749 research outputs found
, Ross Laird
No full textRoss Laird, PhD RCC is a clinical consultant focused on trauma, addictions, and social vulnerability. He is also a best-selling author, award-winning scholar and educator, and clinical supervisor for BC’s largest licensed non-profit program in addictions, trauma, and mental health. Dr. Laird focuses particularly on traumatized and marginalized client populations — those navigating homelessness, mental illness, and complex trauma — and provides professional development training for organizations that serve them: social service agencies, first responders, cultural groups, nonprofits, and educational institutions. He also works extensively with organizations in arts and culture and Indigenous communities to develop trauma-informed practices for cultural programming, museum exhibitions, and community initiatives
Tumbled smooth by the rapids: Rediscovering and reconnecting in the wake of turbulence
No full textRoss Laird, PhD RCC is a clinical consultant focused on trauma, addictions, and social vulnerability. He is also a best-selling author, award-winning scholar and educator, and clinical supervisor for BC’s largest licensed non-profit program in addictions, trauma, and mental health. Dr. Laird focuses particularly on traumatized and marginalized client populations — those navigating homelessness, mental illness, and complex trauma — and provides professional development training for organizations that serve them: social service agencies, first responders, cultural groups, nonprofits, and educational institutions. He also works extensively with organizations in arts and culture and Indigenous communities to develop trauma-informed practices for cultural programming, museum exhibitions, and community initiatives.presentationBetter Together Conferenc
fgui: A Method for Automatically Creating Graphical User Interfaces for Command-Line R Packages
No full textThe fgui R package is designed for developers of R packages, to help rapidly, and sometimes fully automatically, create a graphical user interface for a command line R package. The interface is built upon the Tcl/Tk graphical interface included in R. The package further facilitates the developer by loading in the help files from the command line functions to provide context sensitive help to the user with no additional effort from the developer. Passing a function as the argument to the routines in the fgui package creates a graphical interface for the function, and further options are available to tweak this interface for those who want more flexibility.
Freud e Johnson-Laird: Modelos Mentais no «Caso Dora»
No full textAfreudite : Revista Lusófona de Psicanálise Pura e AplicadaTrabalho sobre a relação entre a teoria dos modelos mentais de Johnson-Laird e o conceito de transferência em Freud.The author underline the relationship between Johnson-Laird's mental patterns theory and the concept of transfer in Freud
Sunitinib treatment exacerbates intratumoral heterogeneity in metastatic renal cancer
No full textThis work was supported by the Chief Scientist Office, Scotland (ETM37; to G.D. Stewart, A.C.P. Riddick, M. Aitchison, and D.J. Harrison), Cancer Research UK (Experimental Cancer Medicine Centre; to T. Powles, London and D.J. Harrison, Edinburgh), Medical Research Council (to A. Laird and D.J. Harrison), Royal College of Surgeons of Edinburgh (to A. Laird), Melville Trust (to A. Laird), Medical Research Council (MC_UU_12018/25; to I.M. Overton), Royal Society of Edinburgh Scottish Government Fellowship cofunded by Marie Curie Actions (to I.M. Overton), Renal Cancer Research Fund (to G.D. Stewart), Kidney Cancer Scotland (to G.D. Stewart) and an educational grant from Pfizer (to T. Powles).Purpose: The aim of this study was to investigate the effect of VEGF targeted therapy (sunitinib) on molecular intratumoral heterogeneity (ITH) in metastatic clear cell renal cancer (mccRCC). Experimental design: Multiple tumor samples (n=187 samples) were taken from the primary renal tumors of mccRCC patients who were sunitinib treated (n=23, SuMR clinical trial) or untreated (n=23, SCOTRRCC study). ITH of pathological grade, DNA (aCGH), mRNA (Illumina Beadarray) and candidate proteins (reverse phase protein array) were evaluated using unsupervised and supervised analyses (driver mutations, hypoxia and stromal related genes). ITH was analysed using intratumoral protein variance distributions and distribution of individual patient aCGH and gene expression clustering. Results: Tumor grade heterogeneity was greater in treated compared to untreated tumors (P=0.002). In unsupervised analysis, sunitinib therapy was not associated with increased ITH in DNA or mRNA. However, there was an increase in ITH for the driver mutation gene signature (DNA and mRNA) as well as increasing variability of protein expression with treatment (p<0.05). Despite this variability, significant chromosomal and transcript changes to key targets of sunitinib, such as VHL, PBRM1 and CAIX, occurred in the treated samples. Conclusions: These findings suggest that sunitinib treatment has significant effects on the expression and ITH of key tumor and treatment specific genes/proteins in mccRCC. The results, based on primary tumor analysis, do not support the hypothesis that resistant clones are selected and predominate following targeted therapy.Peer reviewe
Multivariate logistic regression with incomplete covariate and auxiliary information
No full textAbstractIn this article, we propose and explore a multivariate logistic regression model for analyzing multiple binary outcomes with incomplete covariate data where auxiliary information is available. The auxiliary data are extraneous to the regression model of interest but predictive of the covariate with missing data. Horton and Laird [N.J. Horton, N.M. Laird, Maximum likelihood analysis of logistic regression models with incomplete covariate data and auxiliary information, Biometrics 57 (2001) 34–42] describe how the auxiliary information can be incorporated into a regression model for a single binary outcome with missing covariates, and hence the efficiency of the regression estimators can be improved. We consider extending the method of [9] to the case of a multivariate logistic regression model for multiple correlated outcomes, and with missing covariates and completely observed auxiliary information. We demonstrate that in the case of moderate to strong associations among the multiple outcomes, one can achieve considerable gains in efficiency from estimators in a multivariate model as compared to the marginal estimators of the same parameters
The True Nature of the Satyricon?
No full textThis paper considers the Satyrica in relation to the developing history of Greek prose fiction, highlighting some problems presented by a panoramic view of Greco-Roman literary history for interpretation of this work. The aim of this discussion is not to argue firmly for a later period of composition for the Satyrica, but to highlight the fact that its date has not yet been properly settled. This awkward question cannot but bear on the way in which the work is viewed in relation to a constellation of potential Greek influences and sources. Andrew Laird is Reader in Classical Literature in Warwick University. He has published widely on Latin prose fiction and is co-editor of A Companion to the Prologue of Apuleius\u27 Metamorphoses (OUP 2001). He is author of Powers of Expression, Expressions of Power (OUP 1999) and The Epic of America (Duckworth 2006)
Different Dialects - a World Conversation on Work Integrated learning
No full textLisa Ward (University of Huddersfield) and Ron Laird (University of Ulster) will provide conference with an insight to selected themes from recent Work Integrated Learning conferences and symposia. Their dialogue will enable delegates to hear of developments and practice from around the world of co-operative education. Their observations should enable all delegates to evaluate aspects of their own practice within a wider international context and lead to improvement
Multivariate logistic regression with incomplete covariate and auxiliary information
No full textIn this article, we propose and explore a multivariate logistic regression model for analyzing multiple binary outcomes with incomplete covariate data where auxiliary information is available. The auxiliary data are extraneous to the regression model of interest but predictive of the covariate with missing data. Horton and Laird [N.J. Horton, N.M. Laird, Maximum likelihood analysis of logistic regression models with incomplete covariate data and auxiliary information, Biometrics 57 (2001) 34-42] describe how the auxiliary information can be incorporated into a regression model for a single binary outcome with missing covariates, and hence the efficiency of the regression estimators can be improved. We consider extending the method of [9] to the case of a multivariate logistic regression model for multiple correlated outcomes, and with missing covariates and completely observed auxiliary information. We demonstrate that in the case of moderate to strong associations among the multiple outcomes, one can achieve considerable gains in efficiency from estimators in a multivariate model as compared to the marginal estimators of the same parameters.Asymptotic relative efficiency Auxiliary information Incomplete data Logistic regression model Missing covariates Multiple outcomes
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