Enhancing engagement in evidence-based tobacco cessation treatment for smokers with mental illness: A pilot randomized trial.

ObjectiveTo evaluate the efficacy of a brief telephone-delivered Motivational Interviewing (MI)-based intervention to facilitate engagement in evidence-based cessation treatment for Veterans with mental illness referred to smoking cessation treatment.Methods86 military Veteran smokers with mental illness were recruited from a tobacco cessation consult clinic and randomized to receive either a MI-based treatment engagement intervention (TE; n = 48) or a non-MI assessment and information control (CON; n = 38) condition. Intervention was delivered during a single brief telephone contact. Primary engagement outcomes were 1) attending a treatment session within 30 days and 2) combination treatment (attending session plus using pharmacotherapy). Cessation outcomes included self-reported 24 h cessation attempts and 7 day point abstinence at 3 months post-intervention. Outcomes were assessed at 1 and 3 months post intervention.ResultsOutcome analyses included 85 participants (47 TE, 38 CON) using an intent-to-treat analytic approach. Participants were on average 49.5 (13.4) years old, 88% Male, 59% white, 18% African American and 14% Hispanic/Latino(a). Following intervention delivery TE and CON participants did not differ on likelihood of attending a treatment session during the subsequent 30 days (47% vs 45%, respectively). A significant difference was observed when classified as utilizing combination treatment, 40% of TE versus 18% of CON reported use of smoking cessation medication and behavioral counseling (p = 0.04). No statistical differences were observed for cessation outcomes, although more TE than CON participants reported 7 day point abstinence at 3 months post-intervention (30% vs 18%).ConclusionsThe present pilot study provides initial evidence for the feasibility, acceptability and efficacy of a telephone delivered TE intervention for enhancing engagement in combinationevidence evidence-based treatment in a sample of Veteran smokers with mental illness referred to smoking cessation treatment. Smokers with mental illness typically have greater difficulty stopping smoking than those without mental illness. Increased engagement in combination treatment thus has the potential to increase quit rates and ultimately reduce the burden of tobacco use for this population

Freight logistics services for rural economies : User needs and future challenges

Peer reviewedPublisher PD

Reflection Symmetries for Multiqubit Density Operators

For multiqubit density operators in a suitable tensorial basis, we show that a number of nonunitary operations used in the detection and synthesis of entanglement are classifiable as reflection symmetries, i.e., orientation changing rotations. While one-qubit reflections correspond to antiunitary symmetries, as is known for example from the partial transposition criterion, reflections on the joint density of two or more qubits are not accounted for by the Wigner Theorem and are well-posed only for sufficiently mixed states. One example of such nonlocal reflections is the unconditional NOT operation on a multiparty density, i.e., an operation yelding another density and such that the sum of the two is the identity operator. This nonphysical operation is admissible only for sufficiently mixed states.Comment: 9 page

Measurement of the α Asymmetry Parameter for the Ω-→ΛK- Decay

We have measured the α parameter of the Ω-→ΛK- decay using data collected with the HyperCP spectrometer during the 1997 fixed-target run at Fermilab. Analyzing a sample of 0.96×106 Ω-→ΛK-, Λ→pπ- decays, we obtain αΩαΛ=[1.33±0.33(stat)±0.52(syst)]×10-2. With the accepted value ofαΛ, αΩ is found to be [2.07±0.51(stat)±0.81(syst)]×10-2

Visualising the structure of document search results: A comparison of graph theoretic approaches

This is the post-print of the article - Copyright @ 2010 Sage PublicationsPrevious work has shown that distance-similarity visualisation or ‘spatialisation’ can provide a potentially useful context in which to browse the results of a query search, enabling the user to adopt a simple local foraging or ‘cluster growing’ strategy to navigate through the retrieved document set. However, faithfully mapping feature-space models to visual space can be problematic owing to their inherent high dimensionality and non-linearity. Conventional linear approaches to dimension reduction tend to fail at this kind of task, sacrificing local structural in order to preserve a globally optimal mapping. In this paper the clustering performance of a recently proposed algorithm called isometric feature mapping (Isomap), which deals with non-linearity by transforming dissimilarities into geodesic distances, is compared to that of non-metric multidimensional scaling (MDS). Various graph pruning methods, for geodesic distance estimation, are also compared. Results show that Isomap is significantly better at preserving local structural detail than MDS, suggesting it is better suited to cluster growing and other semantic navigation tasks. Moreover, it is shown that applying a minimum-cost graph pruning criterion can provide a parameter-free alternative to the traditional K-neighbour method, resulting in spatial clustering that is equivalent to or better than that achieved using an optimal-K criterion

Accounting for changing temperature patterns increases historical estimates of climate sensitivity

Eight atmospheric general circulation models (AGCMs) are forced with observed historical (1871–2010) monthly sea surface temperature and sea ice variations using the Atmospheric Model Intercomparison Project II data set. The AGCMs therefore have a similar temperature pattern and trend to that of observed historical climate change. The AGCMs simulate a spread in climate feedback similar to that seen in coupled simulations of the response to CO2 quadrupling. However, the feedbacks are robustly more stabilizing and the effective climate sensitivity (EffCS) smaller. This is due to a pattern effect, whereby the pattern of observed historical sea surface temperature change gives rise to more negative cloud and longwave clear‐sky feedbacks. Assuming the patterns of long‐term temperature change simulated by models, and the radiative response to them, are credible; this implies that existing constraints on EffCS from historical energy budget variations give values that are too low and overly constrained, particularly at the upper end. For example, the pattern effect increases the long‐term Otto et al. (2013, https://doi.org/10.1038/ngeo1836) EffCS median and 5–95% confidence interval from 1.9 K (0.9–5.0 K) to 3.2 K (1.5–8.1 K

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators

Biophysics at the coffee shop: lessons learned working with George Oster

Over the past 50 years, the use of mathematical models, derived from physical reasoning, to describe molecular and cellular systems has evolved from an art of the few to a cornerstone of biological inquiry. George Oster stood out as a pioneer of this paradigm shift from descriptive to quantitative biology not only through his numerous research accomplishments, but also through the many students and postdocs he mentored over his long career. Those of us fortunate enough to have worked with George agree that his sharp intellect, physical intuition and passion for scientific inquiry not only inspired us as scientists but also greatly influenced the way we conduct research. We would like to share a few important lessons we learned from George in honor of his memory and with the hope that they may inspire future generations of scientists.Comment: 22 pages, 3 figures, accepted in Molecular Biology of the Cel