960 resultados para surrogate pair


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Unicode标准中的非BMP平面字符多用于古籍研究或者少数民族语言文字,由于这些字符的使用面特别窄,多数软件系统包括办公软件都不支持对这些字符的处理。本文以开源办公套件OpenOffice.org为基础,分析了它对非BMP平面支持的现状,然后着重探讨了实现对非BMP平面字符的全面支持所需要解决的一系列问题,并分别给出了合理的改进方案,最后以CJK和藏文为例展示了改进后的效果。

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The problem of bipartite ranking, where instances are labeled positive or negative and the goal is to learn a scoring function that minimizes the probability of mis-ranking a pair of positive and negative instances (or equivalently, that maximizes the area under the ROC curve), has been widely studied in recent years. A dominant theoretical and algorithmic framework for the problem has been to reduce bipartite ranking to pairwise classification; in particular, it is well known that the bipartite ranking regret can be formulated as a pairwise classification regret, which in turn can be upper bounded using usual regret bounds for classification problems. Recently, Kotlowski et al. (2011) showed regret bounds for bipartite ranking in terms of the regret associated with balanced versions of the standard (non-pairwise) logistic and exponential losses. In this paper, we show that such (non-pairwise) surrogate regret bounds for bipartite ranking can be obtained in terms of a broad class of proper (composite) losses that we term as strongly proper. Our proof technique is much simpler than that of Kotlowski et al. (2011), and relies on properties of proper (composite) losses as elucidated recently by Reid and Williamson (2010, 2011) and others. Our result yields explicit surrogate bounds (with no hidden balancing terms) in terms of a variety of strongly proper losses, including for example logistic, exponential, squared and squared hinge losses as special cases. An important consequence is that standard algorithms minimizing a (non-pairwise) strongly proper loss, such as logistic regression and boosting algorithms (assuming a universal function class and appropriate regularization), are in fact consistent for bipartite ranking; moreover, our results allow us to quantify the bipartite ranking regret in terms of the corresponding surrogate regret. We also obtain tighter surrogate bounds under certain low-noise conditions via a recent result of Clemencon and Robbiano (2011).

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This thesis details methodology to estimate urban stormwater quality based on a set of easy to measure physico-chemical parameters. These parameters can be used as surrogate parameters to estimate other key water quality parameters. The key pollutants considered in this study are nitrogen compounds, phosphorus compounds and solids. The use of surrogate parameter relationships to evaluate urban stormwater quality will reduce the cost of monitoring and so that scientists will have added capability to generate a large amount of data for more rigorous analysis of key urban stormwater quality processes, namely, pollutant build-up and wash-off. This in turn will assist in the development of more stringent stormwater quality mitigation strategies. The research methodology was based on a series of field investigations, laboratory testing and data analysis. Field investigations were conducted to collect pollutant build-up and wash-off samples from residential roads and roof surfaces. Past research has identified that these impervious surfaces are the primary pollutant sources to urban stormwater runoff. A specially designed vacuum system and rainfall simulator were used in the collection of pollutant build-up and wash-off samples. The collected samples were tested for a range of physico-chemical parameters. Data analysis was conducted using both univariate and multivariate data analysis techniques. Analysis of build-up samples showed that pollutant loads accumulated on road surfaces are higher compared to the pollutant loads on roof surfaces. Furthermore, it was found that the fraction of solids smaller than 150 ìm is the most polluted particle size fraction in solids build-up on both roads and roof surfaces. The analysis of wash-off data confirmed that the simulated wash-off process adopted for this research agrees well with the general understanding of the wash-off process on urban impervious surfaces. The observed pollutant concentrations in wash-off from road surfaces were different to pollutant concentrations in wash-off from roof surfaces. Therefore, firstly, the identification of surrogate parameters was undertaken separately for roads and roof surfaces. Secondly, a common set of surrogate parameter relationships were identified for both surfaces together to evaluate urban stormwater quality. Surrogate parameters were identified for nitrogen, phosphorus and solids separately. Electrical conductivity (EC), total organic carbon (TOC), dissolved organic carbon (DOC), total suspended solids (TSS), total dissolved solids (TDS), total solids (TS) and turbidity (TTU) were selected as the relatively easy to measure parameters. Consequently, surrogate parameters for nitrogen and phosphorus were identified from the set of easy to measure parameters for both road surfaces and roof surfaces. Additionally, surrogate parameters for TSS, TDS and TS which are key indicators of solids were obtained from EC and TTU which can be direct field measurements. The regression relationships which were developed for surrogate parameters and key parameter of interest were of a similar format for road and roof surfaces, namely it was in the form of simple linear regression equations. The identified relationships for road surfaces were DTN-TDS:DOC, TP-TS:TOC, TSS-TTU, TDS-EC and TSTTU: EC. The identified relationships for roof surfaces were DTN-TDS and TSTTU: EC. Some of the relationships developed had a higher confidence interval whilst others had a relatively low confidence interval. The relationships obtained for DTN-TDS, DTN-DOC, TP-TS and TS-EC for road surfaces demonstrated good near site portability potential. Currently, best management practices are focussed on providing treatment measures for stormwater runoff at catchment outlets where separation of road and roof runoff is not found. In this context, it is important to find a common set of surrogate parameter relationships for road surfaces and roof surfaces to evaluate urban stormwater quality. Consequently DTN-TDS, TS-EC and TS-TTU relationships were identified as the common relationships which are capable of providing measurements of DTN and TS irrespective of the surface type.

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Reliability and validity in the testing of spoken language are essential in order to assess learners' English language proficiency as evidence of their readiness to begin courses in tertiary institutions. Research has indicated that the task chosen to elicit language samples can have a marked effect on both the nature of the interaction, including the power differential, and assessment, raising the issue of ethics. This exploratory studey, with a group of 32 students from the Peoples's Republic of China preparing for tertiary study in Singapore, compares test-takers' reactions to the use of an oral proficiency interview and a pair interaction.

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This paper presents the outcomes of a research project, which focused on developing a set of surrogate parameters to evaluate urban stormwater quality using simulated rainfall. Use of surrogate parameters has the potential to enhance the rapid generation of urban stormwater quality data based on on-site measurements and thereby reduce resource intensive laboratory analysis. The samples collected from rainfall simulations were tested for a range of physico-chemical parameters which are key indicators of nutrients, solids and organic matter. The analysis revealed that [total dissolved solids (TDS) and dissolved organic carbon (DOC)]; [total solids (TS) and total organic carbon (TOC)]; [turbidity (TTU)]; [electrical conductivity (EC)]; [TTU and EC] as appropriate surrogate parameters for dissolved total nitrogen (DTN), total phosphorus (TP), total suspended solids (TSS), TDS and TS respectively. Relationships obtained for DTN-TDS, DTN-DOC, and TP-TS demonstrated good portability potential. The portability of the relationship developed for TP and TOC was found to be unsatisfactory. The relationship developed for TDS-EC and TS-EC also demonstrated poor portability.

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Background Research involving incapacitated persons with dementia entails complex scientific, legal, and ethical issues, making traditional surveys of layperson views on the ethics of such research challenging. We therefore assessed the impact of democratic deliberation (DD), involving balanced, detailed education and peer deliberation, on the views of those responsible for persons with dementia. Methods One hundred and seventy-eight community-recruited caregivers or primary decision-makers for persons with dementia were randomly assigned to either an all-day DD session group or a control group. Educational materials used for the DD session were vetted for balance and accuracy by an interdisciplinary advisory panel. We assessed the acceptability of family-surrogate consent for dementia research (“surrogate-based research”) from a societal policy perspective as well as from the more personal perspectives of deciding for a loved one or for oneself (surrogate and self-perspectives), assessed at baseline, immediately post-DD session, and 1 month after DD date, for four research scenarios of varying risk-benefit profiles. Results At baseline, a majority in both the DD and control groups supported a policy of family consent for dementia research in all research scenarios. The support for a policy of family consent for surrogate-based research increased in the DD group, but not in the control group. The change in the DD group was maintained 1 month later. In the DD group, there were transient changes in attitudes from surrogate or self-perspectives. In the control group, there were no changes from baseline in attitude toward surrogate consent from any perspective. Conclusions Intensive, balanced, and accurate education, along with peer deliberation provided by democratic deliberation, led to a sustained increase in support for a societal policy of family consent in dementia research among those responsible for dementia patients.

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Stormwater is a potential and readily available alternative source for potable water in urban areas. However, its direct use is severely constrained by the presence of toxic pollutants, such as heavy metals (HMs). The presence of HMs in stormwater is of concern because of their chronic toxicity and persistent nature. In addition to human health impacts, metals can contribute to adverse ecosystem health impact on receiving waters. Therefore, the ability to predict the levels of HMs in stormwater is crucial for monitoring stormwater quality and for the design of effective treatment systems. Unfortunately, the current laboratory methods for determining HM concentrations are resource intensive and time consuming. In this paper, applications of multivariate data analysis techniques are presented to identify potential surrogate parameters which can be used to determine HM concentrations in stormwater. Accordingly, partial least squares was applied to identify a suite of physicochemical parameters which can serve as indicators of HMs. Datasets having varied characteristics, such as land use and particle size distribution of solids, were analyzed to validate the efficacy of the influencing parameters. Iron, manganese, total organic carbon, and inorganic carbon were identified as the predominant parameters that correlate with the HM concentrations. The practical extension of the study outcomes to urban stormwater management is also discussed.

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We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.

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The importance of community resilience to natural disasters is being increasingly recognised. This paper presents an approach for the development of surrogate indicators for comprehensive assessment of community resilience, which is crucial in the context of predicted increase in natural disasters resulting from extreme weather events due to climate change. The use of surrogate indicators is advocated because a comprehensive assessment of community resilience across various thematic areas and associated key areas requires the measurement of a large number of resilience indicators which is not always feasible due to time and resource constraints, To overcome this, researchers tend to use secondary data sources, which are easily available but not always reliable. This highlights the need for surrogate indicators that are easy to measure from reliable primary data sources and are adequate to capture the resilience of a community. Firstly, the paper discusses the two approaches for defining and conceptualising community resilience and the need to account for the complex interrelationships between thematic areas, key areas and resilience indicators and their implications for research. Secondly, a comprehensive framework for the assessment of community resilience is proposed and the difficulties associated with the measurement of overall resilience of the community are discussed. Thirdly, the paper explains a two-step approach to develop surrogate indicators highlighting the necessity and challenges associated with it. Finally, the proposed approach is elaborated with a simple example for better understanding.

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Purpose To evaluate carbonic anhydrase (CA) IX as a surrogate marker of hypoxia and investigate the prognostic significance of different patterns of expression in non-small-cell lung cancer (NSCLC). Methods Standard immunohistochemical techniques were used to study CA IX expression in 175 resected NSCLC tumors. CA IX expression was determined by Western blotting in A549 cell lines grown under normoxic and hypoxic conditions. Measurements from microvessels to CA IX positivity were obtained. Results CA IX immunostaining was detected in 81.8% of patients. Membranous (m) (P = .005), cytoplasmic (c) (P = .018), and stromal (P < .001) CA IX expression correlated with the extent of tumor necrosis (TN). The mean distance from vascular endothelium to the start of tumor cell positivity was 90 μm, which equates to an oxygen pressure of 5.77 mmHg. The distance to blood vessels from individual tumor cells or tumor cell clusters was greater if they expressed mCA IX than if they did not (P < .001). Hypoxic exposure of A549 cells for 16 hours enhanced CAIX expression in the nuclear and cytosolic extracts. Perinuclear (p) CA IX (P = .035) was associated with a poor prognosis. In multivariate analysis, pCA IX (P = .004), stage (P = .001), platelet count (P = .011), sex (P = .027), and TN (P = .035) were independent poor prognostic factors. Conclusion These results add weight to the contention that mCA IX is a marker of tumor cell hypoxia. The absence of CA IX staining close to microvessels suggests that these vessels are functionally active. pCA IX expression is representative of an aggressive phenotype. © 2003 by American Society of Clinical Oncology.

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The launch of the current series of My Kitchen Rules has undoubtedly been successful, both in terms of television ratings and in capturing a social media audience, clearly winning the battle for the Twitter audience on premiere night, and maintaining a lead over both The Block and The Biggest Loser since then. But it is the controversy surrounding Perth contestants Kelly Ramsay and Chloe James that has dominated media coverage today, detailing the abuse to which they have been subjected on social media.

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Many cell types form clumps or aggregates when cultured in vitro through a variety of mechanisms including rapid cell proliferation, chemotaxis, or direct cell-to-cell contact. In this paper we develop an agent-based model to explore the formation of aggregates in cultures where cells are initially distributed uniformly, at random, on a two-dimensional substrate. Our model includes unbiased random cell motion, together with two mechanisms which can produce cell aggregates: (i) rapid cell proliferation, and (ii) a biased cell motility mechanism where cells can sense other cells within a finite range, and will tend to move towards areas with higher numbers of cells. We then introduce a pair-correlation function which allows us to quantify aspects of the spatial patterns produced by our agent-based model. In particular, these pair-correlation functions are able to detect differences between domains populated uniformly at random (i.e. at the exclusion complete spatial randomness (ECSR) state) and those where the proliferation and biased motion rules have been employed - even when such differences are not obvious to the naked eye. The pair-correlation function can also detect the emergence of a characteristic inter-aggregate distance which occurs when the biased motion mechanism is dominant, and is not observed when cell proliferation is the main mechanism of aggregate formation. This suggests that applying the pair-correlation function to experimental images of cell aggregates may provide information about the mechanism associated with observed aggregates. As a proof of concept, we perform such analysis for images of cancer cell aggregates, which are known to be associated with rapid proliferation. The results of our analysis are consistent with the predictions of the proliferation-based simulations, which supports the potential usefulness of pair correlation functions for providing insight into the mechanisms of aggregate formation.

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Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate,l. Estimating D and l is important for investigating the efficacy of a potential treatment and provides insight into the mechanism through which the potential treatment acts. While a few methods for estimating D and l have been proposed, these previous methods lead to point estimates of D and l, and provide no insight into the uncertainty in these estimates. Here, we compare various types of information that can be extracted from images of a scratch assay, and quantify D and l using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and l from synthetic data, as well as a new set of experimental data. For the first time, our approach also provides a method to estimate the uncertainty in our estimates of D and l. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and l, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.

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Work zone safety studies have traditionally relied on historical crash records—an approach which is reactive in nature as it requires crashes to accumulate first before taking any preventive actions. However, detailed and accurate data on work zone crashes are often not available, as is the case for Australian road work zones. The lack of reliable safety records and the reactive nature of the crash-based safety analysis approach motivated this research to seek alternative and proactive measures of safety. Various surrogate measures of safety have been developed in the traffic safety literature including time to collision, time to accident, gap time, post encroachment time, required deceleration rate, proportion of stopping distances, lateral distance to departure, and time to departure. These measures express how close road-user(s) are from a potential crash by analysing their movement trajectories. A review of this fast-growing literature is presented in this paper from the viewpoint of applying the measures to untangle work zone safety issues. The review revealed that the use of the surrogate measures is very limited for analysing work zone safety, although numerous studies have used these measures for analysing safety in other parts of the road network, such as intersections and motorway ramps. There exist great opportunities for adopting this proactive safety assessment approach to transform work zone safety for both roadworkers and motorists.