Advancing Tobacco Product Warning Labels Research Methods and Theory: A Summary of a Grantee Meeting Held by the US National Cancer Institute

BACKGROUND: The World Health Organization's Framework Convention on Tobacco Control recommends prominent pictorial health warnings on tobacco products. To advance research methods, theory and understanding of how tobacco product warning labels (TPWLs) work, the US National Cancer Institute convened a grantee meeting. Our article describes the key insights that emerged from the meeting, situated within the context of the scientific literature. RESULTS & RECOMMENDATIONS: First, presentations confirmed that large, pictorial TPWLs motivate people to try to quit and encourage smoking cessation. Second, pictorial TPWLs increase attention, knowledge, negative affect, and thinking about the warning. Third, TPWL studies have primarily used brief-exposure laboratory studies and observational studies of sustained exposure through national policy implementation, with a few randomized trials involving several weeks of exposure-with generally consistent results found across study designs. Fourth, novel assessment methods include brain imaging, eye tracking and "best-worst" discrete choice experiments. To make TPWL even more effective, research is needed to confirm the mechanisms of their influence, their impact across vulnerable populations, and their effect on social media posts about tobacco products. Research is also needed on the effect of trial design choices, the predictive validity of new measurement approaches, and warning labels for non-cigarette tobacco products. IMPLICATIONS: To improve scientific understanding of TPWL effects, this grantee meeting summary describes emerging research methods, theory and study results. Directions for future research include examination of the mechanisms of how warning labels work across diverse tobacco products and across different populations and contexts

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

Applications of Real-Time Simulation Technologies in Power and Energy Systems

Real-time (RT) simulation is a highly reliable simulation method that is mostly based on electromagnetic transient simulation of complex systems comprising many domains. It is increasingly used in power and energy systems for both academic research and industrial applications. Due to the evolution of the computing power of RT simulators in recent years, new classes of applications and expanded fields of practice could now be addressed with RT simulation. This increase in computation power implies that models can be built more accurately and the whole simulation system gets closer to reality. This Task Force paper summarizes various applications of digital RT simulation technologies in the design, analysis, and testing of power and energy systems

Modeling of the condyle elements within a biomechanical knee model

The development of a computational multibody knee model able to capture some of the fundamental properties of the human knee articulation is presented. This desideratum is reached by including the kinetics of the real knee articulation. The research question is whether an accurate modeling of the condyle contact in the knee will lead to reproduction of the complex combination of flexion/extension, abduction/adduction and tibial rotation ob-served in the real knee? The model is composed by two anatomic segments, the tibia and the femur, whose characteristics are functions of the geometric and anatomic properties of the real bones. The biomechanical model characterization is developed under the framework of multibody systems methodologies using Cartesian coordinates. The type of approach used in the proposed knee model is the joint surface contact conditions between ellipsoids, represent-ing the two femoral condyles, and points, representing the tibial plateau and the menisci. These elements are closely fitted to the actual knee geometry. This task is undertaken by con-sidering a parameter optimization process to replicate experimental data published in the lit-erature, namely that by Lafortune and his co-workers in 1992. Then, kinematic data in the form of flexion/extension patterns are imposed on the model corresponding to the stance phase of the human gait. From the results obtained, by performing several computational simulations, it can be observed that the knee model approximates the average secondary mo-tion patterns observed in the literature. Because the literature reports considerable inter-individual differences in the secondary motion patterns, the knee model presented here is also used to check whether it is possible to reproduce the observed differences with reasonable variations of bone shape parameters. This task is accomplished by a parameter study, in which the main variables that define the geometry of condyles are taken into account. It was observed that the data reveal a difference in secondary kinematics of the knee in flexion ver-sus extension. The likely explanation for this fact is the elastic component of the secondary motions created by the combination of joint forces and soft tissue deformations. The proposed knee model is, therefore, used to investigate whether this observed behavior can be explained by reasonable elastic deformations of the points representing the menisci in the model.Fundação para a Ciência e a Tecnologia (FCT) - PROPAFE – Design and Development of a Patello-Femoral Prosthesis (PTDC/EME-PME/67687/2006), DACHOR - Multibody Dynamics and Control of Hybrid Active Orthoses MIT-Pt/BSHHMS/0042/2008, BIOJOINTS - Development of advanced biological joint models for human locomotion biomechanics (PTDC/EME-PME/099764/2008)

HCC recurrence in HCV-infected patients after liver transplantation: SiLVER Study reveals benefits of sirolimus in combination with CNIs - a post-hoc analysis

Factors affecting outcomes in liver transplant (LTx) recipients with hepatocellular carcinoma (HCC) and hepatitis C viral (HCV) infection include the choice of immunosuppression. Here, we analyzed the HCV+ subgroup of patients from the randomized controlled, international SiLVER Study. We performed a post hoc analysis of 166 HCV+ SiLVER Study patients regarding HCC outcome after LTx. Control patients (group A: n = 88) received mTOR inhibitor (mTORi)-free, calcineurin inhibitor (CNI)-based versus sirolimus-based immunosuppression (group B: n = 78). We found no significant difference regarding HCV-RNA titers between group A and B. Since no effect in group B could be due to variable sirolimus dosing, we split group B into patients receiving sirolimus-based immunosuppression + CNIs for >50% (B1; n = 44) or <50% (B2; n = 34) of the time. While there remained no difference in HCV-RNA titer between groups, HCC recurrence-free survival in group B1 (81.8%) was markedly better versus both group A (62.7%; P = 0.0136) and group B2 (64.7%; P = 0.0326); Interestingly, further subgroup analysis revealed an increase (P = 0.0012) in liver enzyme values in group B2. Taken together, in HCV-infected patients with HCC and LTx, mTORi immunosuppression + CNIs yields excellent outcomes. Unexpectedly, higher levels of liver inflammation and poorer outcomes occur with mTORi monotherapy in the HCV+ subgroup

A review of literature on the use of clickers in the business and management discipline

YesClassroom response systems (clickers), in their various forms, are widely used across disciplines, demonstrating effectiveness across a range of different educational settings. However, only a few literature reviews on this technology have been undertaken in general, and no review has yet been performed on this topic in the business and management context. Realising the existing research gap, this article reviews 33 clicker-related studies from the business and management discipline that are largely focused on student perceptions and outcomes. The purpose of this paper is to provide a critical and balanced review of articles from the business and management discipline on various themes such as learner's engagement, performance, learning, participation, satisfaction, feedback, attendance, enjoyability, motivation, and interactivity, to name a few. The review also provides a brief account of lessons learned from the literature published in other disciplines and recommendations provided by studies from the business and management discipline

Visual attention to anti-smoking PSAs: smoking cues versus other attention-grabbing features

This study examines how addicted smokers attend visually to smoking-related public service announcements (PSAs) in adults smokers. Smokers’ onscreen visual fixation is an indicator of cognitive resources allocated to visual attention. Characteristic of individuals with addictive tendencies, smokers are expected to be appetitively activated by images of their addiction—specifically smoking cues. At the same time, these cues are embedded in messages that associate avoidance responses with these appetitive cues, potentially inducing avoidance of PSA processing. Findings suggest that segments of PSAs that contain smoking cues are processed similarly to segments that contain complex stimuli (operationalized in this case as high in information introduced) and that visual attention is aligned with smoking cues on the screen

Cadmium accumulation and buffering of cadmium-induced stress by arbuscular mycorrhiza in three Pisum sativum L. genotypes

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