Distributing Coalition Value Calculations to Coalition Members

Within characteristic function games, agents have the option of joining one of many different coalitions, based on the utility value of each candidate coalition. However, determining this utility value can be computationally complex since the number of coalitions increases exponentially with the number of agents available. Various approaches have been proposed that mediate this problem by distributing the computational load so that each agent calculates only a subset of coalition values. However, current approaches are either highly inefficient due to redundant calculations, or make the benevolence assumption (i.e. are not suitable for adversarial environments). We introduce DCG, a novel algorithm that distributes the calculations of coalition utility values across a community of agents, such that: (i) no inter-agent communication is required; (ii) the coalition value calculations are (approximately) equally partitioned into shares, one for each agent; (iii) the utility value is calculated only once for each coalition, thus redundant calculations are eliminated; (iv) there is an equal number of operations for agents with equal sized shares; and (v) an agent is only allocated those coalitions in which it is a potential member. The DCG algorithm is pre- sented and illustrated by means of an example. We formally prove that our approach allocates all of the coalitions to the agents, and that each coalition is assigned once and only once

Variability in efficiency of particulate organic carbon export: A model study

The flux of organic carbon from the surface ocean to mesopelagic depths is a key component of the global carbon cycle and is ultimately derived from primary production (PP) by phytoplankton. Only a small fraction of organic carbon produced by PP is exported from the upper ocean, referred to as the export efficiency (herein e-ratio). Limited observations of the e-ratio are available and there is thus considerable interest in using remotely-sensed parameters such as sea surface temperature to extrapolate local estimates to global annual export flux. Currently, there are large discrepancies between export estimates derived in this way; one possible explanation is spatial or temporal sampling bias in the observations. Here we examine global patterns in the spatial and seasonal variability in e-ratio and the subsequent effect on export estimates using a high resolution global biogeochemical model. NEMO-MEDUSA represents export as separate slow and fast sinking detrital material whose remineralisation is respectively temperature dependent and a function of ballasting minerals. We find that both temperature and the fraction of export carried by slow sinking particles are factors in determining e-ratio, suggesting that current empirical algorithms for e-ratio that only consider temperature are overly simple. We quantify the temporal lag between PP and export, which is greatest in regions of strong variability in PP where seasonal decoupling can result in large e-ratio variability. Extrapolating global export estimates from instantaneous measurements of e-ratio is strongly affected by seasonal variability, and can result in errors in estimated export of up to ±60%

Particle flux in the oceans: Challenging the steady state assumption

Atmospheric carbon dioxide levels are strongly controlled by the depth at which the organic matter that sinks out of the surface ocean is remineralized. This depth is generally estimated from particle flux profiles measured using sediment traps. Inherent in this analysis is a steady state assumption; that export from the surface does not significantly change in the time it takes material to reach the deepest trap. However, recent observations suggest that a significant fraction of material in the mesopelagic zone sinks slowly enough to bring this into doubt. We use data from a study in the North Atlantic during July/August 2009 to challenge the steady state assumption. An increase in biogenic silica flux with depth was observed which we interpret, based on vertical profiles of diatom taxonomy, as representing the remnants of the spring diatom bloom sinking slowly (<40 m d-1). We were able to reproduce this behaviour using a simple model using satellite-derived export rates and literature-derived remineralization rates. We further provide a simple equation to estimate ‘additional’ (or ‘excess’) POC supply to the dark ocean during non-steady state conditions, which is not captured by traditional sediment trap deployments. In seasonal systems, mesopelagic net organic carbon supply could be wrong by as much as 25% when assuming steady state. We conclude that the steady state assumption leads to misinterpretation of particle flux profiles when input fluxes from the upper ocean vary on the order of weeks, such as in temperate and polar regions with strong seasonal cycles in export

What causes the inverse relationship between primary production and export efficiency in the Southern Ocean?

The ocean contributes to regulating atmospheric CO2 levels, partly via variability in the fraction of primary production (PP) which is exported out of the surface layer (i.e. the e-ratio). Southern Ocean studies have found that, contrary to global scale analyses, an inverse relationship exists between e-ratio and PP. This relationship remains unexplained, with potential hypotheses being i) large export of dissolved organic carbon (DOC) in high PP areas, ii) strong surface microbial recycling in high PP regions and/ or iii) grazing mediated export varies inversely with PP. We find that the export of DOC has a limited influence in setting the negative e-ratio/PP relationship. However, we observed that at sites with low PP and high e-ratios, zooplankton mediated export is large and surface microbial abundance low suggesting that both are important drivers of the magnitude of the e-ratio in the Southern Ocean

Preparation and Characterization of Cationic PLA-PEG Nanoparticles for Delivery of Plasmid DNA

The purpose of the present work was to formulate and evaluate cationic poly(lactic acid)-poly(ethylene glycol) (PLA-PEG) nanoparticles as novel non-viral gene delivery nano-device. Cationic PLA-PEG nanoparticles were prepared by nanoprecipitation method. The gene loaded nanoparticles were obtained by incubating the report gene pEGFP with cationic PLA-PEG nanoparticles. The physicochemical properties (e.g., morphology, particle size, surface charge, DNA binding efficiency) and biological properties (e.g., integrity of the released DNA, protection from nuclease degradation, plasma stability, in vitro cytotoxicity, and in vitro transfection ability in Hela cells) of the gene loaded PLA-PEG nanoparticles were evaluated, respectively. The obtained cationic PLA-PEG nanoparticles and gene loaded nanoparticles were both spherical in shape with average particle size of 89.7 and 128.9 nm, polydispersity index of 0.185 and 0.161, zeta potentials of +28.9 and +16.8 mV, respectively. The obtained cationic PLA-PEG nanoparticles with high binding efficiency (>95%) could protect the loaded DNA from the degradation by nuclease and plasma. The nanoparticles displayed sustained-release properties in vitro and the released DNA maintained its structural and functional integrity. It also showed lower cytotoxicity than Lipofectamine 2000 and could successfully transfect gene into Hela cells even in presence of serum. It could be concluded that the established gene loaded cationic PLA-PEG nanoparticles with excellent properties were promising non-viral nano-device, which had potential to make cancer gene therapy achievable

A Search for Technosignatures Around 31 Sun-like Stars with the Green Bank Telescope at 1.15-1.73 GHz

We conducted a search for technosignatures in April of 2018 and 2019 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. These observations focused on regions surrounding 31 Sun-like stars near the plane of the Galaxy. We present the results of our search for narrowband signals in this data set as well as improvements to our data processing pipeline. Specifically, we applied an improved candidate signal detection procedure that relies on the topographic prominence of the signal power, which nearly doubles the signal detection count of some previously analyzed data sets. We also improved the direction-of-origin filters that remove most radio frequency interference (RFI) to ensure that they uniquely link signals observed in separate scans. We performed a preliminary signal injection and recovery analysis to test the performance of our pipeline. We found that our pipeline recovers 93% of the injected signals over the usable frequency range of the receiver and 98% if we exclude regions with dense RFI. In this analysis, 99.73% of the recovered signals were correctly classified as technosignature candidates. Our improved data processing pipeline classified over 99.84% of the ~26 million signals detected in our data as RFI. Of the remaining candidates, 4539 were detected outside of known RFI frequency regions. The remaining candidates were visually inspected and verified to be of anthropogenic nature. Our search compares favorably to other recent searches in terms of end-to-end sensitivity, frequency drift rate coverage, and signal detection count per unit bandwidth per unit integration time.Comment: 20 pages, 8 figures, in press at the Astronomical Journal (submitted on Sept. 9, 2020; reviews received Nov. 6; re-submitted Nov. 6; accepted Nov. 17

Epidemiology and interactions of Human Immunodeficiency Virus - 1 and Schistosoma mansoni in sub-Saharan Africa.

Human Immunodeficiency Virus-1/AIDS and Schistosoma mansoni are widespread in sub-Saharan Africa and co-infection occurs commonly. Since the early 1990s, it has been suggested that the two infections may interact and potentiate the effects of each other within co-infected human hosts. Indeed, S. mansoni infection has been suggested to be a risk factor for HIV transmission and progression in Africa. If so, it would follow that mass deworming could have beneficial effects on HIV-1 transmission dynamics. The epidemiology of HIV in African countries is changing, shifting from urban to rural areas where the prevalence of Schistosoma mansoni is high and public health services are deficient. On the other side, the consequent pathogenesis of HIV-1/S. mansoni co-infection remains unknown. Here we give an account of the epidemiology of HIV-1 and S. mansoni, discuss co-infection and possible biological causal relationships between the two infections, and the potential impact of praziquantel treatment on HIV-1 viral loads, CD4+ counts and CD4+/CD8+ ratio. Our review of the available literature indicates that there is evidence to support the hypothesis that S. mansoni infections can influence the replication of the HIV-1, cell-to-cell transmission, as well as increase HIV progression as measured by reduced CD4+ T lymphocytes counts. If so, then deworming of HIV positive individuals living in endemic areas may impact on HIV-1 viral loads and CD4+ T lymphocyte counts.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

The Experiences of Youth Who Identify as Trans* in Relation to Health and Social Care Needs: A Scoping Review

There is an increased interest in the experiences of youth who identify as trans* to promote individual human rights and provide socially inclusive health and social care. This scoping review aimed to explore the experiences of youth who identify as trans*. A full search of relevant electronic databases was undertaken from the years 2006 to 2016. The search resulted in 1,656 hits and following the application of rigorous criteria, 20 papers were included in the final review. Date extraction was executed by two of the authors and a quality assessment tool was used to review the papers. The data were analyzed, and the key themes that emerged included the following: stigma, discrimination, and mental health; family relationships and supports; educational concerns; health care experiences; and vulnerability and health risks. The findings from the review are discussed, and the implications for policy, research, education, and practice are highlighted