BUSCADOR RECOLECTA

Description of the project

• Research question 1 (RQ-1): Does the implementation of the FC method in MRC require adapting standard FC procedures?
• Research question 2 (RQ-2): Is there a particular methodological framework for applying FC in MRC?

RQ-1 is based on the analysis of FC teaching practices in MRC. The aim was to determine whether interventions with students of different levels affected the sequence and habitual actions in FC.

RQ-2 was to determine some kind of regularity or pattern in the eventual variation in the application of the FC method in these types of spaces.

In order to answer these questions, questionnaire-based research was conducted, complemented by in-depth interviews with teachers in rural multigrade classrooms. The data collected came from teachers in a number of schools located in a specific region, allowing the research to be formulated as a case study.

Description of the dataset

Aggregate data from questionnaires-interviews with teachers in rural multigrade classrooms on the implementation of Flipped Classroom methodologies.

Descripción del proyecto

El estudio se centró en la aplicación del método Flipped Classroom (FC) en el contexto del aula rural multigrado (MRC), a partir de dos preguntas de investigación:

• Pregunta de investigación 1 (RQ-1): ¿La aplicación del método FC en MRC requiere adaptar los procedimientos estándar de FC?
• Pregunta de investigación 2 (RQ-2): ¿Existe un marco metodológico concreto para aplicar el método FC en el MRC?

La RQ-1 se basa en el análisis de las prácticas de enseñanza del FC en MRC. El objetivo era determinar si las intervenciones con alumnos de diferentes niveles afectaban a la secuencia y a las acciones habituales en FC.

La RQ-2 consistió en determinar algún tipo de regularidad o patrón en la eventual variación en la aplicación del método de FC en este tipo de espacios.

Para responder a estas preguntas, se realizó una investigación basada en cuestionarios, complementada con entrevistas en profundidad a docentes de aulas rurales multigrado. Los datos recogidos procedían de profesores de varias escuelas situadas en una región específica, lo que permitió formular la investigación como un estudio de caso.

Descripción del dataset

rurales multigrado sobre la implementación de metodologías Flipped Classroom.

QUAM–AFM is the largest dataset of simulated Atomic Force Microscopy (AFM) images generated from a selection of 685,513 molecules that span the most relevant bonding structures and chemical species in organic chemistry. QUAM-AFM contains, for each molecule, 24 3D image stacks, each consisting of constant-height images simulated for 10 tip-sample distances (in the relevant imaging range and spanning a variation of 1 Å (0.1 nanometers)) with one of the 24 different combination of AFM operational parameters, resulting in a total of 165 million images with a resolution of 256x256 pixels. The 3D stacks are especially appropriate to tackle the goal of chemical identification within AFM experiments by using deep learning techniques.

The operational parameters include six different values for the cantilever oscillation amplitude (0.40, 0.60, 0.80, 1.00, 1.20, 1.40 Å), 4 values of the elastic constant describing the tilting of the CO tip (0.40, 0.60, 0.80 and 1.00 N/m). The first parameter is freely chosen in the experiments in order to enhance different features of the image, while the last one reflects differences in the attachment of the CO molecule to the metal tip that are routinely observed and has been characterized in the experiments.

The data provided for each molecule includes, besides a set of AFM images, the ball–and–stick depiction, the IUPAC name, the chemical formula, the atomic coordinates, and the map of atom heights. In order to simplify the use of the collection as a source of information, we have developed a Graphical User Interface (GUI) that allows the search for structures by CID number, IUPAC name or chemical formula.

This dataset arises as a product of the research carried out in collaboration between Quasar Science Resources S.L. (https://quasarsr.com) and the Scanning Probe Microscopy Theory & Nanomechanics Research Group (SPMTH) (http://www.uam.es/spmth) at the Universidad Autónoma de Madrid (UAM), funded by the Comunidad de Madrid under the Industrial Doctorate Programme 2017 (project reference IND2017/IND-7793).

The main goal of this dataset is to support the development of deep learning methods for molecular identification through AFM imaging. Once this project has concluded, this dataset is made freely accessible in order to facilitate and to promote research in a range of fields including Atomic Force Microscopy, on-surface synthesis and deep learning applications.

This dataset contains the folders including gnuplot scripts and datafile to reproduce all the pictures in the published paper.

• 2DEnLight

The ‘quantum age’ of the 21st century has proven to have a tremendous power to revolutionize not only our science but also many sectors of our economy, industry and everyday-life. Its full potential to shape the future of our society and to take us into a new era far beyond the capabilities of today’s familiar digital landscape is yet to be realized. Among many existing candidates for developing and testing fundamental as well as technically innovative ideas in the quantum realm, the quantum aspects of light and light-matter interactions are one of the most fascinating and rapidly emerging research fields. In particular, the non-classical light sources emitting photons with controllable quantum correlations are at the heart of most applications in quantum communication and information processing. The 2DEnLight project focusses on the controllable production of light at its fundamental single-photon limit as well as manipulation of its intrinsic properties. Our proposal includes the possibility of engineering and manipulating coupled emitter-light systems capable of generating non-classical photon streams and demonstrating tunable quantum correlations both at the few- and many-body level.

• NanoQuCo

With NanoQuCo we will design quantum computers based on quantum nanophotonics to overcome the size and speed limitations of current limitations of current platforms, and realize new quantum computing algorithms with near-term applications.

The reemergence of China is changing the world, and that EU needs to develop a long-term approach based on research-based knowledge in order to engage strategically with an increasingly assertive China.

This dataset consists of a semi-structured interview with a person of Chinese nationality, carried out in Chinese and transcribed in Chinese language.