Modelling Desert Dune Fields Based on Discrete Dynamics

A mathematical formulation is developed to model the dynamics of sand dunes. The physical processes display strong non-linearity that has been taken into account in the model. When assessing the success of such a model in capturing physical features we monitor morphology, dune growth, dune migration and spatial patterns within a dune field. Following recent advances, the proposed model is based on a discrete lattice dynamics approach with new features taken into account which reflect physically observed mechanisms

Skin modes in a nonlinear Hatano-Nelson model

Non-Hermitian lattices with non-reciprocal couplings under open boundary conditions are known to possess linear modes exponentially localized on one edge of the chain. This phenomenon, dubbed non-Hermitian skin effect, induces all input waves in the linearized limit of the system to unidirectionally propagate toward the system's preferred boundary. Here we investigate the fate of the non-Hermitian skin effect in the presence of Kerr-type nonlinearity within the well-established Hatano-Nelson lattice model. Our method is to probe the presence of nonlinear stationary modes which are localized at the favored edge, when the Hatano-Nelson model deviates from the linear regime. Based on perturbation theory, we show that families of nonlinear skin modes emerge from the linear ones at any non-reciprocal strength. Our findings reveal that, in the case of focusing nonlinearity, these families of nonlinear skin modes tend to exhibit enhanced localization, bridging the gap between weakly nonlinear modes and the highly nonlinear states (discrete solitons) when approaching the anti-continuum limit with vanishing couplings. Conversely, for defocusing nonlinearity, these nonlinear skin modes tend to become more extended than their linear counterpart. To assess the stability of these solutions, we conduct a linear stability analysis across the entire spectrum of obtained nonlinear modes and also explore representative examples of their evolution dynamics.Comment: 12 pages, 8 figure

A Markov Approach for Increasing Precision in the Assessment of Data-Intensive Behavioral Interventions

Health interventions using real-time sensing technology are characterized by intensive longitudinal data, which has the potential to enable nuanced evaluations of individuals’ responses to treatment. Existing analytic tools were not developed to capitalize on this opportunity as they typically focus on first-order findings such as changes in the level and/or slope of outcome variables over different intervention phases. This paper introduces an exploratory, Markov-based empirical transition method that offers a more comprehensive assessment of behavioral responses when intensive longitudinal data are available. The procedure projects a univariate time-series into discrete states and empirically determines the probability of transitioning from one state to another. State transition probabilities are summarized separately in phase-specific transition matrices. Comparing transition matrices illuminates intricate, quantifiable differences in behavior between intervention phases. Statistical significance is estimated via bootstrapping techniques. This paper introduces the methodology via three case studies from a secondhand smoke reduction trial utilizing real-time air particle sensors. Analysis enabled the identification of complex phenomena such as avoidance and escape behavior in response to punitive contingencies for tobacco use. Additionally, the largest changes in behavior dynamics were associated with the introduction of behavioral feedback. The Markov approach‘s ability to elucidate subtle behavioral details has not typically been feasible with standard methodologies, mainly due to historical limitations associated with infrequent repeated measures. These results suggest that the evaluation of intervention effects in data-intensive single-case designs can be enhanced, providing rich information that can ultimately be used to develop interventions uniquely tailored to specific individuals

Molecular Materials For Organic Electronics.

Organic materials have proven to be efficient active materials in electronics, being possible alternatives to inorganic semiconductors in electronic devices, such as organic field effects transistors (OFETs) or organic solar cells. The versatility of organic synthesis allows us to endow small molecules or polymers with the desired optoelectronic properties. However, the final efficiency of a given device is not only based on the molecular design but also on the way the molecules assemble. In this sense, non-covalent interactions play a crucial role as they are able to control the supramolecular assembly. Hydrogen-bonding has been proven a promising strategy to improve the film morphology in organic electronic devices with semiconductors able to efficiently transport charges. In this project, two compounds have been studied, based on a straightforward diketopyrrolopyrrole (DPP) with a thiophene-capped as the electroactive component and amide groups serving as the hydrogen-bonding units1. Theamide groups are positioned with two different topologies, C-centered (C-1) or N-centered (N-1) which are five carbons apart from the lactam rings of the DPP. We have compared these materials with the control derivative, 1, whose structure lack amide groups (Figure 1). Finally, the potential of these semicondcutors as active components in organic electronics have been tested in organic field effects transistors (OFETs).Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Computational Model for Behavior Shaping as an Adaptive Health Intervention Strategy

Adaptive behavioral interventions that automatically adjust in real-time to participants’ changing behavior, environmental contexts, and individual history are becoming more feasible as the use of real-time sensing technology expands. This development is expected to improve shortcomings associated with traditional behavioral interventions, such as the reliance on imprecise intervention procedures and limited/short-lived effects. JITAI adaptation strategies often lack a theoretical foundation. Increasing the theoretical fidelity of a trial has been shown to increase effectiveness. This research explores the use of shaping, a well-known process from behavioral theory for engendering or maintaining a target behavior, as a JITAI adaptation strategy. A computational model of behavior dynamics and operant conditioning was modified to incorporate the construct of behavior shaping by adding the ability to vary, over time, the range of behaviors that were reinforced when emitted. Digital experiments were performed with this updated model for a range of parameters in order to identify the behavior shaping features that optimally generated target behavior. Narrowing the range of reinforced behaviors continuously in time led to better outcomes compared with a discrete narrowing of the reinforcement window. Rapid narrowing followed by more moderate decreases in window size was more effective in generating target behavior than the inverse scenario. The computational shaping model represents an effective tool for investigating JITAI adaptation strategies. Model parameters must now be translated from the digital domain to real-world experiments so that model findings can be validated

A Korteweg-de Vries description of dark solitons in polariton superfluids

We study the dynamics of dark solitons in an incoherently pumped exciton-polariton condensate by means of a system composed by a generalized open-dissipative Gross-Pitaevskii equation for the polaritons’ wavefunction and a rate equation for the exciton reservoir density. Considering a perturbative regime of sufficiently small reservoir excitations, we use the reductive perturbation method, to reduce the system to a Korteweg-de Vries (KdV) equation with linear loss. This model is used to describe the analytical form and the dynamics of dark solitons. We show that the polariton field supports decaying dark soliton solutions with a decay rate determined analytically in the weak pumping regime. We also find that the dark soliton evolution is accompanied by a shelf, whose dynamics follows qualitatively the effective KdV picture

From nodeless clouds and vortices to gray ring solitons and symmetry-broken states in two-dimensional polariton condensates

We consider the existence, stability and dynamics of the nodeless state and fundamental nonlinear excitations, such as vortices, for a quasi-two-dimensional polariton condensate in the presence of pumping and nonlinear damping. We find a series of interesting features that can be directly contrasted to the case of the typically energy-conserving ultracold alkali-atom Bose–Einstein condensates (BECs). For sizeable parameter ranges, in line with earlier findings, the nodeless state becomes unstable towards the formation of stable nonlinear single or multi-vortex excitations. The potential instability of the single vortex is also examined and is found to possess similar characteristics to those of the nodeless cloud. We also report that, contrary to what is known, e.g., for the atomic BEC case, stable stationary gray ring solitons (that can be thought of as radial forms of Nozaki–Bekki holes) can be found for polariton condensates in suitable parametric regimes. In other regimes, however, these may also suffer symmetry-breaking instabilities. The dynamical, pattern-forming implications of the above instabilities are explored through direct numerical simulations and, in turn, give rise to waveforms with triangular or quadrupolar symmetry.MICINN project FIS2008-0484

Energy localization and transport in two-dimensional electrical lattices

Intrinsic localized modes (ILMs) have been generated and characterized in two-dimensional nonlinear electrical lattices which were driven by a spatially-uniform voltage signal. These ILMs were found to be either stationary or mobile, depending on the details of the lattice unit-cell, as had already been reported in one-dimensional lattices; however, the mo- tion of these ILMs is qualitatively di erent in that it lacks a consistent direction. Furthermore, the hop- ping speed seems to be somewhat reduced in two di- mensions due to an enhanced Peierls-Nabarro (PN)- barrier. We investigate both square and honeycomb lattices composed of 6 x 6 elements. These direct ob- servations were further supported by numerical simu- lations based on realistic models of circuit components. The numerical study moreover allowed for an analysis of ILM dynamics and pattern formation for larger lat- tice sizes

Generation of localized modes in an electrical lattice using subharmonic driving

We show experimentally and numerically that an intrinsic localized mode (ILM) can be stably produced (and experimentally observed) via subharmonic, spatially homogenous driving in the context of a nonlinear electrical lattice. The precise nonlinear spatial response of the system has been seen to depend on the relative location in frequency between the driver frequency, $\omega_d$, and the bottom of the linear dispersion curve, $\omega_0$. If $\omega_d / 2$ lies just below $\omega_0$, then a single ILM can be generated in a 32-node lattice, whereas when $\omega_d / 2$ lies within the dispersion band, a spatially extended waveform resembling a train of ILMs results. To our knowledge, and despite its apparently broad relevance, such an experimental observation of subharmonically driven ILMs has not been previously reported