Response of groundnut (Arachis hypogaea) cultivars to integrated nutrient management on productivity, profitability and nutrient uptake in NEH Region

A field experiment was conducted at Nagaland during 2009 and 2010 to study the response of groundnut (Arachis hypogaea L.) cultivars to integrated nutrient management on productivity, profitability and nutrient uptake in NEH Region on a sandy loam soil. Among the cultivars, FeSEG 10 recorded significantly higher growth, yield attributes and pod yield as compared to JL 24 and FeSEG 8. Nutrients uptake (N, P and K) and nutrients use efficiency was significantly higher under ICGS 76 followed by FeSEG 10 and FeSEG 8. The highest net returns, B: C ratio and crop profitability were recorded with FeSEG 10 followed by ICGS 76. The results showed significant increase in all yield attributes, yield, nutrient uptake and economics due to the application of 75% N through inorganic fertilizers + 25% N through FYM followed by 100% N through inorganic fertilizers

Macrophage entry mediated by HIV Envs from brain and lymphoid tissues is determined by the capacity to use low CD4 levels and overall efficiency of fusion

AbstractHIV infects macrophages and microglia in the central nervous system (CNS), which express lower levels of CD4 than CD4+ T cells in peripheral blood. To investigate mechanisms of HIV neurotropism, full-length env genes were cloned from autopsy brain and lymphoid tissues from 4 AIDS patients with HIV-associated dementia (HAD). Characterization of 55 functional Env clones demonstrated that Envs with reduced dependence on CD4 for fusion and viral entry are more frequent in brain compared to lymphoid tissue. Envs that mediated efficient entry into macrophages were frequent in brain but were also present in lymphoid tissue. For most Envs, entry into macrophages correlated with overall fusion activity at all levels of CD4 and CCR5. gp160 nucleotide sequences were compartmentalized in brain versus lymphoid tissue within each patient. Proline at position 308 in the V3 loop of gp120 was associated with brain compartmentalization in 3 patients, but mutagenesis studies suggested that P308 alone does not contribute to reduced CD4 dependence or macrophage-tropism. These results suggest that HIV adaptation to replicate in the CNS selects for Envs with reduced CD4 dependence and increased fusion activity. Macrophage-tropic Envs are frequent in brain but are also present in lymphoid tissues of AIDS patients with HAD, and entry into macrophages in the CNS and other tissues is dependent on the ability to use low receptor levels and overall efficiency of fusion

Southern African Large Telescope Spectroscopy of BL Lacs for the CTA project

In the last two decades, very-high-energy gamma-ray astronomy has reached maturity: over 200 sources have been detected, both Galactic and extragalactic, by ground-based experiments. At present, Active Galactic Nuclei (AGN) make up about 40% of the more than 200 sources detected at very high energies with ground-based telescopes, the majority of which are blazars, i.e. their jets are closely aligned with the line of sight to Earth and three quarters of which are classified as high-frequency peaked BL Lac objects. One challenge to studies of the cosmological evolution of BL Lacs is the difficulty of obtaining redshifts from their nearly featureless, continuum-dominated spectra. It is expected that a significant fraction of the AGN to be detected with the future Cherenkov Telescope Array (CTA) observatory will have no spectroscopic redshifts, compromising the reliability of BL Lac population studies, particularly of their cosmic evolution. We started an effort in 2019 to measure the redshifts of a large fraction of the AGN that are likely to be detected with CTA, using the Southern African Large Telescope (SALT). In this contribution, we present two results from an on-going SALT program focused on the determination of BL Lac object redshifts that will be relevant for the CTA observatory

Southern African Large Telescope Spectroscopy of BL Lacs for the CTA project

In the last two decades, very-high-energy gamma-ray astronomy has reached maturity: over 200 sources have been detected, both Galactic and extragalactic, by ground-based experiments. At present, Active Galactic Nuclei (AGN) make up about 40% of the more than 200 sources detected at very high energies with ground-based telescopes, the majority of which are blazars, i.e. their jets are closely aligned with the line of sight to Earth and three quarters of which are classified as high-frequency peaked BL Lac objects. One challenge to studies of the cosmological evolution of BL Lacs is the difficulty of obtaining redshifts from their nearly featureless, continuum-dominated spectra. It is expected that a significant fraction of the AGN to be detected with the future Cherenkov Telescope Array (CTA) observatory will have no spectroscopic redshifts, compromising the reliability of BL Lac population studies, particularly of their cosmic evolution. We started an effort in 2019 to measure the redshifts of a large fraction of the AGN that are likely to be detected with CTA, using the Southern African Large Telescope (SALT). In this contribution, we present two results from an on-going SALT program focused on the determination of BL Lac object redshifts that will be relevant for the CTA observatory

Reconstruction of stereoscopic CTA events using deep learning with CTLearn

The Cherenkov Telescope Array (CTA), conceived as an array of tens of imaging atmospheric Cherenkov telescopes (IACTs), is an international project for a next-generation ground-based gamma-ray observatory, aiming to improve on the sensitivity of current-generation instruments a factor of five to ten and provide energy coverage from 20 GeV to more than 300 TeV. Arrays of IACTs probe the very-high-energy gamma-ray sky. Their working principle consists of the simultaneous observation of air showers initiated by the interaction of very-high-energy gamma rays and cosmic rays with the atmosphere. Cherenkov photons induced by a given shower are focused onto the camera plane of the telescopes in the array, producing a multi-stereoscopic record of the event. This image contains the longitudinal development of the air shower, together with its spatial, temporal, and calorimetric information. The properties of the originating very-high-energy particle (type, energy, and incoming direction) can be inferred from those images by reconstructing the full event using machine learning techniques. In this contribution, we present a purely deep-learning driven, full-event reconstruction of simulated, stereoscopic IACT events using CTLearn. CTLearn is a package that includes modules for loading and manipulating IACT data and for running deep learning models, using pixel-wise camera data as input

Prototype Open Event Reconstruction Pipeline for the Cherenkov Telescope Array

The Cherenkov Telescope Array (CTA) is the next-generation gamma-ray observatory currently under construction. It will improve over the current generation of imaging atmospheric Cherenkov telescopes (IACTs) by a factor of five to ten in sensitivity and it will be able to observe the whole sky from a combination of two sites: a northern site in La Palma, Spain, and a southern one in Paranal, Chile. CTA will also be the first open gamma-ray observatory. Accordingly, the data analysis pipeline is developed as open-source software. The event reconstruction pipeline accepts raw data of the telescopes and processes it to produce suitable input for the higher-level science tools. Its primary tasks include reconstructing the physical properties of each recorded shower and providing the corresponding instrument response functions. ctapipe is a framework providing algorithms and tools to facilitate raw data calibration, image extraction, image parameterization and event reconstruction. Its main focus is currently the analysis of simulated data but it has also been successfully applied for the analysis of data obtained with the first CTA prototype telescopes, such as the Large-Sized Telescope 1 (LST-1). pyirf is a library to calculate IACT instrument response functions, needed to obtain physics results like spectra and light curves, from the reconstructed event lists. Building on these two, protopipe is a prototype for the event reconstruction pipeline for CTA. Recent developments in these software packages will be presented