Study of systematics effects on the Cross Power Spectrum of 21 cm Line and Cosmic Microwave Background using Murchison Widefield Array Data

Observation of the 21cm line signal from neutral hydrogen during the Epoch of Reionization is challenging due to extremely bright Galactic and extragalactic foregrounds and complicated instrumental calibration. A reasonable approach for mitigating these problems is the cross correlation with other observables. In this work, we present the first results of the cross power spectrum (CPS) between radio images observed by the Murchison Widefield Array and the cosmic microwave background (CMB), measured by the Planck experiment. We study the systematics due to the ionospheric activity, the dependence of CPS on group of pointings, and frequency. The resulting CPS is consistent with zero because the error is dominated by the foregrounds in the 21cm observation. Additionally, the variance of the signal indicates the presence of unexpected systematics error at small scales. Furthermore, we reduce the error by one order of magnitude with application of a foreground removal using a polynomial fitting method. Based on the results, we find that the detection of the 21cm-CMB CPS with the MWA Phase I requires more than 99.95% of the foreground signal removed, 2000 hours of deep observation and 50% of the sky fraction coverage.Comment: 15 pages, 16 figures, accepted to MNRA

Metagenomics approach towards the understanding of earthworm-microbe interaction in sugarcane rhizosphere.

Resumo. 5° ELAETAO

Dynamic of microbial community during distinct stages of organic matter decomposition in sediments from mangroves of São Paulo state.

Abstract: Mangroves are ecosystems located at coastline areas in tropical and subtropical conditions that are under tide influences. They are recognized as productive regions and have a high export of organic matter (OM) for the adjacent coastal waters. Bacterial communities present in these environments perform primordial functions on the cycling of nutrients and thereby on maintaining your important processes. Therefore, the purpose of this study was to assess the dynamics and phylogenetic diversity of the bacterial community in threes of São Paulo mangroves, during different stages of decomposition plant material. At the same time, the intention was to correlate this event with the emission of greenhouse gases (GHG). Microcosms were constructed with leaf discs of Avicennia schaueriana (A), Laguncularia racemosa (L), Rhizophora mangle (R) were arranged on sediment and water, which were collected from the following Mangroves: Bertioga with contamination (BC), Bertioga (B) and Cananeia (C). These microenvironments were stored at 24 °C and monitored for 60 days. The measurements of gases and DNA extraction were performed at the 7, 15, 30 and 60 days. The collected air samples were analyzed in triplicate in chromatograph model GC-2014 greenhouse gas. The obtained DNA was subjected to PCR reactions aiming the sequencing in large scale of the gene that encoding the ribosomal rRNA Domain Bacteria by Ion Torrent. The assessment of communities dynamics was made with Qiime. Regarding CO2 emissions, the values observed for AB7, RB7 and RBC7 were higher than the other treatments. For N2O the samples AB, ABC7 and RBC7 showed the higher rates. The CH4 gas obtained a homogeneous result for all samples, seeing no significant difference. The bacterial community dynamics showed that treatments: Bertioga, Avicennia schaueriana and decomposition time 60 days, presented a higher clustering within their samples, according to the standard of similarity observed in them

Disentangling the influence of earthworms in sugarcane rhizosphere.

For the last 150 years many studies have shown the importance of earthworms for plant growth, but the exact mechanisms involved in the process are still poorly understood. Many important functions required for plant growth can be performed by soil microbes in the rhizosphere. To investigate earthworm influence on the rhizosphere microbial community, we performed a macrocosm experiment with and without Pontoscolex corethrurus (EW+ and EW?, respectively) and followed various soil and rhizosphere processes for 217 days with sugarcane. In EW+ treatments, N2O concentrations belowground (15 cm depth) and relative abundances of nitrous oxide genes (nosZ) were higher in bulk soil and rhizosphere, suggesting that soil microbes were able to consume earthworm-induced N2O. Shotgun sequencing (total DNA) revealed that around 70 microbial functions in bulk soil and rhizosphere differed between EW+ and EW? treatments. Overall, genes indicative of biosynthetic pathways and cell proliferation processes were enriched in EW+ treatments, suggesting a positive influence of worms. In EW+ rhizosphere, functions associated with plant-microbe symbiosis were enriched relative to EW? rhizosphere. Ecological networks inferred from the datasets revealed decreased niche diversification and increased keystone functions as an earthworm-derived effect. Plant biomass was improved in EW+ and worm population proliferated

Gridded and direct Epoch of Reionisation bispectrum estimates using the Murchison Widefield Array

We apply two methods to estimate the 21~cm bispectrum from data taken within the Epoch of Reionisation (EoR) project of the Murchison Widefield Array (MWA). Using data acquired with the Phase II compact array allows a direct bispectrum estimate to be undertaken on the multiple redundantly-spaced triangles of antenna tiles, as well as an estimate based on data gridded to the $uv$-plane. The direct and gridded bispectrum estimators are applied to 21 hours of high-band (167--197~MHz; $z$=6.2--7.5) data from the 2016 and 2017 observing seasons. Analytic predictions for the bispectrum bias and variance for point source foregrounds are derived. We compare the output of these approaches, the foreground contribution to the signal, and future prospects for measuring the bispectra with redundant and non-redundant arrays. We find that some triangle configurations yield bispectrum estimates that are consistent with the expected noise level after 10 hours, while equilateral configurations are strongly foreground-dominated. Careful choice of triangle configurations may be made to reduce foreground bias that hinders power spectrum estimators, and the 21~cm bispectrum may be accessible in less time than the 21~cm power spectrum for some wave modes, with detections in hundreds of hours.Comment: 19 pages, 10 figures, accepted for publication in PAS

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

De novo mutations in SMCHD1 cause Bosma arhinia microphthalmia syndrome and abrogate nasal development

Bosma arhinia microphthalmia syndrome (BAMS) is an extremely rare and striking condition characterized by complete absence of the nose with or without ocular defects. We report here that missense mutations in the epigenetic regulator SMCHD1 mapping to the extended ATPase domain of the encoded protein cause BAMS in all 14 cases studied. All mutations were de novo where parental DNA was available. Biochemical tests and in vivo assays in Xenopus laevis embryos suggest that these mutations may behave as gain-of-function alleles. This finding is in contrast to the loss-of-function mutations in SMCHD1 that have been associated with facioscapulohumeral muscular dystrophy (FSHD) type 2. Our results establish SMCHD1 as a key player in nasal development and provide biochemical insight into its enzymatic function that may be exploited for development of therapeutics for FSHD

Constraining the 21 cm brightness temperature of the IGM at z = 6.6 around LAEs with the murchison widefield array

The locations of Ly α-emitting galaxies (LAEs) at the end of the Epoch of Reionization (EoR) are expected to correlate with regions of ionized hydrogen, traced by the redshifted 21 cm hyperfine line. Mapping the neutral hydrogen around regions with detected and localized LAEs offers an avenue to constrain the brightness temperature of the Universe within the EoR by providing an expectation for the spatial distribution of the gas, thereby providing prior information unavailable to power spectrum measurements. We use a test set of 12 h of observations from the Murchison Widefield Array (MWA) in extended array configuration, to constrain the neutral hydrogen signature of 58 LAEs, detected with the Subaru Hypersuprime Cam in the Silverrush survey, centred on z = 6.58. We assume that detectable emitters reside in the centre of ionized H II bubbles during the end of reionization, and predict the redshifted neutral hydrogen signal corresponding to the remaining neutral regions using a set of different ionized bubble radii. A pre-whitening matched filter detector is introduced to assess detectability. We demonstrate the ability to detect, or place limits upon, the amplitude of brightness temperature fluctuations, and the characteristic H II bubble size. With our limited data, we constrain the brightness temperature of neutral hydrogen to ΔTB B = 15 ± 2h-1 cMpc

Robust statistics towards detection of the 21 cm signal from the Epoch of Reionization

© 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. We explore methods for robust estimation of the 21 cm signal from the Epoch of Reionization (EoR). A Kernel Density Estimator (KDE) is introduced for measuring the spatial temperature fluctuation power spectrum from the EoR. The KDE estimates the underlying probability distribution function of fluctuations as a function of spatial scale, and contains different systematic biases and errors to the typical approach to estimating the fluctuation power spectrum. Extraction of histograms of visibilities allows moments analysis to be used to discriminate foregrounds from 21 cm signal and thermal noise. We use the information available in the histograms, along with the statistical dis-similarity of foregrounds from two independent observing fields, to robustly separate foregrounds from cosmological signal, while making no assumptions about the Gaussianity of the signal. Using two independent observing fields to robustly discriminate signal from foregrounds is crucial for the analysis presented in this paper. We apply the techniques to 13 h of Murchison Widefield Array EoR data over two observing fields. We compare the output to that obtained with a comparative power spectrum estimation method, and demonstrate the reduced foreground contamination using this approach. Using the second moment obtained directly from the KDE distribution functions yields a factor of 2-3 improvement in power for k < 0.3 h Mpc-1 compared with a matched delay space power estimator, while weighting data by additional statistics does not offer significant improvement beyond that available for thermal noise-only weights