CREPE NOTES: A NEW METHOD FOR SEGMENTING PITCH CONTOURS INTO DISCRETE NOTES

Tracking the fundamental frequency (f0) of a monophonic instrumental performance is effectively a solved problem with several solutions achieving 99% accuracy. However, the related task of automatic music transcription requires a further processing step to segment an f0 contour into discrete notes. This sub-task of note segmentation is necessary to enable a range of applications including musicological analysis and symbolic music generation. Building on CREPE, a state-of-the-art monophonic pitch tracking solution based on a simple neural network, we propose a simple and effective method for post-processing CREPE’s output to achieve monophonic note segmentation. The proposed method demonstrates state-of-the-art results on two challenging datasets of monophonic instrumental music. Our approach also gives a 97% reduction in the total number of parameters used when compared with other deep learning based method

First-principles study of vibrational and dielectric properties of {\beta}-Si3N4

First-principles calculations have been conducted to study the structural, vibrational and dielectric properties of {\beta}-Si3N4. Calculations of the zone-center optical-mode frequencies (including LO-TO splittings), Born effective charge tensors for each atom, dielectric constants, using density functional perturbation theory, are reported. The fully relaxed structural parameters are found to be in good agreement with experimental data. All optic modes are identified and agreement of theory with experiment is excellent. The static dielectric tensor is decomposed into contributions arising from individual infrared-active phonon modes. It is found that high-frequency modes mainly contribute to the lattice dielectric constant.Comment: 15pages, 1 figure, 5 table

Graph Annotations in Modeling Complex Network Topologies

The coarsest approximation of the structure of a complex network, such as the Internet, is a simple undirected unweighted graph. This approximation, however, loses too much detail. In reality, objects represented by vertices and edges in such a graph possess some non-trivial internal structure that varies across and differentiates among distinct types of links or nodes. In this work, we abstract such additional information as network annotations. We introduce a network topology modeling framework that treats annotations as an extended correlation profile of a network. Assuming we have this profile measured for a given network, we present an algorithm to rescale it in order to construct networks of varying size that still reproduce the original measured annotation profile. Using this methodology, we accurately capture the network properties essential for realistic simulations of network applications and protocols, or any other simulations involving complex network topologies, including modeling and simulation of network evolution. We apply our approach to the Autonomous System (AS) topology of the Internet annotated with business relationships between ASs. This topology captures the large-scale structure of the Internet. In depth understanding of this structure and tools to model it are cornerstones of research on future Internet architectures and designs. We find that our techniques are able to accurately capture the structure of annotation correlations within this topology, thus reproducing a number of its important properties in synthetically-generated random graphs

Thermodynamic model of electric-field-induced pattern formation in binary dielectric fluids

An electric-field-induced phase transition and pattern formation in a binary dielectric fluid layer are studied using a coarse-grained free-energy functional. The electrostatic part of the free energy is a nonlinear functional of the dielectric function, which depends in turn on the local colloidal concentration. We determine the phase coexistence curve and find that beyond a critical electric field the system phase separates. Accompanying the phase separation are patterns similar to those observed in a spinodal decomposition of an ordinary binary fluid. The temporal evolution of the phase separating patterns are discussed both analytically and numerically by integrating a Cahn-Hilliard type of equation

Secretoglobin and Transferrin Expression in Bronchoalveolar Lavage Fluid of Horses with Chronic Respiratory Disease

Background: Lower expression of secretoglobin and transferrin has been found in the bronchoalveolar lavage fluid (BALF) of a small number of horses with experimentally induced signs of recurrent airway obstruction (RAO) compared to healthy controls. Hypothesis/Objectives: Secretoglobin and transferrin BALF expression will be similarly decreased in horses with naturally occurring clinical signs of RAO and in horses with experimentally induced clinical signs of RAO as compared to healthy controls and intermediate in horses with inflammatory airway disease (IAD). Animals: Recurrent airway obstruction-affected and control horses were subjected to an experimental hay exposure trial to induce signs of RAO. Client-owned horses with a presumptive diagnosis of RAO and controls from the same stable environments were recruited. Methods: Pulmonary function and BALF were evaluated from control and RAO-affected research horses during an experimental hay exposure trial (n = 5 in each group) and from client-owned horses (RAO-affected horses, n = 17; IAD-affected horses, n = 19; healthy controls, n = 5). The concentrations of secretoglobin and transferrin in BALF were assessed using Western blots. Results: Naturally occurring and experimentally induced RAO horses had similar decreases in BALF transferrin expression, but secretoglobin expression was most decreased in naturally occurring RAO. Secretoglobin and transferrin expression were both lower in BALF of RAO-affected horses than in IAD-affected and control horses. Conclusions and Clinical Importance: Secretoglobin and transferrin expression is decreased in BALF of RAO-affected horses after both experimental and natural exposure. Secretoglobin and transferrin likely play clinically relevant roles in the pathophysiology of RAO, and may thus be used as biomarkers of the disease

Improving Representation of Deforestation Effects on Evapotranspiration in the E3SM Land Model

Evapotranspiration (ET) plays an important role in land-atmosphere coupling of energy, water, and carbon cycles. Following deforestation, ET is typically observed to decrease substantially as a consequence of decreases in leaf area and roots and increases in runoff. Changes in ET (latent heat flux) revise the surface energy and water budgets, which further affects large-scale atmospheric dynamics and feeds back positively or negatively to long-term forest sustainability. In this study, we used observations from a recent synthesis of 29 pairs of adjacent intact and deforested FLUXNET sites to improve model parameterization of stomatal characteristics, photosynthesis, and soil water dynamics in version 1 of the Energy Exascale Earth System Model (E3SM) Land Model (ELMv1). We found that default ELMv1 predicts an increase in ET after deforestation, likely leading to incorrect estimates of the effects of deforestation on land-atmosphere coupling. The calibrated model accurately represented the FLUXNET observed deforestation effects on ET. Importantly, the search for global optimal parameters converged at values consistent with recent observational syntheses, confirming the reliability of the calibrated physical parameters. Applying this improved model parameterization to the globe scale reduced the bias of annual ET simulation by up to ~600 mm/year. Analysis on the roles of parameters suggested that future model development to improve ET simulation should focus on stomatal resistance and soil water-related parameterizations. Finally, our predicted differences in seasonal ET changes from deforestation are large enough to substantially affect land-atmosphere coupling and should be considered in such studies

Evidence on the economic value of end-of-life and palliative care interventions: a narrative review of reviews.

As the demand for palliative care increases, more information is needed on how efficient different types of palliative care models are for providing care to dying patients and their caregivers. Evidence on the economic value of treatments and interventions is key to informing resource allocation and ultimately improving the quality and efficiency of healthcare delivery. We assessed the available evidence on the economic value of palliative and end-of-life care interventions across various settings. Reviews published between 2000 and 2019 were included. We included reviews that focused on cost-effectiveness, intervention costs and/or healthcare resource use. Two reviewers extracted data independently and in duplicate from the included studies. Data on the key characteristics of the studies were extracted, including the aim of the study, design, population, type of intervention and comparator, (cost-) effectiveness resource use, main findings and conclusions. A total of 43 reviews were included in the analysis. Overall, most evidence on cost-effectiveness relates to home-based interventions and suggests that they offer substantial savings to the health system, including a decrease in total healthcare costs, resource use and improvement in patient and caregivers' outcomes. The evidence of interventions delivered across other settings was generally inconsistent. Some palliative care models may contribute to dual improvement in quality of care via lower rates of aggressive medicalization in the last phase of life accompanied by a reduction in costs. Hospital-based palliative care interventions may improve patient outcomes, healthcare utilization and costs. There is a need for greater consistency in reporting outcome measures, the informal costs of caring, and costs associated with hospice