8 resultados para Challenge test
em CentAUR: Central Archive University of Reading - UK
Resumo:
Outbreaks of mass mortality in postlarval abalone, Haliotis diversicolor supertexta (L.), have swept across south China since 2002 and in turn have resulted in many abalone farms closing. Twenty-five representative bacterial isolates were isolated from a sample of five diseased postlarval abalone, taken 15 d postfertilization during an outbreak of postlarval disease in Sanya, Hainan Province, China in October 2004. A dominant isolate, referred to as Strain 6, was found to be highly virulent to postlarvae in an experimental challenge test, with a 50% lethal dose (LD50) value of 3.2 x 10(4) colony forming units (CFU)/mL, while six of the other isolates were weakly virulent with LD50 values ranging from 1 x 10(6) to 1 x 10(7) CFU/mL, and the remaining 18 isolates were classified as avirulent with LD50 values greater than 1 x 10(8) CFU/mL. Using both an API 20E kit and 16S recombinant DNA sequence analysis, Strain 6 was shown to be Vibrio parahaemolyticus. It was sensitive to 4 and intermediately sensitive to 5 of the 16 antibiotics used when screening the antibiotic sensitivities of the bacterium. Extracellular products (ECPs) prepared from the bacterium were lethal to postlarvae when used in a toxicity test at a concentration of 3.77 mg protein/mL, and complete liquefaction of postlarvae tissues occurred within 24 h postexposure. Results from this study implicate V. parahaemolyticus as the pathogen involved in the disease outbreaks in postlarval abalone in Sanya and show that the ECPs may be involved in the pathogenesis of the disease.
Resumo:
Chatterbox Challenge is an annual web-based contest for artificial conversational systems, ACE. The 2010 instantiation was the tenth consecutive contest held between March and June in the 60th year following the publication of Alan Turing’s influential disquisition ‘computing machinery and intelligence’. Loosely based on Turing’s viva voca interrogator-hidden witness imitation game, a thought experiment to ascertain a machine’s capacity to respond satisfactorily to unrestricted questions, the contest provides a platform for technology comparison and evaluation. This paper provides an insight into emotion content in the entries since the 2005 Chatterbox Challenge. The authors find that synthetic textual systems, none of which are backed by academic or industry funding, are, on the whole and more than half a century since Weizenbaum’s natural language understanding experiment, little further than Eliza in terms of expressing emotion in dialogue. This may be a failure on the part of the academic AI community for ignoring the Turing test as an engineering challenge.
Resumo:
This paper assesses the performance of a vocabulary test designed to measure second language productive vocabulary knowledge.The test, Lex30, uses a word association task to elicit vocabulary, and uses word frequency data to measure the vocabulary produced. Here we report firstly on the reliability of the test as measured by a test-retest study, a parallel test forms experiment and an internal consistency measure. We then investigate the construct validity of the test by looking at changes in test performance over time, analyses of correlations with scores on similar tests, and comparison of spoken and written test performance. Last, we examine the theoretical bases of the two main test components: eliciting vocabulary and measuring vocabulary. Interpretations of our findings are discussed in the context of test validation research literature. We conclude that the findings reported here present a robust argument for the validity of the test as a research tool, and encourage further investigation of its validity in an instructional context
Resumo:
This article is a commentary on several research studies conducted on the prospects for aerobic rice production systems that aim at reducing the demand for irrigation water which in certain major rice producing areas of the world is becoming increasingly scarce. The research studies considered, as reported in published articles mainly under the aegis of the International Rice Research Institute (IRRI), have a narrow scope in that they test only 3 or 4 rice varieties under different soil moisture treatments obtained with controlled irrigation, but with other agronomic factors of production held as constant. Consequently, these studies do not permit an assessment of the interactions among agronomic factors that will be of critical significance to the performance of any production system. Varying the production factor of "water" will seriously affect also the levels of the other factors required to optimise the performance of a production system. The major weakness in the studies analysed in this article originates from not taking account of the interactions between experimental and non-experimental factors involved in the comparisons between different production systems. This applies to the experimental field design used for the research studies as well as to the subsequent statistical analyses of the results. The existence of such interactions is a serious complicating element that makes meaningful comparisons between different crop production systems difficult. Consequently, the data and conclusions drawn from such research readily become biased towards proposing standardised solutions for possible introduction to farmers through a linear technology transfer process. Yet, the variability and diversity encountered in the real-world farming environment demand more flexible solutions and approaches in the dissemination of knowledge-intensive production practices through "experiential learning" types of processes, such as those employed by farmer field schools. This article illustrates, based on expertise of the 'system of rice intensification' (SRI), that several cost-effective and environment-friendly agronomic solutions to reduce the demand for irrigation water, other than the asserted need for the introduction of new cultivars, are feasible. Further, these agronomic Solutions can offer immediate benefits of reduced water requirements and increased net returns that Would be readily accessible to a wide range of rice producers, particularly the resource poor smallholders. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
Lactoperoxidase (LP) exerts antimicrobial effects in combination with H2O2 and either thiocyanate (SCN-) or a halide (e. g., I-). Garlic extract in the presence of ethanol has also been used to activate the LP system. This study aimed to determine the effects of 3 LP activation systems (LP+SCN-+H2O2; LP+I-+H2O2; LP + garlic extract + ethanol) on the growth and activity of 3 test organisms (Staphylococcus aureus, Pseudomonas aeruginosa, and Bacillus cereus). Sterilized milk was used as the reaction medium, and the growth pattern of the organisms and a range of keeping quality (KQ) indicators (pH, titratable acidity, ethanol stability, clot on boiling) were monitored during storage at the respective optimum growth temperature for each organism. The LP+I-+H2O2 system reduced bacterial counts below the detection limit shortly after treatment for all 3 organisms, and no bacteria could be detected for the duration of the experiment (35 to 55 h). The KQ data confirmed that the milk remained unspoiled at the end of the experiments. The LP + garlic extract + ethanol system, on the other hand, had no effect on the growth or KQ with P. aeruginosa, but showed a small retardation of growth of the other 2 organisms, accompanied by small increases (5 to 10 h) in KQ. The effects of the LP+SCN-+H2O2 system were intermediate between those of the other 2 systems and differed between organisms. With P. aeruginosa, the system exerted total inhibition within 10 h of incubation, but the bacteria regained viability after a further 5 h, following a logarithmic growth curve. This was reflected in the KQ indicators, which implied an extension of 15 h. With the other 2 bacterial species, LP+SCN-+H2O2 exerted an obvious inhibitory effect, giving a lag phase in the growth curve of 5 to 10 h and KQ extension of 10 to 15 h. When used in combination, I- and SCN- displayed negative synergy.
Resumo:
Objective To examine the impact of increasing numbers of metabolic syndrome (MetS) components on postprandial lipaemia. Methods Healthy men (n = 112) underwent a sequential meal postprandial investigation, in which blood samples were taken at regular intervals after a test breakfast (0 min) and lunch (330 min). Lipids and glucose were measured in the fasting sample, with triacylglycerol (TAG), non-esterified fatty acids and glucose analysed in the postprandial samples. Results Subjects were grouped according to the number of MetS components regardless of the combinations of components (0/1, 2, 3 and 4/5). As expected, there was a trend for an increase in body mass index, blood pressure, fasting TAG, glucose and insulin, and a decrease in fasting high-density lipoprotein cholesterol with increasing numbers of MetS components (P≤0.0004). A similar trend was observed for the summary measures of the postprandial TAG and glucose responses. For TAG, the area under the curve (AUC) and maximum concentration (maxC) were significantly greater in men with ≥ 3 than < 3 components (P < 0.001), whereas incremental AUC was greater in those with 3 than 0/1 and 2, and 4/5 compared with 2 components (P < 0.04). For glucose, maxC after the test breakfast (0-330 min) and total AUC (0-480 min) were higher in men with ≥ 3 than < 3 components (P≤0.001). Conclusions Our data analysis has revealed a linear trend between increasing numbers of MetS components and magnitude (AUC) of the postprandial TAG and glucose responses. Furthermore, the two meal challenge discriminated a worsening of postprandial lipaemic control in subjects with ≥ 3 MetS components.
Resumo:
Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns.
Resumo:
Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.