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Comparative evaluation of the forces produced by tongue on circummaxillary sutures in skeletal Class III malocclusion with maxillary hypoplasia using tongue crib with that of facemask therapy - A FEM study

Data sheet showing stimulation result

openApr 2023View details →

Confocal microsscope and sharp force trauma (Roc de les Orenetes)

3D scans obtained with confocal microscopy (Sensofar S-Neox 3D Optical Profiler (SSN09000)) on the Roc de les Orenetes (Queralbs, Girona, Spain) cut marks. The scans were obtained with SensoScan software, which can be opened and edited with SensoView, and the folder also contains some of the processed images used in this study. This is a supplementary material of the paper "Death in the high mountains: Evidence of interpersonal violence during Late Chalcolithic and Early Bronze Age at Roc de les Orenetes" (Moreno-Ibáñez et al., 2023: submitted). It is divided into two main folders: chop marks and slice marks. The cut marks of each bone have been grouped in folders with their corresponding labels, and in the case of a bone having more than one clearly distinguishable cut mark, these have also been divided into sub-folders, indicating “cut mark 1”, “cut mark 2”, etc. The file names also indicate the label code of the bone, the magnification at which the image was taken (5x, 10x, or 20x), and the type of visualization used in the form of acronyms, which are listed hereafter: ST: stack (conventional confocal display, black and white). FC: false color (visualization of the topography of the bone surface in a range of colors, without texture). FCST: false color + stack (combination of the two aforementioned visualizations, false color topography plus surface texture). FR: form removal (the inclination or concavity of the bone is flattened with SensoView software to better observe the surface topography in false color, without the curvature of the bone hindering the cut mark). VD: viridis (viridis false color range, from yellow to blue through green, used in cases where the desired features of the cut mark were best viewed in this mode). 3D: three-dimensional movable scans. 2D: two-dimensional images.

Deglacial climate changes as forced by different ice sheet reconstructions - model ouputs

This dataset contains the model output corresponding to the paper entitled "Deglacial climate changes as forced by different ice sheet reconstructions" submitted to Climate of the Past. For the description of the model and simulations we refer to this article.   Simulations: degla_P_bathy_500yr_is_SH_nobathy = with ICE_6G_C, fixed bathymetry degla_P_bathy_500yr_is_SH = with ICE_6G_C, evolving bathymetry degla_P_bathy_500yr_is_SH_bis = with ICE_6G_C, evolving bathymetry, mask modified degla_T_bathyT_100yr_is_SH_nobathy = with GLAC-1D, fixed bathymetry degla_T_bathyT_100yr_is_SH = with GLAC-1D, evolving bathymetry degla_T_bathyT_100yr_is_SH_FWF = with GLAC-1D, evolving bathymetry, fresh water flux degla_T_bathyT_100yr_is_SH_FWFtest3 = with GLAC-1D, evolving bathymetry, fresh water flux with intensity divided by 3 degla_T_bathyT_100yr_is_SH_FWFtest4 = with GLAC-1D, evolving bathymetry, fresh water flux with intensity divided by 4   Variables and corresponding files: Evolution of ocean volume (m3): volume_ocean_degla_P_bathy_500yr_is_SH.txt volume_ocean_degla_T_bathyT_100yr_is_SH.txt Evolution of ocean surface area (1e6 km2): surface_area_degla_P_bathy_500yr_is_SH.txt surface_area_degla_T_bathyT_100yr_is_SH.txt Sea land masks for time slices: tmask_bathy_P_0yr_SH_CC_PI.nc tmask_degla_P_bathy_500yr_is_SH_21ka.nc tmask_degla_T_bathyT_100yr_is_SH_21ka.nc tmask_degla_P_bathy_500yr_is_SH_12ka.nc tmask_degla_T_bathyT_100yr_is_SH_12ka.nc tmask_degla_P_bathy_500yr_is_SH_9ka.nc tmask_degla_T_bathyT_100yr_is_SH_9ka.nc Evolution of global mean temperature (degree C): Temperature_evolution_degla_P_bathy_500yr_is_SH_nobathy.txt Temperature_evolution_degla_T_bathyT_100yr_is_SH_nobathy.txt Temperature_evolution_degla_P_bathy_500yr_is_SH.txt Temperature_evolution_degla_P_bathy_500yr_is_SH_bis.txt Temperature_evolution_degla_T_bathyT_100yr_is_SH_nobathy.txt Temperature_evolution_degla_T_bathyT_500yr_is_SH.txt Temperature_evolution_degla_T_bathyT_100yr_is_SH.txt Temperature_evolution_degla_T_bathyT_100yr_is_SH_FWF.txt Temperature_evolution_degla_T_bathyT_100yr_is_SH_FWFtest3.txt Temperature_evolution_degla_T_bathyT_100yr_is_SH_FWFtest4.txt Temperature maps for time slices: temp_degla_P_bathy_500yr_is_SH_nobathy_21ka.nc temp_degla_T_bathyT_100yr_is_SH_nobathy_21ka.nc temp_degla_P_bathy_500yr_is_SH_nobathy_10ka.nc temp_degla_T_bathyT_100yr_is_SH_nobathy_10ka.nc Evolution of salinity: iLOVECLIM_salinity_ICE-6G_C.nc iLOVECLIM_salinity_GLAC-1D.nc Temperature evolution at NGRIP location: iLOVECLIM_t2m_NGRIP_degla_P_bathy_500yr_is_SH_nobathy.nc iLOVECLIM_t2m_NGRIP_degla_P_bathy_500yr_is_SH.nc iLOVECLIM_t2m_NGRIP_degla_P_bathy_500yr_is_SH_bis.nc iLOVECLIM_t2m_NGRIP_degla_T_bathyT_100yr_is_SH_nobathy.nc iLOVECLIM_t2m_NGRIP_degla_T_bathyT_100yr_is_SH.nc iLOVECLIM_t2m_NGRIP_degla_T_bathyT_100yr_is_SH_FWF.nc iLOVECLIM_t2m_NGRIP_degla_T_bathyT_100yr_is_SH_FWFtest3.nc iLOVECLIM_t2m_NGRIP_degla_T_bathyT_100yr_is_SH_FWFtest4.nc Temperature evolution at EDC location: iLOVECLIM_t2m_EDC_degla_T_bathyT_100yr_is_SH.nc iLOVECLIM_t2m_EDC_degla_T_bathyT_100yr_is_SH_nobathy.nc iLOVECLIM_t2m_EDC_degla_P_bathy_500yr_is_SH_nobathy.nc iLOVECLIM_t2m_EDC_degla_P_bathy_500yr_is_SH.nc iLOVECLIM_t2m_EDC_degla_P_bathy_500yr_is_SH_bis.nc iLOVECLIM_t2m_EDC_degla_T_bathyT_100yr_is_SH_FWF.nc iLOVECLIM_t2m_EDC_degla_T_bathyT_100yr_is_SH_FWFtest3.nc iLOVECLIM_t2m_EDC_degla_T_bathyT_100yr_is_SH_FWFtest4.nc Evolution of surface albedo (all globe): iLOVECLIM_alb_all_degla_P_bathy_500yr_is_SH_nobathy.nc iLOVECLIM_alb_all_degla_P_bathy_500yr_is_SH.nc iLOVECLIM_alb_all_degla_P_bathy_500yr_is_SH_bis.nc iLOVECLIM_alb_all_degla_T_bathyT_100yr_is_SH_nobathy.nc iLOVECLIM_alb_all_degla_T_bathyT_100yr_is_SH.nc Evolution of surface albedo (Northern Hemisphere): iLOVECLIM_alb_NH_degla_T_bathyT_100yr_is_SH_nobathy.nc iLOVECLIM_alb_NH_degla_T_bathyT_100yr_is_SH.nc iLOVECLIM_alb_NH_degla_P_bathy_500yr_is_SH_nobathy.nc iLOVECLIM_alb_NH_degla_P_bathy_500yr_is_SH.nc iLOVECLIM_alb_NH_degla_P_bathy_500yr_is_SH_bis.nc Evolution of surface albedo (Southern Hemisphere): iLOVECLIM_alb_SH_degla_P_bathy_500yr_is_SH_nobathy.nc iLOVECLIM_alb_SH_degla_P_bathy_500yr_is_SH.nc iLOVECLIM_alb_SH_degla_P_bathy_500yr_is_SH_bis.nc iLOVECLIM_alb_SH_degla_T_bathyT_100yr_is_SH_nobathy.nc iLOVECLIM_alb_SH_degla_T_bathyT_100yr_is_SH.nc Evolution of sea ice area in the Northern Hemisphere (1e12 km2): iLOVECLIM_sea_ice_NH_degla_P_bathy_500yr_is_SH_nobathy.nc iLOVECLIM_sea_ice_NH_degla_P_bathy_500yr_is_SH.nc iLOVECLIM_sea_ice_NH_degla_T_bathyT_100yr_is_SH_nobathy.nc iLOVECLIM_sea_ice_NH_degla_T_bathyT_100yr_is_SH.nc Evolution of sea ice area in the Southern Hemisphere (1e12 km2): iLOVECLIM_sea_ice_SH_degla_P_bathy_500yr_is_SH_nobathy.nc iLOVECLIM_sea_ice_SH_degla_P_bathy_500yr_is_SH.nc iLOVECLIM_sea_ice_SH_degla_T_bathyT_100yr_is_SH_nobathy.nc iLOVECLIM_sea_ice_SH_degla_T_bathyT_100yr_is_SH.nc Winter sea ice fraction and mixed layer depth (m) at time slices: iLOVECLIM_sea_ice_mld_bathy_P_21000yr_SH_21ka.nc iLOVECLIM_sea_ice_mld_bathy_T_21000yr_SH_21ka.nc iLOVECLIM_sea_ice_mld_degla_P_bathy_500yr_is_SH_nobathy_10ka.nc iLOVECLIM_sea_ice_mld_degla_T_bathyT_100yr_is_SH_nobathy_10ka.nc iLOVECLIM_sea_ice_mld_degla_P_bathy_500yr_is_SH_10ka.nc iLOVECLIM_sea_ice_mld_degla_T_bathyT_100yr_is_SH_10ka.nc Evolution of the maximum strength of AMOC: iLOVECLIM_AMOC_degla_P_bathy_500yr_is_SH_nobathy.nc iLOVECLIM_AMOC_degla_P_bathy_500yr_is_SH.nc iLOVECLIM_AMOC_degla_T_bathyT_100yr_is_SH_nobathy.nc iLOVECLIM_AMOC_degla_T_bathyT_100yr_is_SH.nc iLOVECLIM_AMOC_degla_T_bathyT_100yr_is_SH_FWF.nc iLOVECLIM_AMOC_degla_T_bathyT_100yr_is_SH_FWFtest3.nc iLOVECLIM_AMOC_degla_T_bathyT_100yr_is_SH_FWFtest4.nc Meridional overtunring circulation at time slices: MOC_degla_P_bathy_500yr_is_SH_21ka.nc MOC_degla_P_bathy_500yr_is_SH_10ka.nc MOC_degla_P_bathy_500yr_is_SH_nobathy_10ka.nc MOC_degla_T_bathyT_100yr_is_SH_21ka.nc MOC_degla_T_bathyT_100yr_is_SH_10ka.nc

OpenMM simulations of DLPC using the CHARMM Drude2023 force field

The dataset contains a PSF, a formatted coordinate file (CRD), and DCD files with the final 200 ns from each of 3 replicate simulations from the paper Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids Yalun Yu, Richard M. Venable, Jonathan Thirman, Payal Chatterjee, Anmol Kumar, Richard W. Pastor,* Benoît Roux,* Alexander D. MacKerell, Jr.,* and Jeffery B. Klauda* https://doi.org/10.1021/acs.jctc.3c00203 DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file Each file has 50 ns of data, with coordinate sets spaced at 10 ps between frames.

OpenMM simulations of POPE using the CHARMM Drude2023 force field

The dataset contains a PSF, a formatted coordinate file (CRD), and DCD files with the final 200 ns from each of 3 replicate simulations from the paper Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids Yalun Yu, Richard M. Venable, Jonathan Thirman, Payal Chatterjee, Anmol Kumar, Richard W. Pastor,* Benoît Roux,* Alexander D. MacKerell, Jr.,* and Jeffery B. Klauda* https://doi.org/10.1021/acs.jctc.3c00203 DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file; each file has frames spaced at 10 ps over a 50 ns interval.

OpenMM simulations of DMPC using the CHARMM Drude2023 force field

The dataset contains a PSF, a formatted coordinate file (CRD), and DCD files with the final 200 ns from each of 3 replicate simulations from the paper Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids Yalun Yu, Richard M. Venable, Jonathan Thirman, Payal Chatterjee, Anmol Kumar, Richard W. Pastor,* Benoît Roux,* Alexander D. MacKerell, Jr.,* and Jeffery B. Klauda* https://doi.org/10.1021/acs.jctc.3c00203 DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file  Each file has 50 ns of data, with coordinate sets spaced at 10 ps between frames.

OpenMM simulations of DPPC using the CHARMM Drude2023 force field

The dataset contains a PSF, a formatted coordinate file (CRD), and DCD files with the final 200 ns from each of 3 replicate simulations from the paper Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids Yalun Yu, Richard M. Venable, Jonathan Thirman, Payal Chatterjee, Anmol Kumar, Richard W. Pastor,* Benoît Roux,* Alexander D. MacKerell, Jr.,* and Jeffery B. Klauda* https://doi.org/10.1021/acs.jctc.3c00203 DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file; each file has frames spaced at 10 ps over a 50 ns interval.

OpenMM simulations of POPC using the CHARMM Drude2023 force field

PSF, single CRD file, and DCD format trajectories for the final 200 ns of triplicate POPC simulations, from the publication Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids Yalun Yu, Richard M. Venable, Jonathan Thirman, Payal Chatterjee, Anmol Kumar, Richard W. Pastor,* Benoît Roux,* Alexander D. MacKerell, Jr.,* and Jeffery B. Klauda*  https://doi.org/10.1021/acs.jctc.3c00203 DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file; each file has frames spaced at 10 ps over a 50 ns interval.

OpenMM simulations of DOPC using the CHARMM Drude2023 force field

The dataset contains a PSF, a formatted coordinate file (CRD), and DCD files with the final 200 ns from each of 3 replicate simulations from the paper Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids Yalun Yu, Richard M. Venable, Jonathan Thirman, Payal Chatterjee, Anmol Kumar, Richard W. Pastor,* Benoît Roux,* Alexander D. MacKerell, Jr.,* and Jeffery B. Klauda* https://doi.org/10.1021/acs.jctc.3c00203 DCD file names indicate the lipid, replica number, and the time point of the final coordinate set in the file; each file has frames spaced at 10 ps over a 50 ns interval.

opencc-zeroMay 2023View details →

dryad36/100

Climatic forcing and individual heterogeneity in a resident mountain bird: legacy data reveal effects on reproductive strategies

Optimization of clutch size and timing of reproduction have substantial effects on lifetime reproductive success in vertebrates, and both individual quality and environmental variation may impact life history strategies. We tested hypotheses related to maternal investment and timing of reproduction, using 17 years (1978-1994) of individual-based life history data on willow ptarmigan (Lagopus l. lagopus, n=290 breeding females with n=319 breeding attempts) in central Norway. We analysed whether climatic variation and individual state variables (age and body mass) affected number of offspring and timing of reproduction, and individual repeatability in strategies. The results suggest that willow ptarmigan share a common optimal clutch size that is largely independent of measured individual states. While we found no clear direct weather effects on clutch size, higher spring temperatures advanced onset of breeding, and early breeding was followed by an increased number of offspring. Warmer springs were positively related to maternal mass, and mass interacted with clutch size in production of hatchlings. Finally, clutch size and timing of reproduction were highly repeatable within individuals, indicating that individual quality guided trade-offs in reproductive effort. Our results demonstrate how climatic forcing and individual heterogeneity in combination influenced life history traits in a resident montane keystone species.

opencc-by-4.0Dec 2022View details →

Dataset for "Bias correction and statistical modeling of variable oceanic forcing of Greenland outlet glaciers" by Verjans et al.

Code and data products associated with "Bias correction and statistical modeling of variable oceanic forcing of Greenland outlet glaciers" by Verjans V., Robel A., Thompson A. F., and Seroussi H. Please see readme file for all the information. Contact: vverjans3@gatech.edu Author: Vincent Verjans

opencc-by-4.0May 2023View details →

Simulations for manuscript Unravelling the forcing and feedbacks contributing to Pliocene Arctic warming in EC-Earth simulations

Nine PlioMIP2 experiments were conducted to investigate the mid-Pliocene Arctic climate. These experiments considered three CO2 levels (280, 400 and 560 ppm), modern or Pliocene ice sheet conditions in Greenland and Antarctica and either prescribed or dynamic vegetation. Simulations were performed by the EC-Earth3-LR Veg climate model with a horizontal resolution of ~1.125°. The dataset contains selected output data from the simulations. Simulations were run for 1000 years. The last 200 years were used for analysis after the model reached an equilibrium as measured by global surface air temperature trend less than 0.05 K per century.  The dataset contains Earth system model results from EC-Earth3 presented in the study by Power et al. (2023).

dryad36/100

Data from: Muscle force-length dynamics during walking over obstacles indicates delayed recovery and a shift towards more strut-like function in birds with proprioceptive deficit

Recent studies of in vivo muscle function in guinea fowl revealed that distal leg muscles rapidly modulate force and work to stabilize running in uneven terrain. Previous studies focused on running only, and it remains unclear how muscular mechanisms for stability differ between walking and running. Here we investigate in vivo function of the lateral gastrocnemius (LG) during walking over obstacles. We compare muscle function in birds with intact (iLG) versus self-reinnervated LG (rLG). Self-reinnervation results in proprioceptive feedback deficit due to loss of monosynaptic stretch reflex. We test the hypothesis that proprioceptive deficit results in decreased modulation of EMG activity in response to obstacle contact, and a delayed obstacle recovery compared to iLG. We found that total myoelectric intensity (Etot) of iLG increased by 68% in obstacle strides (S 0) compared to level terrain, suggesting a substantial reflex-mediated response. In contrast, Etot of rLG increased by 31% in S 0 strides compared to level, but also increased by 43% in the first post-obstacle (S+1) stride. In iLG, muscle force and work differed significantly from level only in the S 0 stride, indicating a single-stride recovery. In rLG, force increased in S 0, S+1, and S+2 compared to level, indicating three-stride obstacle recovery. Interestingly, rLG showed little variation in work output and shortening velocity obstacle terrain, indicating a shift towards near isometric strut-like function. Reinnervated birds also adopt a more crouched posture across level and obstacle terrains compared to intact birds. These findings suggest gait specific control mechanisms in walking and running.

opencc-zeroMay 2023View details →

opencc-by-4.0May 2023View details →

Foot sole contact forces vs. ground contact forces to obtain foot joint moments in in-shoe gait. A preliminary study: Experiment data

Experiment data containing the kinematics (joint angles) and the kinetics (joint moments) of the ankle, midtarsal (MT) and metatarsophalangeal (MP) joints during gait for 10 subjects. <ul> <li>I stands for instrumented Insoles</li> <li>P stands for pressure Platform</li> <li>F stands for Flexible shoes</li> <li>R stands for Rigid shoes</li> </ul> Last number in the file name corresponds to trial number (5 trials each subject) Thus, e.g., Subject02_IR4.xls refers to the trial 4 of subject 2 wearing Rigid shoes with instrumented Insoles.

Pure POPC membrane simulations with 1000 mM NaCl with the CHARMM-Drude2023 force field (OpenMM)

220.14 ns MD simulation of pure POPC membrane using Charmm-Drude2023 polarizable force field ( Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids ) .The system contains 128 POPC lipids, 115 NaCl, and 6400 SWM4 water molecules. Before running the Drude simulation, the system has been equilibriated using Charmm36 force field for 200 ns. The last frame of that simulation was used to generate Drude polarizable model. Frame saving frequency is 10ps. There are 22014 frames in this trajectory.

Pure POPC membrane simulations with 350 mM CaCl2 with the CHARMM-Drude2023 force field (OpenMM)

219.59 ns MD simulation of pure POPC membrane using Charmm-Drude2023 polarizable force field ( Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids ) .The system contains 128 POPC lipids, 41 CaCl2, and 6400 SWM4 water molecules. Before running the Drude simulation, the system has been equilibriated using Charmm36 force field for 200 ns. The last frame of that simulation was used to generate Drude polarizable model. Frame saving frequency is 10ps. There are 21959 frames in this trajectory.

opencc-by-4.0Feb 2023View details →

Comparative Study of Molecular Mechanics Force Fields for β-peptidic Foldamers: Folding and Self-Association

Molecular dynamics simulation input files and Python scripts used for preparing the runs and analyzing the trajectories.

Single lipid component membrane bilayer MD with CHARMM36 force field, simulated with the CHARMM program

Data for ten single component lipid bilayer simulations, with 3 files per lipid: a DCD file with coordinates, a PSF file describing the system, and a .zip file containing the starting coordinate set (CHARMM COOR format) and the other inputs used for the CHARMM simulations.  Only the POPG system includes ions: Na+ to neutralize the lipids, and ca. 0.15 M NaCl. The DCD trajectory files contain coordinate sets stored at 0.1 ns intervals,  and are in the original CHARMM binary format. Lipid Nlpd  Nwat  ns DLPC  648  25920  200 DMPC  648  16632  100 DOPC  648  21681  350 DOPE  648  21681  350 DPPC  648  19701  300 POPC  648  20178  200 POPE  720  23049  100 POPG  648  29160  200 PSM   648  18828  200 SDPE  648  25920  100 "Mechanical properties of lipid bilayers from molecular dynamics simulation", R. M. Venable, F. L. Brown and R. W. Pastor, Chemistry and Physics of Lipids, 192 pp. 60-74 (2015).  https://pubmed.ncbi.nlm.nih.gov/26238099/ https://www.sciencedirect.com/science/article/pii/S0009308415300190?via%3Dihub         See also: "Identifying systematic errors in a power spectral analysis of simulated lipid membranes" Muhammed F. Ergüder, Markus Deserno J. Chem. Phys. 154, 214103 (2021); doi: 10.1063/5.0049448

Remote insolation forcing of orbital-scale South Asian summer monsoon variability

CESM simulation data for the manuscript "Remote insolation forcing of orbital-scale South Asian summer monsoon variability", which has been submitted to Geophysical Research Letters.