A Study of the Microwave Carbothermic Reduction of Chromite Ore

Microwave reduction testing using activated charcoal as a reducing agent was performed on a sample of Black Thor chromite ore from the Ring of Fire deposit in Northern Ontario. First, a thermodynamic model was constructed for the system. Activity coefficients for several species were found in the literature. The model predicted chromium grades of 61.60% and recoveries of 93.43% for a 15% carbon addition. Next, reduction testing on the chromite ore was performed. Tests were performed at increasing power levels and reduction times. Testing atmospheres used were air, argon, and vacuum. The reduced product had maximum grades of 72.89% and recoveries of 80.37%. These maximum values were obtained in the same test where an argon atmosphere was used, with a carbon addition of 15%, optimal power level of 1200 W (actual 1171 W), and a time of 400 seconds. During this test, 17.53% of the initial mass was lost as gas, a carbon grade of 1.95% was found for the sintered core product. Additional work is recommended to try and purify the sintered core product as well as reduce more of the initial sample. Changing reagent schemes or a two step reduction / separation process could be implemented.

‘‘Model age-based” and ‘‘copy when uncertain” biases in children’s social learning of a novel task

Theoretical models of social learning predict that individuals can benefit from using strategies that specify when and whom to copy. Here the interaction of two social learning strategies, model age-based biased copying and copy when uncertain, was investigated. Uncertainty was created via a systematic manipulation of demonstration efficacy (completeness) and efficiency (causal relevance of some actions). The participants, 4- to 6-year-old children (N = 140), viewed both an adult model and a child model, each of whom used a different tool on a novel task. They did so in a complete condition, a near-complete condition, a partial demonstration condition, or a no-demonstration condition. Half of the demonstrations in each condition incorporated causally irrelevant actions by the models. Social transmission was assessed by first responses but also through children’s continued fidelity, the hallmark of social traditions. Results revealed a bias to copy the child model both on first response and in continued interactions. Demonstration efficacy and efficiency did not affect choice of model at first response but did influence solution exploration across trials, with demonstrations containing causally irrelevant actions decreasing exploration of alternative methods. These results imply that uncertain environments can result in canalized social learning from specific classes of mode

Comparisons of an aerosol transport model with a 4-year analysis of summer aerosol optical depth retrievals over the Canadian Arctic

Abstract : This is a study concerning comparisons between the Dubovik Aerosol optical depth (AOD) retrievals from AEROCAN (ARONET) stations and AOD estimates from simulations provided by a chemical transport model (GEOS-Chem : Goddard Earth Observing System Chemistry). The AOD products associated with the Dubovik product are divided into total, fine and coarse mode components. The retrieval period is from January 2009 to January 2013 for 5 Arctic stations (Barrow, Alaska; Resolute Bay, Nunavut; 0PAL and PEARL (Eureka), Nunavut; and Thule, Greenland). We also employed AOD retrievals from 10 other mid-latitude Canadian stations for comparisons with the Arctic stations. The results of our investigation were submitted to Atmosphere-Ocean. To briefly summarize those results, the model generally but not always tended to underestimate the (monthly) averaged AOD and its components. We found that the subdivision into fine and coarse mode components could provide unique signatures of particular events (Asian dust) and that the means of characterizing the statistics (log-normal frequency distributions versus normal distributions) was an attribute that was common to both the retrievals and the model.

Evolutionary algorithms for the modeling of bioreactors

This work aims to study the application of Genetic Algorithms in anaerobic digestion modeling, in particular when using dynamical models. Along the work, different types of bioreactors are shown, such as batch, semi-batch and continuous, as well as their mathematical modeling. The work intendeds to estimate the parameter values of two biological reaction model. For that, simulated results, where only one output variable, the produced biogas, is known, are fitted to the model results. For this reason, the problems associated with reverse optimization are studied, using some graphics that provide clues to the sensitivity and identifiability associated with the problem. Particular solutions obtained by the identifiability analysis using GENSSI and DAISY softwares are also presented. Finally, the optimization is performed using genetic algorithms. During this optimization the need to improve the convergence of genetic algorithms was felt. This need has led to the development of an adaptation of the genetic algorithms, which we called Neighbored Genetic Algorithms (NGA1 and NGA2). In order to understand if this new approach overcomes the Basic Genetic Algorithms (BGA) and achieves the proposed goals, a study of 100 full optimization runs for each situation was further developed. Results show that NGA1 and NGA2 are statistically better than BGA. However, because it was not possible to obtain consistent results, the Nealder-Mead method was used, where the initial guesses were the estimated results from GA; Algoritmos Evolucionários para a Modelação de Bioreactores Resumo: Neste trabalho procura-se estudar os algoritmos genéticos com aplicação na modelação da digestão anaeróbia e, em particular, quando se utilizam modelos dinâmicos. Ao longo do mesmo, são apresentados diferentes tipos de bioreactores, como os batch, semi-batch e contínuos, bem como a modelação matemática dos mesmos. Neste trabalho procurou-se estimar o valor dos parâmetros que constam num modelo de digestão anaeróbia para o ajustar a uma situação simulada onde apenas se conhece uma variável de output, o biogas produzido. São ainda estudados os problemas associados à optimização inversa com recurso a alguns gráficos que fornecem pistas sobre a sensibilidade e identifiacabilidade associadas ao problema da modelação da digestão anaeróbia. São ainda apresentadas soluções particulares de idenficabilidade obtidas através dos softwares GENSSI e DAISY. Finalmente é realizada a optimização do modelo com recurso aos algoritmos genéticos. No decorrer dessa optimização sentiu-se a necessidade de melhorar a convergência e, portanto, desenvolveu-se ainda uma adaptação dos algoritmos genéticos a que se deu o nome de Neighboured Genetic Algorithms (NGA1 e NGA2). No sentido de se compreender se as adaptações permitiam superar os algoritmos genéticos básicos e atingir as metas propostas, foi ainda desenvolvido um estudo em que o processo de optimização foi realizado 100 vezes para cada um dos métodos, o que permitiu concluir, estatisticamente, que os BGA foram superados pelos NGA1 e NGA2. Ainda assim, porque não foi possivel obter consistência nos resultados, foi usado o método de Nealder-Mead utilizado como estimativa inicial os resultados obtidos pelos algoritmos genéticos.

Tracking people in 3D using position, size and shape

This paper presents a prototype tracking system for tracking people in enclosed indoor environments where there is a high rate of occlusions. The system uses a stereo camera for acquisition, and is capable of disambiguating occlusions using a combination of depth map analysis, a two step ellipse fitting people detection process, the use of motion models and Kalman filters and a novel fit metric, based on computationally simple object statistics. Testing shows that our fit metric outperforms commonly used position based metrics and histogram based metrics, resulting in more accurate tracking of people.

Final report : enabling team collaboration with pervasive and mobile computing

This is the final report of research project 2002-057-C: Enabling Team Collaboration with Pervasive and Mobile Computing. The research project was carried out by the Australian Cooperative Research Centre for Construction Innovation and has two streams that consider the use of pervasive computing technologies in two different contexts. The first context was the on-site deployment of mobile computing devices, where as the second context was the use and development of intelligent rooms based on sensed environments and new human-computer interfaces (HCI) for collaboration in the design office. The two streams present a model of team collaboration that relies on continues communication to people and information to reduce information leakage. This report consists of five sections: (1) Introduction; (2) Research Project Background; (3) Project Implementation; (4) Case Studies and Outcomes; and (5) Conclusion and Recommendation. Introduction in Section 1 presents a brief description of the research project including general research objectives and structure. Section 2 introduces the background of the research and detailed information regarding project participants, objectives and significance, and also research methodology. Review of all research activities such as literature review and case studies are summarised in Project Implementation in Section 3. Following this, in Section 4 the report then focuses on analysing the case studies and presents their outcomes. Conclusion and recommendation of the research project are summarised in Section 5. Other information to support the content of the report such as research project schedule is provided in Appendices. The purpose of the final project report is to provide industry partners with detailed information on the project activities and methodology such as the implementation of pervasive computing technologies in the real contexts. The report summarises the outcomes of the case studies and provides necessary recommendation to industry partners of using new technologies to support better project collaboration.

Mid-level concept learning with visual contextual ontologies and probabilistic inference for image annotation

To date, automatic recognition of semantic information such as salient objects and mid-level concepts from images is a challenging task. Since real-world objects tend to exist in a context within their environment, the computer vision researchers have increasingly incorporated contextual information for improving object recognition. In this paper, we present a method to build a visual contextual ontology from salient objects descriptions for image annotation. The ontologies include not only partOf/kindOf relations, but also spatial and co-occurrence relations. A two-step image annotation algorithm is also proposed based on ontology relations and probabilistic inference. Different from most of the existing work, we specially exploit how to combine representation of ontology, contextual knowledge and probabilistic inference. The experiments show that image annotation results are improved in the LabelMe dataset.

Skin preparation with alcohol versus alcohol followed by any antiseptic for preventing bacteraemia or contamination of blood for transfusion (Review)

Background: Blood for transfusion may become contaminated at any point between collection and transfusion and may result in bacteraemia (the presence of bacteria in the blood),severe illness or even death for the blood recipient. Donor arm skin is one potential source of blood contamination, so it is usual to cleanse the skin with an antiseptic before blood donation. One-step and two-step alcohol based antiseptic regimens are both commonly advocated but there is uncertainty as to which is most effective.----- Objectives: To assess the effects of cleansing the skin of blood donors with alcohol in a one-step compared with alcohol in a two-step procedure to prevent contamination of collected blood or bacteraemia in the recipient.----- Search strategy: We searched the Cochrane Wounds Group Specialised Register (March 10 2009); The Cochrane Central Register of Controlled Trials(CENTRAL) The Cochrane Library 2009, Issue 1; Ovid MEDLINE - (1950 to February Week 4 2009); Ovid EMBASE - (1980 to 2009 Week 9); and EBSCO CINAHL - (1982 to February Week 4 2009). We also searched the reference lists of key papers.----- Selection criteria: All randomised trials (RCTs) comparing alcohol based donor skin cleansing in a one-step versus a two-step process that includes alcohol and any other antiseptic for pre-venepuncture skin cleansing were considered. Quasi randomised trials were to have been considered in the absence of RCTs.----- Data collection and analysis: Two review authors independently assessed studies for inclusion.----- Main results: No studies (RCTs or quasi RCTs) met the inclusion criteria. Authors’ conclusions We did not identify any eligible studies for inclusion in this review. It is therefore unclear whether a two-step, alcohol followed by antiseptic skin cleansing process prior to blood donation confers any reduction in the risk of blood contamination or bacteraemia in blood recipients, or conversely whether a one-step process increases risk above that associated with a two-step process.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

Analysis of authenticated encryption stream ciphers

Authenticated Encryption (AE) is the cryptographic process of providing simultaneous confidentiality and integrity protection to messages. AE is potentially more efficient than applying a two-step process of providing confidentiality for a message by encrypting the message and in a separate pass, providing integrity protection by generating a Message Authentication Code (MAC) tag. This paper presents results on the analysis of three AE stream ciphers submitted to the recently completed eSTREAM competition. We classify the ciphers based on the methods the ciphers use to provide authenticated encryption and discuss possible methods for mounting attacks on these ciphers.

Resilience in chronic disease : the relationships among risk factors, protective factors, adaptive outcomes, and the level of resilience in adults with diabetes

Background: There are innumerable diabetes studies that have investigated associations between risk factors, protective factors, and health outcomes; however, these individual predictors are part of a complex network of interacting forces. Moreover, there is little awareness about resilience or its importance in chronic disease in adulthood, especially diabetes. Thus, this is the first study to: (1) extensively investigate the relationships among a host of predictors and multiple adaptive outcomes; and (2) conceptualise a resilience model among people with diabetes. Methods: This cross-sectional study was divided into two research studies. Study One was to translate two diabetes-specific instruments (Problem Areas In Diabetes, PAID; Diabetes Coping Measure, DCM) into a Chinese version and to examine their psychometric properties for use in Study Two in a convenience sample of 205 outpatients with type 2 diabetes. In Study Two, an integrated theoretical model is developed and evaluated using the structural equation modelling (SEM) technique. A self-administered questionnaire was completed by 345 people with type 2 diabetes from the endocrine outpatient departments of three hospitals in Taiwan. Results: Confirmatory factor analyses confirmed a one-factor structure of the PAID-C which was similar to the original version of the PAID. Strong content validity of the PAID-C was demonstrated. The PAID-C was associated with HbA1c and diabetes self-care behaviours, confirming satisfactory criterion validity. There was a moderate relationship between the PAID-C and the Perceived Stress Scale, supporting satisfactory convergent validity. The PAID-C also demonstrated satisfactory stability and high internal consistency. A four-factor structure and strong content validity of the DCM-C was confirmed. Criterion validity demonstrated that the DCM-C was significantly associated with HbA1c and diabetes self-care behaviours. There was a statistical correlation between the DCM-C and the Revised Ways of Coping Checklist, suggesting satisfactory convergent validity. Test-retest reliability demonstrated satisfactory stability of the DCM-C. The total scale of the DCM-C showed adequate internal consistency. Age, duration of diabetes, diabetes symptoms, diabetes distress, physical activity, coping strategies, and social support were the most consistent factors associated with adaptive outcomes in adults with diabetes. Resilience was positively associated with coping strategies, social support, health-related quality of life, and diabetes self-care behaviours. Results of the structural equation modelling revealed protective factors had a significant direct effect on adaptive outcomes; however, the construct of risk factors was not significantly related to adaptive outcomes. Moreover, resilience can moderate the relationships among protective factors and adaptive outcomes, but there were no interaction effects of risk factors and resilience on adaptive outcomes. Conclusion: This study contributes to an understanding of how risk factors and protective factors work together to influence adaptive outcomes in blood sugar control, health-related quality of life, and diabetes self-care behaviours. Additionally, resilience is a positive personality characteristic and may be importantly involved in the adjustment process among people living with type 2 diabetes.

A ∑GIi/D/1/∞ queue with heterogeneous input/output slot times

In this paper, we present a ∑GIi/D/1/∞ queue with heterogeneous input/output slot times. This queueing model can be regarded as an extension of the ordinary GI/D/1/∞ model. For this ∑GIi/D/1/∞ queue, we assume that several input streams arrive at the system according to different slot times. In other words, there are different slot times for different input/output processes in the queueing model. The queueing model can therefore be used for an ATM multiplexer with heterogeneous input/output link capacities. Several cases of the queueing model are discussed to reflect different relationships among the input/output link capacities of an ATM multiplexer. In the queueing analysis, two approaches: the Markov model and the probability generating function technique, are adopted to develop the queue length distributions observed at different epochs. This model is particularly useful in the performance analysis of ATM multiplexers with heterogeneous input/output link capacities.

Lateral shearing interferometry for analysis of tear film surface kinetics

Purpose: To date, there have been no measuring techniques available that could clearly identify all phases of tear film surface kinetics in one interblink interval. ----- ----- Methods: Using a series of cases, we show that lateral shearing interferometry equipped with a set of robust parameter estimation techniques is able to characterize up to five different phases of tear film surface kinetics that include: (i) initial fast tear film build-up phase, (ii) further slower tear film build-up phase, (iii) tear film stability, (iv) tear film thinning, and (v), after a detected break-up, subsequent tear film deterioration. ----- ----- Results: Several representative examples are given for estimating tear film surface kinetics in measurements in which the subjects were asked to blink and keep their eyes open as long as they could. ----- ----- Conclusions: Lateral shearing interferometry is a noninvasive technique that provides means for temporal characterization of tear film surface kinetics and the opportunity for the analysis of the two-step tear film build-up process.

The biological application of cobalt

This review collects and summarises the biological applications of the element cobalt. Small amounts of the ferromagnetic metal can be found in rock, soil, plants and animals, but is mainly obtained as a by-product of nickel and copper mining, and is separated from the ores (mainly cobaltite, erythrite, glaucodot and skutterudite) using a variety of methods. Compounds of cobalt include several oxides, including: green cobalt(II) (CoO), blue cobalt(II,III) (Co3O4), and black cobalt(III) (Co2O3); four halides including pink cobalt(II) fluoride (CoF2), blue cobalt(II) chloride (CoCl2), green cobalt(II) bromide (CoBr2), and blue-black cobalt(II) iodide (CoI2). The main application of cobalt is in its metal form in cobalt-based super alloys, though other uses include lithium cobalt oxide batteries, chemical reaction catalyst, pigments and colouring, and radioisotopes in medicine. It is known to mimic hypoxia on the cellular level by stabilizing the α subunit of hypoxia inducing factor (HIF), when chemically applied as cobalt chloride (CoCl2). This is seen in many biological research applications, where it has shown to promote angiogenesis, erythropoiesis and anaerobic metabolism through the transcriptional activation of genes such as vascular endothelial growth factor (VEGF) and erythropoietin (EPO), contributing significantly to the pathophysiology of major categories of disease, such as myocardial, renal and cerebral ischaemia, high altitude related maladies and bone defects. As a necessary constituent for the formation of vitamin B12, it is essential to all animals, including humans, however excessive exposure can lead to tissue and cellular toxicity. Cobalt has been shown to provide promising potential in clinical applications, however further studies are necessary to clarify its role in hypoxia-responsive genes and the applications of cobalt-chloride treated tissues.