Reinforcement learning of normative monitoring intensities

Choosing actions within norm-regulated environments involves balancing achieving one’s goals and coping with any penalties for non-compliant behaviour. This choice becomes more complicated in environments where there is uncertainty. In this paper, we address the question of choosing actions in environments where there is uncertainty regarding both the outcomes of agent actions and the intensity of monitoring for norm violations. Our technique assumes no prior knowledge of probabilities over action outcomes or the likelihood of norm violations being detected by employing reinforcement learning to discover both the dynamics of the environment and the effectiveness of the enforcer. Results indicate agents become aware of greater rewards for violations when enforcement is lax, which gradually become less attractive as the enforcement is increased

Safety and Adverse Events after Targeted Lung Denervation for Symptomatic Moderate to Severe COPD (AIRFLOW):A Multicenter Randomized Controlled Trial

International audienc

Bacterial communities on classroom surfaces vary with human contact

BACKGROUND: Humans can spend the majority of their time indoors, but little is known about the interactions between the human and built-environment microbiomes or the forces that drive microbial community assembly in the built environment. We sampled 16S rRNA genes from four different surface types throughout a university classroom to determine whether bacterial assemblages on each surface were best predicted by routine human interactions or by proximity to other surfaces within the classroom. We then analyzed our data with publicly-available datasets representing potential source environments. RESULTS: Bacterial assemblages from the four surface types, as well as individual taxa, were indicative of different source pools related to the type of human contact each surface routinely encounters. Spatial proximity to other surfaces in the classroom did not predict community composition. CONCLUSIONS: Our results indicate that human-associated microbial communities can be transferred to indoor surfaces following contact, and that such transmission is possible even when contact is indirect, but that proximity to other surfaces in the classroom does not influence community composition

Resolving the neural circuits of anxiety

Although anxiety disorders represent a major societal problem demanding new therapeutic targets, these efforts have languished in the absence of a mechanistic understanding of this subjective emotional state. While it is impossible to know with certainty the subjective experience of a rodent, rodent models hold promise in dissecting well-conserved limbic circuits. The application of modern approaches in neuroscience has already begun to unmask the neural circuit intricacies underlying anxiety by allowing direct examination of hypotheses drawn from existing psychological concepts. This information points toward an updated conceptual model for what neural circuit perturbations could give rise to pathological anxiety and thereby provides a roadmap for future therapeutic development.National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (NIH Director’s New Innovator Award DP2-DK-102256-01)National Institute of Mental Health (U.S.) (NIH) R01-MH102441-01)JPB Foundatio

GWTC-2.1: Deep extended catalog of compact binary coalescences observed by LIGO and Virgo during the first half of the third observing run

The second Gravitational-Wave Transient Catalog, GWTC-2, reported on 39 compact binary coalescences observed by the Advanced LIGO and Advanced Virgo detectors between 1 April 2019 15 ∶ 00 UTC and 1 October 2019 15 ∶ 00 UTC. Here, we present GWTC-2.1, which reports on a deeper list of candidate events observed over the same period. We analyze the final version of the strain data over this period with improved calibration and better subtraction of excess noise, which has been publicly released. We employ three matched-filter search pipelines for candidate identification, and estimate the probability of astrophysical origin for each candidate event. While GWTC-2 used a false alarm rate threshold of 2 per year, we include in GWTC-2.1, 1201 candidates that pass a false alarm rate threshold of 2 per day. We calculate the source properties of a subset of 44 high-significance candidates that have a probability of astrophysical origin greater than 0.5. Of these candidates, 36 have been reported in GWTC-2. We also calculate updated source properties for all binary black hole events previously reported in GWTC-1. If the eight additional high-significance candidates presented here are astrophysical, the mass range of events that are unambiguously identified as binary black holes (both objects ≥ 3 M⊙ ) is increased compared to GWTC-2, with total masses from ∼ 14 M ⊙ for GW190924_021846 to ∼ 182 M⊙ for GW190426_190642. Source properties calculated using our default prior suggest that the primary components of two new candidate events (GW190403_051519 and GW190426_190642) fall in the mass gap predicted by pair-instability supernova theory. We also expand the population of binaries with significantly asymmetric mass ratios reported in GWTC-2 by an additional two events (the mass ratio is less than 0.65 and 0.44 at 90% probability for GW190403_051519 and GW190917_114630 respectively), and find that two of the eight new events have effective inspiral spins χeff > 0 (at 90% credibility), while no binary is consistent with χeff < 0 at the same significance. We provide updated estimates for rates of binary black hole and binary neutron star coalescence in the local Universe

All-sky, all-frequency directional search for persistent gravitational waves from Advanced LIGO’s and Advanced Virgo’s first three observing runs

We present the first results from an all-sky all-frequency (ASAF) search for an anisotropic stochastic gravitational-wave background using the data from the first three observing runs of the Advanced LIGO and Advanced Virgo detectors. Upper limit maps on broadband anisotropies of a persistent stochastic background were published for all observing runs of the LIGO-Virgo detectors. However, a broadband analysis is likely to miss narrowband signals as the signal-to-noise ratio of a narrowband signal can be significantly reduced when combined with detector output from other frequencies. Data folding and the computationally efficient analysis pipeline, {\tt PyStoch}, enable us to perform the radiometer map-making at every frequency bin. We perform the search at 3072 {\tt{HEALPix}} equal area pixels uniformly tiling the sky and in every frequency bin of width $1/32$~Hz in the range $20-1726$~Hz, except for bins that are likely to contain instrumental artefacts and hence are notched. We do not find any statistically significant evidence for the existence of narrowband gravitational-wave signals in the analyzed frequency bins. Therefore, we place $95\%$ confidence upper limits on the gravitational-wave strain for each pixel-frequency pair, the limits are in the range $(0.030 - 9.6) \times10^{-24}$. In addition, we outline a method to identify candidate pixel-frequency pairs that could be followed up by a more sensitive (and potentially computationally expensive) search, e.g., a matched-filtering-based analysis, to look for fainter nearly monochromatic coherent signals. The ASAF analysis is inherently independent of models describing any spectral or spatial distribution of power. We demonstrate that the ASAF results can be appropriately combined over frequencies and sky directions to successfully recover the broadband directional and isotropic results

Shifting school populations in the Long Beach Unified School District. - Page 69

Abstract. We propose a programming framework for the implementation of norm-aware multi-agent systems. The framework integrates the N-2APL norm-aware agent programming language with the 2OPL organisation programming language. Integration of N-2APL and 2OPL is achieved using a tuple space which represents both the (brute) state of the multi-agent environment and the detached norms and sanctions comprising its normative state. To the best of our knowledge, this is the first implementation of an integrated framework for norm-aware MAS in which autonomous agents deliberate about whether to conform to the norms imposed by a normative organisation. The use of a tuple space makes it straight-forward to integrate other system components. To illustrate the flexibility of our framework, we briefly describe its application in a novel normative application, a mixed reality game called GeoSense. We show how GeoSense game rules can be expressed as conditional norms with deadlines and sanctions, and how agents can deliberate about their individual goals and the norms imposed by the game.