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

Optimization of respiratory-gated auricular vagus afferent nerve stimulation for the modulation of blood pressure in hypertension

Background: The objective of this pilot study was to identify frequency-dependent effects of respiratory-gated auricular vagus afferent nerve stimulation (RAVANS) on the regulation of blood pressure and heart rate variability in hypertensive subjects and examine potential differential effects by sex/gender or race. Methods: Twenty hypertensive subjects (54.55 ± 6.23 years of age; 12 females and 8 males) were included in a within-person experimental design and underwent five stimulation sessions where they received RAVANS at different frequencies (i.e., 2 Hz, 10 Hz, 25 Hz, 100 Hz, or sham stimulation) in a randomized order. EKG and continuous blood pressure signals were collected during a 10-min baseline, 30-min stimulation, and 10-min post-stimulation periods. Generalized estimating equations (GEE) adjusted for baseline measures were used to evaluate frequency-dependent effects of RAVANS on heart rate, high frequency power, and blood pressure measures, including analyses stratified by sex and race. Results: Administration of RAVANS at 100 Hz had significant overall effects on the reduction of heart rate (β = −2.03, p = 0.002). It was also associated with a significant reduction of diastolic (β = −1.90, p = 0.01) and mean arterial blood pressure (β = −2.23, p = 0.002) in Black hypertensive participants and heart rate in female subjects (β = −2.83, p = 0.01) during the post-stimulation period when compared to sham. Conclusion: Respiratory-gated auricular vagus afferent nerve stimulation exhibits frequency-dependent rapid effects on the modulation of heart rate and blood pressure in hypertensive patients that may further differ by race and sex. Our findings highlight the need for the development of optimized stimulation protocols that achieve the greatest effects on the modulation of physiological and clinical outcomes in this population

Energy balance and diurnal variation in methane production as affected by feeding frequency in Jersey cows in late lactation

Methane (CH4) production of ruminants typically increases with increased dry matter intake (DMI). However, few studies have observed the effects of feeding multiple times a day and its effects on diurnal variation in CH4 production and energy balance in late-lactation dairy cattle. A study using headbox-style indirect calorimetry and 12 multiparous (225 ± 16.2 d in milk; mean ± SD) lactating Jersey cows was conducted to determine the effects of feeding twice daily on diurnal variation in CH4 production and total energy balance. A crossover design with 14-d periods (10 d of adaption and 4 d of collection) was used to compare 2 treatments. Treatments consisted of either once a day feeding (1×; 100% of feed given at 1000 h) or twice a day feeding (2×; 50% of feed given at 1000 h and the final 50% at 2000 h) with a common diet fed in both treatments. Dry matter intake was not different between treatments, with a mean of 16.9 ± 0.88 kg/d. Once a day feeding tended to have greater milk yield compared with twice a day feeding (21.2 vs. 20.4 ± 1.59 kg/d, respectively). Milk fat and milk protein percentage were not different, with means of 6.18 ± 0.20% and 3.98 ± 0.08%, respectively. Total CH4 production did not differ between treatments, with a mean of 402.1 ± 20.8 L/d. Similarly, CH4 per unit of milk yield and DMI was not different between treatments, with means of 20.5 ± 1.81 and 23.8 ± 1.21 L/kg, respectively. Feeding frequency did not affect diurnal variation of hourly CH4 production, with a mean of 17.1 ± 0.74 L/h. A trend was observed for a treatment × hour interaction. Methane production per hour increased after the second feeding for cattle fed twice versus once daily. Gross energy, digestible energy, metabolizable energy, and balance (milk plus tissue) per kilogram of DMI did not differ by feeding frequency, with means of 4.41 ± 0.01, 3.05 ± 0.03, 2.63 ± 0.03, and 1.32 ± 0.08 Mcal/ kg of DM, respectively. Metabolizable energy for maintenance was 146 kcal/kg of metabolic body weight, with an efficiency of converting metabolizable energy to net energy balance (milk plus tissue) of 76%. Nitrogen balance did not differ among treatments, with a mean balance of 17.3 ± 13.0 g/d. Therefore, total CH4 production and energy maintenance were not affected by feeding frequency. However, CH4 was variable throughout the day, and caution should be exercised when collecting CH4 samples at a limited number of time points because this may under- or overestimate total production

Reducing methane production with corn oil and calcium sulfate: Responses on whole-animal energy and nitrogen balance in dairy cattle

The addition of fat and calcium sulfate to diets fed to ruminants has resulted in a reduction in methane production, but the effects on energy balance have not been studied. A study using indirect calorimetry and 16 multiparous (8 Holstein and 8 Jersey; 78 ± 15 d in milk; mean ± standard deviation) lactating dairy cows was conducted to determine how mitigating methane production by adding corn oil or calcium sulfate to diets containing reduced-fat distillers grains affects energy and nitrogen balance. A replicated 4 × 4 Latin square design with 35-d periods (28 d of adaption and 4 d of collections) was used to compare 4 different dietary treatments. Treatments were composed of a control (CON) diet, which did not contain reduced-fat distillers grain and solubles (DDGS), and treatment diets containing 20% (dry matter basis) DDGS (DG), 20% DDGS with 1.38% (dry matter basis) added corn oil (CO), and 20% DDGS with 0.93% (dry matter basis) added calcium sulfate (CaS). Compared with CON, dry matter intake was not affected by treatment, averaging 29.6 ± 0.67 kg/d. Milk production was increased for diets containing DDGS compared with CON (26.3 vs. 27.8 ± 0.47 kg/d for CON vs. DDGS, respectively), likely supported by increased energy intake. Compared with CON, energy-corrected milk was greater in DG and CO (30.1 vs. 31.4, 31.7, and 31.0 ± 0.67 kg/d for CON, DG, CO, and CaS, respectively). Compared with CON, the addition of calcium sulfate and corn oil to diets containing DDGS reduced methane production per kg of dry matter intake (22.3, 19.9, and 19.6 ± 0.75 L/kg per d for CON, CO, and CaS, respectively). Similarly, methane production per kilogram of energy-corrected milk was reduced with the addition of calcium sulfate and corn oil to diets containing DDGS (14.2, 12.5, and 12.4 ± 0.50 L/kg per d for CON, CO, and CaS, respectively). Compared with CON and CaS, the intake of digestible energy was greater for DG and CO treatments (57.7, 62.1, 62.0, and 59.0 ± 1.38 Mcal/d for CON, DG, CO, and CaS, respectively). Intake of metabolizable energy was greater in all treatments containing DDGS compared with CON (50.5 vs. 54.0 ± 1.08 Mcal/d for CON vs. DDGS, respectively). Net balance (milk plus tissue energy) per unit of dry matter was greater in CO (containing DDGS and oil) than CON (1.55 vs. 1.35 ± 0.06 Mcal/kg for CO vs. CON, respectively). Tissue energy was greater in DG and CO compared with CON (6.08, 7.04, and 3.16 ± 0.99 Mcal/d for DG, CO, and CON, respectively. Results of this study suggest that the addition of oil and calcium sulfate to diets containing DDGS may be a viable option to reduce methane production and in the case of oil also improve net energy balance in lactating dairy cows

Energy balance and diurnal variation in methane production as affected by feeding frequency in Jersey cows in late lactation

Methane (CH4) production of ruminants typically increases with increased dry matter intake (DMI). However, few studies have observed the effects of feeding multiple times a day and its effects on diurnal variation in CH4 production and energy balance in late-lactation dairy cattle. A study using headbox-style indirect calorimetry and 12 multiparous (225 ± 16.2 d in milk; mean ± SD) lactating Jersey cows was conducted to determine the effects of feeding twice daily on diurnal variation in CH4 production and total energy balance. A crossover design with 14-d periods (10 d of adaption and 4 d of collection) was used to compare 2 treatments. Treatments consisted of either once a day feeding (1×; 100% of feed given at 1000 h) or twice a day feeding (2×; 50% of feed given at 1000 h and the final 50% at 2000 h) with a common diet fed in both treatments. Dry matter intake was not different between treatments, with a mean of 16.9 ± 0.88 kg/d. Once a day feeding tended to have greater milk yield compared with twice a day feeding (21.2 vs. 20.4 ± 1.59 kg/d, respectively). Milk fat and milk protein percentage were not different, with means of 6.18 ± 0.20% and 3.98 ± 0.08%, respectively. Total CH4 production did not differ between treatments, with a mean of 402.1 ± 20.8 L/d. Similarly, CH4 per unit of milk yield and DMI was not different between treatments, with means of 20.5 ± 1.81 and 23.8 ± 1.21 L/kg, respectively. Feeding frequency did not affect diurnal variation of hourly CH4 production, with a mean of 17.1 ± 0.74 L/h. A trend was observed for a treatment × hour interaction. Methane production per hour increased after the second feeding for cattle fed twice versus once daily. Gross energy, digestible energy, metabolizable energy, and balance (milk plus tissue) per kilogram of DMI did not differ by feeding frequency, with means of 4.41 ± 0.01, 3.05 ± 0.03, 2.63 ± 0.03, and 1.32 ± 0.08 Mcal/ kg of DM, respectively. Metabolizable energy for maintenance was 146 kcal/kg of metabolic body weight, with an efficiency of converting metabolizable energy to net energy balance (milk plus tissue) of 76%. Nitrogen balance did not differ among treatments, with a mean balance of 17.3 ± 13.0 g/d. Therefore, total CH4 production and energy maintenance were not affected by feeding frequency. However, CH4 was variable throughout the day, and caution should be exercised when collecting CH4 samples at a limited number of time points because this may under- or overestimate total production

First GPS Baseline Results from the North Andes

The CASA UNO GPS (Global Positioning System) experiment (January-February 1988) has provided the first epoch baseline measurements for the study of plate motions and crustal deformation in and around the North Andes. Two dimensional horizontal baseline repeatabilities are as good as 5 parts in 108 for short baselines (100-1000km), and better than3 parts in 108 for long baselines (\u3e1000km). Vertical repeatabilities are typically 4 -6 cm, with a weak dependence on baseline length. The expected rate of plate convergence across the Colombia Trench is 6-8 cm/yr, which should be detectable by the repeat experiment planned for 1991. Expected deformation rates within the North Andes are of the order of 1 cm/yr, which may be detectable with the 1991 experiment

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

The effect of monomer evaporation on a simple model of submonolayer growth

We present a model for thin film growth by particle deposition that takes into account the possible evaporation of the particles deposited on the surface. Our model focuses on the formation of two-dimensional structures. We find that the presence of evaporation can dramatically affect the growth kinetics of the film, and can give rise to regimes characterized by different ``growth'' exponents and island size distributions. Our results are obtained by extensive computer simulations as well as through a simple scaling approach and the analysis of rate equations describing the system. We carefully discuss the relationship of our model with previous studies by Venables and Stoyanov of the same physical situation, and we show that our analysis is more general.Comment: 41 pages including figures, Revtex, to be published in Physical Review