We propose a nanosensor with a biological active part able to identify specific odorants. The biological part should be constituted by olfactory receptors pertaining to the G protein-coupled receptors, the most efficient natural sensors for odorant discrimination. Modeling, design, and experiments performed for proving the concept are reported and discussed.

We show that, in particular experimental conditions, the time course of the radiant fluxes, measured from a bioluminescent emission of a Vibrio harveyi related strain, collapse after suitable rescaling onto the Gumbel distribution of extreme value theory. We argue that the activation times of the strain luminous emission follow the universal behavior described by this statistical law, in spite of the fact that no extremal process is known to occur.

We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida, a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence 'quenching' after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi.

Experiments in organic semiconductors (polyacenes) evidence a strong super quadratic increase of the current–voltage (I–V) characteristic at voltages in the transition region between linear (Ohmic) and quadratic (trap-free space-charge-limited current) behaviors. Similarly, excess noise measurements at a given frequency and increasing voltages evidence a sharp peak of the relative spectral density of the current noise in concomitance with the strong superquadratic I–V characteristics. Here, we discuss the physical interpretation of these experiments in terms of an essential contribution from ¯eld-assisted trapping-detrapping processes of injected carriers. To this purpose, the fraction of ¯lled traps determined by the I–V characteristics is used to evaluate the excess noise in the trap-¯lled transition (TFT) regime. We have found an excellent agreement between the predictions of our model and existing experimental results in tetracene and pentacene thin ¯lms of di®erent length in the range 0:65 35 m.

Regime shifts in ecosystems caused by climatic or anthropogenic factors can happen on a relatively short timescale with relevant economic and social effects, a consideration which motivates the large interest in the literature to this topic. A special case of regime shift is given by desertification transitions in semi-arid ecosystems. One desertification model, recently proposed, seems particularly effective in describing several ecological landscapes, taking into account different ecological mechanisms. This model simulates an ecosystem undergoing a desertification transition in term of a stochastic cellular automaton (SCA) subjected to a damage spreading (DS) transition. On the other hand, it is well known that many DS transitions belong to the directed percolation (DP) universality class under certain rather general conditions. Here we investigate the universality class of the SCA model and we identify the region of parameters space inside which it belongs to the DP class.

We present an analytical expression for the first return time (FRT) probability density function of a stationary correlated signal. Precisely, we start by considering a stationary discrete-time Ornstein-Uhlenbeck (OU) process with exponenial decaying correlation function. The first return time distribution for this process is derived by adopting a well known formalism typically used in the study of the FRT statistics for non-stationary diffusive processes. Then, by a subordination approach, we treat the case of a stationary process with power law tail correlation function and diverging correlation time. We numerically test our findings, obtaining in both cases a good agreement with the analytical results. We notice that neither in the standard OU nor in the subordinated case a simple form of waiting time statistics like stretched-exponential or similar can be obtained while it is apparent that long time transient may shadow the final asymptotic behavior.

The identification of early warning signals for regime shifts in ecosystems is of crucial importance given their impact in terms of economic and social effects. We present here the results of a theoretical study on the desertification transition in semiarid ecosystems under external stress. We performed numerical simulations based on a stochastic cellular automaton model, and we studied the dynamics of the vegetation clusters in terms of percolation theory, assumed as an effective tool for analyzing the geometrical properties of the clusters. Focusing on the role played by the strength of external stresses, measured by the mortality rate m, we followed the progressive degradation of the ecosystem for increasing m, identifying different stages: first, the fragmentation transition occurring at relatively low values of m, then the desertification transition at higher mortality rates, and finally the full desertification transition corresponding to the extinction of the vegetation and the almost complete degradation of the soil, attained at the maximum value of m. For each transition we calculated the spanning probabilities as functions of m and the percolation thresholds according to different spanning criteria. The identification of the different thresholds is proposed as an useful tool for monitoring the increasing degradation of real-world finite-size systems. Moreover, we studied the time fluctuations of the sizes of the biggest clusters of vegetated and nonvegetated cells over the entire range of mortality values. The change of sign in the skewness of the size distributions, occurring at the fragmentation threshold for the biggest vegetation cluster and at the desertification threshold for the nonvegetated cluster, offers new early warning signals for desertification. Other new and robust indicators are given by the maxima of the root-mean-square deviation of the distributions, which are attained respectively inside the fragmentation interval, for the vegetated biggest cluster, and inside the desertification interval, for the nonvegetated cluster.

Measurements of electrical transport and excess current noise in semiconducting films of polyacenes revealed a superquadratic increase of the current and a sharp peak of the relative noise at voltage values corresponding to the trap-filling transition region. Recently, we formulated an explanation of these findings in terms of trapping and detrapping processes of the injected carriers by deep defect states. This interpretation was based on a phenomenological model that takes as input the measured I − V characteristic curve. Here we introduce a new percolative approach to transport and noise in these materials. In particular we develop two percolation models, differing in the voltage dependence of the trapping and detrapping rates: precisely, one model neglects and the other accounts for the Poole-Frenkel effect. We then discuss the results of both models in connections with experimental findings.

Sensing proteins (receptors) are nanostructures that exhibit very complex behaviors (ions pumping, conformational change, reaction catalysis, etc). They are constituted by a specific sequence of amino acids within a codified spatial organization. The functioning of these macromolecules is intrinsically connected with their spatial structure, which modifications are normally associated with their biological function. With the advance of nanotechnology, the investigation of the electrical properties of receptors has emerged as a demanding issue. Beside the fundamental interest, the possibility to exploit the electrical properties for the development of bioelectronic devices of new generations has attracted major interest. From the experimental side, we investigate three complementary kinds of measurements: (1) current-voltage (I-V) measurements in nanometric layers sandwiched between macroscopic contacts, (2) I-V measurements within an AFM environment in nanometric monolayers deposited on a conducting substrate, and (3) electrochemical impedance spectroscopy measurements on appropriate monolayers of self-assembled samples. From the theoretical side, a microscopic interpretation of these experiments is still a challenging issue. This paper reviews recent theoretical results carried out within the European project, Bioelectronic Olfactory Neuron Device, which provides a first quantitative interpretation of charge transport experiments exploiting static and dynamic electrical properties of several receptors. To this purpose, we have developed an impedance network protein analogue (INPA) which considers the interaction between neighboring amino acids within a given radius as responsible of charge transfer throughout the protein. The conformational change, due to the sensing action produced by the capture of the ligand (photon, odour), induces a modification of the spatial structure and, thus, of the electrical properties of the receptor. By a scaling procedure, the electrical change of the receptor when passing from the native to the active state is used to interpret the macroscopic measurement obtained within different methods. The developed INPA model is found to be very promising for a better understanding of the role of receptor topology in the mechanism responsible of charge transfer. Present results point favorably to the development of a new generation of nano-biosensors within the lab-on-chip strategy.

Mammalian olfactory system is the archetype of smell sensor devices. Its complexity resides both in the odorant mechanism of capture by the single olfactory receptor (OR) and in the space organization and codification of the information. The result is a unique profile for each odorant. Our aim is to partially mimick this system, in order to produce a biosensor on nanometric scale. In this paper we present a possible theoretical framework in which the experimental results should be embedded. It consists of the description of the protein in terms of an impedance network able to simulate the electrical characteristics associated with the protein topology.

We discuss the mechanisms of bacterial Quorum Sensing, the biophysical phenomenon point- ing out a social behavior in bacteria, highlighting thus the very complex structure of these sys- tems. Actually, bacterial bioluminescence is an example of a quorum sensing mediated prop- erty. We show that the distribution of the activation times of the bioluminescent emission follows the universal behavior described by the Gumbel distribution of extreme value statis- tics. We provide further evidence on the system size scaling of bioluminescence, showing that the relation between cell density and total number of photons radiated by bacteria is highly non-linear.

The identification of early-warning signals of critical transitions represents a crucial issue for semi-arid ecosystems which are strongly exposed to desertification risks. Previous studies in this field suggested that the observation of vegetation patchiness and, in particular, changes in the patch size distributions, could provide early indicators of desertification transitions. Through numerical simulations based on a cellular automaton model, we have investigated the time fluctuation properties of several quantities characterizing the vegetation patterns of semi-arid ecosystems under different conditions. At increasing value of a mortality parameter measuring the strength of external stresses, we have found different and earlier transition indicators, related to the time fluctuations of the biggest cluster size.

We performed an extreme value analysis of the heart beat fluctuations. We analyzed 24 h Holter ECG signals of 90 healthy individuals and 90 unhealthy individuals suffering of congestive heart failure (chf). Precisely, we studied separately the increment time series ∆RR corresponding to sleeping and daily activities. We found strong differences in the median return times of positive high threshold values of the increments for healthy and nonhealthy individuals, during both daily and sleeping activities. Our results suggest that healthy individuals have more often than chf patients the tendency to suddenly slow their heartbeat rate.

The authors report on the reduction of low-frequency noise in semiconductor polymer nanowires with respect to thin-films made of the same organic material. Flicker noise is experimentally investigated in polymer nanowires in the range of 10-10(5) Hz by means of field-effect transistor architectures. The noise in the devices is well described by the Hooge empirical model and exhibits an average Hooge constant, which describes the current power spectral density of fluctuations, suppressed by 1-2 orders of magnitude compared to thin-film devices. To explain the Hooge constant reduction, a resistor network model is developed, in which the organic semiconducting nanostructures or films are depicted through a two-dimensional network of resistors with a square-lattice structure, accounting for the different anisotropy and degree of structural disorder of the active nanowires and films. Results from modeling agree well with experimental findings. These results support enhanced structural order through size-confinement in organic nanostructures as effective route to improve the noise performance in polymer electronic devices.