Laminar and turbulent natural convection in rectangular cavities

A computer program has been developed for the prediction of buoyancy-driven laminar and turbulent flow in rectangular air-filled two-dimensional cavities with differentially heated side walls. Laminar flow predictions for a square cavity and Rayleigh numbers from Ra = 10^3 up to the onset of unsteady flow have been obtained. Accurate solutions for Ra = 5 x 10^6, 10^7, 5 x 10^7 and 10^8 are presented and an estimate for the critical Rayleigh number at which the steady laminar flow becomes unsteady is given for this geometry. Numerical predictions of turbulent flow have been obtained for RaH~0(10^9 -10^11 ) and compared with existing experimental data. A previously developed second moment closure model (Behnia et al. 1987) has been used to model the turbulence. Results indicate that a second moment closure model is capable of predicting the observed flow features.

Laminar and turbulent natural convection in rectangular cavities

"This chapter discusses laminar and turbulent natural convection in rectangular cavities. Natural convection in rectangular two-dimensional cavities has become a standard problem in numerical heat transfer because of its relevance in understanding a number of problems in engineering. Current research identified a number of difficulties with regard to the numerical methods and the turbulence modeling for this class of flows. Obtaining numerical predictions at high Rayleigh numbers proved computationally expensive such that results beyond Ra ∼ 1014 are rarely reported. The chapter discusses a study in which it was found that turbulent computations in square cavities can't be extended beyond Ra ∼ O (1012) despite having developed a code that proved very efficient for the high Ra laminar regime. As the Rayleigh number increased, thin boundary layers began to form next to the vertical walls, and the central region became progressively more stagnant and highly stratified. Results obtained for the high Ra laminar regime were in good agreement with existing studies. Turbulence computations, although of a preliminary nature, indicated that a second moment closure model was capable of predicting the experimentally observed flow features."--Publisher Summary

Meltdown - a tool for classification and analysis of DSF data

An application that translates raw thermal melt curve data into more easily assimilated knowledge is described. This program, called ‘Meltdown’, performs a number of data remediation steps before classifying melt curves and estimating melting temperatures. The final output is a report that summarizes the results of a differential scanning fluorimetry experiment. Meltdown uses a Bayesian classification scheme, enabling reproducible identification of various trends commonly found in DSF datasets. The goal of Meltdown is not to replace human analysis of the raw data, but to provide a sensible interpretation of the data to make this useful experimental technique accessible to naïve users, as well as providing a starting point for detailed analyses by more experienced users.

Social NUI: Social perspectives in natural user interfaces

Natural User Interfaces (NUI) offer rich ways for interacting with the digital world that make innovative use of existing human capabilities. They include and often combine different input modalities such as voice, gesture, eye gaze, body interactions, touch and touchless interactions. However much of the focus of NUI research and development has been on enhancing the experience of individuals interacting with technology. Effective NUIs must also acknowledge our innately social characteristics, and support how we communicate with each other, play together, learn together and collaboratively work together. This workshop concerns the social aspects of NUI. The workshop seeks to better understand the social uses and applications of these new NUI technologies -- how we design these technologies for new social practices and how we understand the use of these technologies in key social contexts.

Natural variation and Biogeography of the melon fruit fly, Zeugodacus cucurbitae (Diptera : Tephritidae), in Southeast-Asia and the west-pacific

This thesis used multidisciplinary approaches which greatly enhance our understanding of population structure and can be particularly powerful tools for resolving variation of melon fly over geographic and temporal scales, and for determining invasive pathways. The results from this thesis reinforce the value of integrating multiple data sets to better understand and resolve natural variation within an important pest to determine whether there are cryptic species, discrete lineages or host races, and to identify dispersal pathways in an invasive pest. These results are instructive for regional biosecurity, trade and quarantine, and provide important background for future area-wide management programmes. The integrative methodology adopted in this thesis is applicable to a variety of other insect pests.

Predictive technology and natural hazards: Risk for Australian planning authorities?

Purpose The object of this paper is to examine whether the improvements in technology that enhance community understanding of the frequency and severity of natural hazards also increased the risk of potential liability of planning authorities in negligence. In Australia, the National Strategy imposes a resilience based approach to disaster management and stresses that responsible land use planning can reduce or prevent the impact of natural hazards upon communities. Design/methodology/approach This paper analyses how the principles of negligence allocate responsibility for loss suffered by a landowner in a hazard prone area between the landowner and local government. Findings The analysis in this paper concludes that despite being able to establish a causal link between the loss suffered by a landowner and the approval of a local authority to build in a hazard prone area, it would be in the rarest of circumstances a negligence action may be proven. Research limitations/implications The focus of this paper is on planning policies and land development, not on the negligent provision of advice or information by the local authority. Practical implications This paper identifies the issues a landowner may face when seeking compensation from a local authority for loss suffered due to the occurrence of a natural hazard known or predicted to be possible in the area. Originality/value The paper establishes that as risk managers, local authorities must place reliance upon scientific modelling and predictive technology when determining planning processes in order to fulfil their responsibilities under the National Strategy and to limit any possible liability in negligence.

Risk assessment for airborne infectious diseases between natural ventilation and split-system air conditioner in a university classroom

Indoor air quality is a critical factor in the classroom due to high people concentration in a unique space. Indoor air pollutant might increase the chance of both long and short-term health problems among students and staff, reduce the productivity of teachers and degrade the student’s learning environment and comfort. Adequate air distribution strategies may reduce risk of infection in classroom. So, the purpose of air distribution systems in a classroom is not only to maximize conditions for thermal comfort, but also to remove indoor contaminants. Natural ventilation has the potential to play a significant role in achieving improvements in IAQ. The present study compares the risk of airborne infection between Natural Ventilation (opening windows and doors) and a Split-System Air Conditioner in a university classroom. The Wells-Riley model was used to predict the risk of indoor airborne transmission of infectious diseases such as influenza, measles and tuberculosis. For each case, the air exchange rate was measured using a CO2 tracer gas technique. It was found that opening windows and doors provided an air exchange rate of 2.3 air changes/hour (ACH), while with the Split System it was 0.6 ACH. The risk of airborne infection ranged between 4.24 to 30.86 % when using the Natural Ventilation and between 8.99 to 43.19% when using the Split System. The difference of airborne infection risk between the Split System and the Natural Ventilation ranged from 47 to 56%. Opening windows and doors maximize Natural Ventilation so that the risk of airborne contagion is much lower than with Split System.

Behaviour of natural zeolites used for the treatment of simulated and actual coal seam gas water

Coal seam gas operations produce significant quantities of associated water which often require demineralization. Ion exchange with natural zeolites has been proposed as a possible approach. The interaction of natural zeolites with solutions of sodium chloride and sodium bicarbonate in addition to coal seam gas water is not clear. Hence, we investigated ion exchange kinetics, equilibrium, and column behaviour of an Australian natural zeolite. Kinetic tests suggested that the pseudo first order equation best simulated the data. Intraparticle diffusion was part of the rate limiting step and more than one diffusion process controlled the overall rate of sodium ion uptake. Using a constant mass of zeolite and variable concentration of either sodium chloride or sodium bicarbonate resulted in a convex isotherm which was fitted by a Langmuir model. However, using a variable mass of zeolite and constant concentration of sodium ions revealed that the exchange of sodium ions with the zeolite surface sites was in fact unfavourable. Sodium ion exchange from bicarbonate solutions (10.3 g Na/kg zeolite) was preferred relative to exchange from sodium chloride solutions (6.4 g Na/kg zeolite). The formation of calcium carbonate species was proposed to explain the observed behaviour. Column studies of coal seam gas water showed that natural zeolite had limited ability to reduce the concentration of sodium ions (loading 2.1 g Na/kg zeolite) with rapid breakthrough observed. It was concluded that natural zeolites may not be suitable for the removal of cations from coal seam gas water without improvement of their physical properties.

Pheo-type: A diagnostic gene-expression assay for the classification of pheochromocytoma and paraganglioma

Context: Pheochromocytomas and paragangliomas (PPGLs) are heritable neoplasms that can be classified into gene-expression subtypes corresponding to their underlying specific genetic drivers. Objective: This study aimed to develop a diagnostic and research tool (Pheo-type) capable of classifying PPGL tumors into gene-expression subtypes that could be used to guide and interpret genetic testing, determine surveillance programs, and aid in elucidation of PPGL biology. Design: A compendium of published microarray data representing 205 PPGL tumors was used for the selection of subtype-specific genes that were then translated to the Nanostring gene-expression platform. A support vector machine was trained on the microarray dataset and then tested on an independent Nanostring dataset representing 38 familial and sporadic cases of PPGL of known genotype (RET, NF1, TMEM127, MAX, HRAS, VHL, and SDHx). Different classifier models involving between three and six subtypes were compared for their discrimination potential. Results: A gene set of 46 genes and six endogenous controls was selected representing six known PPGL subtypes; RTK1–3 (RET, NF1, TMEM127, and HRAS), MAX-like, VHL, and SDHx. Of 38 test cases, 34 (90%) were correctly predicted to six subtypes based on the known genotype to gene-expression subtype association. Removal of the RTK2 subtype from training, characterized by an admixture of tumor and normal adrenal cortex, improved the classification accuracy (35/38). Consolidation of RTK and pseudohypoxic PPGL subtypes to four- and then three-class architectures improved the classification accuracy for clinical application. Conclusions: The Pheo-type gene-expression assay is a reliable method for predicting PPGL genotype using routine diagnostic tumor samples.

Natural recovery from cannabis use in people with psychosis: A qualitative study

- Objective There is rapidly growing evidence of natural recovery from cannabis use in people with psychosis, but little is known about how it occurs. This qualitative study explores what factors influence the decision to cease cannabis use, maintain cessation, and prevent relapse. - Methods Ten people with early psychosis and lifetime cannabis misuse, who had been abstinent for at least a month, were recruited from public adult mental health services. These six men and four women participated in a semi-structured qualitative interview assessing reasons for addressing cannabis use, effective change strategies, lapse contexts, and methods used to regain control. Interpretative phenomenological analysis was used to identify themes in their responses. - Results Participants had a mean age of 23 years (SD = 3.7), started using cannabis at age 13.7 (SD = 1.6), began daily use at 17 (SD = 3.1), and had abstained from cannabis for 7.9 months (SD = 5.4). Awareness of the negative impact of substance use across multiple domains and the presence of social support for cannabis cessation were seen as vital to sustained success, as was utilization of a combination of coping strategies. The ability to address pressure from substance-using peers was commonly mentioned. - Conclusions Maximally effective treatment may need to focus on eliciting a range of benefits of cessation and control strategies and on maximizing both support for change and resistance to peer pressure. Further research might focus on comparing perceived effective strategies between individuals who obtain sustained cessation versus those who relapse.

Representations of the Natural World in Old English Poetry

Review of Representations of the Natural World in Old English Poetry, by Jennifer Neville (Cambridge UP, 1999).

A model of social work classification in health care

The introduction of casemix funding for Australian acute health care services has challenged Social Work to demonstrate clear reporting mechanisms, demonstrate effective practice and to justify interventions provided. The term 'casemix' is used to describe the mix and type of patients treated by a hospital or other health care services. There is wide acknowledgement that the procedure-based system of Diagnosis Related Groupings (DRGs) is grounded in a medical/illness perspective and is unsatisfactory in describing and predicting the activity of Social Work and other allied health professions in health care service delivery. The National Allied Health Casemix Committee was established in 1991 as the peak body to represent allied health professions in matters related to casemix classification. This Committee has pioneered a nationally consistent, patient-centred information system for allied health. This paper describes the classification systems and codes developed for Social Work, which includes a minimum data set, a classification hierarchy, the set of activity (input) codes and 'indicator for intervention' codes. The advantages and limitations of the system are also discussed.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.