A determination of the molar gas constant R by acoustic thermometry in helium

We have determined the acoustic and microwave frequencies of a misaligned spherical resonator maintained near the temperature of the triple point of water and filled with helium with carefully characterized molar mass M = (4.002 6032 ± 0.000 0015) g mol-1, with a relative standard uncertainty ur(M) = 0.37×10-6. From these data and traceable thermometry we estimate the speed of sound in our sample of helium at TTPW = 273.16 K and zero pressure to be u0 2 = (945 710.45 ± 0.85) m2 s-2 and correspondingly deduce the value R = (8.314 4743 ± 0.000 0088) J mol-1 K-1 for the molar gas constant. We estimate the value k = R/NA = (1.380 6508 ± 0.000 0015) × 10-23 J K-1 for the Boltzmann constant using the currently accepted value of the Avogadro constant NA. These estimates of R and k, with a relative standard uncertainty of 1.06 × 10-6, are 1.47 parts in 106 above the values recommended by CODATA in 2010

Indirect and direct controls of macroinvertebrates and small fish by abiotic factors and trophic interactions in the Florida Everglades

1. The roles of nutrients, disturbance and predation in regulating consumer densities have long been of interest, but their indirect effects have rarely been quantified in wetland ecosystems. The Florida Everglades contains gradients of hydrological disturbance (marsh drying) and nutrient enrichment (phosphorus), often correlated with densities of macroinvertebrate infauna (macroinvertebrates inhabiting periphyton), small fish and larger invertebrates, such as snails, grass shrimp, insects and crayfish. However, most causal relationships have yet to be quantified. 2.  We sampled periphyton (content and community structure) and consumer (small omnivores, carnivores and herbivores, and infaunal macroinvertebrates inhabiting periphyton) density at 28 sites spanning a range of hydrological and nutrient conditions and compared our data to seven a priori structural equation models. 3.  The best model included bottom-up and top-down effects among trophic groups and supported top-down control of infauna by omnivores and predators that cascaded to periphyton biomass. The next best model included bottom-up paths only and allowed direct effects of periphyton on omnivore density. Both models suggested a positive relationship between small herbivores and small omnivores, indicating that predation was unable to limit herbivore numbers. Total effects of time following flooding were negative for all three consumer groups even when both preferred models suggested positive direct effects for some groups. Total effects of nutrient levels (phosphorus) were positive for consumers and generally larger than those of hydrological disturbance and were mediated by changes in periphyton content. 4.  Our findings provide quantitative support for indirect effects of nutrient enrichment on consumers, and the importance of both algal community structure and periphyton biomass to Everglades food webs. Evidence for top-down control of infauna by omnivores was noted, though without substantially greater support than a competing bottom-up-only model

Relative roles of dispersal dynamics and competition in determining the isotopic niche breadth of a wetland fish

1. The niche variation hypothesis predicts that among-individual variation in niche use will increase in the presence of intraspecific competition and decrease in the presence of interspecific competition. We sought to determine whether the local isotopic niche breadth of fish inhabiting a wetland was best explained by competition for resources and the niche variation hypothesis, by dispersal of individuals from locations with different prey resources or by a combination of the two. We analysed stable isotopes of carbon and nitrogen as indices of feeding niche and compared metrics of within-site spread to characterise site-level isotopic niche breadth. We then evaluated the explanatory power of competing models of the direct and indirect effects of several environmental variables spanning gradients of disturbance, competition strength and food availability on among-individual variation of the eastern mosquitofish (Gambusia holbrooki). 2. The Dispersal model posits that only the direct effect of disturbance (i.e. changes in water level known to induce fish movement) influences among-individual variation in isotopic niche. The Partitioning model allows for only direct effects of local food availability on among-individual variation. The Combined model allows for both hypotheses by including the direct effects of disturbance and food availability. 3. A linear regression of the Combined model described more variance than models limited to the variables of either the Dispersal or Partitioning models. Of the independent variables considered, the food availability variable (per cent edible periphyton) explained the most variation in isotopic niche breadth, followed closely by the disturbance variable (days since last drying event). 4. Structural equation modelling provided further evidence that the Combined model was best supported by the data, with the Partitioning and the Dispersal models only modestly less informative. Again, the per cent edible periphyton was the variable with the largest direct effect on niche variability, with other food availability variables and the disturbance variable only slightly less important. Indirect effects of heterospecific and conspecific competitor densities were also important, through their effects on prey density. 5. Our results support the Combined hypotheses, although partitioning mechanisms appear to explain the most diet variation among individuals in the eastern mosquitofish. The results also support some predictions of the niche variation hypothesis, although both conspecific and interspecific competition appeared to increase isotopic niche breadth in contrast to predictions that interspecific competition would decrease it. We think this resulted from high diet overlap of co-occurring species, most of which consume similar macroinvertebrates

Effects of foam on ocean surface microwave emission inferred from radiometric observations of reproducible breaking waves

Includes bibliographical references.WindSat, the first satellite polarimetric microwave radiometer, and the NPOESS Conical Microwave Imager/Sounder both have as a key objective the retrieval of the ocean surface wind vector from radiometric brightness temperatures. Available observations and models to date show that the wind direction signal is only 1-3 K peak-to-peak at 19 and 37 GHz, much smaller than the wind speed signal. In order to obtain sufficient accuracy for reliable wind direction retrieval, uncertainties in geophysical modeling of the sea surface emission on the order of 0.2 K need to be removed. The surface roughness spectrum has been addressed by many studies, but the azimuthal signature of the microwave emission from breaking waves and foam has not been adequately addressed. RECENtly, a number of experiments have been conducted to quantify the increase in sea surface microwave emission due to foam. Measurements from the Floating Instrumentation Platform indicated that the increase in ocean surface emission due to breaking waves may depend on the incidence and azimuth angles of observation. The need to quantify this dependence motivated systematic measurement of the microwave emission from reproducible breaking waves as a function of incidence and azimuth angles. A number of empirical parameterizations of whitecap coverage with wind speed were used to estimate the increase in brightness temperatures measured by a satellite microwave radiometer due to wave breaking in the field of view. These results provide the first empirically based parameterization with wind speed of the effect of breaking waves and foam on satellite brightness temperatures at 10.8, 19, and 37 GHz.This work was supported in part by the Department of the Navy, Office of Naval Research under Awards N00014-00-1-0615 (ONR/YIP) and N00014-03-1-0044 (Space and Remote Sensing) to the University of Massachusetts Amherst, and N00014-00-1-0152 (Space and Remote Sensing) to the University of Washington. The National Polar-orbiting Operational environmental Satellite System Integrated Program Office supported the Naval Research Laboratory's participation through Award NA02AANEG0338 and supported data analysis at Colorado State University and the University of Washington through Award NA05AANEG0153

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study

BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin-eosin (HE)-stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers. In the present study, we investigated whether deep convolutional neural networks (CNNs) can extract prognosticators directly from these widely available images. METHODS AND FINDINGS: We hand-delineated single-tissue regions in 86 CRC tissue slides, yielding more than 100,000 HE image patches, and used these to train a CNN by transfer learning, reaching a nine-class accuracy of >94% in an independent data set of 7,180 images from 25 CRC patients. With this tool, we performed automated tissue decomposition of representative multitissue HE images from 862 HE slides in 500 stage I-IV CRC patients in the The Cancer Genome Atlas (TCGA) cohort, a large international multicenter collection of CRC tissue. Based on the output neuron activations in the CNN, we calculated a "deep stroma score," which was an independent prognostic factor for overall survival (OS) in a multivariable Cox proportional hazard model (hazard ratio [HR] with 95% confidence interval [CI]: 1.99 [1.27-3.12], p = 0.0028), while in the same cohort, manual quantification of stromal areas and a gene expression signature of cancer-associated fibroblasts (CAFs) were only prognostic in specific tumor stages. We validated these findings in an independent cohort of 409 stage I-IV CRC patients from the "Darmkrebs: Chancen der Verhütung durch Screening" (DACHS) study who were recruited between 2003 and 2007 in multiple institutions in Germany. Again, the score was an independent prognostic factor for OS (HR 1.63 [1.14-2.33], p = 0.008), CRC-specific OS (HR 2.29 [1.5-3.48], p = 0.0004), and relapse-free survival (RFS; HR 1.92 [1.34-2.76], p = 0.0004). A prospective validation is required before this biomarker can be implemented in clinical workflows. CONCLUSIONS: In our retrospective study, we show that a CNN can assess the human tumor microenvironment and predict prognosis directly from histopathological images

The Global Lake Ecological Observatory Network (GLEON): the evolution of grassroots network science

Nine years later, with over 380 members from 40 countries, and 50 publications to its credit, GLEON is growing at a rapid pace and pushing the boundaries of the practice of network science. GLEON is really three networks: a network of lakes, data, and peopl

Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models

This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6–17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using Hierarchical Bayesian Regression from N = 42,993 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N = 6285) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born preterm.</p

Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models

This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6–17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using Hierarchical Bayesian Regression from N = 42,993 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N = 6285) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born preterm.</p

Periphyton responses to eutrophication in the Florida Everglades: Cross-system patterns of structural and compositional change

We examined periphyton along transects in five Everglades marshes and related compositional and functional aspects to phosphorus(P ) gradients caused by enriched inflows. Results were compared to those of a P-addition experiment in a pristine Everglades marsh. While the water total P (TP) concentration was not related to P load in the marshes or experiment the concentration of TP in periphyton was strongly correlated with the distance from the P source. Increased P concentration in periphyton was associated with a loss of biomass,p articularly of the calcifying mat-forming matrix, regardless of the growth form of the periphyton (epiphytic, floating,or epilithic). Diatom species composition was also strongly related to P availability, but the TP optima of many species varied among marshes. Enriched periphyton communities were found 14 km downstream of P inputs to one marsh that has been receiving enhanced P loads for decades, where other studies using different biotic indicators show negligible change in the same marsh. Although recovery trajectories are unknown, periphyton indicators should serve as excellent metrics for the progression or amelioration of P-related effects in the Everglades