Specialized motor-driven dusp1 expression in the song systems of multiple lineages of vocal learning birds.

Mechanisms for the evolution of convergent behavioral traits are largely unknown. Vocal learning is one such trait that evolved multiple times and is necessary in humans for the acquisition of spoken language. Among birds, vocal learning is evolved in songbirds, parrots, and hummingbirds. Each time similar forebrain song nuclei specialized for vocal learning and production have evolved. This finding led to the hypothesis that the behavioral and neuroanatomical convergences for vocal learning could be associated with molecular convergence. We previously found that the neural activity-induced gene dual specificity phosphatase 1 (dusp1) was up-regulated in non-vocal circuits, specifically in sensory-input neurons of the thalamus and telencephalon; however, dusp1 was not up-regulated in higher order sensory neurons or motor circuits. Here we show that song motor nuclei are an exception to this pattern. The song nuclei of species from all known vocal learning avian lineages showed motor-driven up-regulation of dusp1 expression induced by singing. There was no detectable motor-driven dusp1 expression throughout the rest of the forebrain after non-vocal motor performance. This pattern contrasts with expression of the commonly studied activity-induced gene egr1, which shows motor-driven expression in song nuclei induced by singing, but also motor-driven expression in adjacent brain regions after non-vocal motor behaviors. In the vocal non-learning avian species, we found no detectable vocalizing-driven dusp1 expression in the forebrain. These findings suggest that independent evolutions of neural systems for vocal learning were accompanied by selection for specialized motor-driven expression of the dusp1 gene in those circuits. This specialized expression of dusp1 could potentially lead to differential regulation of dusp1-modulated molecular cascades in vocal learning circuits

Silage produces biofuel for local consumption

<p>Abstract</p> <p>Background</p> <p>In the normal process of bioethanol production, biomass is transported to integrated large factories for degradation to sugar, fermentation, and recovery of ethanol by distillation. Biomass nutrient loss occurs during preservation and degradation. Our aim was to develop a decentralized ethanol production system appropriate for farm or co-operative level production that uses a solid-state fermentation method for producing bio-ethanol from whole crops, provides cattle feed, and produces no wastes. The idea is to incorporate traditional silage methods with simultaneous saccharification and fermentation. Harvested, fresh biomass is ensiled with biomass-degrading enzymes and yeast. Multiple parallel reactions for biomass degradation and ethanol and lactic acid production are induced in solid culture in hermetically sealed containers at a ranch. After fermentation, ethanol is collected on site from the vapor from heated fermented products.</p> <p>Results</p> <p>The parallel reactions of simultaneous saccharification and fermentation were induced efficiently in the model fermentation system. In a laboratory-scale feasibility study of the process, 250 g of freshly harvested forage rice with 62% moisture was treated with 0.86 filter paper units/g dry matter (DM) of cellulase and 0.32 U/g DM of glucoamylase. After 20 days of incubation at 28°C, 6.4 wt.% of ethanol in fresh matter (equivalent to 169 g/kg DM) was produced. When the 46 wt.% moisture was gathered as vapor from the fermented product, 74% of the produced ethanol was collected. Organic cellular contents (such as the amylase and pronase degradable fractions) were decreased by 63% and organic cell wall (fiber) content by 7% compared to silage prepared from the same material.</p> <p>Conclusions</p> <p>We confirmed that efficient ethanol production is induced in nonsterilized whole rice plants in a laboratory-scale solid-state fermentation system. For practical use of the method, further study is needed to scale-up the fermentation volume, develop an efficient ethanol recovery method, and evaluate the fermentation residue as an actual cattle feed.</p

Critical dynamics of phase transition driven by dichotomous Markov noise

An Ising spin system under the critical temperature driven by a dichotomous Markov noise (magnetic field) with a finite correlation time is studied both numerically and theoretically. The order parameter exhibits a transition between two kinds of qualitatively different dynamics, symmetry-restoring and symmetry-breaking motions, as the noise intensity is changed. There exist regions called channels where the order parameter stays for a long time slightly above its critical noise intensity. Developing a phenomenological analysis of the dynamics, we investigate the distribution of the passage time through the channels and the power spectrum of the order parameter evolution. The results based on the phenomenological analysis turn out to be in quite good agreement with those of the numerical simulation.Comment: 27 pages, 12 figure

Real Hydrostatic Pressure in High-Pressure Torsion Measured by Bismuth Phase Transformations and FEM Simulations

Hydrostatic pressure is a significant parameter influencing the evolution of microstructure and phase transformations in the high-pressure torsion (HPT) process. Currently, there are significant arguments relating to the magnitude of the real hydrostatic pressure during the process. In this study, phase transformations in bismuth, copper and titanium combined with the finite element method (FEM) were employed to determine the real pressure in processing disc samples by HPT. Any break in the variation of steady-state hardness (monitored experimentally by in-situ torque and temperature rise measurements) versus pressure was considered as a phase transition. FEM simulations show that the hydrostatic pressure is reasonably isotropic but decreases with increasing distance from the disc center and remains unchanged across the disc thickness. Both experiments and simulations indicate that the mean hydrostatic pressure during HPT processing closely corresponds to the compressive load over the disc area plus the contact area between the anvils.1166Ysciescopu

Influence of severe plastic deformation on the precipitation hardening of a FeSiTi steel

The combined strengthening effects of grain refinement and high precipitated volume fraction (~6at.%) on the mechanical properties of FeSiTi alloy subjected to SPD processing prior to aging treatment were investigated by atom probe tomography and scanning transmission electron microscopy. It was shown that the refinement of the microstructure affects the precipitation kinetics and the spatial distribution of the secondary hardening intermetallic phase, which was observed to nucleate heterogeneously on dislocations and sub-grain boundaries. It was revealed that alloys successively subjected to these two strengthening mechanisms exhibit a lower increase in mechanical strength than a simple estimation based on the summation of the two individual strengthening mechanisms

L\'{e}vy scaling: the Diffusion Entropy Analysis applied to DNA sequences

We address the problem of the statistical analysis of a time series generated by complex dynamics with a new method: the Diffusion Entropy Analysis (DEA) (Fractals, {\bf 9}, 193 (2001)). This method is based on the evaluation of the Shannon entropy of the diffusion process generated by the time series imagined as a physical source of fluctuations, rather than on the measurement of the variance of this diffusion process, as done with the traditional methods. We compare the DEA to the traditional methods of scaling detection and we prove that the DEA is the only method that always yields the correct scaling value, if the scaling condition applies. Furthermore, DEA detects the real scaling of a time series without requiring any form of de-trending. We show that the joint use of DEA and variance method allows to assess whether a time series is characterized by L\'{e}vy or Gauss statistics. We apply the DEA to the study of DNA sequences, and we prove that their large-time scales are characterized by L\'{e}vy statistics, regardless of whether they are coding or non-coding sequences. We show that the DEA is a reliable technique and, at the same time, we use it to confirm the validity of the dynamic approach to the DNA sequences, proposed in earlier work.Comment: 24 pages, 9 figure

Nonconcave entropies in multifractals and the thermodynamic formalism

We discuss a subtlety involved in the calculation of multifractal spectra when these are expressed as Legendre-Fenchel transforms of functions analogous to free energy functions. We show that the Legendre-Fenchel transform of a free energy function yields the correct multifractal spectrum only when the latter is wholly concave. If the spectrum has no definite concavity, then the transform yields the concave envelope of the spectrum rather than the spectrum itself. Some mathematical and physical examples are given to illustrate this result, which lies at the root of the nonequivalence of the microcanonical and canonical ensembles. On a more positive note, we also show that the impossibility of expressing nonconcave multifractal spectra through Legendre-Fenchel transforms of free energies can be circumvented with the help of a generalized free energy function, which relates to a recently introduced generalized canonical ensemble. Analogies with the calculation of rate functions in large deviation theory are finally discussed.Comment: 9 pages, revtex4, 3 figures. Changes in v2: sections added on applications plus many new references; contains an addendum not contained in published versio