Extended states in random dimer gated graphene superlattices.

Ordered and disordered semiconductor superlattices represent structures with completely opposed properties. For instance, ordered superlattices exhibit extended Bloch-like states, while disordered superlattices present localized states. These characteristics lead to higher conductance in ordered superlattices compared to disordered ones. Surprisingly, disordered dimer superlattices, which consist of two types of quantum wells with one type always appearing in pairs, exhibit extended states. The percentage of dissimilar wells does not need to be large to have extended states. Furthermore, the conductance is intermediate between ordered and disordered superlattices. In this work, we explore disordered dimer superlattices in graphene. We calculate the transmission and transport properties using the transfer matrix method and the Landauer-Büttiker formalism, respectively. We identify and discuss the main energy regions where the conductance of random dimer superlattices in graphene is intermediate to that of ordered and disordered superlattices. We also analyze the resonant energies of the double quantum well cavity and the electronic structure of the host gated graphene superlattice (GGSL), finding that the coupling between the resonant energies and the superlattice energy minibands gives rise to the extended states in random dimer GGSLs.

Texture Analysis of Dried Droplets for the Quality Control of Medicines.

The quality control of medicines guarantees the effectiveness of treatments for diseases. We explore the use of texture analysis of patterns in dried droplets as a tool to readily detect both impurities and changes in drug concentration. Four types of medicines associated with different routes of administration were analyzed: Methotrexate, Ciprofloxacin, Clonazepam, and Budesonide. We use NaCl and a hot substrate at 63 ∘C to promote aggregate formation and to reduce droplet drying time. Depending on the medicine, optical microscopy reveals different complex aggregates such as circular to oval splatters, fern-like islands, crown shapes, crown needle-like and bump-like patterns as well as dendritic branched and star-like crystals. We use some physical features of the stains (as the stain diameter and superficial area) and gray level co-occurrence matrix (GLCM) to characterize patterns of dried droplets. Finally, we show that structural analysis of stains can achieve 95% accuracy in identifying medicines with 30% water dilution, while it achieves 99% accuracy in detecting drugs with 10% other substances.

Effects of substrate temperature on patterns produced by dried droplets of proteins.

Rapid diagnosis provides better clinical management of patients, helps control possible outbreaks, and increases survival. The study of deposits produced by the evaporation of droplets is a useful tool in the diagnosis of some health problems. With the aim to improve diagnostic time in clinical practice where we use the evaporation of droplets, we explored the effects of substrate temperature on pattern formation of dried droplets in globular protein solutions. Three deposit groups were observed: "functional" patterns (from 25 to 37 ∘C), "transition" patterns (from 44 to 50 ∘C), and "eye" patterns (from 58 to 63 ∘C). The dried droplets of the first two groups show a ring structure ("coffee-ring") that confines a great diversity of aggregates such as needle-like structures, tiny blade-shape crystals, highly symmetrical crystallization patterns, and amorphous salt aggregates. In contrast, the "eye" patterns are deposits with a large inner aggregate surrounded by a coffee ring, and they can appear from the evaporation of droplets in protein binary mixtures and blood serum. Interestingly, the unfolding proteins correlates with the formation of "eye" patterns. We measured stain diameter, "coffee-ring" thickness, radial density profile, and entropy computed by GLCM-statistics to quantify the structural differences among deposit groups. We found that "functional" patterns are structurally indistinguishable among them, but they are clearly different from elements of the other deposit groups. An exponential decay function describes pattern formation time as a function of substrate temperature, which is independent from protein concentration. Patterns formation at 32 ∘C takes place up to 63% less time and preserves the structural characteristics of dried droplets in proteins formed at room temperature. Therefore, we argue that droplet evaporation at this substrate temperature could be an excellent candidate to make a more efficient diagnosis based on droplet evaporation of biofluids.

Floral morphogenesis: stochastic explorations of a gene network epigenetic landscape.

In contrast to the classical view of development as a preprogrammed and deterministic process, recent studies have demonstrated that stochastic perturbations of highly non-linear systems may underlie the emergence and stability of biological patterns. Herein, we address the question of whether noise contributes to the generation of the stereotypical temporal pattern in gene expression during flower development. We modeled the regulatory network of organ identity genes in the Arabidopsis thaliana flower as a stochastic system. This network has previously been shown to converge to ten fixed-point attractors, each with gene expression arrays that characterize inflorescence cells and primordial cells of sepals, petals, stamens, and carpels. The network used is binary, and the logical rules that govern its dynamics are grounded in experimental evidence. We introduced different levels of uncertainty in the updating rules of the network. Interestingly, for a level of noise of around 0.5-10%, the system exhibited a sequence of transitions among attractors that mimics the sequence of gene activation configurations observed in real flowers. We also implemented the gene regulatory network as a continuous system using the Glass model of differential equations, that can be considered as a first approximation of kinetic-reaction equations, but which are not necessarily equivalent to the Boolean model. Interestingly, the Glass dynamics recover a temporal sequence of attractors, that is qualitatively similar, although not identical, to that obtained using the Boolean model. Thus, time ordering in the emergence of cell-fate patterns is not an artifact of synchronous updating in the Boolean model. Therefore, our model provides a novel explanation for the emergence and robustness of the ubiquitous temporal pattern of floral organ specification. It also constitutes a new approach to understanding morphogenesis, providing predictions on the population dynamics of cells with different genetic configurations during development.

Comparing the coherence resonance curves invoked by different types of forcing.

We study the different coherence resonance (CR) phenomena induced when an excitable FitzHugh-Nagumo-type system is forced using diverse deterministic and/or stochastic time series. The possible implications of this comparative study involving these different CR's are also discussed. The main result of the present work suggests that for appropriate forcing and system parameters the generated CR curves reflect the correlations of the superimposed time series.

Regulating noise-induced spiking using feedback.

We report successful manipulation of the noise provoked spiking behavior using delayed feedback control. Experiments were performed in a three electrode electrochemical cell under potentiostatic conditions. The uncontrolled system exhibited noise invoked oscillations whose regularity was quantified using normalized variance (NV). Superimposing delayed feedback, for appropriate values of delay (t), an enhancement in the regularity of the spike sequence was attained. Numerical simulations corroborated experimental observations.

Intrinsic coherence resonance in an electrochemical cell.

We study the interaction of intrinsic electrochemical noise with autonomous nonlinear dynamics of a three-electrode electrochemical cell. The amplitude of this intrinsic (internal) noise, regulated by the concentration of chloride ions, is monotonically increased and the provoked dynamics is analyzed. The experimentally constructed coherence factor beta versus the concentration of the chloride ions' curve has a unimodal shape indicating the emergence of intrinsic coherence resonance. The abscissa for the maxima of this unimodal curve corresponds to the optimum value of intrinsic noise where maximum regularity of the invoked dynamics is observed.

Stochastic resonance of electrochemical aperiodic spike trains.

Aperiodic stochastic resonance in an electrochemical system with excitable dynamics is characterized in experiments and simulations. Two different spike trains, one with stochastic and the other with chaotic interspike intervals, are imposed on the system as subthreshold aperiodic signals. Information transmission is quantified by the cross correlation between the subthreshold input signal and the noise induced system response. A maximum is exhibited in the input-output correlation as a function of the noise amplitude. Numerical simulations with an electrochemical model are in excellent agreement with the experimental observations.

Experimental evidence of coexisting periodic stochastic resonance and coherence resonance phenomena.

We report evidence of coexisting period stochastic resonance (PSR) and coherence resonance (CR) phenomena in an electrochemical cell. The anodic voltage (V) in the cell is chosen such that the anodic current (I) exhibits excitable fixed point behavior. Subsequently, the anodic voltage is modulated by an external perturbation that is a composite of a subthreshold periodic pulse signal and Gaussian white noise (GWN). As the amplitude of the GWN is increased, the regularity of the invoked dynamics is analyzed using normalized variance curve. The calculated resonance curve shows a double minima, implying the existence of two optimum noise levels where enhanced regularity of the induced spike sequence is detected. Numerical simulations corroborate experimental findings.

Experiments on coherence resonance: noisy precursors to Hopf bifurcations.

Experimental and numerical evidence of coherence resonance in an electrochemical system is reported. External noise with a Gaussian distribution is superimposed on the system when the anodic current is exhibiting stationary (fixed point) dynamics below a supercritical Hopf bifurcation. The amplitude of the added stochastic perturbations is increased monotonically and the induced oscillatory behavior is analyzed. It is observed, both in experiments and in simulations, that the regularity of the noise induced current oscillations reaches a maximum value for an optimum noise level. This is indicative of coherence resonance and can be explained with a mechanism based on noisy precursors to a Hopf bifurcation.

Resonances via deterministic and stochastic perturbations: a comparative study.

We study periodic and coherence resonances invoked by aperiodic yet deterministic perturbations. Chaotic perturbations with varying levels of intrinsic correlations are superimposed parametrically on an excitable chemical model. This enables us to analyze the system response and characterize the induced resonances as a function of correlation in the perturbing signal. Using standard measures such as normalized variance and normalized number of peaks, dynamics for different deterministic signals are quantified and eventually compared to resonances invoked via stochastic perturbations.