50 research outputs found
ULB ToysTable
No full textULB ToysTable sequence by LISA ULB
The test sequence "ULB ToysTable" is provided by Daniele Bonatto, Sarah Fachada, Gauthier Lafruit, members of the LISA department, EPB (Ecole Polytechnique de Bruxelles), ULB (Universite Libre de Bruxelles), Belgium.
License:
CC BY-NC-SA
Terms of Use:
Anykind of publication or report using this sequence should refer to the following references.
[1] Daniele Bonatto, Sarah Fachada, Gauthier Lafruit, "ULB ToysTable", 2021.
@misc{bonatto_toystable_2021,
title = {{ULB} {ToysTable}},
author = {Bonatto, Daniele and Fachada, Sarah and Lafruit, Gauthier},
month = feb,
year = {2021},
doi = {10.5281/zenodo.5055542}
}
[2] A. Schenkel, D. Bonatto, S. Fachada, H.-L. Guillaume, et G. Lafruit, « Natural Scenes Datasets for Exploration in 6DOF Navigation », in 2018 International Conference on 3D Immersion (IC3D), Brussels, Belgium, déc. 2018, p. 1-8. doi: 10.1109/IC3D.2018.8657865.
@inproceedings{schenkel_natural_b_2018,
address = {Brussels, Belgium},
title = {Natural {Scenes} {Datasets} for {Exploration} in {6DOF} {Navigation}},
isbn = {978-1-5386-7590-8},
url = {https://doi.org/10.1109/IC3D.2018.8657865},
doi = {10.1109/IC3D.2018.8657865},
language = {en},
urldate = {2019-04-11},
booktitle = {2018 {International} {Conference} on {3D} {Immersion} ({IC3D})},
publisher = {IEEE},
author = {Schenkel, Arnaud and Bonatto, Daniele and Fachada, Sarah and Guillaume, Henry-Louis and Lafruit, Gauthier},
month = dec,
year = {2018},
pages = {1--8}
}
[3] D. Bonatto, A. Schenkel, T. Lenertz, Y. Li, et G. Lafruit, « [MPEG-I Visual] ULB High Density 2D/3D Camera Array data set, version 2 [m41083] », in ISO/IEC JTC1/SC29/WG11 MPEG2017/M41083, Torino, Italy, juill. 2017.
@inproceedings{bonatto_mpeg-i_2017,
address = {Torino, Italy},
title = {[{MPEG}-{I} {Visual}] {ULB} {High} {Density} {2D}/{3D} {Camera} {Array} data set, version 2 [m41083]},
doi = {ISO/IEC JTC1/SC29/WG11 MPEG2017/M41083},
author = {Bonatto, Daniele and Schenkel, Arnaud and Lenertz, Tim and Li, Yan and Lafruit, Gauthier},
month = jul,
year = {2017}
}
Production:
Laboratory of Image Synthesis and Analysis, LISA department, Ecole Polytechnique de Bruxelles, Universite Libre de Bruxelles, Belgium.
Content:
This dataset contains a static test scene created using a robotic bench described in [3]. We provide RGB textures and their associated depth maps captured using a Microsoft Kinect v2. We also provide depth maps estimated using MPEG's Depth Estimation Reference Software (DERS) [5].
The scene contains a table with several toys, boxes, a chessboard and the datacolor Spydercheckr® 24. The pictures were taken in a controlled light environment. In a post-processing pass, the colors were corrected and the depth map undistorded and reprojected as described in [2] to match the RGB images.
The dataset contains two bands of regurarly spaced 5x5 images (Plane A) and 3x5 images (Plane B) respectively.
In addition to the images and their depth maps, an accurate camera calibration file is provided following the format of [4]. It was computed as described in [2].
The dataset contains:
- a `camera.json` file in OMAF coordinates system (Camera position: X: forwards, Y:left, Z: up, Rotation: yaw, pitch, roll) [3],
- a `textures` folder containing the rendered views in png format,
- a `depths_DERS` folder containing the associated depth maps in exr format.
References and links:
[4] S. Fachada, B. Kroon, D. Bonatto, B. Sonneveldt, et G. Lafruit, « Reference View Synthesizer (RVS) 2.0 manual, [N17759] », juill. 2018.
[5] S. Rogge and D. Bonatto and J. Sancho and R. Salvador and E. Juarez and A. Munteanu and G. Lafruit, "MPEG-I Depth Estimation Reference Software", in 2019 International Conference on 3D Immersion (IC3D), 2019
RabbitStamp Test Sequence
No full text# RabbitStamp sequence by LISA ULB
The test sequence "RabbitStamp" is provided by Sarah Fachada, Yupeng Xie, Daniele Bonatto, Gauthier Lafruit, Mehrdad Teratani, members of the LISA department, EPB (Ecole Polytechnique de Bruxelles), ULB (Universite Libre de Bruxelles), Belgium.
# License:
CC BY-NC-SA
ONLY Available for Academic Usage
# Terms of Use:
Anykind of publication or report using this sequence should refer to the following references.
[1] Sarah Fachada, Yupeng Xie, Daniele Bonatto, Gauthier Lafruit, Mehrdad Teratani, "RabbitStamp Test Sequence", 2021.
@misc{fachada_RabbitStamp_2021,
title = {{RabbitStamp} {Test} {Sequence}},
author = {Fachada, Sarah and Xie; Yupeng and Bonatto, Daniele and Lafruit, Gauthier and Teratani, Mehrdad },
month = jul,
year = {2021},
doi = {10.5281/zenodo.5053771}
}
[2] Sarah Fachada, Yupeng Xie, Daniele Bonatto, Gauthier Lafruit, Mehrdad Teratani, "[DLF] Plenoptic 2.0 Multiview Lenslet Dataset and Preliminary Experiments [m56429]", 2021.
@article{fachada_RabbitStamp_2021,
title = {[DLF] {Plenoptic} 2.0 {Multiview} {Lenslet} {Dataset} and {Preliminary} {Experiments} [m56429]},
author = {Fachada, Sarah and Xie; Yupeng and Bonatto, Daniele and Lafruit, Gauthier and Teratani, Mehrdad },
journal = {ISO/IEC JTC1/SC29/WG11},
month = apr,
year = {2021}
}
[3] Sarah Fachada, Yupeng Xie, Daniele Bonatto, Gauthier Lafruit, Mehrdad Teratani, "[LVC] Update for RabbitStamp: Plenoptic 2.0 Multiview Lenslet Dataset [m57100]", 2021.
@article{fachada_RabbitStamp_2021,
title = {[LVC] {Update} for {RabbitStamp}: {Plenoptic} 2.0 {Multiview} {Dataset} [m56429]},
author = {Fachada, Sarah and Xie; Yupeng and Bonatto, Daniele and Lafruit, Gauthier and Teratani, Mehrdad },
journal = {ISO/IEC JTC1/SC29/WG11},
month = jul,
year = {2021}
}
[4] Sarah Fachada, Yupeng Xie, Daniele Bonatto, Gauthier Lafruit, Mehrdad Teratani, "[LVC] Exploration Experiments using RabbitStamp Multiview Lenslet Images [m57101]", 2021.
@article{fachada_RabbitStamp_2021,
title = {[LVC] {Exploration} {Experiments} {Using} {RabbitStamp} {Multiview} {Lenslet} {Images} [m56429]},
author = {Fachada, Sarah and Xie; Yupeng and Bonatto, Daniele and Lafruit, Gauthier and Teratani, Mehrdad},
journal = {ISO/IEC JTC1/SC29/WG11},
month = jul,
year = {2021}
}
# Production:
Laboratory of Image Synthesis and Analysis, LISA department, Ecole Polytechnique de Bruxelles, Universite Libre de Bruxelles, Belgium.
# Content:
This dataset contains a test scene acquired with a raytrix camera [1] array of 7x3 views. For details of the dataset, please refer to the references mentioned above.
The dataset contains:
- a `depth_7x3_center` depth maps computed with DERS reference software [2] in yuv40016ble format and json configuration files to do so,
- a `multiview_7x3_5x5_images` Calibrated subimages computed with RLC [3] in yuv42010ble format, the cameras.json with the camera parameters and view_synthesis.json with the view synthesis experiment.
- a `multiview_7x3_lenslets` folder containing the lenslet views in yuv42010ble format, the Raytrix xml calibration file and RLC cfg file for conversion to multiview.
# References and links:
[1] Raytrix, https://raytrix.de/
[2] S. Rogge and D. Bonatto and J. Sancho and R. Salvador and E. Juarez and A. Munteanu and G. Lafruit, "MPEG-I Depth Estimation Reference Software", in 2019 International Conference on 3D Immersion (IC3D), 2019.
[3] M. Teratani and T. Fujii, "[MPEG-I Visual] Conversion of Lenslet Data Capture by Single Focussed Plenoptic Camera to Multiview Video using RLC0.3 [N18567]", ISO/IEC JTC1/SC29/WG11, 201
Transparent Magritte Test Sequence
No full textTransparent-Magritte sequence by LISA ULB
The test sequence "Transparent Magritte" is provided by Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, Gauthier Lafruit, members of the LISA department, EPB, ULB.
License:
CC BY-NC-SA
Terms of Use:
Anykind of publication or report using this sequence should refer to the following references.
[1] Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, Gauthier Lafruit, "Transparent Magritte Test Sequence", 2021.
@misc{fachada_transparent_2021,
title = {Transparent {Magritte} {Test} {Sequence}},
author = {Fachada, Sarah and Bonatto, Daniele and Teratani, Mehrdad and Lafruit, Gauthier},
month = feb,
year = {2021},
doi = {10.5281/zenodo.4488243}
}
[2] Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, and Gauthier Lafruit, "Light Field Rendering for non-Lambertian Objects," presented at the Electronic Imaging, 2021.
@inproceedings{fachada_light_2021,
title = {Light {Field} {Rendering} for non-{Lambertian} {Objects}},
booktitle = {Electronic {Imaging}},
author = {Fachada, Sarah and Bonatto, Daniele and Teratani, Mehrdad and Lafruit, Gauthier},
year = {2021}
}
Production
Laboratory of Image Synthesis and Analysis, LISA department, EPB, Universite Libre de Bruxelles, Belgium.
Content:
This dataset contains a test scene created and rendered with Blender [1] and the addon script [2] extended for Blender 2.8. We provide the Bblender file and the rendered scene.
The scene contains a transparent refractive torus rendered in a regular camera array of 21x21 cameras.
In addition to the 3D model, two folders are available:
- `centered_cameras` resolution of 1000x1000, the cameras are centered on the refractive torus.
- `parallel_cameras` resolution of 2000x2000, the cameras are parallel, with a principal point at the center of the image.
Each of these folders contains:
- a `camera.json` file in OMAF coordinates system (Camera position: X: forwards, Y:left, Z: up, Rotation: yaw, pitch, roll) [3],
- a `parameters.cfg` generated with [2],
- a `texture` folder containing the rendered views in png format,
- a `depth` folder containing the associated depth maps in exr format.
References and links:
[1] Blender Online Community, "Blender - a 3D modelling and rendering package." Blender Institute, Amsterdam: Blender Foundation, 2020.
[2] K. Honauer, O. Johannsen, D. Kondermann, and B. Goldluecke, "A Dataset and Evaluation Methodology for Depth Estimation on 4D Light Fields" in Asian Conference on Computer Vision, 2016,
https://github.com/lightfield-analysis/blender-addon
https://github.com/dbonattoj/blender-addon
[3] B. Kroon, "Reference View Synthesizer (RVS) manual [N18068]," ISO/IEC JTC1/SC29/WG11, Macau SAR, China, p. 19, Oct. 2018.
https://mpeg.chiariglione.org/standards/mpeg-i/omnidirectional-media-formatAcknoledgments:
This work was supported by
Les Fonds de la Recherche Scientifique - FNRS, Belgium, under Grant n°3679514$, ColibriH
The European Commision project n°951989 on Interactive Technologies, H2020-ICT-2019-3, Hovitron.
Sarah Fachada is a Research Fellow of the Fonds de la Recherche Scientifique - FNRS, Belgiu
Magritte Sphere
No full text# Magritte-Sphere sequence by LISA ULB
The test sequence "Magritte Sphere" is provided by Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, Gauthier Lafruit, members of the LISA department, EPB (Ecole Polytechnique de Bruxelles), ULB (Universite Libre de Bruxelles), Belgium.
# License:
CC BY-NC-SA
# Terms of Use:
Anykind of publication or report using this sequence should refer to the following references.
[1] Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, Gauthier Lafruit, "Magritte Sphere Test Sequence", 2021.
@misc{fachada_magritte_2021,
title = {{Magritte} {Sphere} {Test} {Sequence}},
author = {Fachada, Sarah and Bonatto, Daniele and Teratani, Mehrdad and Lafruit, Gauthier},
month = feb,
year = {2021},
doi = {10.5281/zenodo.5048265}
}
[2] Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, and Gauthier Lafruit, "Light Field Rendering for non-Lambertian Objects," presented at the Electronic Imaging, 2021.
@inproceedings{fachada_light_2021,
title = {Light {Field} {Rendering} for non-{Lambertian} {Objects}},
booktitle = {Electronic {Imaging}},
author = {Fachada, Sarah and Bonatto, Daniele and Teratani, Mehrdad and Lafruit, Gauthier},
year = {2021}
}
# Production:
Laboratory of Image Synthesis and Analysis, LISA department, EPB, Universite Libre de Bruxelles, Belgium.
# Content:
This dataset contains a test scene created and rendered with Blender [1] and the addon script [2] extended for Blender 2.8. We provide the Blender file and the rendered scene.
The scene contains a non-Lambertian (transparent-refractive (T) or mirror-specular (M)) sphere rendered in a regular camera array of 21x21 cameras.
In addition to the 3D model, we provide the rendered images : resolution of 2000x2000, the cameras are parallel, with a principal point at the center of the image.
The dataset contains:
- a `camera.json` file in OMAF coordinates system (Camera position: X: forwards, Y:left, Z: up, Rotation: yaw, pitch, roll) [3],
- a `parameters.cfg` generated with [2],
- a `texture_M` folder containing the rendered views in png format for the mirror object,
- a `texture_T` folder containing the rendered views in png format for the transparent object,
- a `mask` folder containing the mask indicating the sphere,
- a `depth` folder containing the associated depth maps in exr format.
# References and links:
[1] Blender Online Community, "Blender - a 3D modelling and rendering package." Blender Institute, Amsterdam: Blender Foundation, 2020.
[2] K. Honauer, O. Johannsen, D. Kondermann, and B. Goldluecke, "A Dataset and Evaluation Methodology for Depth Estimation on 4D Light Fields" in Asian Conference on Computer Vision, 2016,
https://github.com/lightfield-analysis/blender-addon
https://github.com/dbonattoj/blender-addon
[3] B. Kroon, "Reference View Synthesizer (RVS) manual [N18068]," ISO/IEC JTC1/SC29/WG11, Macau SAR, China, p. 19, Oct. 2018.
https://mpeg.chiariglione.org/standards/mpeg-i/omnidirectional-media-formatAcknowledgments:
This work was supported by:
Les Fonds de la Recherche Scientifique - FNRS, Belgium, under Grant n°3679514$, ColibriH,
The European Commision project n°951989 on Interactive Technologies, H2020-ICT-2019-3, Hovitron.
Sarah Fachada is a Research Fellow of the Fonds de la Recherche Scientifique - FNRS, Belgiu
HoviTronBear
No full text<p> # Sequence: HoviTronBear <br>
This dataset "HoviTronBear" is provided by Yupeng XIE, Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, Gauthier Lafruit, members of the LISA department, EPB (Ecole polytechnique de Bruxelles), ULB (Universite Libre de Bruxelles), Belgium. <br>
Supported by the EU project HoviTron (Holographic Vision for Immersive Tele-Robotic OperatioN), Call identifier: H2020-ICT-2019-3, Grant Agreement: 951989.</p>
<p> # License: <br>
CC BY-NC-SA</p>
<p> # Terms of Use: <br>
Any kind of publication or report using this sequence should refer to the following references.</p>
<p>[1] Sarah Fachada, Daniele Bonatto, Mehrdad Teratani, Gauthier Lafruit, "HoviTronBear", 2021.</p>
<p>@misc{xie_hovitronbear_2021,<br>
title = {{HoviTronBear} {Test} {Sequence}},<br>
author = {Xie, Yupeng and Fachada, Sarah and Bonatto, Daniele and Lafruit, Gauthier},<br>
month = July,<br>
year = {2021},<br>
doi = {10.5281/zenodo.5047464}<br>
}</p>
<p>[2] Xie, Yupeng and Fachada, Sarah and Bonatto, Daniele and Lafruit, Gauthier</p>
<p>@inproceedings{xie2021view,<br>
title={View Synthesis: LiDAR Camera versus Depth Estimation},<br>
author={Xie, Yupeng and Fachada, Sarah and Bonatto, Daniele and Lafruit, Gauthier},<br>
booktitle={International Conference on Computer Graphics, Visualization and Computer Vision 2021 (WSCG)},<br>
year={2021}<br>
}</p>
<p><br>
# Production:<br>
Laboratory of Image Synthesis and Analysis, LISA department, EPB, ULB.</p>
<p> # Content:<br>
This dataset contains:<br>
- Sequences:<br>
RGB images acquired by the Intel Realsense LiDAR L515 camera [1], which have been calibrated by software [2][3].<br>
<br>
- LiDAR_DepthMaps:<br>
Depth maps acquired by the Intel Realsense LiDAR L515 camera have been registered to Sequences and calibrated by software [2][3].<br>
<br>
- DERS_DepthMaps:<br>
High-accurate depth maps are estimated by DERS [4] (Depth Estimation Reference Software). The inputs are from Sequences. <br>
<br>
- cfgs/DERS:<br>
Configuration files for implementing the DERS. Please be aware of setting your own system path to reading these files.<br>
<br>
- cam_params.json:<br>
file in OMAF coordinates system (Camera position: X: forwards, Y: left, Z: up, Rotation: yaw, pitch, roll) [5]</p>
<p> # References and links:</p>
<p>[1] https://www.intelrealsense.com/lidar-camera-l515/</p>
<p>[2] https://github.com/ethz-asl/kalibr</p>
<p>[3] https://github.com/colmap/colmap</p>
<p>[4] S.Rogge et al. In: MPEG-I Depth Estimation Reference Software. 2019, pp. 1–6. DOI: 10 .1109/IC3D48390.2019.8975995.</p>
<p>[5] B. Kroon, "Reference View Synthesizer (RVS) manual [N18068]," ISO/IEC JTC1/SC29/WG11, Macau SAR, China, p. 19, Oct. 2018.<br>
https://mpeg.chiariglione.org/standards/mpeg-i/omnidirectional-media-format</p>
Synthetic Rabbit Plenoptic Test Sequence
No full text<p> The test sequence "Synthetic Rabbit" is provided by Sarah Fachada, Daniele Bonatto, Gauthier Lafruit, Mehrdad Teratani, members of the LISA department, EPB (Ecole Polytechnique de Bruxelles), ULB (Universite Libre de Bruxelles), Belgium.</p>
<h3><strong>License: </strong></h3>
<p>CC BY-NC-SA</p>
<p>ONLY Available for Academic Usage </p>
<h3><strong>Terms of Use: </strong></h3>
<p>Anykind of publication or report using this sequence should refer to the following references.</p>
<p>[1] Sarah Fachada, Daniele Bonatto, Gauthier Lafruit, Mehrdad Teratani, "Synthetic Rabbit Plenoptic Test Sequence", 2024.</p>
<p>@misc{fachada_syntheticrabbit_2024,<br> title = {{Synthetic} {Rabbit} {Plenoptic} {Test} {Sequence}},<br> author = {Fachada, Sarah and Bonatto, Daniele and Lafruit, Gauthier and Teratani, Mehrdad },<br> month = mar,<br> year = {2024},<br> doi = {10.5281/zenodo.10894522}<br>}</p>
<h3><strong>Production:</strong></h3>
<p>Laboratory of Image Synthesis and Analysis, LISA department, Ecole Polytechnique de Bruxelles, Universite Libre de Bruxelles, Belgium.</p>
<h3><strong>Content:</strong></h3>
<p>This dataset contains a test scene acquired with synthetic plenoptic cameras and a line of 51 pinhole images. </p>
<p>The dataset structure is the following:</p>
<ul>
<li>"cameras.json" which is a json file with the parameters of the plenoptic cameras and of the pinhole cameras located at the main lens centers;</li>
<li>"cameras_nav.json" which is a json file with the parameters of a line of 51 pinhole cameras;</li>
<li>three folders, "Keplerian", "R5", "R8", each corresponding to a different plenoptic camera models, inspired respectively from Tsinghua University’s camera [1], Raytrix R5 and R8 models [2], each containing:<br>
<ul>
<li>a "color" folder with images in plenoptic format. The images are in 4 versions, without degradation, with blur due to multi-focus, with luminance decay and with blur and luminance decay;</li>
<li>a "depth" folder with depth images associated to the color plenoptic image. The depth maps are in millimeters, from the main lens. We provide the ground truth depth maps, and depth maps obtained from Plenoptic Toolbox [3] and LLMV [4] disparity estimations;</li>
<li>a "pinhole" folder with the pinhole image placed at center of the main lens and its associated depth map;</li>
<li>a "navigation" folder with 51 color pinhole images placed every two millimeters.</li>
</ul>
</li>
</ul>
<h3><br><strong>References and links:</strong></h3>
<p>[1] X. Sun, X. Jin, T. Zhong, et P. Wang, "[MPEG-I Visual] A New Self-designed Focused Plenoptic Camera and the Captured Video Sequence “Boys” [m46259]", Marrakesh, Morocco, janv. 2019. doi: ISO/IEC JTC1/SC29/WG11 MPEG2019/M46259.</p>
<p>[2] Raytrix, https://raytrix.de/</p>
<p>[3] L. Palmieri, R. Koch, et R. O. H. Veld, "The Plenoptic 2.0 Toolbox: Benchmarking of Depth Estimation Methods for MLA-Based Focused Plenoptic Cameras", in 2018 25th IEEE International Conference on Image Processing (ICIP), IEEE, 2018. doi: 10.1109/ICIP.2018.8451073.</p>
<p>[4] D. Bonatto et al., "Multiview from Micro-Lens Image of Multi-Focused Plenoptic Camera", in 2021 International Conference on 3D Immersion, Brussels, Belgium, déc. 2021, p. 8. doi: 10.1109/IC3D53758.2021.9687243.</p>
<p> </p>
<h3><strong>Acknoledgements:</strong></h3>
<p>Sarah Fachada is a postdoctoral researcher of the FNRS<br>This work was supported in part by the FER 2021 project (1060H000066-FAISAN), Belgium; <br>in part by the Emile DEFAY 2021 project (4R00H000236), Belgium; <br>and in part by the FER 2023 project (1060H000075), Belgium.</p>
<p> </p><p>Sarah Fachada is a postdoctoral researcher of the FNRS<br>This work was supported in part by the FER 2021 project (1060H000066-FAISAN), Belgium; <br>in part by the Emile DEFAY 2021 project (4R00H000236), Belgium; <br>and in part by the FER 2023 project (1060H000075), Belgium.</p>
Correlación entre la Escala de dependencia de cuidados de pacientes ingresados en UCI y su perfil epidemiológico
No full textIntroduction: The Intensive Care Unit (ICU) is an environment where critical patients must be treated by a multidisciplinary team. What becomes extremely important to recognize the clinical epidemiological profile to evaluate individually. Objective: To analyze the epidemiological profile of patients admitted to an ICU of a University Hospital and its relationship with the Fugulin scale. Method: This is a retrospective, descriptive study with a quantitative approach, which carried out an analysis of the epidemiological profile, outcomes and variables associated with morbidity and mortality, through reports of patients hospitalized from March to August 2020. Results: It was observed that most of these hospitalized patients were male, referred by the Emergency Medical Care Service, were diagnosed more frequently: acute respiratory failure, sepsis and acute renal failure, with a prevalent outcome in deaths, having been observed correlation of the Fugulin scale with the mortality and severity scores of these patients. Conclusion: In view of the complexity in the care of critically ill patients, the study demonstrates that the Fugulin scale can be an alternative in clinical practice, relating the need for care with severity and mortality to patients in an ICU.Introducción: La Unidad de Cuidados Intensivos (UCI) es un ambiente donde los pacientes críticos deben ser tratados por un equip multidisciplinario. Es de suma importancia reconocer el perfil clínico epidemiológico para evaluar individualmente los pacientes. Objetivo: Analizar el perfil epidemiológico de los pacientes ingresados en una UCI de un Hospital Universitario y su relación con la escala de Fugulin. Método: Estudio retrospectivo, descriptivo, con enfoque cuantitativo, que realizó un análisis del perfil epidemiológico, desenlaces y variables asociadas a la morbimortalidad, a través de relatos de pacientes hospitalizados de marzo a agosto de 2020. Resultados: Se observó que la mayoría de estos pacientes hospitalizados era del sexo masculino, remitidos por el Servicio de Atención Médica de Urgencias, se les diagnosticó con mayor frecuencia: insuficiencia respiratoria aguda, sepsis e insuficiencia renal aguda, con un desenlace prevalente en muertes, habiéndose observado correlación de la escala de Fugulin con la mortalidad y puntuaciones de gravedad de estos pacientes. Conclusión: Ante la complejidad en el cuidado del paciente crítico, el estudio demuestra que la escala de Fugulin puede ser una alternativa en la práctica clínica, relacionando la necesidad de cuidado con la gravedad y mortalidad de los pacientes en uma UCI
Mercer 5: A probable new globular cluster in the Galactic bulge
No full textWe present a detailed study of a dust-obscured Galactic star cluster Mercer 5 ([MCM2005b] 5) in an extremely crowded field in the Milky Way. Near-infrared (near-IR) photometry from United Kingdom Infrared Digital Sky Surveys (UKIDSS) and the Son of ISAAC on the New Technology Telescope (SofI/NTT), combined with near-IR spectroscopy also from SofI, indicates that it is almost certainly a Galactic globular cluster, located at the edge of the Galactic bulge. The cluster suffers ~9 mag of visual extinction, with strong evidence for an extinction gradient across the cluster. A simulation of the differential reddening in the cluster using empirical data from NGC 6539 (chosen because it had high signal-to-noise ratio data and low field star contamination) as a template mimics the observations extremely well. This simulation and other arguments are used to indicate that the most prominent clump of stars in the colour-magnitude diagrams is a horizontal branch clump. On this basis we conclude that the cluster is at a distance of ~5.5kpc and suffers from visual extinction ranging from ~8.5 to ~12.5 mag. Alternative explanations for its nature, such as a young cluster or an old open cluster, are much less likely, on the grounds of no visible main sequence or stars with IR excesses for the former and location versus lifetime arguments for the latter. © 2011 The Authors Monthly Notices of the Royal Astronomical Society © 2011 RAS
Algebraic structures for knot coloring
No full textTitle: Algebraic Structures for Knot Coloring Author: Martina Vaváčková Department: Department of Algebra Supervisor: doc. RNDr. David Stanovský, Ph.D., Department of Algebra Abstract: This thesis is devoted to the study of the algebraic structures providing coloring invariants for knots and links. The main focus is on the relationship between these invariants. First of all, we characterize the binary algebras for arc and semiarc coloring. We give an example that the quandle coloring invariant is strictly stronger than the involutory quandle coloring invariant, and we show the connection between the two definitions of a biquandle, arising from different approaches to semiarc coloring. We use the relationship between links and braids to conclude that quandles and biquandles yield the same coloring invariants. Keywords: knot, coloring invariant, quandle, biquandle ii
Algebraické struktury pro barvení uzlů
No full textTitle: Algebraic Structures for Knot Coloring Author: Martina Vaváčková Department: Department of Algebra Supervisor: doc. RNDr. David Stanovský, Ph.D., Department of Algebra Abstract: This thesis is devoted to the study of the algebraic structures providing coloring invariants for knots and links. The main focus is on the relationship between these invariants. First of all, we characterize the binary algebras for arc and semiarc coloring. We give an example that the quandle coloring invariant is strictly stronger than the involutory quandle coloring invariant, and we show the connection between the two definitions of a biquandle, arising from different approaches to semiarc coloring. We use the relationship between links and braids to conclude that quandles and biquandles yield the same coloring invariants. Keywords: knot, coloring invariant, quandle, biquandle iiiNázev práce: Algebraické struktury barvení uzlů Autor: Martina Vaváčková Katedra: Katedra algebry Vedoucí diplomové práce: doc. RNDr. David Stanovský, Ph.D., Katedra algebry Abstrakt: Tato práce je věnována studiu algebraických struktur, z kterých plynou barvicí invarianty uzlů. Hlavním tématem jsou vztahy mezi těmito invarianty. Nejprve charakte- rizujeme binární algebry barvení oblouků a polooblouků. Uvedeme příklad, který ukazuje, že barvení pomocí quandlů je silnějším invariantem než barvení pomocí involučních quan- dlů, a dokážeme ekvivalenci dvou definic biquandlu, které vycházejí z různých přístupů k barvení polooblouků. S využitím vztahu mezi uzly a copy dojdeme k závěru, že quandly a biquandly dávají stejné barvicí invarianty. Klíčová slova: uzel, barvicí invariant, quandle, biquandleKatedra algebryDepartment of AlgebraMatematicko-fyzikální fakultaFaculty of Mathematics and Physic
