970 resultados para Datasets
Resumo:
Cultivation and cropping of soils results in a decline in soil organic carbon and soil nitrogen, and can lead to reduced crop yields. The CENTURY model was used to simulate the effects of continuous cultivation and cereal cropping on total soil organic matter (C and N), carbon pools, nitrogen mineralisation, and crop yield from 6 locations in southern Queensland. The model was calibrated for each replicate from the original datasets, allowing comparisons for each replicate rather than site averages. The CENTURY model was able to satisfactorily predict the impact of long-term cultivation and cereal cropping on total organic carbon, but was less successful in simulating the different fractions and nitrogen mineralisation. The model firstly over-predicted the initial (pre-cropping) soil carbon and nitrogen concentration of the sites. To account for the unique shrinking and swelling characteristics of the Vertosol soils, the default annual decomposition rates of the slow and passive carbon pools were doubled, and then the model accurately predicted initial conditions. The ability of the model to predict carbon pool fractions varied, demonstrating the difficulty inherent in predicting the size of these conceptual pools. The strength of the model lies in the ability to closely predict the starting soil organic matter conditions, and the ability to predict the impact of clearing, cultivation, fertiliser application, and continuous cropping on total soil carbon and nitrogen.
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Deep convolutional network models have dominated recent work in human action recognition as well as image classification. However, these methods are often unduly influenced by the image background, learning and exploiting the presence of cues in typical computer vision datasets. For unbiased robotics applications, the degree of variation and novelty in action backgrounds is far greater than in computer vision datasets. To address this challenge, we propose an “action region proposal” method that, informed by optical flow, extracts image regions likely to contain actions for input into the network both during training and testing. In a range of experiments, we demonstrate that manually segmenting the background is not enough; but through active action region proposals during training and testing, state-of-the-art or better performance can be achieved on individual spatial and temporal video components. Finally, we show by focusing attention through action region proposals, we can further improve upon the existing state-of-the-art in spatio-temporally fused action recognition performance.
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Road traffic emissions are often considered the main source of ultrafine particles (UFP, diameter smaller than 100 nm) in urban environments. However, recent studies worldwide have shown that - in high-insolation urban regions at least - new particle formation events can also contribute to UFP. In order to quantify such events we systematically studied three cities located in predominantly sunny environments: Barcelona (Spain), Madrid (Spain) and Brisbane (Australia). Three long term datasets (1-2 years) of fine and ultrafine particle number size distributions (measured by SMPS, Scanning Mobility Particle Sizer) were analysed. Compared to total particle number concentrations, aerosol size distributions offer far more information on the type, origin and atmospheric evolution of the particles. By applying k-Means clustering analysis, we categorized the collected aerosol size distributions in three main categories: “Traffic” (prevailing 44-63% of the time), “Nucleation” (14-19%) and “Background pollution and Specific cases” (7-22%). Measurements from Rome (Italy) and Los Angeles (California) were also included to complement the study. The daily variation of the average UFP concentrations for a typical nucleation day at each site revealed a similar pattern for all cities, with three distinct particle bursts. A morning and an evening spike reflected traffic rush hours, whereas a third one at midday showed nucleation events. The photochemically nucleated particles burst lasted 1-4 hours, reaching sizes of 30-40 nm. On average, the occurrence of particle size spectra dominated by nucleation events was 16% of the time, showing the importance of this process as a source of UFP in urban environments exposed to high solar radiation. On average, nucleation events lasting for 2 hours or more occurred on 55% of the days, this extending to >4hrs in 28% of the days, demonstrating that atmospheric conditions in urban environments are not favourable to the growth of photochemically nucleated particles. In summary, although traffic remains the main source of UFP in urban areas, in developed countries with high insolation urban nucleation events are also a main source of UFP. If traffic-related particle concentrations are reduced in the future, nucleation events will likely increase in urban areas, due to the reduced urban condensation sinks.
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Land condition monitoring information is required for the strategic management of grazing land and for a better understanding of ecosystem processes. Yet, for policy makers and those land managers whose properties are situated within north-eastern Australia's vast Great Barrier Reef catchments, there has been a general lack of geospatial land condition monitoring information. This paper provides an overview of integrated land monitoring activity in rangeland areas of two major Reef catchments in Queensland: the Burdekin and Fitzroy regions. The project aims were to assemble land condition monitoring datasets that would assist grazing land management and support decision-makers investing public funds; and deliver these data to natural resource management(NRM) community groups, which had been given increased responsibility for delivering local environmental outcomes. We describe the rationale and processes used to produce new land condition monitoring datasets derived from remotely sensed Landsat thematic mapper (TM) and high resolution SPOT 5 satellite imagery and from rapid land condition ground assessment. Specific products include subcatchment groundcover change maps, regional mapping of indicative very poor land condition, and stratified land condition site summaries. Their application, integration, and limitations are discussed. The major innovation is a better understanding of NRM issues with respect to land condition across vast regional areas, and the effective transfer of decision-making capacity to the local level. Likewise, with an increased ability to address policy questions from an evidence-based position, combined with increased cooperation between community, industry and all levels of government, a new era has emerged for decision-makers in rangeland management.
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Purpose: Emotional intelligence (EI) is an increasingly important aspect of a health professional’s skill set. It is strongly associated with empathy, reflection and resilience; all key aspects of radiotherapy practice. Previous work in other disciplines has formed contradictory conclusions concerning development of EI over time. This study aimed to determine the extent to which EI can develop during a radiotherapy undergraduate course and identify factors affecting this. Methods and materials: This study used anonymous coded Likert-style surveys to gather longitudinal data from radiotherapy students relating to a range of self-perceived EI traits during their 3-year degree. Data were gathered at various points throughout the course from the whole cohort. Results: A total of 26 students provided data with 14 completing the full series of datasets. There was a 17·2% increase in self-reported EI score with a p-value<0·0001. Social awareness and relationship skills exhibited the greatest increase in scores compared with self-awareness. Variance of scores decreased over time; there was a reduced change in EI for mature students who tended to have higher initial scores. EI increase was most evident immediately after clinical placements. Conclusions: Radiotherapy students increase their EI scores during a 3-year course. Students reported higher levels of EI immediately after their clinical placement; radiotherapy curricula should seek to maximise on these learning opportunities.
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DEVELOPING A TEXTILE ONTOLOGY FOR THE SEMANTIC WEB AND CONNECTING IT TO MUSEUM CATALOGING DATA The goal of the Semantic Web is to share concept-based information in a versatile way on the Internet. This is achievable using formal data structures called ontologies. The goal of this re-search is to increase the usability of museum cataloging data in information retrieval. The work is interdisciplinary, involving craft science, terminology science, computer science, and museology. In the first part of the dissertation an ontology of concepts of textiles, garments, and accessories is developed for museum cataloging work. The ontology work was done with the help of thesauri, vocabularies, research reports, and standards. The basis of the ontology development was the Museoalan asiasanasto MASA, a thesaurus for museum cataloging work which has been enriched by other vocabularies. Concepts and terms concerning the research object, as well as the material names of textiles, costumes, and accessories, were focused on. The research method was terminological concept analysis complemented by an ontological view of the Semantic Web. The concept structure was based on the hierarchical generic relation. Attention was also paid to other relations between terms and concepts, and between concepts themselves. Altogether 977 concept classes were created. Issues including how to choose and name concepts for the ontology hierarchy and how deep and broad the hierarchy could be are discussed from the viewpoint of the ontology developer and museum cataloger. The second part of the dissertation analyzes why some of the cataloged terms did not match with the developed textile ontology. This problem is significant because it prevents automatic ontological content integration of the cataloged data on the Semantic Web. The research datasets, i.e. the cataloged museum data on textile collections, came from three museums: Espoo City Museum, Lahti City Museum and The National Museum of Finland. The data included 1803 textile, costume, and accessory objects. Unmatched object and textile material names were analyzed. In the case of the object names six categories (475 cases), and of the material names eight categories (423 cases), were found where automatic annotation was not possible. The most common explanation was that the cataloged field was filled with a long sentence comprised of many terms. Sometimes in the compound term, the object name and material, or the name and the way of usage, were combined. As well, numeric values in the material name cataloging field prevented annotation and so did the absence of a corresponding concept in the ontology. Ready-made drop-down lists of materials used in one cataloging system facilitated the annotation. In the case of naming objects and materials, one should use terms in basic form without attributes. The developed textile ontology has been applied in two cultural portals, MuseumFinland and Culturesampo, where one can search for and browse information based on cataloged data using integrated ontologies in an interoperable way. The textile ontology is also part of the national FinnONTO ontology infrastructure. Keywords: annotation, concept, concept analysis, cataloging, museum collection, ontology, Semantic Web, textile collection, textile material
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This article presents a method for checking the conformance between an event log capturing the actual execution of a business process, and a model capturing its expected or normative execution. Given a business process model and an event log, the method returns a set of statements in natural language describing the behavior allowed by the process model but not observed in the log and vice versa. The method relies on a unified representation of process models and event logs based on a well-known model of concurrency, namely event structures. Specifically, the problem of conformance checking is approached by folding the input event log into an event structure, unfolding the process model into another event structure, and comparing the two event structures via an error-correcting synchronized product. Each behavioral difference detected in the synchronized product is then verbalized as a natural language statement. An empirical evaluation shows that the proposed method scales up to real-life datasets while producing more concise and higher-level difference descriptions than state-of-the-art conformance checking methods.
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Long-running datasets from aerial surveys of kangaroos (Macropus giganteus, Macropus [uliginosus, Macropus robustus and Macropus rufus) across Queensland, New South Wales and South Australia have been analysed, seeking better predictors of rates of increase which would allow aerial surveys to be undertaken less frequently than annually. Early models of changes in kangaroo numbers in response to rainfall had shown great promise, but much variability. We used normalised difference vegetation index (NDVI) instead, reasoning that changes in pasture condition would provide a better predictor than rainfall. However, except at a fine scale, NDVI proved no better; although two linked periods of rainfall proved useful predictors of rates of increase, this was only in some areas for some species. The good correlations reported in earlier studies were a consequence of data dominated by large droughtinduced adult mortality, whereas over a longer time frame and where changes between years are less dramatic, juvenile survival has the strongest influence on dynamics. Further, harvesting, density dependence and competition with domestic stock are additional and important influences and it is now clear that kangaroo movement has a greater influence on population dynamics than had been assumed. Accordingly, previous conclusions about kangaroo populations as simple systems driven by rainfall need to be reassessed. Examination of this large dataset has permitted descriptions of shifts in distribution of three species across eastern Australia, changes in dispersion in response to rainfall, and an evaluation of using harvest statistics as an index of density and harvest rate. These results have been combined into a risk assessment and decision theory framework to identify optimal monitoring strategies.
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The most common causes of urinary tract infections (UTIs) are Gram-negative pathogens such as Escherichia coli; however, Gram-positive organisms including Streptococcus agalactiae, or group B streptococcus (GBS), also cause UTI. In GBS infection, UTI progresses to cystitis once the bacteria colonize bladder, but the host responses triggered in the bladder immediately following infection are largely unknown. Here, we used genome-wide expression profiling to map the bladder transcriptome of GBS UTI in mice infected transurethrally with uropathogenic GBS that was cultured from a 35 year-old women with cystitis. RNA from bladders was applied to Affymetrix Gene-1.0ST microarrays; qRT-PCR was used to analyze selected gene responses identified in array datasets. A surprisingly small significant gene list of 172 genes was identified at 24h; this compared to 2507 genes identified in a side-by-side comparison with uropathogenic E. coli (UPEC). No genes exhibited significantly altered expression at 2h in GBS-infected mice according to arrays despite high bladder bacterial loads at this early time point. The absence of a marked early host response to GBS juxtaposed with broad-based bladder responses activated by UPEC at 2h. Bioinformatics analyses including integrative systems-level network mapping revealed multiple activated biological pathways in the GBS cystitis transcriptome that regulate leukocyte activation, inflammation, apoptosis, and cytokine-chemokine biosynthesis. These findings define a novel, minimalistic type of bladder host response triggered by GBS UTI, which comprises collective antimicrobial pathways that differ dramatically from those activated by UPEC. Overall, this study emphasizes the unique nature of bladder immune activation mechanisms triggered by distinct uropathogens.
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Epidemiological studies have demonstrated associations between endometriosis and certain histotypes of ovarian cancer, including clear cell, low-grade serous and endometrioid carcinomas. We aimed to determine whether the observed associations might be due to shared genetic aetiology. To address this, we used two endometriosis datasets genotyped on common arrays with full-genome coverage (3194 cases and 7060 controls) and a large ovarian cancer dataset genotyped on the customized Illumina Infinium iSelect (iCOGS) arrays (10 065 cases and 21 663 controls). Previous work has suggested that a large number of genetic variants contribute to endometriosis and ovarian cancer (all histotypes combined) susceptibility. Here, using the iCOGS data, we confirmed polygenic architecture for most histotypes of ovarian cancer. This led us to evaluate if the polygenic effects are shared across diseases. We found evidence for shared genetic risks between endometriosis and all histotypes of ovarian cancer, except for the intestinal mucinous type. Clear cell carcinoma showed the strongest genetic correlation with endometriosis (0.51, 95% CI = 0.18–0.84). Endometrioid and low-grade serous carcinomas had similar correlation coefficients (0.48, 95% CI = 0.07–0.89 and 0.40, 95% CI = 0.05–0.75, respectively). High-grade serous carcinoma, which often arises from the fallopian tubes, showed a weaker genetic correlation with endometriosis (0.25, 95% CI = 0.11–0.39), despite the absence of a known epidemiological association. These results suggest that the epidemiological association between endometriosis and ovarian adenocarcinoma may be attributable to shared genetic susceptibility loci.
Resumo:
Endometriosis is primarily characterized by the presence of tissue resembling endometrium outside the uterine cavity and is usually diagnosed by laparoscopy. The most commonly used classification of disease, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on disease severity (I to IV), has been questioned as it does not correlate well with underlying symptoms, posing issues in diagnosis and choice of treatment. Using two independent European genome-wide association (GWA) datasets and top-level classification of the endometriosis cases based on rAFS [minimal or mild (Stage A) and moderate-to-severe (Stage B) disease], we previously showed that Stage B endometriosis has greater contribution of common genetic variation to its aetiology than Stage A disease. Herein, we extend our previous analysis to four endometriosis stages [minimal (Stage I), mild (Stage II), moderate (Stage III) and severe (Stage IV) disease] based on the rAFS classification system and compared the genetic burden across stages. Our results indicate that genetic burden increases from minimal to severe endometriosis. For the minimal disease, genetic factors may contribute to a lesser extent than other disease categories. Mild and moderate endometriosis appeared genetically similar, making it difficult to tease them apart. Consistent with our previous reports, moderate and severe endometriosis showed greater genetic burden than minimal or mild disease. Overall, our results provide new insights into the genetic architecture of endometriosis and further investigation in larger samples may help to understand better the aetiology of varying degrees of endometriosis, enabling improved diagnostic and treatment modalities.
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BACKGROUND There has been intensive debate whether migraine with aura (MA) and migraine without aura (MO) should be considered distinct subtypes or part of the same disease spectrum. There is also discussion to what extent migraine cases collected in specialised headache clinics differ from cases from population cohorts, and how female cases differ from male cases with respect to their migraine. To assess the genetic overlap between these migraine subgroups, we examined genome-wide association (GWA) results from analysis of 23,285 migraine cases and 95,425 population-matched controls. METHODS Detailed heterogeneity analysis of single-nucleotide polymorphism (SNP) effects (odds ratios) between migraine subgroups was performed for the 12 independent SNP loci significantly associated (p < 5 x 10(-8); thus surpassing the threshold for genome-wide significance) with migraine susceptibility. Overall genetic overlap was assessed using SNP effect concordance analysis (SECA) at over 23,000 independent SNPs. RESULTS: Significant heterogeneity of SNP effects (p het < 1.4 x 10(-3)) was observed between the MA and MO subgroups (for SNP rs9349379), and between the clinic- and population-based subgroups (for SNPs rs10915437, rs6790925 and rs6478241). However, for all 12 SNPs the risk-increasing allele was the same, and SECA found the majority of genome-wide SNP effects to be in the same direction across the subgroups. CONCLUSIONS Any differences in common genetic risk across these subgroups are outweighed by the similarities. Meta-analysis of additional migraine GWA datasets, regardless of their major subgroup composition, will identify new susceptibility loci for migraine.
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MADAM, Androgenetic alopecia (AGA) is a common age-dependent trait, characterized by a progressive loss of hair from the scalp. The hair loss may commence during puberty and up to 80% of white men experience some degree of AGA during their lifetime.1 Research has established that two essential aetiological factors for AGA are a genetic predisposition and the presence of androgens (male sex hormones).1,2 A recent meta-analysis of genome-wide association studies (GWAS) has increased the number of identified loci associated with this trait at the molecular level to a total of eight.3 However, despite these successes, a large fraction of the genetic contribution remains to be identified. One way to identify further genetic loci is to combine the resource of GWAS datasets with knowledge about specific biological factors likely to be involved in the development of disease. The focused evaluation of a limited number of candidate genes in GWAS datasets avoids the necessity for extensive correction for multiple testing, which typically limits the power for detecting genetic loci at a genome-wide level.4 Because the presence of genetic association suggests that candidate genes are likely to operate early in the causative chain of events leading to the phenotype, this approach may also function to favour biological pathways for their importance in the development of AGA.
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Very limited scientific knowledge exists on the trends and explanations of socioeconomic differences in physical activity among adults. There is a paucity of studies examining whether determinants vary across socioeconomic position and different life stages. This study examines a) how socioeconomic differences in leisure-time and commuting physical activity have changed in Finland from 1978 to 2002 and b) the contribution of childhood socioeconomic position, adolescence sports and exercise, adulthood socioeconomic position, working conditions and other adulthood health behaviours to socioeconomic differences in leisure-time physical activity. This study utilised three population-based datasets collected by the National Institute for Health and Welfare (THL, formerly National Institute for Public Health): the Health Behaviour and Health among the Finnish Adult Population Study from 1978 to 2002 (N=96 105), the National FINRISK Study 2002 and its physical activity sub-study (N= 9 179), and the Health 2000 Study (N=8 028). Survey information was collected by self-administered questionnaires, interviews at home, and measurements made at the study site. The response rates varied from 69 to 89 per cent. Several socioeconomic measures were linked from the national population registers. Based on the results, those with low income were physically inactive during leisure-time and while commuting from 1978 to 2002. Manual worker women, however, were more physically active commuters compared to their counterparts. Parental socioeconomic position contributed directly to adulthood educational differences in leisure-time physical inactivity but also indirectly through adulthood socioeconomic position (occupation, household income) and other unhealthy behaviours (mainly smoking). Among those with low education participation in competitive sports in youth and among those with high education exercise in late adolescence contributed to leisure-time physical activity in adulthood. Long exposure to physically strenuous working conditions in men and current job strain in women contributed to occupational class differences in leisure-time physical activity. Socioeconomic differences in physical activity have remained similar for twenty years in Finland. Educational career seems to have a strong contribution to physical activity. To adopt a lifelong physically active life-style, one should participate in a range of different sports and exercise in adolescence and in youth, have a low exposure to physically and mentally strenuous working conditions in later life and have other healthy behaviours in later life.
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Endometriosis is a common gynecological disease associated with pelvic pain and subfertility. We conducted a genome-wide association study (GWAS) in 3,194 individuals with surgically confirmed endometriosis (cases) and 7,060 controls from Australia and the UK. Polygenic predictive modeling showed significantly increased genetic loading among 1,364 cases with moderate to severe endometriosis. The strongest association signal was on 7p15.2 (rs12700667) for 'all' endometriosis (P = 2.6 x 10(-)(7), odds ratio (OR) = 1.22, 95% CI 1.13-1.32) and for moderate to severe disease (P = 1.5 x 10(-)(9), OR = 1.38, 95% CI 1.24-1.53). We replicated rs12700667 in an independent cohort from the United States of 2,392 self-reported, surgically confirmed endometriosis cases and 2,271 controls (P = 1.2 x 10(-)(3), OR = 1.17, 95% CI 1.06-1.28), resulting in a genome-wide significant P value of 1.4 x 10(-)(9) (OR = 1.20, 95% CI 1.13-1.27) for 'all' endometriosis in our combined datasets of 5,586 cases and 9,331 controls. rs12700667 is located in an intergenic region upstream of the plausible candidate genes NFE2L3 and HOXA10.