366 research outputs found
Recurrent ATM mutations in T-PLL on diverse haplotypes: no support for their germline origin
No full textNorms Expanded, Clark & Paivio (2004b)
No full textExpanded Norms for 2,311 Items"reference_to_cite: "Clark, J. M., & Paivio, A. (2004). Extensions of the Paivio, Yuille, and Madigan (1968) norms. Behavior Research Methods, Instruments, and Computers, xx, xx-xx."url_information: "Authors' website ( http://io.uwinnipeg.ca/~clark/cog/norms/cp2004.html )"public_note: "Note 1. Imagery values for 925 items (PYM>0) obtained from Paivio, A. U., Yuille, J. C., & Madigan, S. A. (1968). Concreteness, imagery, and meaningfulness values for 925 nouns. Journal of Experimental Psychology, 76(1, PT. 2), 1-25. Reprinted with permission of Allan Paivio and American Psychological Association."</div
Toward a Heterodox Property Law and Economics
No full textProperty law is profoundly unsatisfying. This statement is not meant to suggest that property is wrong or bad. Nor does it mean to take issue with any particular rule of property law, at least in a way that is not already reflected in the rich property literature. Rather, property law is unsatisfying because, often, its settlements and compromises seem wanting and iniquitous, even while envisioned alternatives seem untenable and unfair. Indeed, the standard first-year Property syllabus reads like a compendium of the Catch-22
Norms, Clark & Paivio (2004)
No full textExpanded Norms for Original 925 Paivio, Yuille, and Madigan (1968) Items.reference_to_cite: "Clark, J. M., & Paivio, A. (2004). Extensions of the Paivio, Yuille, and Madigan (1968) norms. Behavior Research Methods, Instruments, and Computers, 36 (3), 371-383"url_information: "Authors' website ( http://io.uwinnipeg.ca/~clark/cog/norms/cp2004.html ), http://psychonomic.org"public_note: > Note 1. Log10 of values obtained from John Benjafield and described in Keenan, T. R., & Benjafield, J. G. (1994). An additional measure of availability derived from the Oxford English Dictionary. Psychonomic Bulletin & Review, 1, 255-257. Reprinted with permission. Note 2. Log10 of values obtained from David Rubin and descripted in Rubin, D. C., & Friendly, M. (1986). Predicting which words get recalled: Measures of free recall, availability, goodness, emotionality, and pronounceability for 925 nouns. Memory & Cognition, 14, 79-94. Reprinted with permission. Note 3. Values obtained from Paivio, A. U., Yuille, J. C., & Madigan, S. A. (1968). Concreteness, imagery, and meaningfulness values for 925 nouns. Journal of Experimental Psychology, 76(1, PT. 2), 1-25. Reprinted with permission of American Psychological Association and Allan Paivio."</div
Inferring sexually deviant behavior from corresponding fantasies: The role of personality and pornography consumption
No full textThere is widespread concern that deviant sexual fantasies promote corresponding behaviors. The authors investigated whether that concern is valid in nonoffender samples. Self-reports of nine deviant sexual fantasies and behaviors were compared in two samples of male undergraduates. In Study 1, 95% of respondents reported experiencing at least one sexually deviant fantasy, and 74% reported engaging in at least one sexually deviant behavior. The correlations were all positive and averaged .44. However, only 38% of the high-fantasy group reported acting out fantasies. The effect of pornography use on deviant behaviors was partially mediated by increases in deviant fantasies. Study 2 investigated possible moderators, including eight personality variables. The fantasy-behavior association held only for those high in self-reported psychopathy. In addition, the association between pornography use and deviant sexual behavior held only for participants high in psychopathy. Overall, theoretically relevant individual difference variables moderated the relation between sexually deviant fantasies and behaviors and between pornography use and deviant behaviors.Peer reviewedFinal article publishedsexual deviancesexual fantasiesparaphiliaspornographypsychopath
A comparison of treatment adherence in individuals with a first episode of psychosis and inpatients with psychosis
No full textIn predicting treatment compliance in individuals with severe mental illness, research has focused on variables such as substance abuse, personality, history of child abuse, and symptomatology, although these relationships have not been investigated in great detail in individuals at the onset of mental illness. To better understand these correlates of treatment compliance, two samples were examined: a sample of 117 individuals presenting with a first episode of psychosis and a more chronic forensic sample of 65 participants recruited from a psychiatric hospital. These samples were investigated for service engagement in terms of violence history, substance abuse, symptom severity, psychopathic traits and history of childhood abuse. Linear regressions performed for the first episode sample revealed that childhood physical abuse was the strongest predictor of poor service engagement, followed by problems with alcohol, a history of physical violence, any history of violence and higher psychopathic traits. Linear regression revealed for the forensic group that a lower level of service engagement was most strongly predicted by a history of childhood abuse and a higher score on the Brief Psychiatric Rating Scale (BPRS). Results are presented in light of the existing literature and clinical implications are discussed.Peer reviewedFinal article publishedCompliancePsychosisTraumaViolence and psychopath
Advanced biobanking and good management
No full textThis paper has three main propositions. First, the success of translational research requires changes in practice and culture by universities, hospitals and industry. Second, biobanking networks are one of the most effective ways of enabling those changes – if the networks have standards that can reach across universities, hospitals and industry. Third, a network quality management system based on ISO9001 requirements can be an effective tool to drive the changes required for a biobanking network to function. The goal of academic biomedical research has been to serve a scientific good: to understand the human organism in health and disease. The goal of clinical and industrial research has been to serve a public good: to develop and innovate for the alleviation of human disease and ill-health. Today, in the rapidly changing landscape of biomedical research, academic researchers are capable of and are being encouraged by society to address both goals. To address two goals in place of one goal requires changes in work practices by, and shifts in culture of, academia, clinicians and industry. One important change in practices is due to large research infrastructures whose use is also driving cultural shifts. One basic research infrastructure – the biobanking network – can provide large-scale sample management to support the analysis and meta-analysis of biomarkers required across translational research - from research to development to innovation. The EU and some Member States have made progress in constructing such a network. The problem of ensuring consistency and interoperability across network has not been fully resolved. In the UK, an academic national DNA banking network introduced a system to promote consistency and interoperability - an ISO9001 quality management system - driven by the need for stakeholder engagement. Recently, this system was overhauled to create for the first time a Quality Network Management System (QNMS). This may be one of the most effective ways of achieving the changes in practices and culture that we require for successful translation to improved health of populations
Advanced biobanking and good management
No full textThis paper has three main propositions. First, the success of translational research requires changes in practice and culture by universities, hospitals and industry. Second, biobanking networks are one of the most effective ways of enabling those changes – if the networks have standards that can reach across universities, hospitals and industry. Third, a network quality management system based on ISO9001 requirements can be an effective tool to drive the changes required for a biobanking network to function. The goal of academic biomedical research has been to serve a scientific good: to understand the human organism in health and disease. The goal of clinical and industrial research has been to serve a public good: to develop and innovate for the alleviation of human disease and ill-health. Today, in the rapidly changing landscape of biomedical research, academic researchers are capable of and are being encouraged by society to address both goals. To address two goals in place of one goal requires changes in work practices by, and shifts in culture of, academia, clinicians and industry. One important change in practices is due to large research infrastructures whose use is also driving cultural shifts. One basic research infrastructure – the biobanking network – can provide large-scale sample management to support the analysis and meta-analysis of biomarkers required across translational research - from research to development to innovation. The EU and some Member States have made progress in constructing such a network. The problem of ensuring consistency and interoperability across network has not been fully resolved. In the UK, an academic national DNA banking network introduced a system to promote consistency and interoperability - an ISO9001 quality management system - driven by the need for stakeholder engagement. Recently, this system was overhauled to create for the first time a Quality Network Management System (QNMS). This may be one of the most effective ways of achieving the changes in practices and culture that we require for successful translation to improved health of populations
Advanced biobanking and good management
No full textThis paper has three main propositions. First, the success of translational research requires changes in practice and culture by universities, hospitals and industry. Second, biobanking networks are one of the most effective ways of enabling those changes – if the networks have standards that can reach across universities, hospitals and industry. Third, a network quality management system based on ISO9001 requirements can be an effective tool to drive the changes required for a biobanking network to function. The goal of academic biomedical research has been to serve a scientific good: to understand the human organism in health and disease. The goal of clinical and industrial research has been to serve a public good: to develop and innovate for the alleviation of human disease and ill-health. Today, in the rapidly changing landscape of biomedical research, academic researchers are capable of and are being encouraged by society to address both goals. To address two goals in place of one goal requires changes in work practices by, and shifts in culture of, academia, clinicians and industry. One important change in practices is due to large research infrastructures whose use is also driving cultural shifts. One basic research infrastructure – the biobanking network – can provide large-scale sample management to support the analysis and meta-analysis of biomarkers required across translational research - from research to development to innovation. The EU and some Member States have made progress in constructing such a network. The problem of ensuring consistency and interoperability across network has not been fully resolved. In the UK, an academic national DNA banking network introduced a system to promote consistency and interoperability - an ISO9001 quality management system - driven by the need for stakeholder engagement. Recently, this system was overhauled to create for the first time a Quality Network Management System (QNMS). This may be one of the most effective ways of achieving the changes in practices and culture that we require for successful translation to improved health of populations
T-cell prolymphocytic leukemia (T-PLL)
No full textReview on T-cell prolymphocytic leukemia (T-PLL), with data on clinics, and the genes involved
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