The development and application of audit criteria for assessing knowledge exchange plans in health research grant applications.

Background: Research funders expect evidence of end user engagement and impact plans in research proposals. Drawing upon existing frameworks, we developed audit criteria to help researchers and their institutions assess the knowledge exchange plans of health research proposals. Findings: Criteria clustered around five themes: problem definition; involvement of research users; public and patient engagement; dissemination and implementation; and planning, management and evaluation of knowledge exchange. We applied these to a sample of grant applications from one research institution in the United Kingdom to demonstrate feasibility. Conclusion: Our criteria may be useful as a tool for researcher self-assessment and for research institutions to assess the quality of knowledge exchange plans and identify areas for systematic improvement

The use of segmented regression in analysing interrupted time series studies : an example in pre-hospital ambulance care

Peer reviewedPublisher PD

The Relationship Between CO2 Levels and CO2 Related Symptoms Reported on the ISS

Medical Operations, Toxicology, and the Lifetime Surveillance of Astronaut Health collaborated to assess the association of CO2 levels on board the International Space Station and USOS crew reported symptoms inflight, i.e. headache and vision changes. Private Medical Conference (PMC) documents and the weekly Space Medicine Operations Team (SMOT) Notes were used to provide a robust data set of inflight medical events. All events and nonevents were documented independent of CO2 levels and other potential contributors. Average (arithmetic mean) and single point maximum ppCO2 was calculated for the 24 hours and 7 days prior to the PMC or SMOT date and time provided by LSAH. Observations falling within the first 7 days of flight (147) were removed from the datasets analyzed to avoid confounding with Space Adaptation Syndrome. The final analysis was based on 1716 observations. For headache, 46 headaches were observed. CO2 level, age at launch, time inflight, and data source were all significantly associated with headache. In particular, for each 1 mmHg increase in CO2, the odds of a crewmember reporting a headache doubled. For vision changes, 29 reports of vision changes were observed. These observations were not found to be statistically associated with CO2 levels as analyzed. While the incidence of headache has was not high (~3%), headaches may be an indicator of underlying increases in intracranial pressure, which may result likely from the synergy between CO2induced cerebral vasodilatation and decreased venous drainage in microgravity. Vision changes were inconsistently reported and as a result did not align appropriately with the CO2 levels. Further analysis is needed. Our results support ongoing efforts to lower the CO2 exposure limits in spacecraft

Electrodynamics of Magnetic Pulse Welding Machines: Global and Local Electrical Analogues

In this paper, a theoretical, experimental and numerical study of MPW machines is carried out. While it is known that such machines are very complex by nature because of the coupling between different parts, we used simple electrical analogues to describe its dynamics. A RLC circuit modeling the whole machine is depicted and experimental results are shown. A further study including numerical simulations allows to compute the current distribution and estimate the magnetic field within the coil but also the magnetic pressure generated in the process, all using a 2D model and reasonable assumptions. A late theoretical study opens the way for innovative experimental measurements regarding the kinetics of the deformations of metallic tubes, but also their mechanical behavior before the welding process, making use of their capacitive properties

Aerosol composition and source apportionment in the Mexico City Metropolitan Area with PIXE/PESA/STIM and multivariate analysis

International audienceAerosols play an important role in the atmosphere but are poorly characterized, particularly in urban areas like the Mexico City Metropolitan Area (MCMA). The chemical composition of urban particles must be known to assess their effects on the environment, and specific particulate emissions sources should be identified to establish effective pollution control standards. For these reasons, samples of particulate matter ?2.5 ?m (PM2.5) were collected during the MCMA-2003 Field Campaign for elemental and multivariate analyses. Proton-Induced X-ray Emission (PIXE), Proton-Elastic Scattering Analysis (PESA) and Scanning Transmission Ion Microscopy (STIM) measurements were done to determine concentrations of 19 elements from Na to Pb, hydrogen, and total mass, respectively. The most abundant elements from PIXE analysis were S, Si, K, Fe, Ca, and Al, while the major emissions sources associated with these elements were industry, wind-blown soil, and biomass burning. Wind trajectories suggest that metals associated with industrial emissions came from northern areas of the city whereas soil aerosols came from the southwest and increased in concentration during dry conditions. Elemental markers for fuel oil combustion, V and Ni, correlated with a large SO2 plume to suggest an anthropogenic, rather than volcanic, emissions source. By subtracting major components of soil and sulfates determined by PIXE analysis from STIM total mass measurements, we estimate that approximately 50% of non-volatile PM2.5 consisted of carbonaceous material

Missing Data and Multiple Imputation: An Unbiased Approach

The default method of dealing with missing data in statistical analyses is to only use the complete observations (complete case analysis), which can lead to unexpected bias when data do not meet the assumption of missing completely at random (MCAR). For the assumption of MCAR to be met, missingness cannot be related to either the observed or unobserved variables. A less stringent assumption, missing at random (MAR), requires that missingness not be associated with the value of the missing variable itself, but can be associated with the other observed variables. When data are truly MAR as opposed to MCAR, the default complete case analysis method can lead to biased results. There are statistical options available to adjust for data that are MAR, including multiple imputation (MI) which is consistent and efficient at estimating effects. Multiple imputation uses informing variables to determine statistical distributions for each piece of missing data. Then multiple datasets are created by randomly drawing on the distributions for each piece of missing data. Since MI is efficient, only a limited number, usually less than 20, of imputed datasets are required to get stable estimates. Each imputed dataset is analyzed using standard statistical techniques, and then results are combined to get overall estimates of effect. A simulation study will be demonstrated to show the results of using the default complete case analysis, and MI in a linear regression of MCAR and MAR simulated data. Further, MI was successfully applied to the association study of CO2 levels and headaches when initial analysis showed there may be an underlying association between missing CO2 levels and reported headaches. Through MI, we were able to show that there is a strong association between average CO2 levels and the risk of headaches. Each unit increase in CO2 (mmHg) resulted in a doubling in the odds of reported headaches

Mexico City basin wind circulation during the MCMA-2003 field campaign

International audienceMCMA-2003 was a major field campaign investigating the atmospheric chemistry of the Mexico City Metropolitan Area (MCMA) in April of 2003. This paper describes the wind circulation patterns during the campaign both within the Mexico City basin and on the regional scale. ''Time roses'' are introduced to concisely analyze the diurnal wind patterns. Three episode types were identified that explain the conditions encountered: ''O3-South'', ''Cold Surge'' and ''O3-North''. These can be diagnosed from a combination of synoptic and basin observations based on whether the day was predominantly cloudy, or whether the O3 peak was in the north or south of the basin. O3-South days have weak synoptic forcing due to an anti-cyclone over the eastern Pacific. Strong solar heating leads to northerly flows in the basin and an evening shift due to a gap flow from the south-east. Peak ozone concentrations are in the convergence zone in the south of the city. Cold Surge days are associated with ''El Norte'' events, with strong surface northerlies bringing cold moist air and rain. Stable conditions lead to high concentrations of primary pollutants and peak ozone in the city center. O3-North days occur when the sub-tropical jet is closer to Mexico City. With strong westerlies aloft, the circulation pattern is the same as O3-South days except for a wind shift in the mid-afternoon leading to ozone peaks in the north of the city. This classification is proposed as a means of understanding pollutant transport in the Mexico City basin and as a basis for future meteorological and chemical analysis. Furthermore, model evaluation and design of policy recommendations will need to take into account the three episode types

Adaptive Optics for Astronomy

Adaptive Optics is a prime example of how progress in observational astronomy can be driven by technological developments. At many observatories it is now considered to be part of a standard instrumentation suite, enabling ground-based telescopes to reach the diffraction limit and thus providing spatial resolution superior to that achievable from space with current or planned satellites. In this review we consider adaptive optics from the astrophysical perspective. We show that adaptive optics has led to important advances in our understanding of a multitude of astrophysical processes, and describe how the requirements from science applications are now driving the development of the next generation of novel adaptive optics techniques.Comment: to appear in ARA&A vol 50, 201

Challenges in Evaluating Relationships Between Quantitative Data (Carbon Dioxide) and Qualitative Data (Self-Reported Visual Changes)

Understanding the nuances in clinical data is critical in developing a successful data analysis plan. Carbon dioxide (CO2) data are collected on board the International Space Station (ISS) in a continuous stream. Clinical data on ISS are primarily collected via conversations between individual crewmembers and NASA Flight Surgeons during weekly Private Medical Conferences (PMC). Law, et.al, 20141 demonstrated a statistically significant association between weekly average CO2 levels on ISS and self-reported headaches over the reporting period from March 14, 2001 to May 31, 2012. The purpose of this analysis is to describe the evaluation of a possible association between visual changes and CO2 levels on ISS and to discuss challenges in developing an appropriate analysis plan. METHODS & PRELIMINARY RESULTS: A first analysis was conducted following the same study design as the published work on CO2 and self-reported headaches1; substituting self-reported changes in visual acuity in place of self-reported headaches. The analysis demonstrated no statistically significant association between visual impairment characterized by vision symptoms self-reported during PMCs and ISS average CO2 levels over ISS missions. Closer review of the PMC records showed that vision outcomes are not well-documented in terms of clinical severity, timing of onset, or timing of resolution, perhaps due to the incipient nature of vision changes. Vision has been monitored in ISS crewmembers, pre- and post-flight, using standard optometry evaluations. In-flight visual assessments were limited early in the ISS program, primarily consisting of self-perceived changes reported by crewmembers. Recently, on-orbit capabilities have greatly improved. Vision data ranges from self-reported post-flight changes in visual acuity, pre- to postflight changes identified during fundoscopic examination, and in-flight progression measured by advanced on-orbit clinical imaging capabilities at predetermined testing intervals. In contrast, CO2 data are recorded in a continuous stream over time; however, for the initial analysis this data was categorized into weekly averages