Difract: Un nuevo laboratorio virtual para la modelización matemática de las propiedades de difracción de redes fractales

[EN] This work presents a new virtual laboratory, Difract, developed with Easy Java Simulations, for using in Optics courses as a computer tool for the mathematical modelling of the diffraction properties of 1D and 2D fractal gratings. This virtual laboratory enables students to quickly and easily analyze the influence on the Fraunhofer diffraction pattern of the different construction parameters of the fractal grating. As an application example, the Cantor fractal set has been considered.[ES] En este trabajo presentamos un nuevo laboratorio virtual, Difract, desarrollado con Easy Java Simulations para su uso en cursos de Óptica como una herramienta informática para la modelización matemática de las propiedades de difracción de redes fractales 1D y 2D. Este laboratorio virtual permite a los estudiantes analizar rápida y fácilmente la influencia en el patrón de difracción de Fraunhofer de los diferentes parámetros de construcción de la red fractal. Como ejemplo de aplicación se ha considerado el conjunto fractal de Cantor.Giménez, M.; Monsoriu, J.; Giménez, F.; Pons, A.; Barreiro, J.; Furlan, W. (2011). Difract: Un nuevo laboratorio virtual para la modelización matemática de las propiedades de difracción de redes fractales. Modelling in Science Education and Learning. 4:223-229. doi:10.4995/msel.2011.3075SWORD223229

Analysis of false waves in numerical sea simulations

[EN] It is common practice to consider the random sea waves as a succession of discrete waves characterized by individual amplitudes and periods. The zero-up-crossing criterion for discretizing waves, as well as other criteria proposed by different authors, has been found to isolate some discrete waves that do not correspond to physical waves. These false waves alter the wave statistics of random sea waves. A new orbital criterion is proposed to avoid this problem. The orbital criterion has been shown to be consistent and robust with respect to the zero-up-crossing criterion. Furthermore, the new criterion produces a distribution of wave heights in better agreement with the Rayleigh distribution. The mean period of the discrete waves corresponding to the orbital criterion is proved to be T01, while the mean period of the zero-up-crossing waves is T02. A formula relating the Longuet-Higgins spectral bandwidth nu with the relative number of false waves is given.Gimenez Valentin, MH.; Sánchez Carratalá, CR.; Medina, JR. (1994). Analysis of false waves in numerical sea simulations. Ocean Engineering. 21(8):751-764. doi:10.1016/0029-8018(94)90050-7S75176421

Co-productive agility and four collaborative pathways to sustainability transformations

Co-production, the collaborative weaving of research and practice by diverse societal actors, is argued to play an important role in sustainability transformations. Yet, there is still poor understanding of how to navigate the tensions that emerge in these processes. Through analyzing 32 initiatives worldwide that co-produced knowledge and action to foster sustainable social-ecological relations, we conceptualize ‘co-productive agility’ as an emergent feature vital for turning tensions into transformations. Co-productive agility refers to the willingness and ability of diverse actors to iteratively engage in reflexive dialogues to grow shared ideas and actions that would not have been possible from the outset. It relies on embedding knowledge production within processes of change to constantly recognize, reposition, and navigate tensions and opportunities. Co-productive agility opens up multiple pathways to transformation through: (1) elevating marginalized agendas in ways that maintain their integrity and broaden struggles for justice; (2) questioning dominant agendas by engaging with power in ways that challenge assumptions, (3) navigating conflicting agendas to actively transform interlinked paradigms, practices, and structures; (4) exploring diverse agendas to foster learning and mutual respect for a plurality of perspectives. We explore six process considerations that vary by these four pathways and provide a framework to enable agility in sustainability transformations. We argue that research and practice spend too much time closing down debate over different agendas for change – thereby avoiding, suppressing, or polarizing tensions, and call for more efforts to facilitate better interactions among different agendas

Co-productive agility and four collaborative pathways to sustainability transformations

Co-production, the collaborative weaving of research and practice by diverse societal actors, is argued to play an important role in sustainability transformations. Yet, there is still poor understanding of how to navigate the tensions that emerge in these processes. Through analyzing 32 initiatives worldwide that co-produced knowledge and action to foster sustainable social-ecological relations, we conceptualize ‘co-productive agility’ as an emergent feature vital for turning tensions into transformations. Co-productive agility refers to the willingness and ability of diverse actors to iteratively engage in reflexive dialogues to grow shared ideas and actions that would not have been possible from the outset. It relies on embedding knowledge production within processes of change to constantly recognize, reposition, and navigate tensions and opportunities. Co-productive agility opens up multiple pathways to transformation through: (1) elevating marginalized agendas in ways that maintain their integrity and broaden struggles for justice; (2) questioning dominant agendas by engaging with power in ways that challenge assumptions, (3) navigating conflicting agendas to actively transform interlinked paradigms, practices, and structures; (4) exploring diverse agendas to foster learning and mutual respect for a plurality of perspectives. We explore six process considerations that vary by these four pathways and provide a framework to enable agility in sustainability transformations. We argue that research and practice spend too much time closing down debate over different agendas for change – thereby avoiding, suppressing, or polarizing tensions, and call for more efforts to facilitate better interactions among different agendas

Modelización de superredes cuánticas con Mathematica

[EN] Quantum superlattices are composite aperiodic structures comprised of alternating layers of several semiconductors following the rules of an aperiodic sequence. From a pedagogical point of view, it is easy to obtain the electronic scattering properties of these systems by means of the Transfer Matrix Method (TMM). In this work we present a TMM code developed in Mathematica that allows modeling periodic and aperiodic superlattices for motivating students of quantum physics by using unconventional geometries such as fractals or the Fibonacci sequence.[ES] Las superredes cuánticas son dispositivos nanoestruturados formados por varias capas delgadas de semiconductores distribuidas generalmente de forma periódica. Desde un punto de vista pedagógico, resulta sencillo determinar la dispersión de electrones en estos sistemas aplicando un modelo de pozos de potencial definido por la estructura de la red. De esta forma, los coeficientes de transmisión y reflexión pueden calcularse con fines docentes mediante el uso del Método de las Matrices de Transferencia (MMT). En esta contribución se presenta un sencillo código MMT desarrollado con Mathematica que permite la modelización tanto de redes periódicas como de superredes aperiódicas cuasirregulares con la intención de motivar a los estudiantes de física cuántica mediante el uso de geometrías no convencionales como son los fractales o la sucesión de Fibonacci.Monsoriu, J.; Giménez, M.; Giménez, F.; Marín, M. (2011). Modelización de superredes cuánticas con Mathematica. Modelling in Science Education and Learning. 4:299-305. doi:10.4995/msel.2011.3094SWORD299305