Attachment and alcohol : testing a motivational model of problem drinking /

The purpose of this study was to replicate and extend a motivational model of problem drinking (Cooper, Frone, Russel, & Mudar, 1995; Read, Wood, Kahler, Maddock & Tibor, 2003), testing the notion that attachment is a common antecedent for both the affective and social paths to problem drinking. The model was tested with data from three samples, first-year university students (N=679), students about to graduate from university (N=206), and first-time clients at an addiction treatment facility (N=21 1). Participants completed a battery of questionnaires assessing alcohol use, alcohol-related consequences, drinking motives, peer models of alcohol use, positive and negative affect, attachment anxiety and attachment avoidance. Results underscored the importance of the affective path to problem drinking, while putting the social path to problem drinking into question. While drinking to cope was most prominent among the clinical sample, coping motives served as a risk factor for problem drinking for both individuals identified as problem drinkers and university students. Moreover, drinking for enhancement purposes appeared to be the strongest overall predictor of alcohol use. Results of the present study also supported the notion that attachment anxiety and avoidance are antecedents for the affective path to problem drinking, such that those with higher levels of attachment anxiety and avoidance were more vulnerable to experiencing adverse consequences related to their drinking, explained in terms of diminished affect regulation. Evidence that nonsecure attachment is a potent predictor of problem drinking was also demonstrated by the finding that attachment anxiety was directly related to alcohol-related consequences over and above its indirect relationship through affect regulation. However, results failed to show that attachment anxiety or attachment avoidance increased the risk of problem drinking via social influence.

X-ray diffraction of a gram-negative bacterial membrane mimetic

This thesis applies x-ray diffraction to measure he membrane structure of lipopolysaccharides and to develop a better model of a LPS bacterial melilbrane that can be used for biophysical research on antibiotics that attack cell membranes. \iVe ha'e Inodified the Physics department x-ray machine for use 3.'3 a thin film diffractometer, and have lesigned a new temperature and relative humidity controlled sample cell.\Ve tested the sample eel: by measuring the one-dimensional electron density profiles of bilayers of pope with 0%, 1%, 1G :VcJ, and 100% by weight lipo-polysaccharide from Pse'udo'lTwna aeTuginosa. Background VVe now know that traditional p,ntibiotics ,I,re losing their effectiveness against ever-evolving bacteria. This is because traditional antibiotic: work against specific targets within the bacterial cell, and with genetic mutations over time, themtibiotic no longer works. One possible solution are antimicrobial peptides. These are short proteins that are part of the immune systems of many animals, and some of them attack bacteria directly at the membrane of the cell, causing the bacterium to rupture and die. Since the membranes of most bacteria share common structural features, and these featuret, are unlikely to evolve very much, these peptides should effectively kill many types of bacteria wi Lhout much evolved resistance. But why do these peptides kill bacterial cel: '3 , but not the cells of the host animal? For gramnegative bacteria, the most likely reason is that t Ileir outer membrane is made of lipopolysaccharides (LPS), which is very different from an animal :;ell membrane. Up to now, what we knovv about how these peptides work was likely done with r !10spholipid models of animal cell membranes, and not with the more complex lipopolysa,echaricies, If we want to make better pepticies, ones that we can use to fight all types of infection, we need a more accurate molecular picture of how they \vork. This will hopefully be one step forward to the ( esign of better treatments for bacterial infections.

Determinants and Consequences of Dehumanization: An Interspecies Model of Prejudice

Dehumanizing ideologies that explicitly liken other humans to “inferior” animals can have negative consequences for intergroup attitudes and relations. Surprisingly, very little is known about the causes of dehumanization, and essentially no research has examined strategies for reducing dehumanizing tendencies. The Interspecies Model of Prejudice specifies that animalistic dehumanization may be rooted in basic hierarchical beliefs regarding human superiority over animals. This theoretical reasoning suggests that narrowing the human-animal divide should also reduce dehumanization. The purpose of the present dissertation, therefore, was to gain a more complete understanding of the predictors of and solutions to dehumanization by examining the Interspecies Model of Prejudice, first from a layperson’s perspective and then among young children. In Study 1, laypeople strongly rejected the human-animal divide as a probable cause of, or solution to, dehumanization, despite evidence that their own personal beliefs in the human-animal divide positively predicted their dehumanization (and prejudice) scores. From Study 1, it was concluded that the human-animal divide, despite being a robust empirical predictor of dehumanization, is largely unrecognized as a probable cause of, or solution to, dehumanization by non-experts in the psychology of prejudice. Studies 2 and 3 explored the expression of dehumanization, as well as the Interspecies Model of Prejudice, among children ages six to ten years (Studies 2 and 3) and parents (Study 3). Across both studies, White children showed evidence of racial dehumanization by attributing a Black child target fewer “uniquely human” characteristics than the White child target, representing the first systematic evidence of racial dehumanization among children. In Study 3, path analyses supported the Interspecies Model of Prejudice among children. Specifically, children’s beliefs in the human-animal divide predicted greater racial prejudice, an effect explained by heightened racial dehumanization. Moreover, parents’ Social Dominance Orientation (preference for social hierarchy and inequality) positively predicted children’s human-animal divide beliefs. Critically, these effects remained significant even after controlling for established predictors of child-prejudice (i.e., parent prejudice, authoritarian parenting, and social-cognitive skills) and relevant child demographics (i.e., age and sex). Similar patterns emerged among parent participants, further supporting the Interspecies Model of Prejudice. Encouragingly, children reported narrower human-animal divide perceptions after being exposed to an experimental prime (versus control) that highlighted the similarities among humans and animals. Together the three studies reported in this dissertation offer important and novel contributions to the dehumanization and prejudice literature. Not only did we find the first systematic evidence of racial dehumanization among children, we established the human-animal divide as a meaningful dehumanization precursor. Moreover, empirical support was obtained for the Interspecies Model of Prejudice among diverse samples including university students (Study 1), children (Studies 2 and 3), and adult-aged samples (Study 3). Importantly, each study also highlights the promising social implication of targeting the human-animal divide in interventions to reduce dehumanization and other prejudicial processes.

Does the Barro-Gordon Model Explain the Behavior of US Inflation? a Reexamination of the Empirical Evidence

This paper tests the predictions of the Barro-Gordon model using US data on inflation and unemployment. To that end, it constructs a general game-theoretical model with asymmetric preferences that nests the Barro-Gordon model and a version of Cukierman’s model as special cases. Likelihood Ratio tests indicate that the restriction imposed by the Barro-Gordon model is rejected by the data but the one imposed by the version of Cukierman’s model is not. Reduced-form estimates are consistent with the view that the Federal Reserve weights more heavily positive than negative unemployment deviations from the expected natural rate.

Product autoregressive models for non-negative variables

When variables in time series context are non-negative, such as for volatility, survival time or wave heights, a multiplicative autoregressive model of the type Xt = Xα t−1Vt , 0 ≤ α < 1, t = 1, 2, . . . may give the preferred dependent structure. In this paper, we study the properties of such models and propose methods for parameter estimation. Explicit solutions of the model are obtained in the case of gamma marginal distribution

The Bogota – sabana region : the political economy behind the struggle to implement a sustainable urban development model

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L´onconasa com a model per l´estudi de les bases moleculars de la citotoxicitat de les ribonucleases pancreàtiques. Aplicacions a la construcció de ribonucleases amb activitat antimicrobiana

La primera part d'aquest treball s´ha centrat en la caracterització i optimització del procés d'activació de l´onconasa recombinant per tal d'obtenir l´enzim igual a la forma nativa. Per això, les reaccions d'eliminació de la Met-1 i la ciclació de la Glu1, necessàries per generar el piroglutamic han estat seguides per MALDI-TOF MS. La segona part d´aquest treball s´ha centrat en l´estudi de la contribució del pont disulfur 30-75 de l´onconasa a les seves propietats biològiques. Els resultats suggereixen que el potencial redox del citosol cel·lular podria reduir el pont disulfur 30-75 de l´onconasa salvatge afectant la unió onconasa -inhibidor proteic de ribonucleases. La tercera part ha consistit en la construcció de variants de l´HP-RNasa i onconasa amb activitat bactericida. Per això, s´ha introduït el determinant bactericida (YRWR) descrit per la proteïna catiònica d'eosinòfils en els dos enzims. Els resultats obtinguts han evidenciat que les dues ribonucleases amb el determinant bactericida presenten activitat citotòxica contra bacteris gram-negatius preferentment.

The counter-propagating Rossby-wave perspective on baroclinic instability. II: Application to the Charney model

The constant-density Charney model describes the simplest unstable basic state with a planetary-vorticity gradient, which is uniform and positive, and baroclinicity that is manifest as a negative contribution to the potential-vorticity (PV) gradient at the ground and positive vertical wind shear. Together, these ingredients satisfy the necessary conditions for baroclinic instability. In Part I it was shown how baroclinic growth on a general zonal basic state can be viewed as the interaction of pairs of ‘counter-propagating Rossby waves’ (CRWs) that can be constructed from a growing normal mode and its decaying complex conjugate. In this paper the normal-mode solutions for the Charney model are studied from the CRW perspective. Clear parallels can be drawn between the most unstable modes of the Charney model and the Eady model, in which the CRWs can be derived independently of the normal modes. However, the dispersion curves for the two models are very different; the Eady model has a short-wave cut-off, while the Charney model is unstable at short wavelengths. Beyond its maximum growth rate the Charney model has a neutral point at finite wavelength (r=1). Thereafter follows a succession of unstable branches, each with weaker growth than the last, separated by neutral points at integer r—the so-called ‘Green branches’. A separate branch of westward-propagating neutral modes also originates from each neutral point. By approximating the lower CRW as a Rossby edge wave and the upper CRW structure as a single PV peak with a spread proportional to the Rossby scale height, the main features of the ‘Charney branch’ (0model where the positive PV gradient exists only at the tropopause

Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model

A physically motivated statistical model is used to diagnose variability and trends in wintertime ( October - March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity q(s) has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.

Simulating current global river runoff with a global hydrological model: model revisions, validation, and sensitivity analysis

Global hydrological models (GHMs) model the land surface hydrologic dynamics of continental-scale river basins. Here we describe one such GHM, the Macro-scale - Probability-Distributed Moisture model.09 (Mac-PDM.09). The model has undergone a number of revisions since it was last applied in the hydrological literature. This paper serves to provide a detailed description of the latest version of the model. The main revisions include the following: (1) the ability for the model to be run for n repetitions, which provides more robust estimates of extreme hydrological behaviour, (2) the ability of the model to use a gridded field of coefficient of variation (CV) of daily rainfall for the stochastic disaggregation of monthly precipitation to daily precipitation, and (3) the model can now be forced with daily input climate data as well as monthly input climate data. We demonstrate the effects that each of these three revisions has on simulated runoff relative to before the revisions were applied. Importantly, we show that when Mac-PDM.09 is forced with monthly input data, it results in a negative runoff bias relative to when daily forcings are applied, for regions of the globe where the day-to-day variability in relative humidity is high. The runoff bias can be up to - 80% for a small selection of catchments but the absolute magnitude of the bias may be small. As such, we recommend future applications of Mac-PDM.09 that use monthly climate forcings acknowledge the bias as a limitation of the model. The performance of Mac-PDM.09 is evaluated by validating simulated runoff against observed runoff for 50 catchments. We also present a sensitivity analysis that demonstrates that simulated runoff is considerably more sensitive to method of PE calculation than to perturbations in soil moisture and field capacity parameters.

Estimating the hidden number of scrapie affected holdings in great Britain using a simple, truncated count model allowing for heterogeneity.

None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture–recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture–recapture models. Alternative methods, still under the capture–recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture–recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao’s lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates—in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

A predictive model for early-warning of Septoria leaf blotch on winter wheat

Disease-weather relationships influencing Septoria leaf blotch (SLB) preceding growth stage (GS) 31 were identified using data from 12 sites in the UK covering 8 years. Based on these relationships, an early-warning predictive model for SLB on winter wheat was formulated to predict the occurrence of a damaging epidemic (defined as disease severity of 5% or > 5% on the top three leaf layers). The final model was based on accumulated rain > 3 mm in the 80-day period preceding GS 31 (roughly from early-February to the end of April) and accumulated minimum temperature with a 0A degrees C base in the 50-day period starting from 120 days preceding GS 31 (approximately January and February). The model was validated on an independent data set on which the prediction accuracy was influenced by cultivar resistance. Over all observations, the model had a true positive proportion of 0.61, a true negative proportion of 0.73, a sensitivity of 0.83, and a specificity of 0.18. True negative proportion increased to 0.85 for resistant cultivars and decreased to 0.50 for susceptible cultivars. Potential fungicide savings are most likely to be made with resistant cultivars, but such benefits would need to be identified with an in-depth evaluation.

Estimating the hidden number of scrapie affected holdings in great Britain using a simple, truncated count model allowing for heterogeneity

None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture-recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture-recapture models. Alternative methods, still under the capture-recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture-recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao's lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates-in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model

A physically motivated statistical model is used to diagnose variability and trends in wintertime ( October - March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity q(s) has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.

Knowledge communication and translation- A knowledge transfer model

Purpose – The purpose of this paper is to propose a process model for knowledge transfer in using theories relating knowledge communication and knowledge translation. Design/methodology/approach – Most of what is put forward in this paper is based on a research project titled “Procurement for innovation and knowledge transfer (ProFIK)”. The project is funded by a UK government research council – The Engineering and Physical Sciences Research Council (EPSRC). The discussions are mainly grounded on a thorough review of literature accomplished as part of the research project. Findings – The process model developed in this paper has built upon the theory of knowledge transfer and the theory of communication. Knowledge transfer, per se, is not a mere transfer of knowledge. It involves different stages of knowledge transformation. Depending on the context of knowledge transfer, it can also be influenced by many factors; some positive and some negative. The developed model of knowledge transfer attempts to encapsulate all these issues in order to create a holistic framework. Originality/value of paper – An attempt has been made in the paper to combine some of the significant theories or findings relating to knowledge transfer together, making the paper an original and valuable one.