hamiltonian eigenstates) in exactly solvable quantum systems. As examples we apply the theory to several models of current interest in the study of Bose-Einstein condensates, which have been successfully created using ultracold dilute atomic gases. The first model we introduce describes Josephson tunnelling between two coupled Bose-Einstein condensates. It can be used not only for the study of tunnelling between condensates of atomic gases, but for solid state Josephson junctions and coupled Cooper pair boxes. The theory is also applicable to models of atomic-molecular Bose-Einstein condensates, with two examples given and analysed. Additionally, these same two models are relevant to studies in quantum optics; Finally, we discuss the model of Bardeen, Cooper and Schrieffer in this framework, which is appropriate for systems of ultracold fermionic atomic gases, as well as being applicable for the description of superconducting correlations in metallic grains with nanoscale dimensions.; In applying all the above models to. physical situations, the need for an exact analysis of small-scale systems is established due to large quantum fluctuations which render mean-field approaches inaccurate.

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Many images consist of two or more 'phases', where a phase is a collection of homogeneous zones. For example, the phases may represent the presence of different sulphides in an ore sample. Frequently, these phases exhibit very little structure, though all connected components of a given phase may be similar in some sense. As a consequence, random set models are commonly used to model such images. The Boolean model and models derived from the Boolean model are often chosen. An alternative approach to modelling such images is to use the excursion sets of random fields to model each phase. In this paper, the properties of excursion sets will be firstly discussed in terms of modelling binary images. Ways of extending these models to multi-phase images will then be explored. A desirable feature of any model is to be able to fit it to data reasonably well. Different methods for fitting random set models based on excursion sets will be presented and some of the difficulties with these methods will be discussed.

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Except for a few large scale projects, language planners have tended to talk and argue among themselves rather than to see language policy development as an inherently political process. A comparison with a social policy example, taken from the United States, suggests that it is important to understand the problem and to develop solutions in the context of the political process, as this is where decisions will ultimately be made.

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Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response theory (IRT). It begins by outlining the primary structural distinction between the two major types of polytomous IRT models. This focuses on the two types of response probability that are unique to polytomous models and their associated response functions, which are modeled differently by the different types of IRT model. It describes, both conceptually and mathematically, the major specific polytomous models, including the Nominal Response Model, the Partial Credit Model, the Rating Scale model, and the Graded Response Model. Important variations, such as the Generalized Partial Credit Model are also described as are less common variations, such as the Rating Scale version of the Graded Response Model. Relationships among the models are also investigated and the operation of measurement information is described for each major model. Practical examples of major models using real data are provided, as is a chapter on choosing an appropriate model. Figures are used throughout to illustrate important elements as they are described.

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This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.