Regulation of motor vehicle advertising: toward a framework for compliance research

There is concern that certain content within some motor vehicle television advertising may negatively influence the driving attitudes and behaviours of viewers, particularly young people, and hence have a negative impact on road safety. In recognition of this concern, many developed countries have adopted a self-regulatory approach to motor vehicle advertising. The basic elements of self-regulation are a code of practice or guiding principles governing advertising content and the establishment of a process for hearing and adjudicating complaints about alleged breaches of that code. However, as in other areas, the effectiveness of self-regulation is being questioned in that many motor vehicle advertisements in Australia and elsewhere appear non-compliant with self-regulatory codes. Applying lessons from studies of alcohol advertising, this paper first reviews the research assessing the content of motor vehicle advertising. A suggested research framework is then proposed to inform the development of motor vehicle advertising regulatory codes where they do not exist, and to better monitor compliance with codes where they do exist. The research framework suggested includes expert content analysis of ads, the impact of advertising on risk-taking cognitions and decisions in computer-simulated traffic situations, and assessing audience perceptions of, and reactions to, messages in advertisements mapped against regulatory code content. An example of audience reaction research is also presented

Creation, Coordination, and Activation of Resources in Physics and Mathematics Learning

This project seeks to study introductory college level courses in physics, mechanics, and mathematics. The research questions involve the processes by which students become able to use resources across contexts (such as between mathematics and physics), how ideas in math and physics form a resource network, and what mechanisms trigger individual resources or coordinated networks. The researcher will conduct clinical interviews, small group interviews, and statistical analysis of survey questions as well as videos from classroom and help sessions. The data being collected would be analyzed for purpose of describing the development of students as they refine skills in mathematics and physical reasoning. A small group of students (15) at the University of Maine will be the subject of the study.The outcome of this project is expected to be a better model of student reasoning and learning . The reviewers were particularly interested in the possibly useful observations about the connections between mathematics and physics learning. Papers would be prepared for all education research associations, including physics

Simulation-Based Height of Burst Map for Asteroid Airburst Damage Prediction

Entry and breakup models predict that airburst in the Earth's atmosphere is likely for asteroids up to approximately 200 meters in diameter. Objects of this size can deposit over 250 megatons of energy into the atmosphere. Fast-running ground damage prediction codes for such events rely heavily upon methods developed from nuclear weapons research to estimate the damage potential for an airburst at altitude. (Collins, 2005; Mathias, 2017; Hills and Goda, 1993). In particular, these tools rely upon the powerful yield scaling laws developed for point-source blasts that are used in conjunction with a Height of Burst (HOB) map to predict ground damage for an airburst of a specific energy at a given altitude. While this approach works extremely well for yields as large as tens of megatons, it becomes less accurate as yields increase to the hundreds of megatons potentially released by larger airburst events. This study revisits the assumptions underlying this approach and shows how atmospheric buoyancy becomes important as yield increases beyond a few megatons. We then use large-scale three-dimensional simulations to construct numerically generated height of burst maps that are appropriate at the higher energy levels associated with the entry of asteroids with diameters of hundreds of meters. These numerically generated HOB maps can then be incorporated into engineering methods for damage prediction, significantly improving their accuracy for asteroids with diameters greater than 80-100 m

Minimizing the overlap problem in protein NMR: a computational framework for precision amino acid labeling

Motivation: Recent advances in cell-free protein expression systems allow specific labeling of proteins with amino acids containing stable isotopes (¹⁵N, ¹³C and ²H), an important feature for protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. Given this labeling ability, we present a mathematical optimization framework for designing a set of protein isotopomers, or labeling schedules, to reduce the congestion in the NMR spectra. The labeling schedules, which are derived by the optimization of a cost function, are tailored to a specific protein and NMR experiment. Results: For 2D ¹⁵N-¹H HSQC experiments, we can produce an exact solution using a dynamic programming algorithm in under 2 h on a standard desktop machine. Applying the method to a standard benchmark protein, calmodulin, we are able to reduce the number of overlaps in the 500 MHZ HSQC spectrum from 10 to 1 using four samples with a true cost function, and 10 to 4 if the cost function is derived from statistical estimates. On a set of 448 curated proteins from the BMRB database, we are able to reduce the relative percent congestion by 84.9% in their HSQC spectra using only four samples. Our method can be applied in a high-throughput manner on a proteomic scale using the server we developed. On a 100-node cluster, optimal schedules can be computed for every protein coded for in the human genome in less than a month. Availability: A server for creating labeling schedules for ¹⁵N-¹H HSQC experiments as well as results for each of the individual 448 proteins used in the test set is available at http://nmr.proteomics.ics.uci.edu

A deterministic model predicts the properties of stochastic calcium oscillations in airway smooth muscle cells

The inositol trisphosphate receptor ([Formula: see text]) is one of the most important cellular components responsible for oscillations in the cytoplasmic calcium concentration. Over the past decade, two major questions about the [Formula: see text] have arisen. Firstly, how best should the [Formula: see text] be modeled? In other words, what fundamental properties of the [Formula: see text] allow it to perform its function, and what are their quantitative properties? Secondly, although calcium oscillations are caused by the stochastic opening and closing of small numbers of [Formula: see text], is it possible for a deterministic model to be a reliable predictor of calcium behavior? Here, we answer these two questions, using airway smooth muscle cells (ASMC) as a specific example. Firstly, we show that periodic calcium waves in ASMC, as well as the statistics of calcium puffs in other cell types, can be quantitatively reproduced by a two-state model of the [Formula: see text], and thus the behavior of the [Formula: see text] is essentially determined by its modal structure. The structure within each mode is irrelevant for function. Secondly, we show that, although calcium waves in ASMC are generated by a stochastic mechanism, [Formula: see text] stochasticity is not essential for a qualitative prediction of how oscillation frequency depends on model parameters, and thus deterministic [Formula: see text] models demonstrate the same level of predictive capability as do stochastic models. We conclude that, firstly, calcium dynamics can be accurately modeled using simplified [Formula: see text] models, and, secondly, to obtain qualitative predictions of how oscillation frequency depends on parameters it is sufficient to use a deterministic model

A prospective adaptive utility trial to validate performance of a novel urine exosome gene expression assay to predict high-grade prostate cancer in patients with prostate-specific antigen 2-10ng/ml at initial biopsy

BACKGROUND: Discriminating indolent from clinically significant prostate cancer (PCa) in the initial biopsy setting remains an important issue. Prospectively evaluated diagnostic assays are necessary to ensure efficacy and clinical adoption. OBJECTIVE: Performance and utility assessment of ExoDx Prostate (IntelliScore) (EPI) urine exosome gene expression assay versus standard clinical parameters for discriminating Grade Group (GG) ≥2 PCa from GG1 PCa and benign disease on initial biopsy. DESIGN, SETTING, AND PARTICIPANTS: A two-phase adaptive clinical utility study (NCT03031418) comparing EPI results with biopsy outcomes in men, with age ≥50 yr and prostate-specific antigen (PSA) 2-10ng/ml, scheduled for initial prostate biopsy. After EPI performance assessment during phase I, a clinical implementation document (ie, CarePath) was developed for utilizing the EPI test in phase II, where the biopsy decision is uncertain. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Performance evaluation of the EPI test in patients enrolled in phase I and publication of a consensus CarePath for phase II. RESULTS AND LIMITATIONS: In a total of 503 patients, with median age of 64 yr, median PSA 5.4ng/ml, 14% African American, 70% Caucasian, 53% positive biopsy rate (22% GG1, 17% GG2, and 15% ≥ GG3), EPI was superior to an optimized model of standard clinical parameters with an area under the curve (AUC) 0.70 versus 0.62, respectively, comparable with previously published results (n=519 patients, EPI AUC 0.71). Validated cut-point 15.6 would avoid 26% of unnecessary prostate biopsies and 20% of total biopsies, with negative predictive value (NPV) 89% and missing 7% of ≥GG2 PCa. Alternative cut-point 20 would avoid 40% of unnecessary biopsies and 31% of total biopsies, with NPV 89% and missing 11% of ≥GG2 PCa. The clinical investigators reached consensus recommending use of the 15.6 cut-point for phase II. Outcome of the decision impact cohort in phase II will be reported separately. CONCLUSIONS: EPI is a noninvasive, easy-to-use, gene expression urine assay, which has now been successfully validated in over 1000 patients across two prospective validation trials to stratify risk of ≥GG2 from GG1 cancer and benign disease. The test improves identification of patients with higher grade disease and would reduce the total number of unnecessary biopsies. PATIENT SUMMARY: It is challenging to predict which men are likely to have high-grade prostate cancer (PCa) at initial biopsy with prostate-specific antigen 2-10ng/ml. This study further demonstrates that the ExoDx Prostate (IntelliScore) test can predict ≥GG2 PCa at initial biopsy and defer unnecessary biopsies better than existing risk calculator\u27s and standard clinical data