Laboratory simulation of cometary x rays using a high-resolution microcalorimeter

X-ray emission following charge exchange has been studied on the University of California Lawrence Livermore National Laboratory electron beam ion traps EBIT-I and EBIT-II using a high-resolution microcalorimeter. The measured spectra include the K-shell emission from hydrogenlike and heliumlike C, N, O, and Ne needed for simulations of cometary x-ray emission. A comparison of the spectra produced in the interaction of O8+ with N2 and CH4 is presented that illustrates the dependence of the observed spectrum on the interaction gas.Comment: 11 pages, 2 figure

Carbono orgânico dissolvido e biodisponibilidade de N e P como indicadores de qualidade do solo

Nas últimas décadas, qualidade do solo tem se tornado um tópico importante na ciência do solo. Embora esforços consideráveis tenham sido dedicados com o intuito de definir "qualidade do solo", ainda não há um conceito amplamente aceito pela comunidade cientifica. A seleção de índices qualitativos para definir qualidade do solo é uma tarefa extremamente difícil, e diversas propriedades químicas, físicas e biológicas tem sido sugeridas como potenciais indicadores. A matéria orgânica do solo está associada com processos químicos, físicos e biológicos no solo, e, portanto, é considerada um dos melhores indicadores de qualidade do solo. O manejo do solo pode influenciar significativamente a dinâmica do carbono orgânico e o ciclo de N, P, e S. Entretanto, mudanças na concentração total da matéria organica em resposta ao manejo pode ser dificil de ser detectada devido à variabilidade natural do solo. Quando comparada com a matéria orgânica total do solo, a fração mais prontamente disponível, como o carbono orgânico dissolvido (COD), é mais sensível às mudanças no manejo do solo a curto e médio prazo e, portanto, pode ser utilizada como indicador fundamental de qualidade do solo ou das alterações das condições naturais. Embora a fração dissolvida represente apenas uma pequena porção da matéria orgânica total do solo, o COD é móvel no solo e constitui uma importante fonte de C para os microorganismos, podendo facilmente refletir os efeitos de diferentes sistemas de manejo. Inúmeros métodos são utilizados para caracterizar o COD, mas os processos que influenciam sua mineralização e a disponibilidade dos elementos associado com a matéria orgânica (N, P, e S) ainda não são completamente entendidos. Pesquisas futuras devem buscar entender os processos que governam a dinâmica de nutrientes e do COD e como os mesmos afetam a qualidade do solo.Soil quality has become an important issue in soil science. Considerable attempts have been made to define soil quality, but a general concept has not yet been accepted by the scientific community. The selection of quantitative indices for soil quality is extremely difficult, and a considerable number of chemical, physical, and biochemical properties have been suggested as potential indicators of soil quality. Because soil organic matter (SOM) can be associated with different soil chemical, physical and biological processes, it has been widely considered as one of the best soil quality indicator. Land use can significantly influence dynamics of organic carbon and N, P, and S cycle. However, changes in total soil organic carbon (SOC) contents in response to land use may be difficult to detect because of the natural soil variability. In the short to medium term, biological properties and readily decomposable fractions of SOC, such as dissolved organic carbon (DOC), are much more sensitive to soil management than is SOM as a whole, and can be used as a key indicator of soil natural functions. Despite the fact that labile C accounts for a small portion of the total organic matter in the soils, DOC is the most mobile and important C-source for microorganisms, and can easily reflect the effects of land use on soil quality. Although several methods are used to characterize DOC, the factors influencing mineralization and bioavailability of elements associated with organic matter (N, P, and S) remains unclear. Future research should focus on the processes that govern DOC and nutrient dynamics and how they affect soil quality

Factors influencing terrestriality in primates of the Americas and Madagascar

Among mammals, the order Primates is exceptional in having a high taxonomic richness in which the taxa are arboreal, semiterrestrial, or terrestrial. Although habitual terrestriality is pervasive among the apes and African and Asian monkeys (catarrhines), it is largely absent among monkeys of the Americas (platyrrhines), as well as galagos, lemurs, and lorises (strepsirrhines), which are mostly arboreal. Numerous ecological drivers and species-specific factors are suggested to set the conditions for an evolutionary shift from arboreality to terrestriality, and current environmental conditions may provide analogous scenarios to those transitional periods. Therefore, we investigated predominantly arboreal, diurnal primate genera from the Americas and Madagascar that lack fully terrestrial taxa, to determine whether ecological drivers (habitat canopy cover, predation risk, maximum temperature, precipitation, primate species richness, human population density, and distance to roads) or species-specific traits (body mass, group size, and degree of frugivory) associate with increased terrestriality. We collated 150,961 observation hours across 2,227 months from 47 species at 20 sites in Madagascar and 48 sites in the Americas. Multiple factors were associated with ground use in these otherwise arboreal species, including increased temperature, a decrease in canopy cover, a dietary shift away from frugivory, and larger group size. These factors mostly explain intraspecific differences in terrestriality. As humanity modifies habitats and causes climate change, our results suggest that species already inhabiting hot, sparsely canopied sites, and exhibiting more generalized diets, are more likely to shift toward greater ground use

Customer emotions in service failure and recovery encounters

Emotions play a significant role in the workplace, and considerable attention has been given to the study of employee emotions. Customers also play a central function in organizations, but much less is known about customer emotions. This chapter reviews the growing literature on customer emotions in employee–customer interfaces with a focus on service failure and recovery encounters, where emotions are heightened. It highlights emerging themes and key findings, addresses the measurement, modeling, and management of customer emotions, and identifies future research streams. Attention is given to emotional contagion, relationships between affective and cognitive processes, customer anger, customer rage, and individual differences

Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment. Tumor-infiltrating lymphocytes (TILs) were identified from standard pathology cancer images by a deep-learning-derived \u201ccomputational stain\u201d developed by Saltz et al. They processed 5,202 digital images from 13 cancer types. Resulting TIL maps were correlated with TCGA molecular data, relating TIL content to survival, tumor subtypes, and immune profiles