Published July 29, 2022
| Version v1.0
Dataset
Open
Raw images corresponding to article "Relative assessment of cloth mask protection against ballistic droplets: a frugal approach"
Authors/Creators
- 1. Center for Complex Systems, Physics Faculty, University of Havana, Cuba
Contributors
Research group (3):
- 1. Gran Sasso Science Institute, Italy
- 2. Zeolites Engineering Laboratory, Institute of Materials and Reagents (IMRE), University of Havana, Cuba
- 3. Instituto Superior de Ciencia y Tecnología Aplicadas (InSTEC), University of Havana, Cuba
Description
The images correspond to scans used to obtain the data reported on V. Márquez-Alvarez, J. Amigó-Vega, A. Rivera, A. J. Batista-Leyva, and E. Altshuler, Relative assessment of cloth mask protection against ballistic droplets: A frugal approach. PLOS ONE 17, e0275376 (2022). doi: 10.1371/journal.pone.0275376.
Notes
Files
Files
(7.1 GB)
| Name | Size | |
|---|---|---|
|
md5:032a9261a60c03e52c4e6bd6c0a87ada
|
150.6 MB | Download |
|
md5:3a5389767920ee24b4d33d24aa93d08c
|
150.6 MB | Download |
|
md5:93e4e7ff93374fb6f3691215e779ada1
|
150.8 MB | Download |
|
md5:f8d0245f99196e7e15ec5397f0ad5c7e
|
150.6 MB | Download |
|
md5:b3d209ba2fdade9e1bc9a0b1b3890500
|
152.0 MB | Download |
|
md5:ac89daab4ddc5acfde3fccedb583ab11
|
150.6 MB | Download |
|
md5:0861b8ed2aff826f680d55740ab21597
|
150.1 MB | Download |
|
md5:a98a65e4a0e64a21ecb838fca66e731c
|
149.8 MB | Download |
|
md5:f7f13ff54487b20cf4b83278fccd8151
|
151.4 MB | Download |
|
md5:b8773b4edb971ae47092ccc0a7634842
|
152.4 MB | Download |
|
md5:494ceade0f57c2f3a3ce814995b3a952
|
151.5 MB | Download |
|
md5:87cd54b56939b3edaa53b6bc6a5d3cb4
|
150.5 MB | Download |
|
md5:c0f98292b87e8e671456939e2a335ba2
|
150.6 MB | Download |
|
md5:ae68880a62ae57ef15ea3d3d21aade75
|
150.1 MB | Download |
|
md5:07f06be24b49a3b894cdbc9a739100d6
|
136.4 MB | Download |
|
md5:12835b31697944b2aff81268bc021f4c
|
134.9 MB | Download |
|
md5:abfaa5c8ecd1f421b956230af5a250d1
|
157.5 MB | Download |
|
md5:303cadf3a17b6fdd31654eb8a57e371f
|
157.5 MB | Download |
|
md5:54677f53f3c9d9837da0ee83a93e9497
|
157.5 MB | Download |
|
md5:5e89e0a314fe729d667fbc6cf5047c1d
|
157.5 MB | Download |
|
md5:9268a490c29caa2da2e577eb2bc62a08
|
152.4 MB | Download |
|
md5:3790b14fc3a04a131f2868e0617e7885
|
148.9 MB | Download |
|
md5:5e7dcfe746b06ab0a7e2108cc9957e85
|
152.9 MB | Download |
|
md5:1e647590aa4bda61b491fa491f1bd344
|
154.1 MB | Download |
|
md5:169a245b06559bcf7bf9016c0ebeea1d
|
150.5 MB | Download |
|
md5:aa332a5080ccbe78b7d64141dc3fa9cf
|
151.7 MB | Download |
|
md5:9bb01567a06c36846170b117f45d7105
|
153.7 MB | Download |
|
md5:536759f06f8a18cebae164fdae132e44
|
153.7 MB | Download |
|
md5:5e89510d9a06dbdd5de35e648d7f32fd
|
153.7 MB | Download |
|
md5:30779ed3382d1ec5109c402d5904f4ef
|
150.6 MB | Download |
|
md5:c314d0535623e319bea9c70489b40e92
|
150.6 MB | Download |
|
md5:3b3bf36f30a03e1e9c1319db92e4262d
|
150.6 MB | Download |
|
md5:06cdcb3072a5f8298954286a9aa57d11
|
150.6 MB | Download |
|
md5:0f04862749bcd37a1ed74531e26fc6f7
|
153.7 MB | Download |
|
md5:9aa3a6f70dd3c32a67f350c2d86ec9bb
|
153.7 MB | Download |
|
md5:79cc9849254e63ccc4c09966c6a70832
|
153.7 MB | Download |
|
md5:e6a53d5045da5389f872292577fc2af6
|
153.7 MB | Download |
|
md5:81bbcbc7c067ad1de9dad2d73e8cadb6
|
153.7 MB | Download |
|
md5:42c13491796f876ef78971ab04b5743e
|
153.7 MB | Download |
|
md5:d21e0a1a9a890ef783a6dc17e4fc053a
|
153.7 MB | Download |
|
md5:e4d10dacc37c0475d1ddaa7874238229
|
153.7 MB | Download |
|
md5:b7d75db9c64d5da3d5d5a1fe3abdba43
|
151.5 MB | Download |
|
md5:87233af3ad97f4994375c75a0c911910
|
149.2 MB | Download |
|
md5:21c28760e1b5a460bd1b8d40d31ece63
|
153.1 MB | Download |
|
md5:961c4ec73ed68f438f68f5d481d64fbb
|
152.0 MB | Download |
|
md5:4bad42d06d760af6a3860afe970a745f
|
149.4 MB | Download |
|
md5:eb2cf5c8cd818ed4403f103dd6b559c4
|
150.9 MB | Download |
Additional details
Related works
- Is supplement to
- Journal article: 10.1371/journal.pone.0275376 (DOI)
- Thesis: 10.5281/zenodo.7094693 (DOI)
- Software: 10.5281/zenodo.7020684 (DOI)
- Software: https://github.com/vmalv/Binary-Image-Mean-Pixel-Value/tree/v1.1.0 (URL)