On the perception of raga motifs by trained musicians.

A prominent aspect of the notion of musical similarity across the music of various cultures is related to the local matching of melodic motifs. This holds for Indian art music, a highly structured form with raga playing a critical role in the melodic organization. Apart from the tonal material, a raga is characterized by a set of melodic phrases that serve as important points of reference in a music performance. Musicians acquire in their training a knowledge of the melodic phrase shapes or motifs particular to a raga and the proficiency to render these correctly in performance. This phenomenon of learned schema might be expected to influence the musicians' perception of variations of the melodic motif in terms of pitch contour shape. Motivated by the parallels between the musical structure and prosodic structure in speech, identification and discrimination experiments are presented, which explore the differences between trained musicians' (TMs) and non-musicians' perception of ecologically valid synthesized variants of a raga-characteristic motif, presented both in and out of context. It is found that trained musicians are relatively insensitive to acoustic differences associated with note duration in the vicinity of a prototypical phrase shape while also clearly demonstrating the heightened sensitivity associated with categorical perception in the context of the boundary between ragas.

Commonality and variation in mental representations of music revealed by a cross-cultural comparison of rhythm priors in 15 countries.

Music is present in every known society but varies from place to place. What, if anything, is universal to music cognition? We measured a signature of mental representations of rhythm in 39 participant groups in 15 countries, spanning urban societies and Indigenous populations. Listeners reproduced random 'seed' rhythms; their reproductions were fed back as the stimulus (as in the game of 'telephone'), such that their biases (the prior) could be estimated from the distribution of reproductions. Every tested group showed a sparse prior with peaks at integer-ratio rhythms. However, the importance of different integer ratios varied across groups, often reflecting local musical practices. Our results suggest a common feature of music cognition: discrete rhythm 'categories' at small-integer ratios. These discrete representations plausibly stabilize musical systems in the face of cultural transmission but interact with culture-specific traditions to yield the diversity that is evident when mental representations are probed across many cultures.

Mapping cover crop species in southeastern Michigan using Sentinel-2 satellite data and Google Earth Engine.

Cover crops are a critical agricultural practice that can improve soil quality, enhance crop yields, and reduce nitrogen and phosphorus losses from farms. Yet there is limited understanding of the extent to which cover crops have been adopted across large spatial and temporal scales. Remote sensing offers a low-cost way to monitor cover crop adoption at the field scale and at large spatio-temporal scales. To date, most studies using satellite data have mapped the presence of cover crops, but have not identified specific cover crop species, which is important because cover crops of different plant functional types (e.g., legumes, grasses) perform different ecosystem functions. Here we use Sentinel-2 satellite data and a random forest classifier to map the cover crop species cereal rye and red clover, which represent grass and legume functional types, in the River Raisin watershed in southeastern Michigan. Our maps of agricultural landcover across this region, including the two cover crop species, had moderate to high accuracies, with an overall accuracy of 83%. Red clover and cereal rye achieved F1 scores that ranged from 0.7 to 0.77, and user's and producer's accuracies that ranged from 63.3% to 86.2%. The most common misclassification of cover crops was fallow fields with remaining crop stubble, which often looked similar because these cover crop species are typically planted within existing crop stubble, or interseeded into a grain crop. We found that red-edge bands and images from the end of April and early July were the most important for classification accuracy. Our results demonstrate the potential to map individual cover crop species using Sentinel-2 imagery, which is critical for understanding the environmental outcomes of increasing crop diversity on farms.

Inconsistent definitions of "urban" result in different conclusions about the size of urban carbon and nitrogen stocks.

There is conflicting evidence about the importance of urban soils and vegetation in regional C budgets that is caused, in part, by inconsistent definitions of "urban" land use. We quantified urban ecosystem contributions to C stocks in the Boston (Massachusetts, USA) Metropolitan Statistical Area (MSA) using several alternative urban definitions. Development altered aboveground and belowground C and N stocks, and the sign and magnitude of these changes varied by land use and development intensity. Aboveground biomass (live trees, dbh > or = 5 cm) for the MSA was 7.2 +/- 0.4 kg C/m2 (mean +/- SE), reflecting a high proportion of forest cover. Vegetation C was highest in forest (11.6 +/- 0.5 kg C/m2), followed by residential (4.6 +/- 0.5 kg C/m2), and then other developed (2.0 +/- 0.4 kg C/m2) land uses. Soil C (0-10 cm depth) followed the same pattern of decreasing C concentration from forest, to residential, to other developed land uses (4.1 +/- 0.1, 4.0 +/- 0.2, and 3.3 +/- 0.2 kg C/m2, respectively). Within a land use type, urban areas (which we defined as > 25% impervious surface area [ISA] within a 1-km(2) moving window) generally contained less vegetation C, but slightly more soil C, than nonurban areas. Soil N concentrations were higher in urban areas than nonurban areas of the same land use type, except for residential areas, which had similarly high soil N concentrations. When we compared our definition of urban to other commonly used urban extents (U.S. Census Bureau, Global Rural-Urban Mapping Project [GRUMP], and the MSA itself), we found that urban soil (1 m depth) and vegetation C stocks spanned a wide range, from 14.4 +/- 0.8 to 54.5 +/- 3.4 Tg C and from 4.2 +/- 0.4 to 27.3 +/- 3.2 Tg C, respectively. Conclusions about the importance of urban soils and vegetation to regional C and N stocks are very sensitive to the definition of urban used by the investigators. Urban areas, regardless of definition, are rapidly expanding in their extent; a systematic understanding of how our development patterns influence ecosystems is necessary to inform future development choices.

Human papillomavirus vaccination and the primary prevention of cancer: implications for survivors of childhood cancer.

Effective vaccination is now available to prevent human papillomavirus (HPV), the most common sexually transmitted infection and the cause of cervical cancer, the second most common cancer among women worldwide. HPV vaccine uptake is particularly important for females surviving cancer, who are at high risk for HPV-related complication due to the direct and indirect effects of cancer therapy. Thus, Version 3.0 of the Children's Oncology Group Long-Term Follow-Up Guidelines for Survivors of Childhood, Adolescent and Young Adult Cancer recommends HPV vaccination for all eligible females surviving childhood cancer. Because this vaccine was only FDA approved in 2006, little is known about the complexity of vaccination uptake among those surviving childhood cancer. This chapter describes HPV vaccination and its usefulness in survivors of childhood cancer, provides a rationale for describing survivors as being at increased risk for HPV-related complication, identifies factors that are predictive of HPV vaccination, and discusses the utilization of these predictors in designing strategies to promote adherence to the HPV vaccination recommendations among survivors.

Using Sentinel-1, Sentinel-2, and Planet satellite data to map field-level tillage practices in smallholder systems.

Remote sensing can be used to map tillage practices at large spatial and temporal scales. However, detecting such management practices in smallholder systems is challenging given that the size of fields is smaller than historical readily-available satellite imagery. In this study we used newer, higher-resolution satellite data from Sentinel-1, Sentinel-2, and Planet to map tillage practices in the Eastern Indo-Gangetic Plains in India. We specifically tested the classification performance of single sensor and multiple sensor random forest models, and the impact of spatial, temporal, or spectral resolution on classification accuracy. We found that when considering a single sensor, the model that used Planet imagery (3 m) had the highest classification accuracy (86.55%) while the model that used Sentinel-1 data (10 m) had the lowest classification accuracy (62.28%). When considering sensor combinations, the model that used data from all three sensors achieved the highest classification accuracy (87.71%), though this model was not statistically different from the Planet only model when considering 95% confidence intervals from bootstrap analyses. We also found that high levels of accuracy could be achieved by only using imagery from the sowing period. Considering the impact of spatial, temporal, and spectral resolution on classification accuracy, we found that improved spatial resolution from Planet contributed the most to improved classification accuracy. Overall, it is possible to use readily-available, high spatial resolution satellite data to map tillage practices of smallholder farms, even in heterogeneous systems with small field sizes.

On the Impact of Granularity of Space-based Urban CO2 Emissions in Urban Atmospheric Inversions: A Case Study for Indianapolis, IN.

Quantifying greenhouse gas (GHG) emissions from cities is a key challenge towards effective emissions management. An inversion analysis from the INdianapolis FLUX experiment (INFLUX) project, as the first of its kind, has achieved a top-down emission estimate for a single city using CO2 data collected by the dense tower network deployed across the city. However, city-level emission data, used as a priori emissions, are also a key component in the atmospheric inversion framework. Currently, fine-grained emission inventories (EIs) able to resolve GHG city emissions at high spatial resolution, are only available for few major cities across the globe. Following the INFLUX inversion case with a global 1×1 km ODIAC fossil fuel CO2 emission dataset, we further improved the ODIAC emission field and examined its utility as a prior for the city scale inversion. We disaggregated the 1×1 km ODIAC non-point source emissions using geospatial datasets such as the global road network data and satellite-data driven surface imperviousness data to a 30×30 m resolution. We assessed the impact of the improved emission field on the inversion result, relative to priors in previous studies (Hestia and ODIAC). The posterior total emission estimate (5.1 MtC/yr) remains statistically similar to the previous estimate with ODIAC (5.3 MtC/yr). However, the distribution of the flux corrections was very close to those of Hestia inversion and the model-observation mismatches were significantly reduced both in forward and inverse runs, even without hourly temporal changes in emissions. EIs reported by cities often do not have estimates of spatial extents. Thus, emission disaggregation is a required step when verifying those reported emissions using atmospheric models. Our approach offers gridded emission estimates for global cities that could serves as a prior for inversion, even without locally reported EIs in a systematic way to support city-level Measuring, Reporting and Verification (MRV) practice implementation.

Variability, drivers, and effects of atmospheric nitrogen inputs across an urban area: Emerging patterns among human activities, the atmosphere, and soils.

Atmospheric deposition of nitrogen (N) is a major input of N to the biosphere and is elevated beyond preindustrial levels throughout many ecosystems. Deposition monitoring networks in the United States generally avoid urban areas in order to capture regional patterns of N deposition, and studies measuring N deposition in cities usually include only one or two urban sites in an urban-rural comparison or as an anchor along an urban-to-rural gradient. Describing patterns and drivers of atmospheric N inputs is crucial for understanding the effects of N deposition; however, little is known about the variability and drivers of atmospheric N inputs or their effects on soil biogeochemistry within urban ecosystems. We measured rates of canopy throughfall N as a measure of atmospheric N inputs, as well as soil net N mineralization and nitrification, soil solution N, and soil respiration at 15 sites across the greater Boston, Massachusetts area. Rates of throughfall N are 8.70±0.68kgNha-1yr-1, vary 3.5-fold across sites, and are positively correlated with rates of local vehicle N emissions. Ammonium (NH4+) composes 69.9±2.2% of inorganic throughfall N inputs and is highest in late spring, suggesting a contribution from local fertilizer inputs. Soil solution NO3- is positively correlated with throughfall NO3- inputs. In contrast, soil solution NH4+, net N mineralization, nitrification, and soil respiration are not correlated with rates of throughfall N inputs. Rather, these processes are correlated with soil properties such as soil organic matter. Our results demonstrate high variability in rates of urban throughfall N inputs, correlation of throughfall N inputs with local vehicle N emissions, and a decoupling of urban soil biogeochemistry and throughfall N inputs.

Carbon dioxide and methane measurements from the Los Angeles Megacity Carbon Project - Part 1: calibration, urban enhancements, and uncertainty estimates.

We report continuous surface observations of carbon dioxide (CO2) and methane (CH4) from the Los Angeles (LA) Megacity Carbon Project during 2015. We devised a calibration strategy, methods for selection of background air masses, calculation of urban enhancements, and a detailed algorithm for estimating uncertainties in urban-scale CO2 and CH4 measurements. These methods are essential for understanding carbon fluxes from the LA megacity and other complex urban environments globally. We estimate background mole fractions entering LA using observations from four "extra-urban" sites including two "marine" sites located south of LA in La Jolla (LJO) and offshore on San Clemente Island (SCI), one "continental" site located in Victorville (VIC), in the high desert northeast of LA, and one "continental/mid-troposphere" site located on Mount Wilson (MWO) in the San Gabriel Mountains. We find that a local marine background can be established to within ~1 ppm CO2 and ~10 ppb CH4 using these local measurement sites. Overall, atmospheric carbon dioxide and methane levels are highly variable across Los Angeles. "Urban" and "suburban" sites show moderate to large CO2 and CH4 enhancements relative to a marine background estimate. The USC (University of Southern California) site near downtown LA exhibits median hourly enhancements of ~20 ppm CO2 and ~150 ppb CH4 during 2015 as well as ~15 ppm CO2 and ~80 ppb CH4 during mid-afternoon hours (12:00-16:00 LT, local time), which is the typical period of focus for flux inversions. The estimated measurement uncertainty is typically better than 0.1 ppm CO2 and 1 ppb CH4 based on the repeated standard gas measurements from the LA sites during the last 2 years, similar to Andrews et al. (2014). The largest component of the measurement uncertainty is due to the single-point calibration method; however, the uncertainty in the background mole fraction is much larger than the measurement uncertainty. The background uncertainty for the marine background estimate is ~10 and ~15 % of the median mid-afternoon enhancement near downtown LA for CO2 and CH4, respectively. Overall, analytical and background uncertainties are small relative to the local CO2 and CH4 enhancements; however, our results suggest that reducing the uncertainty to less than 5 % of the median mid-afternoon enhancement will require detailed assessment of the impact of meteorology on background conditions.

Matrix effects for calcium and potassium K-X-rays, in fenugreek plants grown in iron rich soils.

The present work comprises the matrix effects study of the plant system (plant and soil) for macronutrients Ca and K with elevated levels of iron in the soil. The earlier derived matrix effect terms from fundamental relations of intensities of analyte and substrate elements with basic atomic and experimental setup parameters had led to iterative determination of enhanced elements rather than avoiding their enhancement. The relations also facilitated the evaluations of absorption for close Z interfering constituents (like Ca and K) in samples of a lot of particular category with interpolation of matrix terms with elemental amounts. The process has already been employed successfully for potato, radish, rice and maize plants. On similar lines, the observed prominent change in interpolation parameters for the plants in the present experiment serves as a tool to check the toxicity/contamination of the growing medium.