1,585 research outputs found

    Phages and human health: More than idle hitchhikers

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    The Price Revolution in the Ottoman Context: Economic Upheaval in the Sixteenth Century

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    The inflationary pressures of the Price Revolution had an impact on Ottoman agricultural organization, state finances, industry, and the growth of corruption. This analysis will examine the causes, effects, and scope of inflation in the sixteenth century. Inflation alone did not cause these drastic changes, as other very significant developments also contributed to the turbulent economic environment. However inflation did, in fact, influence many basic transformations, including shifts in wealth, power, and the enrichment of specific social classes at the expense of others

    The Assistive Multi-Armed Bandit

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    Learning preferences implicit in the choices humans make is a well studied problem in both economics and computer science. However, most work makes the assumption that humans are acting (noisily) optimally with respect to their preferences. Such approaches can fail when people are themselves learning about what they want. In this work, we introduce the assistive multi-armed bandit, where a robot assists a human playing a bandit task to maximize cumulative reward. In this problem, the human does not know the reward function but can learn it through the rewards received from arm pulls; the robot only observes which arms the human pulls but not the reward associated with each pull. We offer sufficient and necessary conditions for successfully assisting the human in this framework. Surprisingly, better human performance in isolation does not necessarily lead to better performance when assisted by the robot: a human policy can do better by effectively communicating its observed rewards to the robot. We conduct proof-of-concept experiments that support these results. We see this work as contributing towards a theory behind algorithms for human-robot interaction.Comment: Accepted to HRI 201

    Transferrable protection by gut microbes against STING-associated lung disease

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    STING modulates immunity by responding to bacterial and endogenous cyclic dinucleotides (CDNs). Humans and mice with STING gain-of-function mutations develop a syndrome known as STING-associated vasculopathy with onset in infancy (SAVI), which is characterized by inflammatory or fibrosing lung disease. We hypothesized that hyperresponsiveness of gain-of-function STING to bacterial CDNs might explain autoinflammatory lung disease in SAVI mice. We report that depletion of gut microbes with oral antibiotics (vancomycin, neomycin, and ampicillin [VNA]) nearly eliminates lung disease in SAVI mice, implying that gut microbes might promote STING-associated autoinflammation. However, we show that germ-free SAVI mice still develop severe autoinflammatory disease and that transferring gut microbiota from antibiotics-treated mice to germ-free animals eliminates lung inflammation. Depletion of anaerobes with metronidazole abolishes the protective effect of the VNA antibiotics cocktail, and recolonization with the metronidazole-sensitive anaerobe Bacteroides thetaiotaomicron prevents disease, confirming a protective role of a metronidazole-sensitive microbe in a model of SAVI

    Policy Feedback and the Politics of the Affordable Care Act

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    There is a large body of literature devoted to how “policies create politics” and how feedback effects from existing policy legacies shape potential reforms in a particular area. Although much of this literature focuses on self‐reinforcing feedback effects that increase support for existing policies over time, Kent Weaver and his colleagues have recently drawn our attention to self‐undermining effects that can gradually weaken support for such policies. The following contribution explores both self‐reinforcing and self‐undermining policy feedback in relationship to the Affordable Care Act, the most important health‐care reform enacted in the United States since the mid‐1960s. More specifically, the paper draws on the concept of policy feedback to reflect on the political fate of the ACA since its adoption in 2010. We argue that, due in part to its sheer complexity and fragmentation, the ACA generates both self‐reinforcing and self‐undermining feedback effects that, depending of the aspect of the legislation at hand, can either facilitate or impede conservative retrenchment and restructuring. Simultaneously, through a discussion of partisan effects that shape Republican behavior in Congress, we acknowledge the limits of policy feedback in the explanation of policy stability and change

    The Value Proposition of the Global Health Security Index

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    Infectious disease outbreaks pose major threats to human health and security. Countries with robust capacities for preventing, detecting and responding to outbreaks can avert many of the social, political, economic and health system costs of such crises. The Global Health Security Index (GHS Index)—the first comprehensive assessment and benchmarking of health security and related capabilities across 195 countries—recently found that no country is sufficiently prepared for epidemics or pandemics. The GHS Index can help health security stakeholders identify areas of weakness, as well as opportunities to collaborate across sectors, collectively strengthen health systems and achieve shared public health goals. Some scholars have recently offered constructive critiques of the GHS Index’s approach to scoring and ranking countries; its weighting of select indicators; its emphasis on transparency; its focus on biosecurity and biosafety capacities; and divergence between select country scores and corresponding COVID-19-associated caseloads, morbidity, and mortality. Here, we (1) describe the practical value of the GHS Index; (2) present potential use cases to help policymakers and practitioners maximise the utility of the tool; (3) discuss the importance of scoring and ranking; (4) describe the robust methodology underpinning country scores and ranks; (5) highlight the GHS Index’s emphasis on transparency and (6) articulate caveats for users wishing to use GHS Index data in health security research, policymaking and practice

    Assessing plant performance in the Enviratron

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    Background: Assessing the impact of the environment on plant performance requires growing plants under controlled environmental conditions. Plant phenotypes are a product of genotype × environment (G × E), and the Enviratron at Iowa State University is a facility for testing under controlled conditions the effects of the environment on plant growth and development. Crop plants (including maize) can be grown to maturity in the Enviratron, and the performance of plants under different environmental conditions can be monitored 24 h per day, 7 days per week throughout the growth cycle. Results: The Enviratron is an array of custom-designed plant growth chambers that simulate different environmental conditions coupled with precise sensor-based phenotypic measurements carried out by a robotic rover. The rover has workflow instructions to periodically visit plants growing in the different chambers where it measures various growth and physiological parameters. The rover consists of an unmanned ground vehicle, an industrial robotic arm and an array of sensors including RGB, visible and near infrared (VNIR) hyperspectral, thermal, and time-of-flight (ToF) cameras, laser profilometer and pulse-amplitude modulated (PAM) fluorometer. The sensors are autonomously positioned for detecting leaves in the plant canopy, collecting various physiological measurements based on computer vision algorithms and planning motion via “eye-in-hand” movement control of the robotic arm. In particular, the automated leaf probing function that allows the precise placement of sensor probes on leaf surfaces presents a unique advantage of the Enviratron system over other types of plant phenotyping systems. Conclusions: The Enviratron offers a new level of control over plant growth parameters and optimizes positioning and timing of sensor-based phenotypic measurements. Plant phenotypes in the Enviratron are measured in situ—in that the rover takes sensors to the plants rather than moving plants to the sensors

    Breeding progress and preparedness for mass‐scale deployment of perennial lignocellulosic biomass crops switchgrass, miscanthus, willow and poplar

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    UK: The UK‐led miscanthus research and breeding was mainly supported by the Biotechnology and Biological Sciences Research Council (BBSRC), Department for Environment, Food and Rural Affairs (Defra), the BBSRC CSP strategic funding grant BB/CSP1730/1, Innovate UK/BBSRC “MUST” BB/N016149/1, CERES Inc. and Terravesta Ltd. through the GIANT‐LINK project (LK0863). Genomic selection and genomewide association study activities were supported by BBSRC grant BB/K01711X/1, the BBSRC strategic programme grant on Energy Grasses & Bio‐refining BBS/E/W/10963A01. The UK‐led willow R&D work reported here was supported by BBSRC (BBS/E/C/00005199, BBS/E/C/00005201, BB/G016216/1, BB/E006833/1, BB/G00580X/1 and BBS/E/C/000I0410), Defra (NF0424) and the Department of Trade and Industry (DTI) (B/W6/00599/00/00). IT: The Brain Gain Program (Rientro dei cervelli) of the Italian Ministry of Education, University, and Research supports Antoine Harfouche. US: Contributions by Gerald Tuskan to this manuscript were supported by the Center for Bioenergy Innovation, a US Department of Energy Bioenergy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science, under contract number DE‐AC05‐00OR22725. Willow breeding efforts at Cornell University have been supported by grants from the US Department of Agriculture National Institute of Food and Agriculture. Contributions by the University of Illinois were supported primarily by the DOE Office of Science; Office of Biological and Environmental Research (BER); grant nos. DE‐SC0006634, DE‐SC0012379 and DE‐SC0018420 (Center for Advanced Bioenergy and Bioproducts Innovation); and the Energy Biosciences Institute. EU: We would like to further acknowledge contributions from the EU projects “OPTIMISC” FP7‐289159 on miscanthus and “WATBIO” FP7‐311929 on poplar and miscanthus as well as “GRACE” H2020‐EU.3.2.6. Bio‐based Industries Joint Technology Initiative (BBI‐JTI) Project ID 745012 on miscanthus.Peer reviewedPostprintPublisher PD

    Mapping local and global variability in plant trait distributions

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    Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration - specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ∌50×50-km cells across the entire vegetated land surface. We do this in several ways - without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means
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