Emergence of collective changes in travel direction of starling flocks from individual birds' fluctuations

One of the most impressive features of moving animal groups is their ability to perform sudden coherent changes in travel direction. While this collective decision can be a response to an external alarm cue, directional switching can also emerge from the intrinsic fluctuations in individual behaviour. However, the cause and the mechanism by which such collective changes of direction occur are not fully understood yet. Here, we present an experimental study of spontaneous collective turns in natural flocks of starlings. We employ a recently developed tracking algorithm to reconstruct three-dimensional trajectories of each individual bird in the flock for the whole duration of a turning event. Our approach enables us to analyse changes in the individual behaviour of every group member and reveal the emergent dynamics of turning. We show that spontaneous turns start from individuals located at the elongated tips of the flocks, and then propagate through the group. We find that birds on the tips deviate from the mean direction of motion much more frequently than other individuals, indicating that persistent localized fluctuations are the crucial ingredient for triggering a collective directional change. Finally, we quantitatively verify that birds follow equal-radius paths during turning, the effects of which are a change of the flock''s orientation and a redistribution of individual locations in the group.     

Degradation of phenol using Co- and Co,F-doped PbO(2) anodes in electrochemical filter-press cells

A comparative study on the electrooxidation of phenol in H(2)SO(4) medium using pure PbO(2) or F-, Co- and Co,F-doped PbO(2) electrodes in filter-press cells was carried out. The oxide films were obtained by galvanostatic electrodeposition using an electrolytic bath containing sodium lauryl sulfate as additive and Pb(2+), F(-), Co(2+) or Co(2+)+F(-), under magnetic stirring (to obtain 4-cm(2) electrodes) or ultrasound waves (to obtain 63-cm(2) electrodes). The best results were attained with PbO(2) electrodes doped with a low-Co content (1mM Co(2+) in the electrolytic bath) along with F(-): the chemical oxygen demand (COD) and the total organic carbon content (TOC) of the simulated wastewaters were removed by about 75% and 50%, respectively. When pure PbO(2) electrodes were used, the COD and TOC removals were about 60% and 45%, respectively. For the smaller electrodes, an average current efficiency (ACE) and an energy consumption (EC) of about 16% and 70 kWh kg(COD)(-1), respectively, were obtained. For the larger electrodes, the ACE and EC values were about 18% and 105 kWh kg(COD)(-1), respectively. Stability tests of the electrodes showed that they are suitable for use in the electrochemical treatment of phenol wastewaters.     

Profiling of hydrophilic proteins from Olea europaea olive pollen by MALDI TOF mass spectrometry

The antigenic profile of Olea europaea pollen from different Mediterranean cultivars was obtained by MALDI mass spectrometry. A simple procedure of chemical fractionation of the whole antigen extract was developed, whereby less complex, or pure, fractions of antigen candidate were obtained prior to mass spectrometric analysis. Some of the features of protein structure and distribution probably depend on cultivar adaptation to the environment. The profilings of pollen proteins thus obtained allow the distinction of the analyzed cultivars into three distinct groups: (i) those characterized by a low Ole e 1 content; (ii) those over-enriched in Ole e 1 and (iii) that containing Ole e 3 and Ole e 7 only. The latter consists of at least four isoforms differing by the degree of glycosilation. These results demonstrate that the proposed experimental procedure, can supply valuable information on the antigens' micro heterogeneity.     

Modeling retention and selectivity as a function of pH and column temperature in liquid chromatography

In reversed-phase liquid chromatography (RPLC), the retention of weak acids and bases is a sigmoidal function of the mobile-phase pH. Therefore, pH is a key chromatographic variable to optimize retention and selectivity. Furthermore, at an eluent pH close to the pKa of the solute, the dependence of ionization of the buffer and solute on temperature can be used to improve chromatographic separations involving ionizable solutes by an adequate handling of column temperature. In this paper, we derive a general equation for the prediction of the retentive behavior of ionizable compounds upon simultaneous changes in mobile-phase pH and column temperature. Four experiments, two limiting pH values and two temperatures, provide the input data that allow predictions in the whole range of these two variables, based on the thermodynamic fundamentals of the involved equilibria. Also, the study demonstrates the significant role that the choice of the buffer compound would have on selectivity factors in RPLC at temperatures higher than 25 degrees C.     

Aspirin-loaded electrospun poly(ε-caprolactone) tubular scaffolds: potential small-diameter vascular grafts for thrombosis prevention

Thrombosis is the main cause of failure of small-diameter synthetic vascular grafts when used for by-pass procedures. The development of bioresorbable vascular scaffolds with localized and sustained intra-luminal antithrombotic drug release could be considered a desirable improvement towards a valuable solution for this relevant clinical need. For this aim, we present the fabrication and characterization of aspirin-loaded electrospun poly(ε-caprolactone) tubular scaffolds as a vascular drug-delivery graft. Three different drug concentrations were considered (i.e., 1, 5 or 10 % w/w). Although a fibrous structure was clearly observed for all the collected scaffolds, aspirin content was directly implied in the final microstructure leading to a bimodal fiber diameter distribution and fused fibers at crossing-points (5 or 10 % w/w). Mechanical response highlighted a direct relationship for modulus and stress at break with the aspirin content, while the elongation at break was not remarkably different for the investigated cases. The temporal drug release was strongly dependent from the amount of loaded aspirin, reaching a steady state release after about 50 h. Finally, the adhesion assay confirmed the capability of the electrospun scaffolds to reduce platelet adhesion/aggregation onto aspirin loaded polymeric fibers. Aspirin-loaded electrospun tubular scaffold could represent a feasible candidate to develop a novel bioresorbable drug-releasing graft for small-diameter vessel replacements.     

A novel nanostructured composite formed by interaction of copper octa(3-aminopropyl)octasilsesquioxane with azide ligands: Preparation, characterization and a voltammetric application

This study presents the preparation, characterization and application of copper octa(3-aminopropyl)octasilsesquioxane following its subsequent reaction with azide ions (ASCA). The precursor (AC) and the novel compound (ASCA) were characterized by Fourier transform infrared spectra (FTIR), nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR), scanning electronic microscopy (SEM), X-ray diffraction (XRD), Thermogravimetric analyses and voltammetric technique. The cyclic voltammogram of the modified graphite paste electrode with ASCA (GPE-ASCA), showed one redox couple with formal potential () = 0.30 V and an irreversible process at 1.1 V (vs. Ag/AgCl; NaCl 1.0 M; v=20 mV s−1). The material is very sensitive to nitrite concentrations. The modified graphite paste electrode (GPE-ASCA) gives a linear range from 1.0 × 10⁻⁴ to 4.0 × 10⁻³ mol L⁻¹ for the determination of nitrite, with a detection limit of 2.1 × 10⁻⁴ mol L⁻¹ and the amperometric sensitivity of 8.04 mA/mol L⁻¹.     

Nonlinear Versus Linear Learning Devices: A Procedural Perspective

We provide a discussion of bounded rationality learning behind traditional learning mechanisms, i.e., Recursive Ordinary Least Squares and Bayesian Learning . These mechanisms lack for many reasons a behavioral interpretation and, following the Simon criticism, they appear to be substantively rational. In this paper, analyzing the Cagan model, we explore two learning mechanisms which appear to be more plausible from a behavioral point of view and somehow procedurally rational: Least Mean Squares learning for linear models and Back Propagation for Artificial Neural Networks . The two algorithms look for a minimum of the variance of the error forecasting by means of a steepest descent gradient procedure. The analysis of the Cagan model shows an interesting result: non-convergence of learning to the Rational Expectations Equilibrium is not due to the restriction to linear learning devices; also Back Propagation learning for Artificial Neural Networks may fail to converge to the Rational Expectations Equilibrium of the model.     

On the necessity of explicit cross-layer data formats in near-data processing systems

Distributed and Parallel Databases - Massive data transfers in modern data-intensive systems resulting from low data-locality and data-to-code system design hurt their performance and scalability....     

Gene regulatory networks reconstruction from time series datasets using genetic programming: a comparison between tree-based and graph-based approaches

Genetic programming researchers have shown a growing interest in the study of gene regulatory networks in the last few years. Our team has also contributed to the field, by defining two systems for the automatic reverse engineering of gene regulatory networks called GRNGen and GeNet. In this paper, we revise this work by describing in detail the two approaches and empirically comparing them. The results we report, and in particular the fact that GeNet can be used on large networks while GRNGen cannot, encourage us to pursue the study of GeNet in the future. We conclude the paper by discussing the main research directions that we are planning to investigate to improve GeNet.