X Particles 2.59 Serial 13
Julio Cesar Thap
@mikksu, thanks for the heads up about regular particles still working. at least good to know it still exists there, although its a shame they are removing the option for hair. the down side to using regular particles for object instancing is that with hair particles you can go into particle edit mode and get finer grained control of the distribution of the instanced objects. especially useful for example if you are making a particle tree forest and you want to add/remove a few trees to tweak the composition.
painting objects is working!
You are only doing it the wrong way.
You have to bake the hair to do particle-editing
and for using the grow/shrink along the hair-path the
object has to be in the x-y-plane in edit-mode,
cause the hair-system uses this orientation.
Only thing, that is not working with online update
is when changing the length of hair or editing
the single hair-points around, then one have
to toggle edit/object to see the rendered objects
according to the twisted hairs.
a sample -
like said, painting works,
the hairsystem has to be baked first.
New objects will be added with the hair-default-settings
of the hairsystem.
Editing the hair-knots will update the objects after toggle
of edit-particle-edit-mode (just press Tab two times)
@test-dr: You are completely right! works fine when everything is set correctly (in every frame painting objects works, following path, too, particle editing behaves properly). Many thanks for spending your time and sharing your knowledge and example files :).
Long version: my New Year resolution to finish last years projects brought me back to an old frustrating problem: grass made from grouped objects distributed with the particles system was messed up in the latest Blender versions due to changes made in Blender after release 2.59. And I actually never understood well the particle settings mechanism so I decided to try harder. Actually it is not a fix, as nothing is really broken, just a matter of understanding what those settings actually do.
Hi Oana! Very helpful information! I was wondering if object distribution using particle system can be achieved with a grayscale density image. Could I use that kind of image as reference for the density of the object spreading over a subdivided plane?
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This study aims to elucidate the effects of soil particle composition and fractal dimension on soil physical and chemical properties following sand-binding revegetation within straw checkerboard in south-eastern Tengger Desert. Three afforested plantations in the year of 2016 (i.e., 1 year), 2013 (i.e., 4 years) and 1987 (i.e., 30 years) were selected as study sites, with the adjacent mobile sand land as control (CK). We measured soil particle composition, soil fractal dimension, and the changes of soil physical and chemical properties. The relationship between soil particle composition, soil fractal dimension, and soil properties was analyzed. The results showed that contents of soil particle with the size of both 100-250 μm and 250-500 μm were greater than that of 50-100 μm, ranging from 42.5% to 80.1% and from 12.5% to 42.2% relative to that ranging from 0.2% to 20.8%. Contents of soil particle with the size of 1 a>CK>30 a, and CK>1 a>4 a> 30a, respectively. Soil particle with the size of 500-1000 μm occupied little of soil particle composition, with no significant difference between each site. The fractal dimension of soil particles ranged from 0.54 to 2.59. There was significantly greater soil fractal dimension in 30 a in comparison to 4 a, 1 a and CK, with the intermediate values in 4 a and 1 a, and the lowest values in CK. There was a significantly positive correlation of fractal dimension of soil particles with soil particle content of clay, silt, very fine sand, and a significantly negative correlation of fractal dimension of soil particles with soil particle content of medium sand. Fractal dimension of soil particles was positively correlated with soil electrical conductivity, organic carbon, total nitrogen, and carbon-nitrogen ratio, but with no correlation with soil pH and soil water content. Soil particle content at the size of
I disagree that the main issue here is an underrepresentation of 2D projections for some angles. We had various datasets where the angular distribution looked similar to what you show, for particles maybe a bit bigger, and this did not prevent to reach an acceptable density map. When you have a 180 coverage that should work.
If you have a lot of particles, you need maybe to clean it more. There are various discussions about parameters used for ab-initio that may came at hand for small particles. Have a look at those threads. There are also a couple of threads about parameters for NU-refinement, but you should think about this only when your ab-initio is satisfactory. Cheers
Thank you very much for your suggestions. We are considering collecting tilted data, but it may not solve the problem with such a small protein.
I have tried to do several rounds of 3D classification with 1-6 classes and 3-6 A resolutions but made no difference, it seems that there is no larger conformation change of the complex.
I am thinking about maybe I can focus on the process of particle selection for this data because I found there is one dominated view of 2D, maybe I need to throw away part of them to balance the views?
Thank you for your good suggestions! After 2D classes, I got about 400k particles, after 3D classes and heterogeneous refinement the number of particles goes to 150-200k, and I could get a good model after ab-initio and the model be much better after heterogeneous refinement. I believed the biggest issue for this data is the 3D refinement not working, I will definitely try more parameters and methods to do the 3D refinement.
Thank you!
Your reply is so helpful! I think i have the same problem for small protein. Some views are just too hard to get aligned. I was told by several people to skip 2d and go directly to 3D but at least in cryosparc i have not seem much improvement. Do you run 3D classification in cryosparc or relion? Any specific parameter recommended?
Thanks a lot!
Yes, I believe we got very similar results, unfortunately, I still work on it and could not figure it out. We think it is possibly an orientation issue by carefully checking the 2D classification results. We are currently trying to test with different types of grads and different detergents. I will update my progress if I finally work it out.
MP 10 are microparticles with a mean diameter of 10.3 m. The distribution of this dust is monodisperse; the geometric standard deviation of the distribution is only 2.59 m. Due to this small distribution, these dusts are used for scientific analysis and can also be used to calibrate measuring devices.
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The database on particle number emission factors has been very limited to date despite the increasing interest in the effects of human exposure to particles in the submicrometer range. There are also major questions on the comparability of emission factors derived through dynamometer versus on-road studies. Thus, the aims of this study were (1) to quantify vehicle number emission factors in the submicrometer (and also supermicrometer) range for stop-start and free-flowing traffic at about 100 km h-1 driving conditions through extensive road measurements and (2) to compare the emission factors from the road measurements with those obtained previously from dynamometer studies conducted in Brisbane. For submicrometer particles the average emission factors for Tora Street were estimated at (1.89 plus or minus 3.40) x 10(super 13) particles km-1 (mean plus or minus standard error; n = 386) for petrol and (7.17 plus or minus 2.80) x 10(super 14) particles km-1 (diesel; n = 196) and for supermicrometer particles at 2.59 x 10(super 9) particles km-1 and 1.53 x 10(super 12) particles km-1, respectively. The average number emission factors for submicrometer particles estimated for Ipswich Road (stop-start traffic mode) were (2.18 plus or minus 0.57) x 10(super13) particles km-1 (petrol) and (2.04 plus or minus 0.24) x 10(super 14) particles km-1 (diesel). One implication of the conclusion that emission factors of heavy duty diesel vehicles are over 1 order of magnitude higher than emission factors of petrol-fueled passenger cars is that future control and management strategies should in particular target heavy duty vehicles, as even a moderate decrease in emissions of these vehicles would have a significant impact on lowering atmospheric concentrations of particles. The finding that particle number emissions per vehicle-km are significantly larger for higher speed vehicle operation has an important implication on urban traffic planning and optimization of vehicle speed to lower their impact on airborne pollution. Additionally, statistical analysis showed that neither the measuring method (dynamometer or on-road), nor data origin (Brisbane or elsewhere in the world), is associated with a statistically significant difference between the average values of emission factors for diesel. petrol, and vehicle fleet mix. However, statistical analyses of the effect of fuel showed that the mean values of emission factors for petrol and diesel are different at a 5% significance level. (A)
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