Rating Forecasts for Television Programs

This paper investigates the effect of aggregation and non-linearity in relation to television rating forecasts. Several linear models for aggregated and disaggregated television viewing have appeared in the literature. The current analysis extends this work using an empirical approach. We compare the accuracy of population rating models, segment rating models and individual viewing behaviour models. Linear and non-linear models are fitted using regression, decision trees and neural networks, with a two-stage procedure being used to model network choice and viewing time for the individual viewing behaviour model. The most accurate forecast results are obtained from the non-linear segment rating models.Decision Trees, Disaggregation, Discrete Choice Models, Neural Networks, Rating Benchmarks

Calculating Chemical Evolution on the Web

We have constructed a web site that may be of interest to cosmochemists seeking to under-stand the evolution of isotopes in the Galaxy. The URL is http://photon.phys.clemson.edu/gce.html. It is fully interactive and uses IDL on the Net (ION) to construct tables and graphs dynamically. The resulting tables may be downloaded as text files while the graphs may be downloaded as gif or postscript files. The present ab-stract presents a brief tutorial on using the “GCE tool” on this site and illustrates some of its capabilities. Ques-tions or comments should be addressed to either of the first two authors

Fusing data mining, machine learning and traditional statistics to detect biomarkers associated with depression

BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. METHODS: The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. RESULTS: After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). CONCLUSION: The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin

My Road Ahead study protocol: a randomised controlled trial of an online psychological intervention for men following treatment for localised prostate cancer

BACKGROUND There is a need for psychosocial interventions for men with prostate cancer to promote adaptive coping with the challenges and distress associated with diagnosis, treatment and recovery. In addition, interventions are needed that help to overcome barriers to psychosocial treatment such as limited face-to-face psychosocial support services, a shortage of adequately trained professionals, geographical distance, perceived and personal stigma and a preference for consumer-centric and self-directed learning. My Road Ahead is an online cognitive behaviour therapy (CBT) intervention for prostate cancer. This protocol describes a randomised controlled trial (RCT) that will evaluate the efficacy of this online intervention alone, the intervention in combination with a moderated online forum, and the moderated online forum alone. METHODS/DESIGN This study utilises a RCT design with three groups receiving: 1) the 6-module My Road Ahead intervention alone; 2) the My Road Ahead intervention plus a moderated online forum; and 3) the moderated online forum alone. It is expected that 150 men with localised prostate cancer will be recruited into the RCT. Online measures will assess men's psychological distress as well as sexual and relationship adjustment at baseline, post-intervention, 3 month follow-up and 6 month follow-up. The study is being conducted in Australia and participants will be recruited from April 2012 to Feb 2014. The primary aim of this study is to evaluate the efficacy of My Road Ahead in reducing psychological distress. DISCUSSION To our knowledge, My Road Ahead is the first self-directed online psychological intervention developed for men who have been treated for localised prostate cancer. The RCT will assess the efficacy of this intervention in improving psychological well-being, sexual satisfaction, relationship satisfaction and overall quality of life. If successful, this intervention could provide much needed support to men receiving treatment for localised prostate cancer in a highly accessible manner. TRIAL REGISTRATION Australian New Zealand Clinical Trials Registry Identifier: ACTRN12611000278932.The authors would like to acknowledge the funding partners involved in this study; the Prostate Cancer Foundation of Australia (PCFA), beyondblue: the National Depression and Anxiety Initiative with funding support from Movember Foundation

Bedrock erosion by root fracture and tree throw: A coupled biogeomorphic model to explore the humped soil production function and the persistence of hillslope soils

In 1877, G. K. Gilbert reasoned that bedrock erosion is maximized under an intermediate soil thickness and declines as soils become thinner or thicker. Subsequent analyses of this “humped” functional relationship proposed that thin soils are unstable and that perturbations in soil thickness would lead to runaway thinning or thickening of the soil. To explore this issue, we developed a numerical model that simulates the physical weathering of bedrock by root fracture and tree throw. The coupled biogeomorphic model combines data on conifer population dynamics, rootwad volumes, tree throw frequency, and soil creep from the Pacific Northwest (USA). Although not hardwired into the model, a humped relationship emerges between bedrock erosion and soil thickness. The magnitudes of the predicted bedrock erosion rates and their functional dependency on soil thickness are consistent with independent field measurements from a coniferous landscape in the region. Imposed perturbations of soil erosion during model runs demonstrate that where bedrock weathering is episodic and localized, hillslope soils do not exhibit runaway thinning or thickening. The pit-and-mound topography created by tree throw produces an uneven distribution of soil thicknesses across a hillslope; thus, although episodes of increased erosion can lead to temporary soil thinning and even the exposure of bedrock patches, local areas of thick soils remain. These soil patches provide habitat for trees and serve as nucleation points for renewed bedrock erosion and soil production. Model results also suggest that where tree throw is a dominant weathering process, the initial mantling of bedrock is not only a vertical process but also a lateral process: soil mounds created by tree throw flatten over time, spreading soil over bedrock surfaces

Photoactivated chemotherapy (PACT) : the potential of excited-state d-block metals in medicine

The fields of phototherapy and of inorganic chemotherapy both have long histories. Inorganic photoactivated chemotherapy (PACT) offers both temporal and spatial control over drug activation and has remarkable potential for the treatment of cancer. Following photoexcitation, a number of different decay pathways (both photophysical and photochemical) are available to a metal complex. These pathways can result in radiative energy release, loss of ligands or transfer of energy to another species, such as triplet oxygen. We discuss the features which need to be considered when developing a metal-based anticancer drug, and the common mechanisms by which the current complexes are believed to operate. We then provide a comprehensive overview of PACT developments for complexes of the different d-block metals for the treatment of cancer, detailing the more established areas concerning Ti, V, Cr, Mn, Re, Fe, Ru, Os, Co, Rh, Pt, and Cu and also highlighting areas where there is potential for greater exploration. Nanoparticles (Ag, Au) and quantum dots (Cd) are also discussed for their photothermal destructive potential. We also discuss the potential held in particular by mixed-metal systems and Ru complexes

WASp-deficient B cells play a critical, cell-intrinsic role in triggering autoimmunity

In a manner dependent on CD4 T cell help and Toll-like receptor signals, B cells lacking WASp induce autoantibody production and autoimmune disease in mice

Postnatal Cytomegalovirus Exposure in Infants of Antiretroviral-Treated and Untreated HIV-Infected Mothers

HIV-1 and CMV are important pathogens transmitted via breastfeeding. Furthermore, perinatal CMV transmission may impact growth and disease progression in HIV-exposed infants. Although maternal antiretroviral therapy reduces milk HIV-1 RNA load and postnatal transmission, its impact on milk CMV load is unclear. We examined the relationship between milk CMV and HIV-1 load (4-6 weeks postpartum) and the impact of antiretroviral treatment in 69 HIV-infected, lactating Malawian women and assessed the relationship between milk CMV load and postnatal growth in HIV-exposed, breastfed infants through six months of age. Despite an association between milk HIV-1 RNA and CMV DNA load (0.39 log 10 rise CMV load per log 10 rise HIV-1 RNA load, 95% CI 0.13-0.66), milk CMV load was similar in antiretroviral-treated and untreated women. Higher milk CMV load was associated with lower length-for-age (−0.53, 95% CI: −0.96, −0.10) and weight-for-age (−0.40, 95% CI: −0.67, −0.13) Zscore at six months in exposed, uninfected infants. As the impact of maternal antiretroviral therapy on the magnitude of postnatal CMV exposure may be limited, our findings of an inverse relationship between infant growth and milk CMV load highlight the importance of defining the role of perinatal CMV exposure on growth faltering of HIV-exposed infants