Using baseline-dependent window functions for data compression and field-of-interest shaping in radio interferometry

In radio interferometry, observed visibilities are intrinsically sampled at some interval in time and frequency. Modern interferometers are capable of producing data at very high time and frequency resolution; practical limits on storage and computation costs require that some form of data compression be imposed. The traditional form of compression is a simple averaging of the visibilities over coarser time and frequency bins. This has an undesired side effect: the resulting averaged visibilities "decorrelate", and do so differently depending on the baseline length and averaging interval. This translates into a non-trivial signature in the image domain known as "smearing", which manifests itself as an attenuation in amplitude towards off-centre sources. With the increasing fields of view and/or longer baselines employed in modern and future instruments, the trade-off between data rate and smearing becomes increasingly unfavourable. In this work we investigate alternative approaches to low-loss data compression. We show that averaging of the visibility data can be treated as a form of convolution by a boxcar-like window function, and that by employing alternative baseline-dependent window functions a more optimal interferometer smearing response may be induced. In particular, we show improved amplitude response over a chosen field of interest, and better attenuation of sources outside the field of interest. The main cost of this technique is a reduction in nominal sensitivity; we investigate the smearing vs. sensitivity trade-off, and show that in certain regimes a favourable compromise can be achieved. We show the application of this technique to simulated data from the Karl G. Jansky Very Large Array (VLA) and the European Very-long-baseline interferometry Network (EVN)

Maize grain yield response to changes in acid soil characteristics with yearly leguminous crop rotation, fallow, slash, burn and liming practices

Open Access JournalAn experiment was conducted for 4 years to assess the effectiveness of fallow, slash and burn farming systems on maize grain yield and soil chemical characteristics. It was also meant to measure the response to yearly rotation of maize and leguminous crops (cowpea and mucuna), as options for managing the acidity of the soil of the study site. The maize tolerant cultivar (cvr) out yielded the sensitive cvr and the farmers’ variety by 43% and 16% respectively. On the maize/grain legume rotation plots, the tolerant and sensitive cvr yielded 5% and 7% respectively more than their corresponding yields on plots with fallow, slash and burn rotation. Maize/grain legume rotation demonstrated one of the least soil acidifications, exhibiting the least increase in exchangeable Al (23%), H (24%), and Al saturation (5%) resulting in improved soil fertility through increase in available Ca (2%), Mg (85%), P (75%), and CEC (14%). The fallow, slash and burn rotation, associated with the tolerant cvr showed similar grain yield with grain legume rotation, but contributed more to soil acidification. Maize/leafy legume rotation gave a similar yield to the above mentioned practices. The yearly application of 250 kg ha-1 of dolomitic lime for four consecutive years did not result in significant changes in soil characteristics and grain yield especially for the Al tolerant cvr. However, application of 2250 kg ha-1 of lime neutralized the Al toxicity, regardless of the rotation scheme. The study concluded that the four years maize cultivation through fallow/ slash and burn rotation extensively used in the humid forest zone is not the best option on acid soil

Faceting for direction-dependent spectral deconvolution

Reproduced with permission from Astronomy & Astrophysics, © 2018 ESO. Content in the UH Research Archive is made available for personal research, educational, and non-commercial purposes only. Unless otherwise stated, all content is protected by copyright, and in the absence of an open license, permissions for further re-use should be sought from the publisher, the author, or other copyright holder.The new generation of radio interferometers is characterized by high sensitivity, wide fields of view and large fractional bandwidth. To synthesize the deepest images enabled by the high dynamic range of these instruments requires us to take into account the direction-dependent Jones matrices, while estimating the spectral properties of the sky in the imaging and deconvolution algorithms. In this paper we discuss and implement a wideband wide-field spectral deconvolution framework (ddfacet) based on image plane faceting, that takes into account generic direction-dependent effects. Specifically, we present a wide-field co-planar faceting scheme, and discuss the various effects that need to be taken into account to solve for the deconvolution problem (image plane normalization, position-dependent Point Spread Function, etc). We discuss two wideband spectral deconvolution algorithms based on hybrid matching pursuit and sub-space optimisation respectively. A few interesting technical features incorporated in our imager are discussed, including baseline dependent averaging, which has the effect of improving computing efficiency. The version of ddfacet presented here can account for any externally defined Jones matrices and/or beam patterns.Peer reviewe

Hydrodynamical backflow in X-shaped radio galaxy PKS 2014− 55:

We present MeerKAT 1.28 GHz total-intensity, polarization, and spectral-index images covering the giant (projected length l ≈ 1.57 Mpc) X-shaped radio source PKS 2014−55 with an unprecedented combination of brightness sensitivity and angular resolution. They show the clear ‘double boomerang’ morphology of hydrodynamical backflows from the straight main jets deflected by the large and oblique hot-gas halo of the host galaxy PGC 064440

The extended H i halo of NGC 4945 as seen by MeerKAT

The State Agency for Research of the Spanish Ministry of Science, Innovation and Universities through the ‘Center of Excellence Severo Ochoa’ awarded to the Instituto de Astrofísica de Andalucía; the Economic Transformation, Industry, Knowledge and Universities Council of the Regional Government of Andalusia and the European Regional Development Fund from the European Union; the South African Radio Astronomy Observatory (SARAO); BMBF Verbundforschung; DFG Sonderforschungsbereich and the European Research Council (ERC).http://mnras.oxfordjournals.orghj2022Physic

The extended H I halo of NGC 4945 as seen by MeerKAT

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Observations of the neutral atomic hydrogen (H I) in the nuclear starburst galaxy NGC 4945 with MeerKAT are presented. We find a large amount of halo gas, previously missed by H I observations, accounting for 6.8 per cent of the total H I mass. This is most likely gas blown into the halo by star formation. Our maps go down to a 3σ column density level of 5 × 1018 cm−2. We model the H I distribution using tilted-ring fitting techniques and find a warp on the galaxy’s approaching and receding sides. The H I in the northern side of the galaxy appears to be suppressed. This may be the result of ionization by the starburst activity in the galaxy, as suggested by a previous study. The origin of the warp is unclear but could be due to past interactions or ram pressure stripping. Broad, asymmetric H I absorption lines extending throughout the H I emission velocity channels are present towards the nuclear region of NGC 4945. Such broad lines suggest the existence of a nuclear ring moving at a high circular velocity. This is supported by the clear rotation patterns in the H I absorption velocity field. The asymmetry of the absorption spectra can be caused by outflows or inflows of gas in the nuclear region of NGC 4945. The continuum map shows small extensions on both sides of the galaxy’s major axis that might be signs of outflows resulting from the starburst activity. © The Author(s) 2022. Published by Oxford University Press on behalf of Royal Astronomical Society.RI acknowledges financial support from grant RTI2018-096228-B-C31 (MCIU/AEI/FEDER,UE) and from the State Agency for Research of the Spanish Ministry of Science, Innovation and Universities through the ‘Center of Excellence Severo Ochoa’ awarded to the Instituto de Astrofísica de Andalucía (SEV-2017-0709), from the grant IAA4SKA (Ref. R18-RT-3082) from the Economic Transformation, Industry, Knowledge and Universities Council of the Regional Government of Andalusia and the European Regional Development Fund from the European Union. The MeerKAT telescope is operated by the South African Radio Astronomy Observatory, which is a facility of the National Research Foundation, an agency of the Department of Science and Innovation. This work is based upon research supported by the South African Research Chairs Initiative of the Department of Science and Technology and National Research Foundation. The financial assistance of the South African Radio Astronomy Observatory (SARAO) towards this research is hereby acknowledged (www.sarao.ac.za). At Ruhr University Bochum, this research is supported by BMBF Verbundforschung grant 05A20PC4 and by DFG Sonderforschungsbereich SFB1491. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme grant agreement no. 882793, project name MeerGas. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no.679627; project name FORNAX).Peer reviewe

Soybean, cowpea, groundnut, and pigeonpea response to soils, rainfall, and cropping season in the forest margins of Cameroon

Yields of groundnut, the traditional grain legume grown in central and southern Cameroon and in much of the humid zone of Central Africa, are generally low. Other food legumes may provide alternatives to groundnut. On-farm experiments examined the relative yields of up to 15 pigeonpea, 10 groundnut, 7 soybean, and 4 cowpea varieties over three growing seasons in four to six rural communities. Soil analytical values and rainfall data from all seasons were used as covariates in the analysis of variance. In the first two trials, variety-within-species interactions were significant (P < 0.0001 and 0.04). Groundnut var. JL-24 yielded 60% more than local groundnuts in the first season of 2000, while soybean var. TGx1838-5E, local cowpea var. `Mefak' and pigeonpea var. ICEAP 00436 outyielded several other varieties of their respective species. Comparing these selected varieties over three seasons, significant species × community and species × season effects (P < 0.0001) were observed. Covariate analysis showed that soybean yields increased with increasing soil Mg saturation and P levels. Groundnut yielded more in the first season of 2000 compared to the second seasons of 1999 and 2000 (average yields of 927 kg ha−1 vs. 422 and 522 kg ha−1, respectively). Improved yields were related to soil exchangeable Ca levels greater than 5 cmol(+) kg−1 in both second seasons, but not during the first season. Cowpea yields were superior in both second seasons. Pigeonpea yields were unrelated to soil factors, showing its wide adaptability to soil conditions. Pigeonpea, which matured in February during the dry season, was severely affected by the early cessation of rains in 2000. In 1999 yields averaged 820 kg ha−1 across communities. The results show that good food legume alternatives to groundnut exist, particularly for second season production. Species can be targeted to communities based on soil properties and season of production

Fast algorithms to approximate the position-dependent point spread function responses in radio interferometric wide-field imaging

International audienc

Anomaly Detection in Power Generation Plants Using Machine Learning and Neural Networks

The availability of constant electricity supply is a crucial factor to the performance of any industry. Nevertheless, the unstable supply of electricity in Cameroon has led to countless periods of electricity load shedding, hence, making the management of the telecom industry to fall on backup power supply such as diesel generators. The fuel consumption of these generators remain a challenge due to some perturbations in the mechanical fuel level gauges and lack of maintenance at the base stations resulting to fuel pilferage. In order to overcome these effects, we detect anomalies in the recorded data by learning the patterns of the fuel consumption using four classification techniques namely; support vector machines (SVM), K-Nearest Neighbors (KNN), Logistic Regression (LR), and MultiLayer Perceptron (MLP) and then compare the performance of these classification techniques on a test data. In this paper, we show the use of supervised machine learning classification based techniques in detecting anomalies associated with the fuel consumed dataset from TeleInfra base stations using the generator as a source of power. Here, we perform the normal feature engineering, selection, and then fit the model classifiers to obtain results and finally, test the performance of these classifiers on a test data. The results of this study show that MLP has the best performance in the evaluation measurement recording a score of 96% in the K-fold cross validation test. In addition, because of class imbalance in the observation, we use the precision-recall curve instead of the ROC curve and registered the probability of the Area Under Curve (AUC) as 0:98