Room temperature ferromagnetic-like behavior in Mn-implanted and post-annealed InAs layers deposited by Molecular Beam Epitaxy

We report on the magnetic and structural properties of Ar and Mn implanted InAs epitaxial films grown on GaAs (100) by Molecular Beam Epitaxy (MBE) and the effect of Rapid Thermal Annealing (RTA) for 30 seconds at 750C. Channeling Particle Induced X- ray Emission (PIXE) experiments reveal that after Mn implantation almost all Mn atoms are subsbtitutional in the In-site of the InAs lattice, like in a diluted magnetic semiconductor (DMS). All of these samples show diamagnetic behavior. But, after RTA treatment the Mn-InAs films exhibit room-temperature magnetism. According to PIXE measurements the Mn atoms are no longer substitutional. When the same set of experiments were performed with As as implantation ion all of the layers present diamagnetism without exception. This indicates that the appearance of room-temperature ferromagnetic-like behavior in the Mn-InAs-RTA layer is not related to lattice disorder produce during implantation, but to a Mn reaction produced after a short thermal treatment. X-ray diffraction patterns (XRD) and Rutherford Back Scattering (RBS) measurements evidence the segregation of an oxygen deficient-MnO2 phase (nominally MnO1.94) in the Mn-InAs-RTA epitaxial layers which might be on the origin of room temperature ferromagnetic-like response observed.Comment: 16 pages, 5 figures. Acepted in J. Appl. Phy

InAs/InP single quantum wire formation and emission at 1.5 microns

Isolated InAs/InP self-assembled quantum wires have been grown using in situ accumulated stress measurements to adjust the optimal InAs thickness. Atomic force microscopy imaging shows highly asymmetric nanostructures with average length exceeding more than ten times their width. High resolution optical investigation of as-grown samples reveals strong photoluminescence from individual quantum wires at 1.5 microns. Additional sharp features are related to monolayer fluctuations of the two dimensional InAs layer present during the early stages of the quantum wire self-assembling process.Comment: 4 pages and 3 figures submitted to Applied Physics Letter

Computational thinking and robotics in education

After the computational thinking sessions in the previous 2016-2018 editions of TEEM Conference, the fourth edition of this track has been organized in the current 2019 edition. Computational thinking is still a very significant topic, especially, but not only, in pre-university education. In this edition, the robotic has a special role in the track, with a strength relationship with the STEM and STEAM education of children at the pre-university levels, seeding the future of our society

A Container-Based Workflow for Distributed Training of Deep Learning Algorithms in HPC Clusters

Deep learning has been postulated as a solution for numerous problems in different branches of science. Given the resource-intensive nature of these models, they often need to be executed on specialized hardware such graphical processing units (GPUs) in a distributed manner. In the academic field, researchers get access to this kind of resources through High Performance Computing (HPC) clusters. This kind of infrastructures make the training of these models difficult due to their multi-user nature and limited user permission. In addition, different HPC clusters may possess different peculiarities that can entangle the research cycle (e.g., libraries dependencies). In this paper we develop a workflow and methodology for the distributed training of deep learning models in HPC clusters which provides researchers with a series of novel advantages. It relies on udocker as containerization tool and on Horovod as library for the distribution of the models across multiple GPUs. udocker does not need any special permission, allowing researchers to run the entire workflow without relying on any administrator. Horovod ensures the efficient distribution of the training independently of the deep learning framework used. Additionally, due to containerization and specific features of the workflow, it provides researchers with a cluster-agnostic way of running their models. The experiments carried out show that the workflow offers good scalability in the distributed training of the models and that it easily adapts to different clusters.Comment: Under review for Cluster Computin

A container-based workflow for distributed training of deep learning algorithms in HPC clusters

Deep learning has been postulated as a solution for numerous problems in different branches of science. Given the resource-intensive nature of these models, they often need to be executed on specialized hardware such graphical processing units (GPUs) in a distributed manner. In the academic field, researchers get access to this kind of resources through High Performance Computing (HPC) clusters. This kind of infrastructures make the training of these models difficult due to their multi-user nature and limited user permission. In addition, different HPC clusters may possess different peculiarities that can entangle the research cycle (e.g., libraries dependencies). In this paper we develop a workflow and methodology for the distributed training of deep learning models in HPC clusters which provides researchers with a series of novel advantages. It relies on udocker as containerization tool and on Horovod as library for the distribution of the models across multiple GPUs. udocker does not need any special permission, allowing researchers to run the entire workflow without relying on any administrator. Horovod ensures the efficient distribution of the training independently of the deep learning framework used. Additionally, due to containerization and specific features of the workflow, it provides researchers with a cluster-agnostic way of running their models. The experiments carried out show that the workflow offers good scalability in the distributed training of the models and that it easily adapts to different clusters

Validación Experimental de Probetas Impresas en 3D para selección de material de fabricación de prótesis externas de seno

El presente PAP, es parte de un proyecto iniciado en el semestre de Primavera 2020. En el periodo de Verano 2022 en el Programa de Desarrollo Tecnológico para la Sustentabilidad Ambiental, Energética y Alimentaria se trabajó en la realización de ensayos de tensión y dureza a probetas de materiales TPU, ABS y PLA. Esto, con la finalidad de elegir el material adecuado para la fabricación de una prótesis externa de seno. Para lograr este propósito se plantearon tres objetivos específicos: Realizar una revisión en la literatura acerca de las propiedades mecánicas de los materiales TPU, ABS y PLA y de las pruebas de evaluación mecánica , establecer parámetros de pruebas mecánicas de los polímeros, realizar ensayos de tensión y dureza en probetas fabricadas por impresión 3D de los materiales TPU, ABS y PLA e interpretar de las gráficas obtenidas el comportamiento mecánico de los polímeros. Para lo anteriormente mencionado, se realizaron ensayos de dureza Rockwell en cinco probetas, cuyos valores obtenidos se consideraron como no concluyentes. Posteriormente, se realizaron los ensayos de tensión, de los cuales se obtuvieron datos significativos para el cumplimiento del objetivo general. A partir de los resultados obtenidos de los ensayos de tensión se definió el material óptimo para la fabricación de la prótesis externa de seno.ITESO, A.C

Biomarkers in ocular chronic graft versus host disease: tear cytokine- and chemokine-based predictive model.

Producción CientíficaPurpose: To develop a tear molecule level-based predictive model based on a panel of tear cytokines and their correlation with clinical features in ocular chronic graft versus host disease (cGVHD). Methods: Twenty-two ocular cGVHD patients and 21 healthy subjects were evaluated in a controlled environmental research laboratory (CERLab). Clinical parameters were recorded, and tears were collected. Levels of 15 molecules (epidermal growth factor [EGF], IL receptor antagonist [IL-1Ra], IL-1β, IL-2, IL-6, IL-8/CXCL8, IL-10, IL-12p70, IL-17A, interferon inducible protein [IP]-10/CXCL10, IFN-γ, VEGF, TNF-α, eotaxin 1, and regulated on activation normal T cell expressed and secreted [RANTES]) were measured by multiplex-bead assay and correlated with clinical parameters. Logistic regression was used to develop a predictive model. Leave-one-out cross-validation was applied. Classification capacity was evaluated in a cohort of individuals with dry eye (DE) of other etiologies different from GVHD. Results: Epidermal growth factor and IP-10/CXCL10 levels were significantly decreased in ocular cGVHD, positively correlating with tear production and stability and negatively correlating with symptoms, hyperemia, and vital staining. Interleukin-1Ra, IL-8/CXCL8, and IL-10 were significantly increased in ocular cGVHD, and the first two correlated positively with symptoms, hyperemia, and ocular surface integrity while negatively correlating with tear production and stability. Predictive models were generated, and the best panel was based on IL-8/CXCL8 and IP-10/CXCL10 tear levels along with age and sex, with an area under the receiving operating curve of 0.9004, sensitivity of 86.36%, and specificity of 95.24%. Conclusions: A predictive model based on tear levels of IL-8/CXCL8 and IP-10/CXCL10 resulted in optimal sensitivity and specificity. These results add further knowledge to the search for potential biomarkers in this devastating ocular inflammatory disease.Ministry of Economy and Competitiveness, Madrid, Spain, SAF-2010 15631 (AES)

Teaching field geology in Spain

The Department of Crystallography and Mineralogy (Complutense University, Madrid) carries out every year a field geology course in San José - Rodalquilar (Almería, SE Spain. The region of Almería offers a unique opportunity for the teaching of field geology because of the variety of contrasted geologic scenarios: 1) Alpine metamorphic complexes; 2) Miocene sedimentary basins; 3) Miocene volcanic rocks including world-class pyroclastic deposits of almost every possible type; 4) epithermal gold and industrial minerals deposits; and 5) a second to none large fault zone (Carboneras Fault Zone, Serrata de Níjar). However, what makes different our field geology course is the fact that the students, in teams of 3 to 4 members, simulate a professional survey. Given that most students will end up working for companies, it is important that they receive some practical training before they leave the university. [RESUMEN] El Departamento de Cristalografía y Mineralogía de la Universidad Complutense de Madrid realiza anualmente un curso de geología de campo en San José – Rodalquilar (Almería, Sureste de España). La región de Almería ofrece una oportunidad única para la enseñanza de la geología de campo ya que en ella encontramos una gran variedad de escenarios geológicos: 1) complejos alpinos; 2) cuencas sedimentarias del Mioceno; 3) rocas volcánicas del Mioceno con extraordinarios ejemplos de diferentes tipos de depósitos piroclásticos; 4) yacimientos epitermales de oro, yacimientos de bentonitas, alunita, y zeolitas; y 5) una gran zona de falla (Zona de Falla de Carboneras, Serrata de Níjar). Sin embargo, lo que hace diferente nuestro curso de campo es el hecho de que los alumnos, en equipos de 3 o 4 miembros, simulan estar realizando un trabajo profesional. Dado que la mayor parte de los alumnos acabará trabajando para alguna empresa, nos parece importante que reciban alguna formación práctica antes de que acaben la carrera