Echo Delay and Overlap with Emitted Orientation Sounds and Doppler-shift Compensation in the Bat, Rhinolophus ferrumequinum

The compensation of Doppler-shifts by the bat, Rhinolophusferrumequinum, functions only when certain temporal relations between the echo and the emitted orientation sound are given. Three echo configurations were used: a) Original orientation sounds were electronically Doppler-shifted and played back either cut at the beginning (variable delay) or at the end (variable duration) of the echo. b) Artificial constant frequency echoes with variable delay or duration were clamped to the frequency of the emitted orientation sound at different Doppler-shifts. c) The echoes were only partially Doppler-shifted and the Doppler-shifted component began after variable delays or had variable durations. With increasing delay or decreasing duration of the Doppler-shifted echo the compensation amplitude for a sinusoidally modulated + 3 kHz Dopplershift (modulation rate 0.08 Hz) decreases for all stimulus configurations (Figs. 1, 2, 3). The range of the Doppler-shift compensation system is therefore limited by the delay due to acoustic travel time to about 4 m distance between bat and target. In this range the overlap duration of the echo with the emitted orientation sound is always sufficiently long, when compared with data on the orientation pulse length during target approach from Schnitzler (1968) (Fig. 5)

Molecular Basis for poly(A) RNP Architecture and Recognition by the Pan2-Pan3 Deadenylase

The stability of eukaryotic mRNAs is dependent on a ribonucleoprotein (RNP) complex of poly(A)-binding proteins (PABPC1/Pab1) organized on the poly(A) tail. This poly(A) RNP not only protects mRNAs from premature degradation but also stimulates the Pan2-Pan3 deadenylase complex to catalyze the first step of poly(A) tail shortening. We reconstituted this process in vitro using recombinant proteins and show that Pan2-Pan3 associates with and degrades poly(A) RNPs containing two or more Pab1 molecules. The cryo-EM structure of Pan2-Pan3 in complex with a poly(A) RNP composed of 90 adenosines and three Pab1 protomers shows how the oligomerization interfaces of Pab1 are recognized by conserved features of the deadenylase and thread the poly(A) RNA substrate into the nuclease active site. The structure reveals the basis for the periodic repeating architecture at the 3' end of cytoplasmic mRNAs. This illustrates mechanistically how RNA-bound Pab1 oligomers act as rulers for poly(A) tail length over the mRNAs' lifetime.We would like to thank ... the MPIB cryo-EM, and core facilities ..

Canonical differential geometry of string backgrounds

String backgrounds and D-branes do not possess the structure of Lorentzian manifolds, but that of manifolds with area metric. Area metric geometry is a true generalization of metric geometry, which in particular may accommodate a B-field. While an area metric does not determine a connection, we identify the appropriate differential geometric structure which is of relevance for the minimal surface equation in such a generalized geometry. In particular the notion of a derivative action of areas on areas emerges naturally. Area metric geometry provides new tools in differential geometry, which promise to play a role in the description of gravitational dynamics on D-branes.Comment: 20 pages, no figures, improved journal versio

Audio Barlow twins: self-supervised audio representation learning

The Barlow Twins self-supervised learning objective requires neither negative samples or asymmetric learning updates, achieving results on a par with the current state-of-the-art within Computer Vision. As such, we present Audio Barlow Twins, a novel self-supervised audio representation learning approach, adapting Barlow Twins to the audio domain. We pre-train on the large-scale audio dataset AudioSet, and evaluate the quality of the learnt representations on 18 tasks from the HEAR 2021 Challenge, achieving results which outperform, or otherwise are on a par with, the current state-of-the-art for instance discrimination self-supervised learning approaches to audio representation learning. Code at https://github.com/jonahanton/SSL_audio

Inelastic light scattering and the excited states of many-electron quantum dots

A consistent calculation of resonant inelastic (Raman) scattering amplitudes for relatively large quantum dots, which takes account of valence-band mixing, discrete character of the spectrum in intermediate and final states, and interference effects, is presented. Raman peaks in charge and spin channels are compared with multipole strengths and with the density of energy levels in final states. A qualitative comparison with the available experimental results is given.Comment: 5 pages, accepted in J. Phys.: Condens. Matte

Exact-Diagonalization Studies of Inelastic Light Scattering in Self-Assembled Quantum Dots

We report exact diagonalization studies of inelastic light scattering in few-electron quantum dots under the strong confinement regime characteristic of self-assembled dots. We apply the orthodox (second-order) theory for scattering due to electronic excitations, leaving for the future the consideration of higher-order effects in the formalism (phonons, for example), which seem relevant in the theoretical description of available experiments. Our numerical results stress the dominance of monopole peaks in Raman spectra and the breakdown of selection rules in open-shell dots. The dependence of these spectra on the number of electrons in the dot and the incident photon energy is explicitly shown. Qualitative comparisons are made with recent experimental results.Comment: 11 pages, 11 figure

Response analysis of a laminar premixed M-flame to flow perturbations using a linearized compressible Navier-Stokes solver

International audienceThe response of a laminar premixed methane-air flame subjected to flow perturbations around a steady state is examined experimentally and using a linearized compressible Navier-Stokes solver with a one-step chemistry mechanism to describe combustion. The unperturbed flame takes an M-shape stabilized both by a central bluff body and by the external rim of a cylindrical nozzle. This base flow is computed by a nonlinear direct simulation of the steady reacting flow, and the flame topology is shown to qualitatively correspond to experiments conducted under comparable conditions. The flame is then subjected to acoustic disturbances produced at different locations in the numerical domain, and its response is examined using the linearized solver. This linear numerical model then allows the componentwise investigation of the effects of flow disturbances on unsteady combustion and the feedback from the flame on the unsteady flow field. It is shown that a wrinkled reaction layer produces hydrodynamic disturbances in the fresh reactant flow field that superimpose on the acoustic field. This phenomenon, observed in several experiments, is fully interpreted here. The additional perturbations convected by the mean flow stem from the feedback of the perturbed flame sheet dynamics onto the flow field by a mechanism similar to that of a perturbed vortex sheet. The different regimes where this mechanism prevails are investigated by examining the phase and group velocities of flow disturbances along an axis oriented along the main direction of the flow in the fresh reactant flow field. It is shown that this mechanism dominates the low-frequency response of the wrinkled shape taken by the flame and, in particular, that it fully determines the dynamics of the flame tip from where the bulk of noise is radiated

Speaker-independent emotion recognition exploiting a psychologically-inspired binary cascade classification schema

In this paper, a psychologically-inspired binary cascade classification schema is proposed for speech emotion recognition. Performance is enhanced because commonly confused pairs of emotions are distinguishable from one another. Extracted features are related to statistics of pitch, formants, and energy contours, as well as spectrum, cepstrum, perceptual and temporal features, autocorrelation, MPEG-7 descriptors, Fujisakis model parameters, voice quality, jitter, and shimmer. Selected features are fed as input to K nearest neighborhood classifier and to support vector machines. Two kernels are tested for the latter: Linear and Gaussian radial basis function. The recently proposed speaker-independent experimental protocol is tested on the Berlin emotional speech database for each gender separately. The best emotion recognition accuracy, achieved by support vector machines with linear kernel, equals 87.7%, outperforming state-of-the-art approaches. Statistical analysis is first carried out with respect to the classifiers error rates and then to evaluate the information expressed by the classifiers confusion matrices. © Springer Science+Business Media, LLC 2011