882 resultados para common factors
Resumo:
Constructed wetlands are a common structural treatment measure employed to remove stormwater pollutants and forms an important part of the Water Sensitive Urban Design (WSUD) treatment suite. In a constructed wetland, a range of processes such as settling, filtration, adsorption, and biological uptake play a role in stormwater treatment. Occurrence and effectiveness of these processes are variable and influenced by hydraulic, chemical and biological factors. The influence of hydraulic factors on treatment processes are of particular concern. This paper presents outcomes of a comprehensive study undertaken to define the treatment performance of a constructed wetland highlighting the influence of hydraulic factors. The study included field monitoring of a well established constructed wetland for quantity and quality factors, development of a conceptual hydraulic model to simulate water movement within the wetland and multivariate analysis of quantity and quality data to investigate correlations and to define linkages between treatment performance and influential hydraulic factors. Total Suspended Solids (TSS), Total Nitrogen (TN) and Total Phosphorus (TP) concentrations formed the primary pollutant parameters investigated in the data analysis. The outcomes of the analysis revealed significant reduction in event mean concentrations of all three pollutants species. Treatment performance of the wetland was significantly different for storm events above and below the prescribed design event. For events below design event, TSS and TN load reduction was comparatively high and strongly influenced by high retention time. For events above design event, TP load reduction was comparatively high and was found to be influenced by the characteristics of TP wash-off from catchment surfaces.
Resumo:
Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.
Resumo:
Given the importance of water for rice production, this study examines the factors affecting the technical efficiency (TE) of irrigated rice farmers in village irrigation systems (VIS) in Sri Lanka. Primary data were collected from 460 rice farmers in the Kurunagala District, Sri Lanka, to estimate a stochastic translog production frontier for rice production. The mean TE of rice farming in village irrigation was found to be 0.72, although 63% of rice farmers exceeded this average. The most influential factors of TE are membership of Farmer Organisations (FOs) and the participatory rate in collective actions organised by FOs. The results suggest that enhancement of co-operative arrangements of farmers by strengthening the membership of FOs is considered important for increasing TE in rice farming in VIS.
Resumo:
There is a growing interest in the use of megavoltage cone-beam computed tomography (MV CBCT) data for radiotherapy treatment planning. To calculate accurate dose distributions, knowledge of the electron density (ED) of the tissues being irradiated is required. In the case of MV CBCT, it is necessary to determine a calibration-relating CT number to ED, utilizing the photon beam produced for MV CBCT. A number of different parameters can affect this calibration. This study was undertaken on the Siemens MV CBCT system, MVision, to evaluate the effect of the following parameters on the reconstructed CT pixel value to ED calibration: the number of monitor units (MUs) used (5, 8, 15 and 60 MUs), the image reconstruction filter (head and neck, and pelvis), reconstruction matrix size (256 by 256 and 512 by 512), and the addition of extra solid water surrounding the ED phantom. A Gammex electron density CT phantom containing EDs from 0.292 to 1.707 was imaged under each of these conditions. The linear relationship between MV CBCT pixel value and ED was demonstrated for all MU settings and over the range of EDs. Changes in MU number did not dramatically alter the MV CBCT ED calibration. The use of different reconstruction filters was found to affect the MV CBCT ED calibration, as was the addition of solid water surrounding the phantom. Dose distributions from treatment plans calculated with simulated image data from a 15 MU head and neck reconstruction filter MV CBCT image and a MV CBCT ED calibration curve from the image data parameters and a 15 MU pelvis reconstruction filter showed small and clinically insignificant differences. Thus, the use of a single MV CBCT ED calibration curve is unlikely to result in any clinical differences. However, to ensure minimal uncertainties in dose reporting, MV CBCT ED calibration measurements could be carried out using parameter-specific calibration measurements.
Resumo:
In the elderly, the risks for protein-energy malnutrition from older age, dementia, depression and living alone have been well-documented. Other risk factors including anorexia, gastrointestinal dysfunction, loss of olfactory and taste senses and early satiety have also been suggested to contribute to poor nutritional status. In Parkinson’s disease (PD), it has been suggested that the disease symptoms may predispose people with PD to malnutrition. However, the risks for malnutrition in this population are not well-understood. The current study’s aim was to determine malnutrition risk factors in community-dwelling adults with PD. Nutritional status was assessed using the Patient-Generated Subjective Global Assessment (PG-SGA). Data about age, time since diagnosis, medications and living situation were collected. Levodopa equivalent doses (LDED) and LDED per kg body weight (mg/kg) were calculated. Depression and anxiety were measured using the Beck’s Depression Inventory (BDI) and Spielberger Trait Anxiety questionnaire, respectively. Cognitive function was assessed using the Addenbrooke’s Cognitive Examination (ACE-R). Non-motor symptoms were assessed using the Scales for Outcomes in Parkinson's disease-Autonomic (SCOPA-AUT) and Modified Constipation Assessment Scale (MCAS). A total of 125 community-dwelling people with PD were included, average age of 70.2±9.3(35-92) years and average time since diagnosis of 7.3±5.9(0–31) years. Average body mass index (BMI) was 26.0±5.5kg/m2. Of these, 15% (n=19) were malnourished (SGA-B). Multivariate logistic regression analysis revealed that older age (OR=1.16, CI=1.02-1.31), more depressive symptoms (OR=1.26, CI=1.07-1.48), lower levels of anxiety (OR=.90, CI=.82-.99), and higher LDED per kg body weight (OR=1.57, CI=1.14-2.15) significantly increased malnutrition risk. Cognitive function, living situation, number of prescription medications, LDED, years since diagnosis and the severity of non-motor symptoms did not significantly influence malnutrition risk. Malnutrition results in poorer health outcomes. Proactively addressing the risk factors can help prevent declines in nutritional status. In the current study, older people with PD with depression and greater amounts of levodopa per body weight were at increased malnutrition risk.
Resumo:
Interaction design is about finding better ways for people to interact with each other through communication technologies. Interaction design involves understanding how people learn, work and play so that we can engineer better, more valuable technologies that are more appropriate to the contexts of their lives. As an academic discipline, interaction design is about the people-research that underpins these technologies. As a comparative tool for business it is about creating innovations that have market pull rather than a technology push. Many examples can be found which demonstrate the value of interaction design within both industry and academia, however finding the common ground between this spectrum of activity is often difficult. Differences in language, approach and outcomes often lead to researchers from either side of the spectrum complaining of an uncommon ground, which often results in a lack of collaboration within such projects. However, as demonstrated through this case study, rather than focussing on finding a common ground to assist in better collaboration between industry and academia, celebrating the uniqueness of each approach whilst bridging them with a common language can lead to new knowledge and commercial innovation. This case study will focus on the research and development phase of a Diversionary Therapy Platform, a collaboration between the Australasian CRC for Interaction Design and The Royal Children's Hospital (Brisbane, Australia). This collaborative effort has led to the formation of a new commercial venture, Diversionary Therapy Pty Ltd, which aims to bring to the market the research outcomes from the project. The case study will outline the collaborative research and development process undertaken between the many stakeholders and reflect on the challenges identified within this process. A key finding from this collaboration was allowing for the co-existence of the common and uncommon ground throughout the project. This concept will be discussed further throughout this paper.
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While the negative influence of passengers on driving is usually studied, young passengers may protect against young drivers’ crash involvement by speaking out and trying to stop unsafe driving behavior. This study sought to examine psychosocial constructs of young passengers who are likely to intervene in their friends’ risky driving. Method: University students aged 17 to 25 years who were single (n = 123) or in a romantic relationship (n = 130) completed an online survey measuring protective factors. Results: The combination of individual, friend and (for participants in a relationship) romantic partner protective factors predicted self-reported passenger intervening intentions. Impact on Industry: Since peer passengers often increase young drivers’ crash risk, research on passenger intervening has significant implications for road safety strategies. The findings provide support for the operationalization of protective factors in strategies that target passenger intervening behavior.
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With the increasing diversity of students attending university, there is a growing interest in the factors predicting academic performance. This study is a prospective investigation of the academic, psychosocial, cognitive, and demographic predictors of academic performance of first year Australian university students. Questionnaires were distributed to 197 first year students 4 to 8 weeks prior to the end of semester exams and overall grade point averages were collected at semester completion. Previous academic performance was identified as the most significant predictor of university performance. Integration into university, self efficacy, and employment responsibilities were also predictive of university grades. Identifying the factors that influence academic performance can improve the targeting of interventions and support services for students at risk of academic problems.
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Ecstasy use may result in lowered mood, anxiety or aggression in the days following use. Yet, few studies have investigated what factors increase the risk of experiencing such symptoms. Ecstasy users (at least once in the last 12 months) who subsequently took ecstasy (n=35) over the next week, were compared on measures of mood, sleep, stress and drug use, with those who abstained (n=21) that week. Measures were administered the week prior to ecstasy use and 1 and 3 days following use, or the equivalent day for abstainers. Mood symptoms were assessed using the Kessler-10 self-report psychological distress scale, a subjective mood rating (1-10), and the depression, anxiety and hostility items of the clinician-rated Brief Psychiatric Rating Scale. Timeline followback methods were used to collect information on drug use and life stress in the past month. Self-reported sleep quality was also assessed. Ecstasy use was not associated with subacute depressive, anxiety or aggressive symptoms. Rather, lowered mood and increased psychological distress were associated with self-reported hours and quality of sleep obtained during the 3-day follow up. These findings highlight the importance of considering sleep disruption in understanding the short-term mood effects of ecstasy use.
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We test the broken windows theory using a field experiment in a shared area of an academic workplace(the department common room). More specifically, we explore academics’ and postgraduate students’ behavior under an order condition (a clean environment) and a disorder condition (a messy environment). We find strong evidence that signs of disorderly behavior trigger littering: In 59% of the cases, subjects litter in the disorder treatment as compared to 18% in the order condition. These results remain robust in a multivariate analysis even when controlling for a large set of factors not directly examined by previous studies. Overall, when academic staff and postgraduate students observe that others have violated the social norm of keeping the common room clean, all else being equal, the probability of littering increases by around 40%.
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The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.
Resumo:
Over the past decade the discipline of nursing has been reviewing its practice, especially in relation to specialty areas. There has been an appreciation by nursing leaders that specialisation brings with it concerns related to a disuniting effect on the discipline and a fragmentation of nursing's traditional generalist practice. Accompanying these concerns is a debate over what is a specialty and how to define a specialist. This qualitative study drew upon a constructivist methodology, to explore how nurses, working in specialty areas, define and give meaning to their practice. Three groups of nurses (n=20) from the specialty of critical care were interviewed using a focus group technique. The data were analysed to build constructions of specialty practice. A distinct and qualitative difference was recognised in the practice behaviours of nurses working in the specialty area. The qualitatively different practice behaviours have been identified as ‘nursing-in-a-specialty’ and ‘specialist nurse’. Two constructions emerged to differentiate the skill behaviours, these were ‘practice’ and ‘knowledge’. The specialist nurse practices were based on two distinct types of practice, that of ‘discretion’ and ‘incorporation’. ‘Knowledge’ was constructed as a synthesis of propositional and practice knowledge.
Resumo:
First year Property Economics students enrolled in the Bachelor of Urban Development at QUT are required to undertake a number of compulsory subjects, alongside students undertaking studies in other disciplines. One such common unit is ‘Stewardship of Land’, an interdisciplinary unit that introduces students to the characteristics of land and land tenure with a focus on land use and property rights. It covers a range of issues including: native title, land contamination, heritage values, alternative uses, the property development process, impact of environmental and social factors, and the management of land, both urban and regional. Teaching such a diverse content to a diverse audience has in previous years proved difficult, from the perspectives of relevance, engagement and content overload. In 2011 a project was undertake to redevelop this unit to reflect ‘threshold concepts’, concepts that are “transformative, probably irreversible, integrative, often troublesome and probably bounded” (Meyer & Land, 2003) . This project involved the development of a new set of underlying concepts students should draw from the unit, application of these to the unit curriculum, and a survey of the student response to these changes. This paper reports on the threshold concepts developed for this unit, the changes this made to the unit curriculum, and a preliminary report on survey responses. Recommendations for other educators seeking to incorporate threshold concepts into their curricula are provided.
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Risk factors for repeat drink driving, an important road safety issue, are well known, but estimates of Australian recidivism rates by risk factors, apart from a recent NSW study, are not. Driving records of a cohort of Queensland drink drivers matched by age, region, BAC level and prior offence to participants in a drink driving rehabilitation program were used to estimate sex-specific two- and five-year re-offence rates overall and by these factors. Estimates of the proportion of Queensland drink drivers with a prior DD offence in 2004 were used to standardise rates to the Queensland drink driving population. Rates were higher in remote areas, as were rates in males, young drivers, drivers with high BAC levels and in drivers with one and especially with at least two prior DD convictions. Five-year rates for Queensland were estimated as 21.8% in males and 16.4% in females, appreciably higher than in NSW.
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This chapter is devoted to the issue of non-fiduciary common law obligations of good faith, as they may arise in the performance and enforcement of joint ventures. In recent times a rush of commercial contractual claims involving good faith has signified the need for a separate chapter examining this issue. Although most of these decisions have arisen in commercial contexts other than joint ventures, the decisions, nevertheless, warrant careful consideration to the extent that they cast light on the likely contours of the common law good faith obligation as it may apply in the joint venture context.