The North Sea autumn spawning Herring (Clupea harengus L.) Spawning Component Abundance Index (SCAI)

The North Sea autumn-spawning herring (Clupea harengus) stock consists of a set of different spawning components. The dynamics of the entire stock have been well characterized, but although time-series of larval abundance indices are available for the individual components, study of the dynamics at the component level has historically been hampered by missing observations and high sampling noise. A simple state-space statistical model is developed that is robust to these problems, gives a good fit to the data, and proves capable of both handling and predicting missing observations well. Furthermore, the sum of the fitted abundance indices across all components proves an excellent proxy for the biomass of the total stock, even though the model utilizes information at the individual-component level. The Orkney-Shetland component appears to have recovered faster from historic depletion events than the other components, whereas the Downs component has been the slowest. These differences give rise to changes in stock composition, which are shown to vary widely within a relatively short time. The modelling framework provides a valuable tool for studying and monitoring the dynamics of the individual components of the North Sea herring stock.

Affirmative action plan : fiscal year ... /

"The Human Rights Act consolidated three state agencies, the Fair Employment Practices Commission, the Department of Equal Employment Opportunity and the Commission on Human Relations into a unified cabinet level civil rights agency for the state, titled "Department of Human Rights."

An investigation of contaminant distribution in subsurface marine wood waste at Mill-A South Terminal, Port of Everett, Washington

This project investigates the correlation between contaminants and the wood waste present in marine sediments off the shore of the Port of Everett in the former Weyerhaeuser Mill-A pulp mill site. The investigation includes the results of two field studies, which tested contaminant levels in 22 boreholes as well as several surface samples. The contaminants include heavy metals and wood waste byproducts. These results, along with 14 other bore logs, provide the framework for a three-dimensional site model, interpolating the full extent of the depositional units and organic and inorganic chemicals found at Mill-A. The sediments of interest are divided into five depositional units defined by the percent wood content and type of wood: native material (<5% wood), intermediate (<30% wood), sawdust (<30% wood), woodchips (<30% wood), and poorly sorted sands with silt (SM-SP) (0% wood). The contaminants include arsenic, 2,4-dimethylphenol, and total organic carbon. Three-dimensional modeling software, RockWorks, interpolated the discrete borehole data of sediment and contaminants assuming horizontal continuity between sampling locations. The sediment distribution was calculated within concentration ranges for each contaminant of concern. The lowest detection limits, the screening levels, and the cleanup levels defined these ranges. Total organic carbon served as a proxy to estimate the quantity of wood waste in the sediment. As a known byproduct of wood decomposition, 2,4-dimethylphenol was expected to be more prevalent in the depositional units with more wood waste. Finally, arsenic was a proxy for other contaminants to determine if contaminants at Mill-A are dominant in sediments with high percentages of wood waste. The volumetric distribution established that high levels of total organic carbon are present in the sediment with higher percentages of wood waste. This correlation was stronger in the decomposing sawdust-rich sediment than the woodchip-rich sediment. The 2,4-dimethylphenol concentrations above cleanup standards were dominant in the sawdust-rich, intermediate and native sediments. Concentrations of 2,4-dimethylphenol below cleanup levels characterized the native sediment. The distribution of arsenic showed no statistically significant correlation to wood content in sediment. These results do not support the hypothesis of contaminant-rich wood waste, as many of the high concentrations of contaminants were not in the wood-rich sediments. This suggests that the contaminants are more distributed among all depositional units at Mill-A rather than focused within sediments with a high percent of wood waste. Understanding the distribution of potentially toxic compounds with wood waste is important for restoring the Puget Sound waterways to a more habitable environment. Future studies should include new data to validate these results and to limit the uncertainty of the extent of contaminants. Future studies may also find motive in looking for a correlation between contaminants and grain size based on previous studies linking these characteristics. These investigations will benefit the current cleanup effort as well as future cleanup efforts at similarly contaminated waterways.

Treatment-seeking behavior and delay in children with severe malaria in Uganda: results of a Markov analysis

Thesis (Master's)--University of Washington, 2016-06

Population pharmacokinetics and association between A77 1726 plasma concentrations and disease activity measures following administration of leflunomide to people with rheumatoid arthritis

Aims To investigate the concentration-effect relationship and pharmacokinetics of leflunomide in patients with rheumatoid arthritis (RA). Methods Data were collected from 23 RA patients on leflunomide therapy (as sole disease modifying antirheumatic drug (DMARD)) for at least 3 months. Main measures were A77 1726 (active metabolite of leflunomide) plasma concentrations and disease activity measures including pain, duration/intensity of morning stiffness, and SF-36 survey. A population estimate was sought for apparent clearance (CL/F ) and volume of distribution was fixed (0.155 l kg(-1)). Factors screened for influence on CL/F were weight, age, gender and estimated creatinine clearance. Results Significantly higher A77 1726 concentrations were seen in patients with less swollen joints and with higher SF-36 mental summary scores than in those with measures indicating more active disease (P < 0.05); concentration-effect trends were seen with five other disease activity measures. Statistical analysis of all disease activity measures showed that mean A77 1726 concentrations in groups with greater control of disease activity were significantly higher than those in whom the measures indicated less desirable control (P < 0.05). There was large between subject variability in the dose-concentration relationship. A steady-state infusion model best described the pharmacokinetic data. Inclusion of age as a covariate decreased interindividual variability (P < 0.01), but this would not be clinically important in terms of dosage changes. Final parameter estimate (% CV interindividual variability) for CL/F was 0.0184 l h(-1) (50%) (95% CI 0.0146, 0.0222). Residual (unexplained) variability (% CV) was 8.5%. Conclusions This study of leflunomide in patients using the drug clinically indicated a concentration-effect relationship. From our data, a plasma A77 1726 concentration of 50 mg l(-1) is more likely to indicate someone with less active disease than is a concentration around 30 mg l(-1). The marked variability in pharmacokinetics suggests a place for individualized dosing of leflunomide in RA therapy.

Optimization of co-current spray drying process of sugar-rich foods. Part I - Moisture and glass transition temperature profile during drying

A steady state mathematical model for co-current spray drying was developed for sugar-rich foods with the application of the glass transition temperature concept. Maltodextrin-sucrose solution was used as a sugar-rich food model. The model included mass, heat and momentum balances for a single droplet drying as well as temperature and humidity profile of the drying medium. A log-normal volume distribution of the droplets was generated at the exit of the rotary atomizer. This generation created a certain number of bins to form a system of non-linear first-order differential equations as a function of the axial distance of the drying chamber. The model was used to calculate the changes of droplet diameter, density, temperature, moisture content and velocity in association with the change of air properties along the axial distance. The difference between the outlet air temperature and the glass transition temperature of the final products (AT) was considered as an indicator of stickiness of the particles in spray drying process. The calculated and experimental AT values were close, indicating successful validation of the model. (c) 2004 Elsevier Ltd. All rights reserved.

Searching for cancer deaths in Australia: National Death Index vs Cancer Registries

OBJECTIVE: To compare the accuracy, costs and utility of using the National Death Index (NDI) and state-based cancer registries in determining the mortality status of a cohort of women diagnosed with ovarian cancer in the early 1990s. METHODS: As part of a large prognostic study, identifying information on 822 women diagnosed with ovarian cancer between 1990 and 1993, was simultaneously submitted to the NDI and three state-based cancer registries to identify deceased women as of June 30, 1999. This was compared to the gold standard of "definite deaths". A comparative evaluation was also made of the time and costs associated with the two methods. RESULTS: Of the 450 definite deaths in our cohort the NDI correctly identified 417 and all of the 372 women known to be alive (sensitivity 93%, specificity 100%). Inconsistencies in identifiers recorded in our cohort files, particularly names, were responsible for the majority of known deaths not matching with the NDI, and if eliminated would increase the sensitivity to 98%. The cancer registries correctly identified 431 of the 450 definite deaths (sensitivity 96%). The costs associated with the NDI search were the same as the cancer registry searches, but the cancer registries took two months longer to conduct the searches. CONCLUSIONS AND IMPLICATIONS: This study indicates that the cancer registries are valuable, cost effective agencies for follow-up of mortality outcome in cancer cohorts, particularly where cohort members were residents of those states. For following large national cohorts the NDI provides additional information and flexibility when searching for deaths in Australia. This study also shows that women can be followed up for mortality with a high degree of accuracy using either service. Because each service makes a valuable contribution to the identification of deceased cancer subjects, both should be considered for optimal mortality follow-up in studies of cancer patients.

The HYP program - Targeted motivational interviewing for adolescent violations of school tobacco policy

Objective. To evaluate the efficacy of a short-term tobacco-focused intervention for high school students referred by school administrators because of tobacco use. Method. A sample of 56 adolescents (66% male, mean age 15 years) was recruited through referrals from three state high schools. Participants were randomly assigned to a one-hour motivational interview (MI) session or to standard care (advice/education). The two groups were followed up at one, three, and six-month intervals. Results. The MI intervention resulted in significant short-term reductions in quantity and frequency of smoking relative to standard care, however, effects were not maintained at 3- and 6-month follow-up. Improvements in refusal self-efficacy were significant relative to standard care. Conclusion. For adolescents who are established smokers and at high risk of other problems, motivational interviewing was associated with modest short-term gains relative to standard care. (c) 2006 Elsevier Inc. All rights reserved.

A study of thermodynamic characteristics and predictive computer modelling of an air to water heat pump system

A study on heat pump thermodynamic characteristics has been made in the laboratory on a specially designed and instrumented air to water heat pump system. The design, using refrigerant R12, was based on the requirement to produce domestic hot water at a temperature of about 50 °C and was assembled in the laboratory. All the experimental data were fed to a microcomputer and stored on disk automatically from appropriate transducers via amplifier and 16 channel analogue to digital converters. The measurements taken were R12 pressures and temperatures, water and R12 mass flow rates, air speed, fan and compressor input powers, water and air inlet and outlet temperatures, wet and dry bulb temperatures. The time interval between the observations could be varied. The results showed, as expected, that the COP was higher at higher air inlet temperatures and at lower hot water output temperatures. The optimum air speed was found to be at a speed when the fan input power was about 4% of the condenser heat output. It was also found that the hot water can be produced at a temperature higher than the appropriate R12 condensing temperature corresponding to condensing pressure. This was achieved by condenser design to take advantage of discharge superheat and by further heating the water using heat recovery from the compressor. Of the input power to the compressor, typically about 85% was transferred to the refrigerant, 50 % by the compression work and 35% due to the heating of the refrigerant by the cylinder wall, and the remaining 15% (of the input power) was rejected to the cooling medium. The evaporator effectiveness was found to be about 75% and sensitive to the air speed. Using the data collected, a steady state computer model was developed. For given input conditions s air inlet temperature, air speed, the degree of suction superheat , water inlet and outlet temperatures; the model is capable of predicting the refrigerant cycle, compressor efficiency, evaporator effectiveness, condenser water flow rate and system Cop.

A hybrid generative/discriminative framework to train a semantic parser from an un-annotated corpus

We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HM-SVMs). The HVS model is an extension of the basic discrete Markov model in which context is encoded as a stack-oriented state vector. The HM-SVMs combine the advantages of the hidden Markov models and the support vector machines. By employing a modified K-means clustering method, a small set of most representative sentences can be automatically selected from an un-annotated corpus. These sentences together with their abstract annotations are used to train an HVS model which could be subsequently applied on the whole corpus to generate semantic parsing results. The most confident semantic parsing results are selected to generate a fully-annotated corpus which is used to train the HM-SVMs. The proposed framework has been tested on the DARPA Communicator Data. Experimental results show that an improvement over the baseline HVS parser has been observed using the hybrid framework. When compared with the HM-SVMs trained from the fully-annotated corpus, the hybrid framework gave a comparable performance with only a small set of lightly annotated sentences. © 2008. Licensed under the Creative Commons.

Modelling and simulation of biomass gasification in a circulating fluidized bed reactor

Computational Fluid Dynamics (CFD) has found great acceptance among the engineering community as a tool for research and design of processes that are practically difficult or expensive to study experimentally. One of these processes is the biomass gasification in a Circulating Fluidized Bed (CFB). Biomass gasification is the thermo-chemical conversion of biomass at a high temperature and a controlled oxygen amount into fuel gas, also sometime referred to as syngas. Circulating fluidized bed is a type of reactor in which it is possible to maintain a stable and continuous circulation of solids in a gas-solid system. The main objectives of this thesis are four folds: (i) Develop a three-dimensional predictive model of biomass gasification in a CFB riser using advanced Computational Fluid Dynamic (CFD) (ii) Experimentally validate the developed hydrodynamic model using conventional and advanced measuring techniques (iii) Study the complex hydrodynamics, heat transfer and reaction kinetics through modelling and simulation (iv) Study the CFB gasifier performance through parametric analysis and identify the optimum operating condition to maximize the product gas quality. Two different and complimentary experimental techniques were used to validate the hydrodynamic model, namely pressure measurement and particle tracking. The pressure measurement is a very common and widely used technique in fluidized bed studies, while, particle tracking using PEPT, which was originally developed for medical imaging, is a relatively new technique in the engineering field. It is relatively expensive and only available at few research centres around the world. This study started with a simple poly-dispersed single solid phase then moved to binary solid phases. The single solid phase was used for primary validations and eliminating unnecessary options and steps in building the hydrodynamic model. Then the outcomes from the primary validations were applied to the secondary validations of the binary mixture to avoid time consuming computations. Studies on binary solid mixture hydrodynamics is rarely reported in the literature. In this study the binary solid mixture was modelled and validated using experimental data from the both techniques mentioned above. Good agreement was achieved with the both techniques. According to the general gasification steps the developed model has been separated into three main gasification stages; drying, devolatilization and tar cracking, and partial combustion and gasification. The drying was modelled as a mass transfer from the solid phase to the gas phase. The devolatilization and tar cracking model consist of two steps; the devolatilization of the biomass which is used as a single reaction to generate the biomass gases from the volatile materials and tar cracking. The latter is also modelled as one reaction to generate gases with fixed mass fractions. The first reaction was classified as a heterogeneous reaction while the second reaction was classified as homogenous reaction. The partial combustion and gasification model consisted of carbon combustion reactions and carbon and gas phase reactions. The partial combustion considered was for C, CO, H2 and CH4. The carbon gasification reactions used in this study is the Boudouard reaction with CO2, the reaction with H2O and Methanation (Methane forming reaction) reaction to generate methane. The other gas phase reactions considered in this study are the water gas shift reaction, which is modelled as a reversible reaction and the methane steam reforming reaction. The developed gasification model was validated using different experimental data from the literature and for a wide range of operating conditions. Good agreement was observed, thus confirming the capability of the model in predicting biomass gasification in a CFB to a great accuracy. The developed model has been successfully used to carry out sensitivity and parametric analysis. The sensitivity analysis included: study of the effect of inclusion of various combustion reaction; and the effect of radiation in the gasification reaction. The developed model was also used to carry out parametric analysis by changing the following gasifier operating conditions: fuel/air ratio; biomass flow rates; sand (heat carrier) temperatures; sand flow rates; sand and biomass particle sizes; gasifying agent (pure air or pure steam); pyrolysis models used; steam/biomass ratio. Finally, based on these parametric and sensitivity analysis a final model was recommended for the simulation of biomass gasification in a CFB riser.

Semi-supervised learning of statistical models for natural language understanding

Natural language understanding is to specify a computational model that maps sentences to their semantic mean representation. In this paper, we propose a novel framework to train the statistical models without using expensive fully annotated data. In particular, the input of our framework is a set of sentences labeled with abstract semantic annotations. These annotations encode the underlying embedded semantic structural relations without explicit word/semantic tag alignment. The proposed framework can automatically induce derivation rules that map sentences to their semantic meaning representations. The learning framework is applied on two statistical models, the conditional random fields (CRFs) and the hidden Markov support vector machines (HM-SVMs). Our experimental results on the DARPA communicator data show that both CRFs and HM-SVMs outperform the baseline approach, previously proposed hidden vector state (HVS) model which is also trained on abstract semantic annotations. In addition, the proposed framework shows superior performance than two other baseline approaches, a hybrid framework combining HVS and HM-SVMs and discriminative training of HVS, with a relative error reduction rate of about 25% and 15% being achieved in F-measure.

Application of the Artificial Intelligence Algorithms for System Analysis of Multi Dimension Physiological Data for Developing Polyparametric Information System of Public Health Diagnostics

The polyparametric intelligence information system for diagnostics human functional state in medicine and public health is developed. The essence of the system consists in polyparametric describing of human functional state with the unified set of physiological parameters and using the polyparametric cognitive model developed as the tool for a system analysis of multitude data and diagnostics of a human functional state. The model is developed on the basis of general principles geometry and symmetry by algorithms of artificial intelligence systems. The architecture of the system is represented. The model allows analyzing traditional signs - absolute values of electrophysiological parameters and new signs generated by the model – relationships of ones. The classification of physiological multidimensional data is made with a transformer of the model. The results are presented to a physician in a form of visual graph – a pattern individual functional state. This graph allows performing clinical syndrome analysis. A level of human functional state is defined in the case of the developed standard (“ideal”) functional state. The complete formalization of results makes it possible to accumulate physiological data and to analyze them by mathematics methods.

Caputo Derivatives in Viscoelasticity: A Non-Linear Finite-Deformation Theory for Tissue

Mathematics Subject Classification: 26A33, 74B20, 74D10, 74L15

A randomised controlled trial of the clinical effectiveness and cost-effectiveness of the levonorgestrel-releasing intrauterine system in primary care against standard treatment for menorrhagia:the ECLIPSE trial

BACKGROUND: Heavy menstrual bleeding (HMB) is a common problem, yet evidence to inform decisions about initial medical treatment is limited. OBJECTIVES: To assess the clinical effectiveness and cost-effectiveness of the levonorgestrel-releasing intrauterine system (LNG-IUS) (Mirena(®), Bayer) compared with usual medical treatment, with exploration of women's perspectives on treatment. DESIGN: A pragmatic, multicentre randomised trial with an economic evaluation and a longitudinal qualitative study. SETTING: Women who presented in primary care. PARTICIPANTS: A total of 571 women with HMB. A purposeful sample of 27 women who were randomised or ineligible owing to treatment preference participated in semistructured face-to-face interviews around 2 and 12 months after commencing treatment. INTERVENTIONS: LNG-IUS or usual medical treatment (tranexamic acid, mefenamic acid, combined oestrogen-progestogen or progesterone alone). Women could subsequently swap or cease their allocated treatment. OUTCOME MEASURES: The primary outcome was the patient-reported score on the Menorrhagia Multi-Attribute Scale (MMAS) assessed over a 2-year period and then again at 5 years. Secondary outcomes included general quality of life (QoL), sexual activity, surgical intervention and safety. Data were analysed using iterative constant comparison. A state transition model-based cost-utility analysis was undertaken alongside the randomised trial. Quality-adjusted life-years (QALYs) were derived from the European Quality of Life-5 Dimensions (EQ-5D) and the Short Form questionnaire-6 Dimensions (SF-6D). The intention-to-treat analyses were reported as cost per QALY gained. Uncertainty was explored by conducting both deterministic and probabilistic sensitivity analyses. RESULTS: The MMAS total scores improved significantly in both groups at all time points, but were significantly greater for the LNG-IUS than for usual treatment [mean difference over 2 years was 13.4 points, 95% confidence interval (CI) 9.9 to 16.9 points; p < 0.001]. However, this difference between groups was reduced and no longer significant by 5 years (mean difference in scores 3.9 points, 95% CI -0.6 to 8.3 points; p = 0.09). By 5 years, only 47% of women had a LNG-IUS in place and 15% were still taking usual medical treatment. Five-year surgery rates were low, at 20%, and were similar, irrespective of initial treatments. There were no significant differences in serious adverse events between groups. Using the EQ-5D, at 2 years, the relative cost-effectiveness of the LNG-IUS compared with usual medical treatment was £1600 per QALY, which by 5 years was reduced to £114 per QALY. Using the SF-6D, usual medical treatment dominates the LNG-IUS. The qualitative findings show that women's experiences and expectations of medical treatments for HMB vary considerably and change over time. Women had high expectations of a prompt effect from medical treatments. CONCLUSIONS: The LNG-IUS, compared with usual medical therapies, resulted in greater improvement over 2 years in women's assessments of the effect of HMB on their daily routine, including work, social and family life, and psychological and physical well-being. At 5 years, the differences were no longer significant. A similar low proportion of women required surgical intervention in both groups. The LNG-IUS is cost-effective in both the short and medium term, using the method generally recommended by the National Institute for Health and Care Excellence. Using the alternative measures to value QoL will have a considerable impact on cost-effectiveness decisions. It will be important to explore the clinical and health-care trajectories of the ECLIPSE (clinical effectiveness and cost-effectiveness of levonorgestrel-releasing intrauterine system in primary care against standard treatment for menorrhagia) trial participants to 10 years, by which time half of the cohort will have reached menopause. TRIAL REGISTRATION: Current Controlled Trials ISRCTN86566246. FUNDING: This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 19, No. 88. See the NIHR Journals Library website for further project information.