This study evaluated the performance of a video-based intervention for improving the belt fit obtained by drivers. Previous laboratory studies have demonstrated that some drivers position their seat belts suboptimally. Specifically, the lap portion of the belt may be higher and farther forward relative to the pelvis than best practice, and the shoulder portion of the belt may be outboard or inboard of mid-shoulder.
A video was developed to present the most important aspects of belt fit best practices, with emphasis on the lap belt. The video demonstrated how a seat belt should be routed with respect to an individual’s anatomy to ensure a proper fit. The three key belt fit concepts conveyed in the video were:
1) Lap belt low on hips, touching the thighs.
2) Shoulder belt crossing middle of collarbone.
3) Belt snug, as close to bones as possible.
Additional context about the ability to achieve to good belt fit, such as opening a heavy coat or adjusting the height adjusters on the B-pillar behind the windows, were also presented.
We provide the parameters used in Umbrella Sampling simulations reported in our study "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method", namely the set positions and spring constants for each window in simulations. Two tables are provided. Table 1 lists the names of the peptides and their corresponding sequences. Table 2 lists the parameters. The abstract of our work is the following:
We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with Weighted Histogram Analysis Method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse-grained (CG) force field (MARTINI) is less prone to significant error induced by biased-sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3-4 residue peptide segments while leaving the remain-ing peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and relia-bly estimate the binding free energy between an arbitrary peptide and an MHC class II molecule.
The ENVIREM dataset v1.0 is a set of 16 climatic and 2 topographic variables that can be used in modeling species' distributions. The strengths of this dataset include their close ties to ecological processes, and their availability at a global scale, at several spatial resolutions, and for several time periods. The underlying temperature and precipitation data that went into their construction comes from the WorldClim dataset ( www.worldclim.org), and the solar radiation data comes from the Consortium for Spatial Information ( www.cgiar-csi.org). The data are compatible with and expand the set of variables from WorldClim v1.4 ( www.worldclim.org).
For more information, please visit the project website: envirem.github.io
Magnetic resonance angiography (MRA) of the aorta of a 30 yo healthy volunteer, segmented and discretized using the software CRIMSON ( www.crimson.software).
Additionally, models corresponding to virtually-aged aortic geometries at ages: 40, 60, and 75.