The effect of atmospheric acid processing on the global deposition of bioavailable phosphorus from dust

The role of dust as a source of bioavailable phosphorus (Bio-P) is quantified using a new parameterization for apatite dissolution in combination with global soil data maps and a global aerosol transport model. Mineral dust provides 31.2 Gg-P yr-1 of Bio-P to the oceans, with 14.3 Gg-P yr-1 from labile P present in the dust, and an aditional 16.9 Gg-P yr from acid dissolution of apatite in the atmosphere, representing an increase of 120%. The North Atlantic, north west Pacific, and Mediterranean Sea are identified as important sites of Bio-P deposition from mineral dust. The acid dissolution process increases the fraction of total-P that is bioavailable from ~10% globally from the labile pool to 23% in the Atlantic Ocean, 45% in the Pacific Ocean, and 21% in the Indian Ocean, with an ocean global mean value of 22%. Strong seasonal variations, especially in the North Pacific, northwest Atlantic, and Indian Ocean, are driven by large-scale meteorology and pollution sources from industrial and biomass-burning regions. Globally constant values of total-P content and bioavailable fraction used previously do not capture the simulated variability. We find particular sensitivity to the representation of particle-to-particle variability of apatite, which supplies Bio-P through acid-dissolution, and calcium carbonate, which helps to buffer the dissolution process. A modest 10% external mixing results in an increase of Bio-P deposition by 18%. The total Bio-P calculated here (31.2 Gg-P yr-1) represents a minimum compared to previous estimates due to the relatively low total-P in the global soil map used

Federated Ensemble-Directed Offline Reinforcement Learning

We consider the problem of federated offline reinforcement learning (RL), a scenario under which distributed learning agents must collaboratively learn a high-quality control policy only using small pre-collected datasets generated according to different unknown behavior policies. Naively combining a standard offline RL approach with a standard federated learning approach to solve this problem can lead to poorly performing policies. In response, we develop the Federated Ensemble-Directed Offline Reinforcement Learning Algorithm (FEDORA), which distills the collective wisdom of the clients using an ensemble learning approach. We develop the FEDORA codebase to utilize distributed compute resources on a federated learning platform. We show that FEDORA significantly outperforms other approaches, including offline RL over the combined data pool, in various complex continuous control environments and real world datasets. Finally, we demonstrate the performance of FEDORA in the real-world on a mobile robot

Determinants in HIV-2 Env and tetherin required for functional interaction

BackgroundThe interferon-inducible factor BST-2/tetherin blocks the release of nascent virions from the surface of infected cells for certain enveloped virus families. The primate lentiviruses have evolved several counteracting mechanisms which, in the case of HIV-2, is a function of its Env protein. We sought to further understand the features of the Env protein and tetherin that are important for this interaction, and to evaluate the selective pressure on HIV-2 to maintain such an activity.ResultsBy examining Env mutants with changes in the ectodomain of the protein (virus ROD14) or the cytoplasmic tail (substitution Y707A) that render the proteins unable to counteract tetherin, we determined that an interaction between Env and tetherin is important for this activity. Furthermore, this Env-tetherin interaction required an alanine face in the tetherin ectodomain, although insertion of this domain into an artificial tetherin-like protein was not sufficient to confer sensitivity to the HIV-2 Env. The replication of virus carrying the ROD14 substitutions was significantly slower than the matched wild-type virus, but it acquired second-site mutations during passaging in the cytoplasmic tail of Env which restored the ability of the protein to both bind to and counteract tetherin.ConclusionsThese results shed light on the interaction between HIV-2 and tetherin, suggesting a physical interaction that maps to the ectodomains of both proteins and indicating a strong selection pressure to maintain an anti-tetherin activity in the HIV-2 Env

Winter Burst of Pristine Kashmir Valley Air

Abstract The Kashmir Valley in India is one of the world’s major tourist attractions and perceived as a pristine environment. Long term monitoring of fine particulate matter, PM2.5 (particles having aerodynamic diameter of 2.5 μm or less), responsible for deteriorating human health, has been done for the period 2013–14. Results indicate that air quality of the capital city Srinagar (34.1°N, 74.8°E) deteriorates significantly in particular during winter, where level of PM2.5 touches a peak value of 348 μg/m³ against the Indian permissible limit of 60 μg/m³. The emissions due to domestic coal usage are found to be 1246.4 tons/yr, which accounts for 84% of the total annual emissions. The on-line high-resolution weather research and forecasting model with embedded chemistry module (WRF-Chem), which accounts for emission inventory developed in this region reproduced the seasonal variability reasonably well. Cold temperatures with dry conditions along with elevated level of biofuel emissions from domestic sector are found to be the major processes responsible for winter period particulate pollution. The back trajectories show that westerly winds originating from Afghanistan and surrounding areas also contribute to the high PM2.5 levels