Bridging scientist and practitioner perspectives in clinical psychology.

Literature suggests that a complex and often hostile relationship exists between the science and practice of clinical psychology. Contributors to this conflict of viewpoints are reconsidered within the proposition that there are different roads to discovery and that there may be good reasons to keep the science and practice of clinical psychology somewhat separate. Results of a national survey of 325 psychologists are reviewed that support the view that psychological practitioners value research and consider their practices to be augmented by scientific findings. However, they are in need of vehicles of communication that will help them translate scientific findings into practice. Results suggest that practitioners do more to understand scientific findings than scientists do to understand the problems that face clinical practitioners. Ways to facilitate communication between and among these groups are considered. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Cross-Border Migration of Hong Kong Residents Under the 'One Country, Two Systems' Policy

Hong Kong is known as a migrant city because its population was sourced from mainland China, and because there has always been outflows of people to overseas countries, especially from the mid-1980s to mid-1990s. Emigration to mainland China has become a significant recent trend. This article discusses this phenomenon in the theoretical contexts of migration and trans-border residential development. It contends that the trend will intensify more quickly than other cross-border movements because the two systems are separated by a political border within one country, and because there are common cultural ties and rapid economic integration.     

News: Titanium dioxide photocatalysis: Treatment hype or hope?

Technology.     

News: Canadian ecological research area faces major funding cuts

Science.     

News: Pilot program will update IRIS health risk database for 11 chemicals

Science.     

The effect of time of day on injury patterns amongst adolescents in Australia

Labour force participation of adolescents in Australia is growing at an unprecedented rate. This increased participation is coupled with a growing realisation of the vulnerability of adolescents in the labour market in terms of occupational injury. Despite recent evidence that time of day may be an important determinant of adolescent injuries, the impact of non-standard and night work on adolescent injury rates has received scant attention to date. The current study addresses this shortcoming by examining injury patterns of 3201 working adolescents in Queensland. Results revealed that female adolescents are 2.5 times more likely to sustain an injury on day shift and 4.71 times more likely to sustain an injury on night shift than their adult counterparts when total work hours are taken into consideration. Similar results were found for male adolescents with an injury to work hours ratio of 2.19 on day shift and 3.05 on night shift. These findings point to the value of considering the temporal pattern of adolescent work in future research aimed at minimising injuries at work and improving the work experience of tomorrow's workforce.     

Computer-assisted techniques to enhance transformative learning in first-year literature courses

When students use computers as learning tools, the whole process of learning, and, indeed, the learners themselves, are transformed. This article illustrates some techniques that foster transformative learning in computer-assisted first-year literature classes: first, a lesson plan on A Valediction: Forbidding Mourning that uses Microsoft Word functions, including format painter, tables, and annotation to explore meaning in context; second, a plan for learners to use subconference options in the Daedalus Interactive Writing Environment to analyze Oedipus Rex; finally, a demonstration of how students engage in a meta-reflection process as they explore Barn Burning with Freelance Graphics.Marguerite Jamieson is an English instructor at Anne Arundel Community College in Arnold, Maryland, and a doctoral student at George Mason University. Her research interests include forming bridges between adult learning theory and contemporary literary theory — especially drawing on transformational learning theory and the work of Mikhail Bakhtin and Lev Vygotsky.Rebecca Kajs holds a doctorate in English from Texas Woman's University with a concentration in rhetoric. For ten years, she taught the use of heuristic tools for reading analysis at the University of Texas at Arlington. She is currently an associate professor of English and Philosophy at Anne Arundel Community College.Anne Agee holds a doctorate in rhetoric from The Catholic University of America. A professor of English and formerly director of the Humanities Computer Center at Anne Arundel Community College, she is currently the college's Coordinator of Instructional Technology. Dr. Agee and Professor Jamieson have collaborated in a study of the learning environment in a computer classroom, the results of which were published in the Fall 1995 issue of Teaching/Learning Conversations. Dr. Agee has also published Using [Daedalus] InterChange as a Teachers' Journal in the Fall 1995 issue of Wings.     

A rapid computational filter for predicting the rate of human renal clearance

In silico models that predict the rate of human renal clearance for a diverse set of drugs, that exhibit both active secretion and net re-absorption, have been produced using three statistical approaches. Partial Least Squares (PLS) and Random Forests (RF) have been used to produce continuous models whereas Classification And Regression Trees (CART) has only been used for a classification model. The best models generated from either PLS or RF produce significant models that can predict acids/zwitterions, bases and neutrals with approximate average fold errors of 3, 3 and 4, respectively, for an independent test set that covers oral drug-like property space. These models contain additional information on top of any influence arising from plasma protein binding on the rate of renal clearance. Classification And Regression Trees (CART) has been used to generate a classification tree leading to a simple set of Renal Clearance Rules (RCR) that can be applied to man. The rules are influenced by lipophilicity and ion class and can correctly predict 60% of an independent test set. These percentages increase to 71% and 79% for drugs with renal clearances of < 0.1 ml/min/kg and > 1 ml/min/kg, respectively. As far as the authors are aware these are the first set of models to appear in the literature that predict the rate of human renal clearance and can be used to manipulate molecular properties leading to new drugs that are less likely to fail due to renal clearance.