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\left\langle \text{LT}\right\rangle ^{2}$). In the final state of the reaction, a particle is emitted from one of the nuclei, and the energy distribution of the emitted particle has been shown experimentally to be isotropic (i.e., $\left\langle \text{EA}\right\rangle =\left\langle \text{EB}\right\rangle =\left\langle \text{EC}\right\rangle =\left\langle
\text{ED}\right\rangle =\left\langle \text{PA}\right\rangle $).
The physics of this reaction can be understood with the help of the impact theory discussed above. As emphasized in Ref. [@ref:layton_etal_PRE03], the particle production with $\left\langle \text{PE}\right\rangle $ in the final state is the branching of the relative momentum spectrum into the number of emitted particles distribution. Since the initial relative velocity of the colliding nuclei is fixed by geometry and energy, the relative momentum spectrum is the sole reaction observable and the reaction is totally determined by this observable. The asymmetry in the evolution of the relative momentum between the emitted particles is described by the average of the reaction observables $A_{\text{meas}}$ with $\left\langle \text{PE}\right\rangle $ in the final state. The distribution of the measured $A_{\text{meas}}$ is then the same as that of the relative momentum distribution of the emitted particles.
The total projectile momentum in the LS interaction is given as the sum of those of the colliding nuclei, $\sum_{\alpha \beta }m_{\alpha }v_{\alpha }=Mv_{\text{tot}}$, where $M=\sum_{\alpha }m_{\alpha }$ is the total mass of the colliding nuclei and $v_{\text{tot}}=\sqrt{\sum_{\alpha }v_{\alpha
}^{2}}$ is the total relative velocity
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GridFS and django-storage
I want to store images in my Django app but I don’t want to use Google/Amazon’s cloud services. I’d like to use a local storage, the idea being that when the app is installed, I’d write the images to disk in some sensible directory and give the user the option to upload to S3 and/or Google Cloud Storage. How can I write a database backend that stores images as GridFS files ( and is this possible with Django?
A:
You might want to look at django-s3 for writing S3-backed models. (Note this is new and not yet in the core Django repo.)
Also I prefer the de-facto standard mechanism for uploading files to S3 through the bucket REST API, rather than GridFS. See the Django docs for details.
Survival of Enterococcus faecalis subsp. faecalis colonizing the subgingival microbiota of periodontitis patients after removal of the source of infection by guided surgery.
The importance of the inoculum source (periodontal pocket, tooth surface, or saliva) for the survival and establishment of Enterococcus faecalis subsp. faecalis (Ef) in the periodontal pocket has not been clearly established. The purpose of this study was to examine, over a 6-month period, the survival of Ef in the subgingival microbiota of 12 periodontitis patients after the periodontal pocket was debrided, by use of plaque or saliva as a source of Ef. Ef was cultured from saliva in the first week and from tooth surfaces and the periodontal pocket of teeth on which Ef was cultured from saliva in the first week. Patients were treated and re-examined 7 and 14 days after the initial session. Bacterial samples were collected from the subgingival pockets of teeth on which Ef was culturable from plaque or saliva, and from the plaque samples collected from tooth surfaces. Ef was detected in the subgingival microbiota of the patients for a mean of 1.6 days, and in the plaque of the patient for a mean of 1.7 days.