398 resultados para Assisted reproductive techniques
Resumo:
Over the last two decades, there has been an increasing awareness of, and interest in, the use of spatial moment techniques to provide insight into a range of biological and ecological processes. Models that incorporate spatial moments can be viewed as extensions of mean-field models. These mean-field models often consist of systems of classical ordinary differential equations and partial differential equations, whose derivation, at some point, hinges on the simplifying assumption that individuals in the underlying stochastic process encounter each other at a rate that is proportional to the average abundance of individuals. This assumption has several implications, the most striking of which is that mean-field models essentially neglect any impact of the spatial structure of individuals in the system. Moment dynamics models extend traditional mean-field descriptions by accounting for the dynamics of pairs, triples and higher n-tuples of individuals. This means that moment dynamics models can, to some extent, account for how the spatial structure affects the dynamics of the system in question.
Resumo:
Endometriosis is a common gynaecological disease with symptoms of pelvic pain and infertility which affects 7-10% of women in their reproductive years. Activation of an oncogenic allele of Kirsten rat sarcoma viral oncogene homologue (KRAS) in the reproductive tract of mice resulted in the development of endometriosis. We hypothesized that variation in KRAS may influence risk of endometriosis in humans. Thirty tagSNPs spanning a region of 60.7 kb across the KRAS locus were genotyped using iPLEX chemistry on a MALDI-TOF MassARRAY platform in 959 endometriosis cases and 959 unrelated controls, and data were analysed for association with endometriosis. Genotypes were obtained for most individuals with a mean completion rate of 99.1%. We identified six haplotype blocks across the KRAS locus in our sample. There were no significant differences between cases and controls in the frequencies of individual single-nucleotide polymorphisms (SNPs) or haplotypes. We also developed a rapid method to screen for 11 common KRAS and BRAF mutations on the Sequenom MassARRAY system. The assay detected all mutations previously identified by direct sequencing in a panel of positive controls. No germline variants for KRAS or BRAF were detected. Our results demonstrate that any risk of endometriosis in women because of common variation in KRAS must be very small.
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Coal seam gas (CSG) is a growing industry in Queensland and represents a potential major employer and deliverer of financial prosperity for years to come. CSG is a natural gas composed primarily of methane and is found trapped underground in coal beds. During the gas extraction process, significant volumes of associated water are also produced. This associated water could be a valuable resource, however, the associated water comprises of various salt constituents that make it problematic for beneficial use. Consequently, there is a need to implement various water treatment strategies to purify the associated water to comply with Queensland’s strict guidelines and to mitigate environmental risks. The resultant brine is also of importance as ultimately it also has to be dealt with in an economical manner. In some ways it can be considered that the CSG industry does not face a water problem, as this has inherent value to society, but rather has a “salt issue” to solve. This study analyzes the options involved in both the water treatment and salt recovery processes. A brief overview of the constituents present in Queensland CS water is made to illustrate the challenges involved and a range of treatment technologies discussed. Water treatment technologies examined include clarification (ballasted flocculation, dissolved air flotation, electrocoagulation), membrane filtration (ultrafiltration), ion exchange softening and desalination (ion exchange, reverse osmosis desalination and capacitance deionization). In terms of brine management we highlighted reinjection, brine concentration ponds, membrane techniques (membrane distillation, forward osmosis), thermal methods, electrodialysis, electrodialysis reversal, bipolar membrane electrodialysis, wind assisted intensive evaporation, membrane crystallization, eutectic freeze crystallization and vapor compression. As an entirety this investigation is designed to be an important tool in developing CS water treatment management strategies for effective management in Queensland and worldwide.
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Sampling design is critical to the quality of quantitative research, yet it does not always receive appropriate attention in nursing research. The current article details how balancing probability techniques with practical considerations produced a representative sample of Australian nursing homes (NHs). Budgetary, logistical, and statistical constraints were managed by excluding some NHs (e.g., those too difficult to access) from the sampling frame; a stratified, random sampling methodology yielded a final sample of 53 NHs from a population of 2,774. In testing the adequacy of representation of the study population, chi-square tests for goodness of fit generated nonsignificant results for distribution by distance from major city and type of organization. A significant result for state/territory was expected and was easily corrected for by the application of weights. The current article provides recommendations for conducting high-quality, probability-based samples and stresses the importance of testing the representativeness of achieved samples.
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In Australia, railway systems play a vital role in transporting the sugarcane crop from farms to mills. In this paper, a novel job shop approach is proposed to create a more efficient integrated harvesting and sugarcane transport scheduling system to reduce the cost of sugarcane transport. There are several benefits that can be attained by treating the train scheduling problem as a job shop problem. Job shop is generic and suitable for all trains scheduling problems. Job shop technique prevents operating two trains on one section at the same time because it considers that the section or the machine is unique. This technique is more promising to find better solutions in reasonable computation times.
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Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.
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This paper presents a statistical aircraft trajectory clustering approach aimed at discriminating between typical manned and expected unmanned traffic patterns. First, a resampled version of each trajectory is modelled using a mixture of Von Mises distributions (circular statistics). Second, the remodelled trajectories are globally aligned using tools from bioinformatics. Third, the alignment scores are used to cluster the trajectories using an iterative k-medoids approach and an appropriate distance function. The approach is then evaluated using synthetically generated unmanned aircraft flights combined with real air traffic position reports taken over a sector of Northern Queensland, Australia. Results suggest that the technique is useful in distinguishing between expected unmanned and manned aircraft traffic behaviour, as well as identifying some common conventional air traffic patterns.
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Electricity generation is vital in developed countries to power the many mechanical and electrical devices that people require. Unfortunately electricity generation is costly. Though electricity can be generated it cannot be stored efficiently. Electricity generation is also difficult to manage because exact demand is unknown from one instant to the next. A number of services are required to manage fluctuations in electricity demand, and to protect the system when frequency falls too low. A current approach is called automatic under frequency load shedding (AUFLS). This article proposes new methods for optimising AUFLS in New Zealand’s power system. The core ideas were developed during the 2015 Maths and Industry Study Group (MISG) in Brisbane, Australia. The problem has been motivated by Transpower Limited, a company that manages New Zealand’s power system and transports bulk electricity from where it is generated to where it is needed. The approaches developed in this article can be used in electrical power systems anywhere in the world.