Elicitator: An expert elicitation tool for regression in ecology

Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modelling, assessing detectability or eradication, ecological condition assessments, risk analysis and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.     

Climate and Bordeaux wine quality: identifying the key factors that differentiate vintages based on consensus rankings

The climate of Bordeaux, France, was examined to determine if climatic factors can distinguish between consensus vintage rankings, developed using eight ratings sources, of red and sweet white wines from 1961 to 2009. Climate variables were computed for the growing season and average plant phenological stages and were compared between the 10 highest and lowest ranked vintages. Good vintages exhibited higher heat accumulation during the growing season and a general lack of rainfall, particularly during veraison. Most climate factors were consistent for both red and sweet white wines. Mean maximum temperature during the growing season was an important discriminator between good and poor vintages for both reds and whites, although sweet white wines were also affected by growing season precipitation and temperatures during the vine's dormant period. In general, consensus vintage quality is consistent between reds and whites (Spearman's ρ?=?0.66, p?相似文献   

Impact of cranberry juice and proanthocyanidins on the ability of <Emphasis Type="Italic">Escherichia coli</Emphasis> to form biofilms

The effects of cranberry juice cocktail (CJC) and proanthocyanidins (PACs) on biofilm formation were investigated. Escherichia coli strain HB101pDC1 and nonfimbriated strain HB101 were grown in 10 wt% CJC or 120 μg/mL PACs for 12 consecutive cultures. Biofilm formation was investigated by incubating bacteria in 96-well polyvinyl chloride (PVC) plates and studying the optical density of the solution using the crystal violet method. We suspect that biofilm formation occurred due to non-specific interactions between the bacteria and the polymer. Both P-fimbriated E. coli HB101pDC1 and the non-fimbriated strain HB101 formed biofilms. E. coli strain HB101pDC1 formed a thicker and more mature biofilm. Cranberry juice inhibited biofilm formation after the first culture; however, for bacteria grown in PACs, a decrease in biofilm formation was observed with increasing number of cultures. The inhibitory effect was reversible. These results demonstrate that CJC is more effective than isolated PACs at preventing biofilm formation, possibly suggesting that other cranberry compounds also play a role in anti-biofilm activity.     

Quantification of particle number emission factors for motor vehicles from on-road measurements

The database on particle number emission factors has been very limited to date despite the increasing interest in the effects of human exposure to particles in the submicrometer range. There are also major questions on the comparability of emission factors derived through dynamometer versus on-road studies. Thus, the aims of this study were (1) to quantify vehicle number emission factors in the submicrometer (and also supermicrometer) range for stop-start and free-flowing traffic at about 100 km h(-1) driving conditions through extensive road measurements and (2) to compare the emission factors from the road measurements with those obtained previously from dynamometer studies conducted in Brisbane. For submicrometer particles the average emission factors for Tora Street were estimated at (1.89 +/- 3.40) x 10(13) particles km(-1) (mean +/- standard error; n = 386) for petrol and (7.17 +/- 2.80) x 10(14) particles km(-1) (diesel; n = 196) and for supermicrometer particles at 2.59 x 10(9) particles km(-1) and 1.53 x 10(12) particles km(-1), respectively. The average number emission factors for submicrometer particles estimated for Ipswich Road (stop-start traffic mode) were (2.18 +/- 0.57) x 10(13) particles km(-1) (petrol) and (2.04 +/- 0.24) x 10(14) particles km(-1) (diesel). One implication of the conclusion that emission factors of heavy duty diesel vehicles are over 1 order of magnitude higher than emission factors of petrol-fueled passenger cars is that future control and management strategies should in particular target heavy duty vehicles, as even a moderate decrease in emissions of these vehicles would have a significant impact on lowering atmospheric concentrations of particles. The finding that particle number emissions per vehicle-km are significantly larger for higher speed vehicle operation has an important implication on urban traffic planning and optimization of vehicle speed to lower their impact on airborne pollution. Additionally, statistical analysis showed that neither the measuring method (dynamometer or on-road), nor data origin (Brisbane or elsewhere in the world), is associated with a statistically significant difference between the average values of emission factors for diesel, petrol, and vehicle fleet mix. However, statistical analyses of the effect of fuel showed that the mean values of emission factors for petrol and diesel are different at a 5% significance level.     

The genome of wine yeast Dekkera bruxellensis provides a tool to explore its food-related properties

The yeast Dekkera/Brettanomyces bruxellensis can cause enormous economic losses in wine industry due to production of phenolic off-flavor compounds. D. bruxellensis is a distant relative of baker's yeast Saccharomyces cerevisiae. Nevertheless, these two yeasts are often found in the same habitats and share several food-related traits, such as production of high ethanol levels and ability to grow without oxygen. In some food products, like lambic beer, D. bruxellensis can importantly contribute to flavor development. We determined the 13.4 Mb genome sequence of the D. bruxellensis strain Y879 (CBS2499) and deduced the genetic background of several "food-relevant" properties and evolutionary history of this yeast. Surprisingly, we find that this yeast is phylogenetically distant to other food-related yeasts and most related to Pichia (Komagataella) pastoris, which is an aerobic poor ethanol producer. We further show that the D. bruxellensis genome does not contain an excess of lineage specific duplicated genes nor a horizontally transferred URA1 gene, two crucial events that promoted the evolution of the food relevant traits in the S. cerevisiae lineage. However, D. bruxellensis has several independently duplicated ADH and ADH-like genes, which are likely responsible for metabolism of alcohols, including ethanol, and also a range of aromatic compounds.     

The effect of dietary fat level and quality on plasma lipoprotein lipids and plasma fatty acids in normocholesterolemic subjects

This study examined the effect on the plasma lipids and plasma phospholipid and cholesteryl ester fatty acids of changing from a typical western diet to a very low fat (VLF) vegetarian diet containing one egg/day. The effect of the addition of saturated, monounsaturated or polyunsaturated fat (PUFA) to the VLF diet was also examined. Three groups of 10 subjects (6 women, 4 men) were fed the VLF diet (10% energy as fat) for two weeks, and then in the next two weeks the dietary fat in each group was increased by 10% energy/week using butter, olive oil or safflower oil. The fat replaced dietary carbohydrate. The VLF diet reduced both the low density lipoprotein (LDL)-and high density lipoprotein (HDL)-cholesterol levels; addition of the monounsaturated fats and PUFA increased the HDL-cholesterol levels, whereas butter increased the cholesterol levels in both the LDL- and HDL-fractions. The VLF diet led to significant reductions in the proportion of linoleic acid (18∶2ω6) and eicosapentaenoic acid (20∶5ω3) and to increases in palmitoleic (16∶1), eicosatrienoic (20∶3ω6) and arachidonic acids (20∶4ω6) in both phospholipids and cholesteryl esters. Addition of butter reversed the changes seen on the VLF diet, with the exception of 16∶1, which remained elevated. Addition of olive oil resulted in a significant rise in the proportion of 18∶1 and significant decreases in all ω3 PUFA except 22∶6 compared with the usual diet. The addition of safflower oil resulted in significant increases in 18∶2 and 20∶4ω6 and significant decreases in 18∶1, 20∶5ω3 and 22∶5ω3. These results indicate that the reduction of saturated fat content of the diet (<6% dietary energy), either by reducing the total fat content of the diet or by exchanging saturated fat with unsaturated fat, reduced the total plasma cholesterol levels by approximately 12% in normocholesterolemic subjects. Although the VLF vegetarian diet reduced both LDL- and HDL-cholesterol levels, the long-term effects of VLF diets are unlikely to be deteterious since populations which habitually consume these diets have low rates of coronary heart disease. The addition of safflower oil or olive oil to a VLF diet produced favorable changes in the lipoprotein lipid profile compared with the addition of butter. The VLF diets and diets rich in butter, olive oil or safflower oil had different effects on the 20 carbon eicosanoid precursor fatty acids in the plasma. This suggests that advice on plasma lipid lowering should also take into account the effect of the diet on the fatty acid profile of the plasma lipids.     

A proposed validation framework for expert elicited Bayesian Networks

The popularity of Bayesian Network modelling of complex domains using expert elicitation has raised questions of how one might validate such a model given that no objective dataset exists for the model. Past attempts at delineating a set of tests for establishing confidence in an entirely expert-elicited model have focused on single types of validity stemming from individual sources of uncertainty within the model. This paper seeks to extend the frameworks proposed by earlier researchers by drawing upon other disciplines where measuring latent variables is also an issue. We demonstrate that even in cases where no data exist at all there is a broad range of validity tests that can be used to establish confidence in the validity of a Bayesian Belief Network.     

The Influence of Growing Region, Cultivar and Harvest Timing on the Diversity of Australian Olive Oil

The quality indices and chemical composition of ten common olive cultivars grown in different regions of Australia were evaluated to determine the diversity of olive oils produced in Australia. Olives from trees from different environments including warmer climates in the north to colder climates in the south were sampled at two different stages of maturity over 2 years. The oil was extracted and standard methods were used to analyse the oil. Oleic acid content ranged from 83.4% in the Picual cultivar grown in Tasmania to 54.5% in Arbequina grown in northern New South Wales/southern Queensland. The Barnea cultivar, which is very commonly grown in Australia, was above 4% for campesterol content, regardless of the region in which it was grown. Parameters, such as palmitic acid, oleic acid, linoleic acid and wax content were found to be significantly affected by growing region for some cultivars. This study shows the growing conditions for olive in Australia gives rise to a diverse range of olive oils.     

Amygdala size and hypothalamus size predict social play frequency in nonhuman primates: A comparative analysis using independent contrasts.

The amygdala and hypothalamus become sexually differentiated by gonadal hormones giving rise to sexually differentiated behaviors, which include play behavior. Phylogenetic comparative analyses test for relationships between social play and brain structure volumes. Relative volume of the amygdala and hypothalamus correlated with social play, but not nonsocial play, even after controlling for the size of other brain structures. The authors propose that behaviors such as social assessment, recognizing and responding to facial expression, and social response appropriateness, which are mediated by the amygdala, are developed through social play. Additionally, the hypothalamus may regulate the motivation to engage in play through positive reinforcement of pleasurable activity. Thus, the instinctive socioemotive aspects of play in primates appear to be those regulated by the amygdala and hypothalamus. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Goal hierarchy: Improving asset data quality by improving motivation

Many have recognized the need for high quality data on assets and the problems in obtaining them, particularly when there is a need for human observation and manual recording. Yet very few have looked at the role of the data collectors themselves in the data quality process. This paper argues that there are benefits to more fully understanding the psychological factors that lay behind data collection and we use goal hierarchy theory to understand these factors. Given the myriad of potential reasons for poor-quality data it has previously proven difficult to identify and successfully deploy employee-driven interventions; however, the goal hierarchy approach looks at all of the goals that an individual has in their life and the connections between them. For instance, does collecting data relate to whether or not they get a promotion? Stay safe? Get a new job? and so on. By eliciting these goals and their connections we can identify commonalities across different groups, sites or organizations that can influence the quality of data collection. Thus, rather than assuming what the data collectors want, a goal hierarchy approach determines that empirically. Practically, this supports the development of customized interventions that will be much more effective and sustainable than previous efforts.