Individual identity in songbirds: signal representations and metric learning for locating the information in complex corvid calls

Bird calls range from simple tones to rich dynamic multi-harmonic structures. The more complex calls are very poorly understood at present, such as those of the scientifically important corvid family (jackdaws, crows, ravens, etc.). Individual birds can recognise familiar individuals from calls, but where in the signal is this identity encoded? We studied the question by applying a combination of feature representations to a dataset of jackdaw calls, including linear predictive coding (LPC) and adaptive discrete Fourier transform (aDFT). We demonstrate through a classification paradigm that we can strongly outperform a standard spectrogram representation for identifying individuals, and we apply metric learning to determine which time-frequency regions contribute most strongly to robust individual identification. Computational methods can help to direct our search for understanding of these complex biological signals

Data-Efficient Weakly Supervised Learning for Low-Resource Audio Event Detection Using Deep Learning

5 pages, 2 figures. arXiv admin note: substantial text overlap with arXiv:1807.03697We propose a method to perform audio event detection under the common constraint that only limited training data are available. In training a deep learning system to perform audio event detection, two practical problems arise. Firstly, most datasets are "weakly labelled" having only a list of events present in each recording without any temporal information for training. Secondly, deep neural networks need a very large amount of labelled training data to achieve good quality performance, yet in practice it is difficult to collect enough samples for most classes of interest. In this paper, we propose a data-efficient training of a stacked convolutional and recurrent neural network. This neural network is trained in a multi instance learning setting for which we introduce a new loss function that leads to improved training compared to the usual approaches for weakly supervised learning. We successfully test our approach on two low-resource datasets that lack temporal labels

An Explicit Time-Domain Hybrid Formulation Based on the Unified Boundary Condition

An approach to stabilize the two-surface, time domain FEM/BI hybrid by means of a unified boundary condition is presented. The first-order symplectic finite element formulation [1] is used along with a version of the unified boundary condition of Jin [2] reformulated for Maxwell's first-order equations in time to provide both stability and accuracy over the first-order ABC. Several results are presented to validate the numerical solutions. In particular the dipole in a free-space box is analyzed and compared to the Dirchlet boundary condition of Ziolkowski and Madsen [3] and to a Neuman boundary condition approach

Coumarins and pyranocoumarins, potential novel pharmacophores for inhibition ofmeasles virus replication

A series of coumarin and pyranocoumarin analogues were evaluated in vitro for antiviral efficacy against measles virus (MV), strain Chicago. Of the 22 compounds tested for inhibition, six were found to have selectivity indices greater than 10. These were compounds 5-hydroxy-7-propionyloxy- 4-propylcoumarin (2a), 5,7-bis(tosyloxy)-4- propylcoumarin (7); 5-hydroxy-4-propyl-7-tosyloxy- coumarin (8); 6,6-dimethyl-9-propionyloxy-4- propyl-2H,6H-benzo[1,2-b:3,4-b′]dipyran-2-one (9); 6,6-dimethyl-9-pivaloyloxy-4-propyl-2H,6Hbenzo[ 1,2-b:3,4-b′]dipyran-2-one (10); and 7,8-cis- 10,11,12-trans-4-propyl-6,6,10,11-tetramethyl- 7,8,9-trihydroxy-2H,6H,12H-benzo[1,2-b:3,4-b′:5,6- b′′]tripyran-2-one (18). Three of the active drugs were propyl coumarin analogues (2a, 7 and 8), two were dipyranone or chromeno-coumarins (9 and 10), and one was a benzotripyranone with a coumarin nucleus (18). Some appeared to be rather specific and potent inhibitors of MV with EC50 values ranging from 0.2 to 50 μg/ml and the majority of the EC50 values being less than 5 μg/ml. The compounds inhibited an additional nine strains of MV, and in virucidal tests the drugs did not physically disrupt the virion to inhibit virus replication. The inhibitory activity for one of the compounds tested (7) was somewhat dependent on virus concentration and it was still active when added to cells up to 24 h after virus exposure. When used in combination with ribavirin, compound 7 appeared not to profoundly affect the antiviral efficacy of ribavirin or its cell-associated toxicity. However, a slightly antagonistic MVinhibitory effect was observed at the highest concentration of ribavirin used in combination with most concentrations of compound 7 tested. This and related compounds may be valuable leads in the development of a potent and selective class of MV inhibitors that could be used in future in the clinic

Facile Preparation of Fluorescent Neoglycoproteins Using p-Nitrophenyl Anthranilate as a Heterobifunctional Linker

A facile preparation of neoglycoconjugates has been developed with a commercially available chemical, p-nitrophenyl anthranilate (PNPA), as a heterobifunctional linker. The two functional groups of PNPA, the aromatic amine and the p-nitrophenyl ester, are fully differentiated to selectively conjugate with glycans and other biomolecules containing nucleophiles. PNPA is efficiently conjugated with free reducing glycans via reductive amination. The glycan−PNPA conjugates (GPNPAs) can be easily purified and quantified by UV absorption. The active p-nitrophenyl ester in the GPNPA conjugates readily reacts with amines under mild conditions, and the resulting conjugates acquire strong fluorescence. This approach was used to prepare several fluorescent neoglycoproteins. The neoglycoproteins were covalently printed on activated glass slides and were bound by appropriate lectins recognizing the glycans

Nucleation of Al3Zr and Al3Sc in aluminum alloys: from kinetic Monte Carlo simulations to classical theory

Zr and Sc precipitate in aluminum alloys to form the compounds Al3Zr and Al3Sc which for low supersaturations of the solid solution have the L12 structure. The aim of the present study is to model at an atomic scale this kinetics of precipitation and to build a mesoscopic model based on classical nucleation theory so as to extend the field of supersaturations and annealing times that can be simulated. We use some ab-initio calculations and experimental data to fit an Ising model describing thermodynamics of the Al-Zr and Al-Sc systems. Kinetic behavior is described by means of an atom-vacancy exchange mechanism. This allows us to simulate with a kinetic Monte Carlo algorithm kinetics of precipitation of Al3Zr and Al3Sc. These kinetics are then used to test the classical nucleation theory. In this purpose, we deduce from our atomic model an isotropic interface free energy which is consistent with the one deduced from experimental kinetics and a nucleation free energy. We test di erent mean-field approximations (Bragg-Williams approximation as well as Cluster Variation Method) for these parameters. The classical nucleation theory is coherent with the kinetic Monte Carlo simulations only when CVM is used: it manages to reproduce the cluster size distribution in the metastable solid solution and its evolution as well as the steady-state nucleation rate. We also find that the capillary approximation used in the classical nucleation theory works surprisingly well when compared to a direct calculation of the free energy of formation for small L12 clusters.Comment: submitted to Physical Review B (2004

Northern Power NW 1500 Direct-Drive Generator: April 12, 2001 - September 30, 2006

This report describes work conducted under a subcontract between NREL and Northern Power Systems to identify, design, and test a megawatt-scale wind turbine drivetrain with the lowest overall life-cycle cost

Double-Stranded RNA Attenuates the Barrier Function of Human Pulmonary Artery Endothelial Cells

Circulating RNA may result from excessive cell damage or acute viral infection and can interact with vascular endothelial cells. Despite the obvious clinical implications associated with the presence of circulating RNA, its pathological effects on endothelial cells and the governing molecular mechanisms are still not fully elucidated. We analyzed the effects of double stranded RNA on primary human pulmonary artery endothelial cells (hPAECs). The effect of natural and synthetic double-stranded RNA (dsRNA) on hPAECs was investigated using trans-endothelial electric resistance, molecule trafficking, calcium (Ca2+) homeostasis, gene expression and proliferation studies. Furthermore, the morphology and mechanical changes of the cells caused by synthetic dsRNA was followed by in-situ atomic force microscopy, by vascular-endothelial cadherin and F-actin staining. Our results indicated that exposure of hPAECs to synthetic dsRNA led to functional deficits. This was reflected by morphological and mechanical changes and an increase in the permeability of the endothelial monolayer. hPAECs treated with synthetic dsRNA accumulated in the G1 phase of the cell cycle. Additionally, the proliferation rate of the cells in the presence of synthetic dsRNA was significantly decreased. Furthermore, we found that natural and synthetic dsRNA modulated Ca2+ signaling in hPAECs by inhibiting the sarco-endoplasmic Ca2+-ATPase (SERCA) which is involved in the regulation of the intracellular Ca2+ homeostasis and thus cell growth. Even upon synthetic dsRNA stimulation silencing of SERCA3 preserved the endothelial monolayer integrity. Our data identify novel mechanisms by which dsRNA can disrupt endothelial barrier function and these may be relevant in inflammatory processes