Radio Recombination Lines at Decametre Wavelengths: Prospects for the Future

This paper considers the suitability of a number of emerging and future instruments for the study of radio recombination lines (RRLs) at frequencies below 200 MHz. These lines arise only in low-density regions of the ionized interstellar medium, and they may represent a frequency-dependent foreground for next-generation experiments trying to detect H I signals from the Epoch of Reionization and Dark Ages ("21-cm cosmology"). We summarize existing decametre-wavelength observations of RRLs, which have detected only carbon RRLs. We then show that, for an interferometric array, the primary instrumental factor limiting detection and study of the RRLs is the areal filling factor of the array. We consider the Long Wavelength Array (LWA-1), the LOw Frequency ARray (LOFAR), the low-frequency component of the Square Kilometre Array (SKA-lo), and a future Lunar Radio Array (LRA), all of which will operate at decametre wavelengths. These arrays offer digital signal processing, which should produce more stable and better defined spectral bandpasses; larger frequency tuning ranges; and better angular resolution than that of the previous generation of instruments that have been used in the past for RRL observations. Detecting Galactic carbon RRLs, with optical depths at the level of 10^-3, appears feasible for all of these arrays, with integration times of no more than 100 hr. The SKA-lo and LRA, and the LWA-1 and LOFAR at the lowest frequencies, should have a high enough filling factor to detect lines with much lower optical depths, of order 10^-4 in a few hundred hours. The amount of RRL-hosting gas present in the Galaxy at the high Galactic latitudes likely to be targeted in 21-cm cosmology studies is currently unknown. If present, however, the spectral fluctuations from RRLs could be comparable to or exceed the anticipated H I signals.Comment: 9 pages; Astron. & Astrophys., in pres

The Radio Sky at Meter Wavelengths: m-Mode Analysis Imaging with the Owens Valley Long Wavelength Array

A host of new low-frequency radio telescopes seek to measure the 21-cm transition of neutral hydrogen from the early universe. These telescopes have the potential to directly probe star and galaxy formation at redshifts $20 \gtrsim z \gtrsim 7$, but are limited by the dynamic range they can achieve against foreground sources of low-frequency radio emission. Consequently, there is a growing demand for modern, high-fidelity maps of the sky at frequencies below 200 MHz for use in foreground modeling and removal. We describe a new widefield imaging technique for drift-scanning interferometers, Tikhonov-regularized $m$-mode analysis imaging. This technique constructs images of the entire sky in a single synthesis imaging step with exact treatment of widefield effects. We describe how the CLEAN algorithm can be adapted to deconvolve maps generated by $m$-mode analysis imaging. We demonstrate Tikhonov-regularized $m$-mode analysis imaging using the Owens Valley Long Wavelength Array (OVRO-LWA) by generating 8 new maps of the sky north of $\delta=-30^\circ$ with 15 arcmin angular resolution, at frequencies evenly spaced between 36.528 MHz and 73.152 MHz, and $\sim$800 mJy/beam thermal noise. These maps are a 10-fold improvement in angular resolution over existing full-sky maps at comparable frequencies, which have angular resolutions $\ge 2^\circ$. Each map is constructed exclusively from interferometric observations and does not represent the globally averaged sky brightness. Future improvements will incorporate total power radiometry, improved thermal noise, and improved angular resolution -- due to the planned expansion of the OVRO-LWA to 2.6 km baselines. These maps serve as a first step on the path to the use of more sophisticated foreground filters in 21-cm cosmology incorporating the measured angular and frequency structure of all foreground contaminants.Comment: 27 pages, 18 figure

Machine Learning with Abstention for Automated Liver Disease Diagnosis

This paper presents a novel approach for detection of liver abnormalities in an automated manner using ultrasound images. For this purpose, we have implemented a machine learning model that can not only generate labels (normal and abnormal) for a given ultrasound image but it can also detect when its prediction is likely to be incorrect. The proposed model abstains from generating the label of a test example if it is not confident about its prediction. Such behavior is commonly practiced by medical doctors who, when given insufficient information or a difficult case, can chose to carry out further clinical or diagnostic tests before generating a diagnosis. However, existing machine learning models are designed in a way to always generate a label for a given example even when the confidence of their prediction is low. We have proposed a novel stochastic gradient based solver for the learning with abstention paradigm and use it to make a practical, state of the art method for liver disease classification. The proposed method has been benchmarked on a data set of approximately 100 patients from MINAR, Multan, Pakistan and our results show that the proposed scheme offers state of the art classification performance.Comment: Preprint version before submission for publication. complete version published in proc. 15th International Conference on Frontiers of Information Technology (FIT 2017), December 18-20, 2017, Islamabad, Pakistan. http://ieeexplore.ieee.org/document/8261064

Efeito da pré-molhagem do agregado nas propriedades das argamassas com agregado reciclado deconcreto e agregado leve

This paper examines the suitability of partially replacing natural aggregate, sand, (NA) with recycled concrete aggregate (RCA) or lightweight aggregate (LWA) in mortars, under the hypothesis that pre-wetting aggregates would produce improvement in mortar properties. Fresh mortar properties such as density, entrained air content, consistency and heat of hydration, as well as hardened mortar properties such as dry density, compressive and flexural strength, and dimensional instability at 0% and 100% saturation were determined. The results show that mortars made with natural aggregate (75%) and recycled concrete aggregate (25%) have similar properties to mortars made with only natural aggregate (100%) and that pre-wetting the aggregates does not influence the properties of mortars significantly. Therefore, partial replacement with recycled concrete aggregate is a viable alternative for producing mortar.Peer ReviewedPostprint (published version

Broadside Dual-channel Orthogonal-Polarization Radiation using a Double-Asymmetric Periodic Leaky-Wave Antenna

The paper demonstrates that double unit-cell asymmetry in periodic leaky-wave antennas (P-LWAs), i.e. asymmetry with respect to both the longitudinal and transversal axes of the structure -- or longitudinal asymmetry (LA) and transversal asymmetry (TA) -- allows for the simultaneous broadside radiation of two orthogonal modes excited at the two ports of the antenna. This means that the antenna may simultaneously support two orthogonal channels, which represents an interesting polarization diversity characteristics for wireless communications. The double asymmetric (DA) unit cell combines a circularly polarized LA unit cell and a coupled mode TA unit cell, where the former provides equal radiation in the series and shunt modes while the latter separates these two modes in terms of their excitation ports. It is also shown that the degree of TA in the DA unit cell controls the cross-polarization discrimination level. The DA P-LWA concept is illustrated by two examples, a series-fed line-connected patch (SF-LCP) P-LWA and a series-fed capacitively-coupled patch (SF-CCP) P-LWA, via full-wave simulation and also experiment for the SF-LCP P-LWA case