Deccan volcanism and K-T boundary signatures

The Deccan Traps in the Indian subcontinent represent one of the most extensive flood basalt provinces in the world. These basalts occur mainly as flat-lying, subaerially erupted tholeiitic lava flows, some of which are traceable for distances of more than 100 km. Offshore drilling and geophysical surveys indicate that a part of the Deccan subsided or was downfaulted to the west beneath the Arabian Sea. The presence of 1 to 5 m thick intertrappean sediments deposited by lakes and rivers indicates periods of quiescence between eruptions. The occurrence of numerous red bole beds among the flows suggests intense weathering of flow tops between eruptive intervals. Although the causative relationship of the Cretaceous-Tertiary (K-T) biotic extinctions to Deccan volcanism is debatable, the fact that the main Deccan eruptions straddle the K-T event appears beyond doubt from the recent Ar-40/Ar-39 ages of various Deccan flows. This temporal relationship of the K-T event with Deccan volcanism makes the petrochemical signatures of the entire Deccan sequence (basalt flows, intercalated intertrappean sediments, infratrappean Lameta beds (with dinosaur fossils), and the bole beds) pertinent to studies of the K-T event. The results of ongoing study is presented

Investigating the generalizability of EEG-based Cognitive Load Estimation Across Visualizations

We examine if EEG-based cognitive load (CL) estimation is generalizable across the character, spatial pattern, bar graph and pie chart-based visualizations for the nback~task. CL is estimated via two recent approaches: (a) Deep convolutional neural network, and (b) Proximal support vector machines. Experiments reveal that CL estimation suffers across visualizations motivating the need for effective machine learning techniques to benchmark visual interface usability for a given analytic task

An EEG-Based Image Annotation System

The success of deep learning in computer vision has greatly increased the need for annotated image datasets. We propose an EEG (Electroencephalogram)-based image annotation system. While humans can recognize objects in 20–200 ms, the need to manually label images results in a low annotation throughput. Our system employs brain signals captured via a consumer EEG device to achieve an annotation rate of up to 10 images per second. We exploit the P300 event-related potential (ERP) signature to identify target images during a rapid serial visual presentation (RSVP) task. We further perform unsupervised outlier removal to achieve an F1-score of 0.88 on the test set. The proposed system does not depend on category-specific EEG signatures enabling the annotation of any new image category without any model pre-training

Role of ocean initial conditions to diminish dry bias in the seasonal prediction of Indian summer monsoon rainfall: A case study using climate forecast system

Coupled models tend to underestimate Indian summer monsoon (ISM) rainfall over most of the Indian subcontinent. Present study demonstrates that a part of dry bias is arising from the discrepancies in Oceanic Initial Conditions (OICs). Two hindcast experiments are carried out using Climate Forecast System (CFSv2) for summer monsoons of 2012-2014 in which two different OICs are utilized. With respect to first experiment (CTRL), second experiment (AcSAL) differs by two aspects: usage of high-resolution atmospheric forcing and assimilation of only ARGO observed temperature and salinity profiles for OICs. Assessment of OICs indicates that the quality of OICs is enhanced due to assimilation of actual salinity profiles. Analysis reveals that AcSAL experiment showed 10 reduction in the dry bias over the Indian land region during the ISM compared to CTRL. This improvement is consistently apparent in each month and is highest for June. The better representation of upper ocean thermal structure of tropical oceans at initial stage supports realistic upper ocean stability and mixing. Which in fact reduced the dominant cold bias over the ocean, feedback to air-sea interactions and land sea thermal contrast resulting better representation of monsoon circulation and moisture transport. This reduced bias of tropospheric moisture and temperature over the Indian land mass and also produced better tropospheric temperature gradient over land as well as ocean. These feedback processes reduced the dry bias in the ISM rainfall. Study concludes that initializing the coupled models with realistic OICs can reduce the underestimation of ISM rainfall prediction. © 2018. The Authors

Solar retinopathy: a new setting of red, green, and blue channels

PURPOSE: To introduce a new color imaging technique using improved settings of red, green, and blue channels for improved delineation of retinal damage in patients with solar retinopathy. METHODS: A retrospective case series of patients with poor vision secondary to solar retinopathy were analyzed. All patients underwent visual acuity, refraction, and dilated fundus examination. A spectral domain–optical coherence tomography of the macula and color fundus imaging using optimized red, green, and blue color setting was performed. Patients were reviewed over a 6-month period. The data were analyzed for statistical significance using an independent t test and a receiver operating characteristic curve. RESULTS: In total, 20 eyes of 10 patients were included between 2009 and 2017. The mean age was 24.9 ± 18.1 years. Best corrected visual acuity at first consultation was 0.78 ± 0.11 and after 6 months was 0.83 ± 0.09. Spectral domain–optical coherence tomography demonstrated retinal abnormalities at the myoid zone, ellipsoid zone, and the outer segment of photoreceptors. Receiver operating characteristic curve analysis showed an improving effect (area under the curve = 0.62; 95% confidence interval = 0.42–0.79). The color channels parameters, which improve visualization of the lesions were found to be 67-0.98-255 for the R-guided setting, 19-0.63-121 for the B-guided setting, and 7-1.00-129 for the G-guided setting. The ideal red, green, and blue setting was in 24-0.82-229. CONCLUSIONS: The use of a new setting of red, green, and blue channels could improve the diagnosis and monitoring of solar retinopathy, hence improving patient care

A simple method of estimating folic acid absorption (a modified faecal excretion method)

This article does not have an abstract

Mining Mini-Halos with MeerKAT I. Calibration and Imaging

Radio mini-halos are clouds of diffuse, low surface brightness synchrotron emission that surround the Brightest Cluster Galaxy (BCG) in massive cool-core galaxy clusters. In this paper, we use third generation calibration (3GC), also called direction-dependent (DD) calibration, and point source subtraction on MeerKAT extragalactic continuum data. We calibrate and image archival MeerKAT L-band observations of a sample of five galaxy clusters (ACO 1413, ACO 1795, ACO 3444, MACS J1115.8+0129, MACS J2140.2-2339). We use the CARACal pipeline for direction-independent (DI) calibration, DDFacet and killMS for 3GC, followed by visibility-plane point source subtraction to image the underlying mini-halo without bias from any embedded sources. Our 3GC process shows a drastic improvement in artefact removal, to the extent that the local noise around severely affected sources was halved and ultimately resulted in a 7\% improvement in global image noise. Thereafter, using these spectrally deconvolved Stokes I continuum images, we directly measure for four mini-halos the flux density, radio power, size and in-band integrated spectra. Further to that, we show the in-band spectral index maps of the mini-halo (with point sources). We present a new mini-halo detection hosted by MACS J2140.2-2339, having flux density $S_{\rm 1.28\,GHz} = 2.61 \pm 0.31$ mJy, average diameter 296 kpc and $\alpha^{\rm 1.5\,GHz}_{\rm 1\,GHz} = 1.21 \pm 0.36$. We also found a $\sim$100 kpc southern extension to the ACO 3444 mini-halo which was not detected in previous VLA L-band observations. Our description of MeerKAT wide-field, wide-band data reduction will be instructive for conducting further mini-halo science.Comment: 16 pages. 10 figure

Parameter estimation in spatially extended systems: The Karhunen-Loeve and Galerkin multiple shooting approach

Parameter estimation for spatiotemporal dynamics for coupled map lattices and continuous time domain systems is shown using a combination of multiple shooting, Karhunen-Loeve decomposition and Galerkin's projection methodologies. The resulting advantages in estimating parameters have been studied and discussed for chaotic and turbulent dynamics using small amounts of data from subsystems, availability of only scalar and noisy time series data, effects of space-time parameter variations, and in the presence of multiple time-scales.Comment: 11 pages, 5 figures, 4 Tables Corresponding Author - V. Ravi Kumar, e-mail address: [email protected]

Vitamin D deficiency contributes directly to the acute respiratory distress syndrome (ARDS)

Rationale: Vitamin D deficiency has been implicated as a pathogenic factor in sepsis and intensive therapy unit mortality but has not been assessed as a risk factor for acute respiratory distress syndrome (ARDS). Causality of these associations has never been demonstrated. Objectives: To determine if ARDS is associated with vitamin D deficiency in a clinical setting and to determine if vitamin D deficiency in experimental models of ARDS influences its severity. Methods: Human, murine and in vitro primary alveolar epithelial cell work were included in this study. Findings: Vitamin D deficiency (plasma 25(OH)D levels 600 genes. In a clinical setting, pharmacological repletion of vitamin D prior to oesophagectomy reduced the observed changes of in vivo measurements of alveolar capillary damage seen in deficient patients. Conclusions: Vitamin D deficiency is common in people who develop ARDS. This deficiency of vitamin D appears to contribute to the development of the condition, and approaches to correct vitamin D deficiency in patients at risk of ARDS should be developed