Ionospheric Electron Density During Solar Eclipse of 20 July 1963

Ionospheric electron density during solar eclips

Gravitational redshift of galaxies in clusters as predicted by general relativity

The theoretical framework of cosmology is mainly defined by gravity, of which general relativity is the current model. Recent tests of general relativity within the \Lambda Cold Dark Matter (CDM) model have found a concordance between predictions and the observations of the growth rate and clustering of the cosmic web. General relativity has not hitherto been tested on cosmological scales independent of the assumptions of the \Lambda CDM model. Here we report observation of the gravitational redshift of light coming from galaxies in clusters at the 99 per cent confidence level, based upon archival data. The measurement agrees with the predictions of general relativity and its modification created to explain cosmic acceleration without the need for dark energy (f(R) theory), but is inconsistent with alternative models designed to avoid the presence of dark matter.Comment: Published in Nature issued on 29 September 2011. This version includes the Letter published there as well as the Supplementary Information. 23 pages, 7 figure

Waves on the surface of the Orion molecular cloud

Massive stars influence their parental molecular cloud, and it has long been suspected that the development of hydrodynamical instabilities can compress or fragment the cloud. Identifying such instabilities has proved difficult. It has been suggested that elongated structures (such as the `pillars of creation') and other shapes arise because of instabilities, but alternative explanations are available. One key signature of an instability is a wave-like structure in the gas, which has hitherto not been seen. Here we report the presence of `waves' at the surface of the Orion molecular cloud near where massive stars are forming. The waves seem to be a Kelvin-Helmholtz instability that arises during the expansion of the nebula as gas heated and ionized by massive stars is blown over pre-existing molecular gas.Comment: Preprint of publication in Natur

Signatures of Young Star Formation Activity Within Two Parsecs of Sgr A*

We present radio and infrared observations indicating on-going star formation activity inside the $\sim2-5$ pc circumnuclear ring at the Galactic center. Collectively these measurements suggest a continued disk-based mode of on-going star formation has taken place near Sgr A* over the last few million years. First, VLA observations with spatial resolution 2.17$"\times0.81"$ reveal 13 water masers, several of which have multiple velocity components. The presence of interstellar water masers suggests gas densities that are sufficient for self-gravity to overcome the tidal shear of the 4$\times10^6$ \msol\, black hole. Second, SED modeling of stellar sources indicate massive YSO candidates interior to the molecular ring, supporting in-situ star formation near Sgr A* and appear to show a distribution similar to that of the counter-rotating disks of $\sim$100 OB stars orbiting Sgr A*. Some YSO candidates (e.g., IRS~5) have bow shock structures suggesting that they have have gaseous disks that are phototoevaporated and photoionized by the strong radiation field. Third, we detect clumps of SiO (2-1) and (5-4) line emission in the ring based on CARMA and SMA observations. The FWHM and luminosity of the SiO emission is consistent with shocked protostellar outflows. Fourth, two linear ionized features with an extent of $\sim0.8$ pc show blue and redshifted velocities between $+50$ and $-40$ \kms, suggesting protostellar jet driven outflows with mass loss rates of $\sim5\times10^{-5}$ solar mass yr$^{-1}$. Finally, we present the imprint of radio dark clouds at 44 GHz, representing a reservoir of molecular gas that feeds star formation activity close to Sgr A*.Comment: 38 pages, 10 figures, ApJ (in press

Predicting Plant Growth from Time-Series Data Using Deep Learning

Phenotyping involves the quantitative assessment of the anatomical, biochemical, and physiological plant traits. Natural plant growth cycles can be extremely slow, hindering the experimental processes of phenotyping. Deep learning offers a great deal of support for automating and addressing key plant phenotyping research issues. Machine learning-based high-throughput phenotyping is a potential solution to the phenotyping bottleneck, promising to accelerate the experimental cycles within phenomic research. This research presents a study of deep networks’ potential to predict plants’ expected growth, by generating segmentation masks of root and shoot systems into the future. We adapt an existing generative adversarial predictive network into this new domain. The results show an efficient plant leaf and root segmentation network that provides predictive segmentation of what a leaf and root system will look like at a future time, based on time-series data of plant growth. We present benchmark results on two public datasets of Arabidopsis (A. thaliana) and Brassica rapa (Komatsuna) plants. The experimental results show strong performance, and the capability of proposed methods to match expert annotation. The proposed method is highly adaptable, trainable (transfer learning/domain adaptation) on different plant species and mutations

Ecological equivalence: a realistic assumption for niche theory as a testable alternative to neutral theory

Hubbell's 2001 neutral theory unifies biodiversity and biogeography by modelling steady-state distributions of species richness and abundances across spatio-temporal scales. Accurate predictions have issued from its core premise that all species have identical vital rates. Yet no ecologist believes that species are identical in reality. Here I explain this paradox in terms of the ecological equivalence that species must achieve at their coexistence equilibrium, defined by zero net fitness for all regardless of intrinsic differences between them. I show that the distinction of realised from intrinsic vital rates is crucial to evaluating community resilience. An analysis of competitive interactions reveals how zero-sum patterns of abundance emerge for species with contrasting life-history traits as for identical species. I develop a stochastic model to simulate community assembly from a random drift of invasions sustaining the dynamics of recruitment following deaths and extinctions. Species are allocated identical intrinsic vital rates for neutral dynamics, or random intrinsic vital rates and competitive abilities for niche dynamics either on a continuous scale or between dominant-fugitive extremes. Resulting communities have steady-state distributions of the same type for more or less extremely differentiated species as for identical species. All produce negatively skewed log-normal distributions of species abundance, zero-sum relationships of total abundance to area, and Arrhenius relationships of species to area. Intrinsically identical species nevertheless support fewer total individuals, because their densities impact as strongly on each other as on themselves. Truly neutral communities have measurably lower abundance/area and higher species/abundance ratios. Neutral scenarios can be parameterized as null hypotheses for testing competitive release, which is a sure signal of niche dynamics. Ignoring the true strength of interactions between and within species risks a substantial misrepresentation of community resilience to habitat los

Comparing the Importance of Iodine and Isoprene on Tropospheric Photochemistry

Isoprene, arguably the most studied biogenically emitted gas, is thought to have a large impact on tropospheric composition. Other naturally emitted species have been considered to play a less important role. Here the GEOS-Chem model is used to compare the impacts of isoprene and iodine emissions on present-day tropospheric composition. Removing isoprene emissions leads to a 3.4 burden, a smaller absolute change than the 5.9+0.60.05 whereas isoprene has a substantial impact on both (−4.34.2. Isoprene emissions and chemistry are seen as essential for tropospheric chemistry models, but iodine is often not. We suggest that iodine should receive greater attention in model development and experimental research to allow improved predictions of past, present, and future tropospheric O3

Evaluation of a low-cost optical particle counter (Alphasense OPC-N2) for ambient air monitoring

A fast-growing area of research is the development of low-cost sensors for measuring air pollutants. The affordability and size of low-cost particle sensors makes them an attractive option for use in experiments requiring a number of instruments such as high-density spatial mapping. However, for these low-cost sensors to be useful for these types of studies their accuracy and precision need to be quantified. We evaluated the Alphasense OPC-N2, a promising low-cost miniature optical particle counter, for monitoring ambient airborne particles at typical urban background sites in the UK. The precision of the OPC-N2 was assessed by co-locating 14 instruments at a site to investigate the variation in measured concentrations. Comparison to two different reference optical particle counters as well as a TEOM-FDMS enabled the accuracy of the OPC-N2 to be evaluated. Comparison of the OPC-N2 to the reference optical instruments shows some limitations for measuring mass concentrations of PM1, PM2.5 and PM10. The OPC-N2 demonstrated a significant positive artefact in measured particle mass during times of high ambient RH (>85%) and a calibration factor was developed based upon °-Köhler theory, using average bulk particle aerosol hygroscopicity. Application of this RH correction factor resulted in the OPC-N2 measurements being within 33% of the TEOM-FDMS, comparable to the agreement between a reference optical particle counter and the TEOM-FDMS (20%). Inter-unit precision for the 14 OPC-N2 sensors of 22±13% for PM10 mass concentrations was observed. Overall, the OPC-N2 was found to accurately measure ambient airborne particle mass concentration provided they are (i) correctly calibrated and (ii) corrected for ambient RH. The level of precision demonstrated between multiple OPC-N2s suggests that they would be suitable devices for applications where the spatial variability in particle concentration was to be determined

Evaluation of a low-cost optical particle counter (Alphasense OPC-N2) for ambient air monitoring

A fast growing area of research is the development of low-cost sensors for measuring air pollutants. The affordability and size of low-cost particle sensors makes them an attractive option for use in experiments requiring a number of instruments such as high density spatial mapping. However, for these low-cost sensors to be useful for these types of studies their accuracy and precision needs to be quantified. We evaluated the Alphasense OPC-N2, a promising low-cost miniature optical particle counter, for monitoring ambient airborne particles at typical urban background sites in the UK. The precision of the OPC-N2 was assessed by co-locating 14 instruments at a site to investigate the variation in measured concentrations. Comparison to two different reference optical particle counters as well as a TEOM-FDMS enabled the accuracy of the OPC-N2 to be evaluated. Comparison of the OPC-N2 to the reference optical instruments demonstrated reasonable agreement for the measured mass concentrations of PM1, PM2.5 and PM10. However, the OPC-N2 demonstrated a significant positive artefact in measured particle mass during times of high ambient RH (> 85 %) and a calibration factor was developed based upon κ-Kohler theory, using average bulk particle aerosol hygroscopicity. Application of this RH correction factor resulted in the OPC-N2 measurements being within 33 % of the TEOM-FDMS, comparable to the agreement between a reference optical particle counter and the TEOM-FDMS (20 %). Reasonable inter-unit precision for the 14 OPC-N2 sensors was observed. Overall, the OPC-N2 was found to accurately measure ambient airborne particle mass concentration provided they are i) correctly calibrated and ii) corrected for ambient RH. The reasonable level of precision demonstrated between multiple OPC-N2 suggests that they would be suitable device for applications where the spatial variability in particle concentration was to be determined