Constraints on the environment and energetics of the Broad-Line Ic SN2014ad from deep radio and X-ray observations

Broad-line type Ic Supernovae (BL-Ic SNe) are characterized by high ejecta velocity ($\gtrsim 10^4$ km s$^{-1}$) and are sometimes associated with the relativistic jets typical of long duration ($\gtrsim 2$ s) Gamma-Ray Bursts (L-GRBs). The reason why a small fraction of BL-Ic SNe harbor relativistic jets is not known. Here we present deep X-ray and radio observations of the BL-Ic SN2014ad extending from $13$ to $930$ days post explosion. SN2014ad was not detected at either frequency and has no observational evidence of a GRB counterpart. The proximity of SN2014ad ($d\sim 26$ Mpc) enables very deep constraints on the progenitor mass-loss rate $\dot{M}$ and on the total energy of the fast ejecta $E$. We consider two synchrotron emission scenarios for a wind-like circumstellar medium (CSM): (i) uncollimated non-relativistic ejecta, and (ii) off-axis relativistic jet. Within the first scenario our observations are consistent with GRB-less BL-Ic SNe characterized by a modest energy budget of their fast ejecta ($E \lesssim 10^{45}$ erg), like SNe 2002ap and 2010ay. For jetted explosions, we cannot rule out a GRB with $E \lesssim 10^{51}$ erg (beam-corrected) with a narrow opening angle ($\theta_j \sim 5^{\circ}$) observed moderately off-axis ($\theta_{\rm obs} \gtrsim 30^{\circ}$) and expanding in a very low CSM density ($\dot{M}$ $\lesssim 10^{-6}$ M$_{\odot}$ yr$^{-1}$). Our study shows that off-axis low-energy jets expanding in a low-density medium cannot be ruled out even in the most nearby BL-Ic SNe with extensive deep observations, and might be a common feature of BL-Ic SNe.Comment: 9 pages, 5 figures, accepted in Ap

Ontologies for Neuroscience: What are they and What are they Good for?

Current information technology practices in neuroscience make it difficult to understand the organization of the brain across spatial scales. Subcellular junctional connectivity, cytoarchitectural local connectivity, and long-range topographical connectivity are just a few of the relevant data domains that must be synthesized in order to make sense of the brain. However, due to the heterogeneity of the data produced within these domains, the landscape of multiscale neuroscience data is fragmented. A standard framework for neuroscience data is needed to bridge existing digital data resources and to help in the conceptual unification of the multiple disciplines of neuroscience. Using our efforts in building ontologies for neuroscience as an example, we examine the benefits and limits of ontologies as a solution for this data integration problem. We provide several examples of their application to problems of image annotation, content-based retrieval of structural data, and integration of data across scales and researchers

Experimental Analysis of Reinforcement Learning Techniques for Spectrum Sharing Radar

In this work, we first describe a framework for the application of Reinforcement Learning (RL) control to a radar system that operates in a congested spectral setting. We then compare the utility of several RL algorithms through a discussion of experiments performed on Commercial off-the-shelf (COTS) hardware. Each RL technique is evaluated in terms of convergence, radar detection performance achieved in a congested spectral environment, and the ability to share 100MHz spectrum with an uncooperative communications system. We examine policy iteration, which solves an environment posed as a Markov Decision Process (MDP) by directly solving for a stochastic mapping between environmental states and radar waveforms, as well as Deep RL techniques, which utilize a form of Q-Learning to approximate a parameterized function that is used by the radar to select optimal actions. We show that RL techniques are beneficial over a Sense-and-Avoid (SAA) scheme and discuss the conditions under which each approach is most effective.Comment: Accepted for publication at IEEE Intl. Radar Conference, Washington DC, Apr. 2020. This is the author's version of the wor

Length functions on currents and applications to dynamics and counting

The aim of this (mostly expository) article is twofold. We first explore a variety of length functions on the space of currents, and we survey recent work regarding applications of length functions to counting problems. Secondly, we use length functions to provide a proof of a folklore theorem which states that pseudo-Anosov homeomorphisms of closed hyperbolic surfaces act on the space of projective geodesic currents with uniform north-south dynamics.Comment: 35pp, 2 figures, comments welcome! Second version: minor corrections. To appear as a chapter in the forthcoming book "In the tradition of Thurston" edited by V. Alberge, K. Ohshika and A. Papadopoulo

Influence of the area per player in non-professional soccer players: A pilot study focused on positional roles

This study analyses the influence of different area per player (AP; 75, 98 and 131 m2 ) on the average metabolic power (MP) and other soccer-related performance variables in relation to the positional roles. We recruited 19 non-professional male soccer players (25.2 ± 6.3 y; 23.7 ± 2.3 kg/m2; 16.4 ± 6.3 y soccer experience) to play three different small-sided games (SSGs): SSG1 (5 vs. 5; 30 × 30 m; 5 min), SSG2 (5 vs. 5; 35 × 45 m; 5 min) and SSG3 (7 vs. 7; 35 × 45 m; 8 min). Specific playing rules were applied. GPS-assessed soccer-related variables were: average MP (AMP), distance covered in 1 min (DIS); % time spent at high speed (v > 16 km/h; % hst) or MP (>20 W/kg; % hmpt); % distance covered at high positive/negative speed (2 < v < 4 m/s2, % ACC; −6 < v < −2 m/s2, % DEC); and number of actions at high MP (hmpa). All recorded variables differed when each SSG was compared to the others (p < 0.05), but for hmpa for attackers. Most performance variables were positively associated with increasing AP (p < 0.05), but for % ACC and % DEC, and differed among positional roles within the same SSG (p < 0.05). Here the general applicability of SSGs, regardless the physical/technical skills of the group of players, to enhance performance is confirmed; furthermore, quantitative advices on AMP and other performance variables are provided to achieve significant improvements in all soccer players of the team

20th World wind energy conference & exhibition. WEEC 2022

This paper represents a preface to the Proceedings of the 20th World Wind Energy Conference & Exhibition (WEEC 2022) held in Rimini, Italy, from the 28th to the 30th of June 2022. Background information, conference resolution and the organizational structure of the meeting, program committee, and acknowledgments of the contributions of the many people who made the conference a success are presented

Development and use of Ontologies Inside the Neuroscience Information Framework: A Practical Approach

An initiative of the NIH Blueprint for neuroscience research, the Neuroscience Information Framework (NIF) project advances neuroscience by enabling discovery and access to public research data and tools worldwide through an open source, semantically enhanced search portal. One of the critical components for the overall NIF system, the NIF Standardized Ontologies (NIFSTD), provides an extensive collection of standard neuroscience concepts along with their synonyms and relationships. The knowledge models defined in the NIFSTD ontologies enable an effective concept-based search over heterogeneous types of web-accessible information entities in NIF’s production system. NIFSTD covers major domains in neuroscience, including diseases, brain anatomy, cell types, sub-cellular anatomy, small molecules, techniques, and resource descriptors. Since the first production release in 2008, NIF has grown significantly in content and functionality, particularly with respect to the ontologies and ontology-based services that drive the NIF system. We present here on the structure, design principles, community engagement, and the current state of NIFSTD ontologies

A Formal Ontology of Subcellular Neuroanatomy

The complexity of the nervous system requires high-resolution microscopy to resolve the detailed 3D structure of nerve cells and supracellular domains. The analysis of such imaging data to extract cellular surfaces and cell components often requires the combination of expert human knowledge with carefully engineered software tools. In an effort to make better tools to assist humans in this endeavor, create a more accessible and permanent record of their data, and to aid the process of constructing complex and detailed computational models, we have created a core of formalized knowledge about the structure of the nervous system and have integrated that core into several software applications. In this paper, we describe the structure and content of a formal ontology whose scope is the subcellular anatomy of the nervous system (SAO), covering nerve cells, their parts, and interactions between these parts. Many applications of this ontology to image annotation, content-based retrieval of structural data, and integration of shared data across scales and researchers are also described