976 resultados para Negative resistance


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Tungro is one of the most destructive viral diseases of rice in South and Southeast Asia. It is associated with two viruses---rice tungro bacilliform virus (RTBV) ,and rice tungro spherical virus (RTSV) (Hibino et al 1978). Both viruses are transmitted by the green leafhopper (GLH) Nephotettix virescens (Ling 1979), However, prior acquisition of RTSV is required for Ihe transmission of RTBV alone (Hibino 1983). Plants infected with both viruses show severe stunting and yellowing. Those infected with RTBV alone show mild stunting but no leaf discoloration whereas those infected with RTSV alone do not show any apparent symptoms (Hibino el al 1978). Since the late 1960s, tungro has been mainly managed through varietal resistance (Khush 1989). The instability of resistant varieties in the field (Dahal et .a1 1990) led to a reexamination of the nature of the incorporated sources of resistance and to the adoption of more precise and more accurate screening methods.

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RTSV is one of two viruses that cause tungro disease. RTSV is independently transmitted, whereas the other virus, rice tungro bacilliform virus (RTBV), is dependent on RTSV for its transmission by the green leafhopper (GLH), Nephotettix virescens. The occurrence and spread of tungro disease therefore depend on the presence of RTSV in the field. Resistance to RTSV infection would slow down the spread of the disease.

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Resistance to rice virus diseases is an important requirement in many Southeast Asian rice breeding programs. Inheritance of resistance to rice tungro spherical virus (RTSV) in TW5, a near-isogenic line derived from Indonesian rice cultivar Utri Merah, was compared to that in TKM6, an Indian rice cultivar. Both TKM6 and Utri Merah are cultivars resistant to RTSV infections. Crosses were made between TKM6 and TN1, a susceptible cultivar, and between TW5 and TN1, and F3 lines were evaluated for their resistance to RTSV using two RTSV inoculum sources and a serological assay (ELISA). In TKM6, the resistance to the mixture of RTSV-V + RTBV inoculum source was controlled by a single recessive gene, whereas in TW5, the resistance was controlled by two recessive genes. A single recessive gene, however, controlled the resistance in TW5 when another RTSV variant, RTSV-VI, was used, suggesting that the resistance in TW5 depends on the nature of the RTSV inoculum used. RT-PCR, sequence, and phylogenetic analyses confirmed that RTSV-VI inoculum differs from RTSV-V inoculum and accurate phenotyping of the resistance to RTSV requires the use of a genetic marker.

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In the study of traffic safety, expected crash frequencies across sites are generally estimated via the negative binomial model, assuming time invariant safety. Since the time invariant safety assumption may be invalid, Hauer (1997) proposed a modified empirical Bayes (EB) method. Despite the modification, no attempts have been made to examine the generalisable form of the marginal distribution resulting from the modified EB framework. Because the hyper-parameters needed to apply the modified EB method are not readily available, an assessment is lacking on how accurately the modified EB method estimates safety in the presence of the time variant safety and regression-to-the-mean (RTM) effects. This study derives the closed form marginal distribution, and reveals that the marginal distribution in the modified EB method is equivalent to the negative multinomial (NM) distribution, which is essentially the same as the likelihood function used in the random effects Poisson model. As a result, this study shows that the gamma posterior distribution from the multivariate Poisson-gamma mixture can be estimated using the NM model or the random effects Poisson model. This study also shows that the estimation errors from the modified EB method are systematically smaller than those from the comparison group method by simultaneously accounting for the RTM and time variant safety effects. Hence, the modified EB method via the NM model is a generalisable method for estimating safety in the presence of the time variant safety and the RTM effects.

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Objective Alcohol-related implicit (preconscious) cognitive processes are established and unique predictors of alcohol use, but most research in this area has focused on alcohol-related implicit cognition and anxiety. This study extends this work into the area of depressed mood by testing a cognitive model that combines traditional explicit (conscious and considered) beliefs, implicit alcohol-related memory associations (AMAs), and self-reported drinking behavior. Method Using a sample of 106 university students, depressed mood was manipulated using a musical mood induction procedure immediately prior to completion of implicit then explicit alcohol-related cognition measures. A bootstrapped two-group (weak/strong expectancies of negative affect and tension reduction) structural equation model was used to examine how mood changes and alcohol-related memory associations varied across groups. Results Expectancies of negative affect moderated the association of depressed mood and AMAs, but there was no such association for tension reduction expectancy. Conclusion Subtle mood changes may unconsciously trigger alcohol-related memories in vulnerable individuals. Results have implications for addressing subtle fluctuations in depressed mood among young adults at risk of alcohol problems.

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In December 2006, the Engineering and Technology Group of Queensland’s Department of Main Roads entered into a three-year skid resistance management research project with QUT Faculty of Built Environment and Engineering researchers and the QUT-based CRC for Integrated Engineering Asset Management (CIEAM). CIEAM undertakes a broad range of asset management research in the areas of defence, utilities, transportation and industrial processes. “The research project is an important activity of Main Roads’ Skid Resistance Management Plan published in June 2006.” said Main Roads project leader Mr Justin Weligamage. “The intended project output is a decision-support model for use by Road Asset Managers throughout a road network. The research objective is to enable road asset managers to better manage the surfacing condition of the road asset with specific focus on skid resistance,” said QUT project leader Professor Arun Kumar. The research project will review existing skid resistance investigatory levels, develop a risk-based method to establish skid resistance investigatory levels and improve the decision support methodology in order to minimise crashes. The new risk-based approach will be used to identify locations on the Queensland state-controlled road network that may have inadequate skid resistance. Once a high risk site is identified, the appropriate remedial action will be decided on. This approach will allow road asset managers to target optimal remedial actions, reducing the incidence and severity of crashes where inadequate skid resistance is a contributing cause.

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A system for agroinoculating rice tungro bacilliform virus (RTBV), one of the two viruses of the rice tungro disease complex, has been optimised. A nontumour-inducing strain of Agrobacterium (pGV3850) was used in order to conform with biosafety regulations. Fourteen-day-old seedlings survived the mechanical damage of the technique and were still young enough to support virus replication. The level of the bacterial inoculum was important to obtain maximum infection, with a high inoculum level (0.5 × 1012 cells/ml) resulting in up to 100% infection of a susceptible variety that was comparable with infection by insect transmission. Agroinoculation with RTBV was successful for all three rice cultivarss tested; TN1 (tungro susceptible), Balimau Putih (tungro tolerant), and IR26 (RTSV and vector resistant). Agroinoculation enables resistance to RTBV to be distinguished from resistance to the leafhopper vector of the virus, and should prove useful in screening rice germplasm, breeding materials, and transgenic rice lines.

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Road accidents are of great concerns for road and transport departments around world, which cause tremendous loss and dangers for public. Reducing accident rates and crash severity are imperative goals that governments, road and transport authorities, and researchers are aimed to achieve. In Australia, road crash trauma costs the nation A$ 15 billion annually. Five people are killed, and 550 are injured every day. Each fatality costs the taxpayer A$1.7 million. Serious injury cases can cost the taxpayer many times the cost of a fatality. Crashes are in general uncontrolled events and are dependent on a number of interrelated factors such as driver behaviour, traffic conditions, travel speed, road geometry and condition, and vehicle characteristics (e.g. tyre type pressure and condition, and suspension type and condition). Skid resistance is considered one of the most important surface characteristics as it has a direct impact on traffic safety. Attempts have been made worldwide to study the relationship between skid resistance and road crashes. Most of these studies used the statistical regression and correlation methods in analysing the relationships between skid resistance and road crashes. The outcomes from these studies provided mix results and not conclusive. The objective of this paper is to present a probability-based method of an ongoing study in identifying the relationship between skid resistance and road crashes. Historical skid resistance and crash data of a road network located in the tropical east coast of Queensland were analysed using the probability-based method. Analysis methodology and results of the relationships between skid resistance, road characteristics and crashes are presented.

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A favorable product country of origin (e.g., an automobile made in Germany) is often considered an asset by marketers. Yet a challenge in today's competitive environment is how marketers of products from less favorably regarded countries can counter negative country of origin perceptions. Three studies investigate how mental imagery can be used to reduce the effects of negative country of origin stereotypes. Study 1 reveals that participants exposed to country of origin information exhibit automatic stereotype activation. Study 2 shows that self-focused counterstereotypical mental imagery (relative to other-focused mental imagery) significantly inhibits the automatic activation of negative country of origin stereotypes. Study 3 shows that this lessening of automatic negative associations persists when measured one day later. The results offer important implications for marketing theory and practice.

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Road crashes cost world and Australian society a significant proportion of GDP, affecting productivity and causing significant suffering for communities and individuals. This paper presents a case study that generates data mining models that contribute to understanding of road crashes by allowing examination of the role of skid resistance (F60) and other road attributes in road crashes. Predictive data mining algorithms, primarily regression trees, were used to produce road segment crash count models from the road and traffic attributes of crash scenarios. The rules derived from the regression trees provide evidence of the significance of road attributes in contributing to crash, with a focus on the evaluation of skid resistance.

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Background: Pregnant women exposed to traffic pollution have an increased risk of negative birth outcomes. We aimed to investigate the size of this risk using a prospective cohort of 970 mothers and newborns in Logan, Queensland. ----- ----- Methods: We examined two measures of traffic: distance to nearest road and number of roads around the home. To examine the effect of distance we used the number of roads around the home in radii from 50 to 500 metres. We examined three road types: freeways, highways and main roads.----- ----- Results: There were no associations with distance to road. A greater number of freeways and main roads around the home were associated with a shorter gestation time. There were no negative impacts on birth weight, birth length or head circumference after adjusting for gestation. The negative effects on gestation were largely due to main roads within 400 metres of the home. For every 10 extra main roads within 400 metres of the home, gestation time was reduced by 1.1% (95% CI: -1.7, -0.5; p-value = 0.001).----- ----- Conclusions: Our results add weight to the association between exposure to traffic and reduced gestation time. This effect may be due to the chemical toxins in traffic pollutants, or because of disturbed sleep due to traffic noise.

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This paper seeks to assimilate Queer Theory: that is, to bring it within the gambit of a ‘mainstream’ or ‘dominant’ space: the academy. It does so by historicising Queer Theory, and investigating, if not what it is, then at least what it has been. This makes it possible to engage critically with Queer Theory. Suggesting that Queer Theory has often employed tropes of assimilation, the paper turns to another cultural site at which such language is popular - science fiction - in order to investigate the assumption of these metaphors. It goes on to suggest some of the assumptions about cultures which underlie these metaphors. Finally, it points to other sites in Queer Theory which undermines these assumptions, and provide other ways - quite uninterested in assimilation - in which to think Queer.

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It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences, but many experiments do not support this hypothesis. The innovative technique presented in paper makes a breakthrough for this difficulty. This technique discovers both positive and negative patterns in text documents as higher level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the higher level features. Substantial experiments using this technique on Reuters Corpus Volume 1 and TREC topics show that the proposed approach significantly outperforms both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and pattern based methods on precision, recall and F measures.