Luminosity Dependence in the Fundamental Plane Projections of Elliptical Galaxies

We analyze the fundamental plane projections of elliptical galaxies as a function of luminosity, using a sample of approximately 80,000 galaxies drawn from Data Release 4 (DR4) of the Sloan Digital Sky Survey (SDSS). We separate brightest cluster galaxies (BCGs) from our main sample and reanalyze their photometry due to a problem with the default pipeline sky subtraction for BCGs. The observables we consider are effective radius (R_e), velocity dispersion (sigma), dynamical mass (M_dyn ~ R_e sigma2), effective density (sigma2/R_e2), and effective surface brightness (mu_e). With the exception of the L-M_dyn correlation, we find evidence of variations in the slope (i.e. the power-law index) of the fundamental plane projections with luminosity for our normal elliptical galaxy population. In particular, the radius-luminosity and Faber-Jackson relations are steeper at high luminosity relative to low luminosity, and the more luminous ellipticals become progressively less dense and have lower surface brightnesses than lower luminosity ellipticals. These variations can be understood as arising from differing formation histories, with more luminous galaxies having less dissipation. Data from the literature and our reanalysis of BCGs show that BCGs have radius-luminosity and Faber-Jackson relations steeper than the brightest non-BCG ellipticals in our sample, consistent with significant growth of BCGs via dissipationless mergers. The variations in slope we find in the Faber-Jackson relation of non-BCGs are qualitatively similar to that reported in the black hole mass-velocity dispersion (M_BH-sigma) correlation. This similarity is consistent with a roughly constant value of M_BH/M_star over a wide range of early type galaxies, where M_star is the stellar mass.Comment: v2: expanded analysis of BCGs; 17 pages, 9 figures; accepted in MNRA

Conductance-Based Refractory Density Approach for a Population of Bursting Neurons

The conductance-based refractory density (CBRD) approach is a parsimonious mathematical-computational framework for modeling interact- ing populations of regular spiking neurons, which, however, has not been yet extended for a population of bursting neurons. The canonical CBRD method allows to describe the firing activity of a statistical ensemble of uncoupled Hodgkin-Huxley-like neurons (differentiated by noise) and has demonstrated its validity against experimental data. The present manuscript generalises the CBRD for a population of bursting neurons; however, in this pilot computational study we consider the simplest setting in which each individual neuron is governed by a piecewise linear bursting dynamics. The resulting popula- tion model makes use of slow-fast analysis, which leads to a novel method- ology that combines CBRD with the theory of multiple timescale dynamics. The main prospect is that it opens novel avenues for mathematical explo- rations, as well as, the derivation of more sophisticated population activity from Hodgkin-Huxley-like bursting neurons, which will allow to capture the activity of synchronised bursting activity in hyper-excitable brain states (e.g. onset of epilepsy).Russian Science Foundation grant (project 16-15- 10201) Spanish grant MINECO-FEDER-UE MTM-2015-71509-C2-2-R Catalan Grant number 2017SGR104

US primary care in 2029: A Delphi survey on the impact of machine learning

ObjectiveTo solicit leading health informaticians' predictions about the impact of AI/ML on primary care in the US in 2029.DesignA three-round online modified Delphi poll.ParticipantsTwenty-nine leading health informaticians.MethodsIn September 2019, health informatics experts were selected by the research team, and invited to participate the Delphi poll. Participation in each round was anonymous, and panelists were given between 4-8 weeks to respond to each round. In Round 1 open-ended questions solicited forecasts on the impact of AI/ML on: (1) patient care, (2) access to care, (3) the primary care workforce, (4) technological breakthroughs, and (5) the long-future for primary care physicians. Responses were coded to produce itemized statements. In Round 2, participants were invited to rate their agreement with each item along 7-point Likert scales. Responses were analyzed for consensus which was set at a predetermined interquartile range of ≤ 1. In Round 3 items that did not reach consensus were redistributed.ResultsA total of 16 experts participated in Round 1 (16/29, 55%). Of these experts 13/16 (response rate, 81%), and 13/13 (response rate, 100%), responded to Rounds 2 and 3, respectively. As a result of developments in AI/ML by 2029 experts anticipated workplace changes including incursions into the disintermediation of physician expertise, and increased AI/ML training requirements for medical students. Informaticians also forecast that by 2029 AI/ML will increase diagnostic accuracy especially among those with limited access to experts, minorities and those with rare diseases. Expert panelists also predicted that AI/ML-tools would improve access to expert doctor knowledge.ConclusionsThis study presents timely information on informaticians' consensus views about the impact of AI/ML on US primary care in 2029. Preparation for the near-future of primary care will require improved levels of digital health literacy among patients and physicians

Why we should use topological data analysis in ageing: Towards defining the “topological shape of ageing”

Living systems are subject to the arrow of time; from birth, they undergo complex transformations (self-organization) in a constant battle for survival, but inevitably ageing and disease trap them to death. Can ageing be understood and eventually reversed? What tools can be employed to further our understanding of ageing? The present article is an invitation for biologists and clinicians to consider key conceptual ideas and computational tools (known to mathematicians and physicists), which potentially may help dissect some of the underlying processes of ageing and disease. Specifically, we first discuss how to classify and analyse complex systems, as well as highlight critical theoretical difficulties that make complex systems hard to study. Subsequently, we introduce Topological Data Analysis - a novel Big Data tool – which may help in the study of complex systems since it extracts knowledge from data in a holistic approach via topological considerations. These conceptual ideas and tools are discussed in a relatively informal way to pave future discussions and collaborations between mathematicians and biologists studying ageing.Basque Government under the grant “Artificial Intelligence in BCAM number EXP. 2019/00432” Inria associated team "NeuroTransSF

Education Matters: Certified health professionals have higher credibility than non health professionals on Instagram

Social media serves as an accessible source of health information and nutrition information. Instagram, an internationally known social media platform with an average of more than 1 billion monthly active users, allows its users to create and share content. However, the credibility of the nutrition content created by users with unknown qualifications may be questionable. The objective of this study is to assess the credibility of content created by nutrition influencers on Instagram by comparing health professionals with non-health professionals.  For this study, “influencer” is defined as an Instagram user with at least 15,000 followers who promotes products, services, or ideas and who creates nutrition- or health-related content. For each influencer (n=29), two posts were selected every month from August 2018 to July 2019. Using the “Credible Information Factsheet” from the Dietitians of Canada, a credibility score based on four dichotomous criteria was created. Looking at the 24 posts of each influencer holistically, a credibility score out of 4 was calculated, with 0 being the least credible and 4 being the most credible.  Without exception, a greater proportion of health professionals compared to non-health professionals met each criterion from the “Credible Information Factsheet”. 92% of the health professionals met criteria 1 (Miracle Cure) compared to only 31% of non-health professionals. This demonstrates how the vast majority of health professionals would not promise a miracle cure, while most non-health professionals would readily promise a miracle cure. Additionally, 46% of health professionals met criteria 4 (Research-based) compared to only 19% of non-health professionals, which demonstrates how non-health professionals do not support claims with research. When looking at the total credibility scores for health professionals and non-health professionals, not a single health professional scored a total of 0, while not a single non-health professional scored a total of 4. Most importantly, health professionals had an average credibility score of 2.4, which is twice as high as that of non-health professionals (1.2).  Overall, health professionals appeared to be more credible than non-health professionals. By viewing nutrition information posted on Instagram by non-health professionals, followers potentially expose themselves to misinformation. Further research should be undertaken to validate the credibility score based on the “Credible Information Factsheet” by determining how adept the factsheet is at differentiating credibility for Instagram content

Canards, Folded Nodes, and Mixed-Mode Oscillations in Piecewise-Linear Slow-Fast Systems

Canard-induced phenomena have been extensively studied in the last three decades, from both the mathematical and the application viewpoints. Canards in slow-fast systems with (at least) two slow variables, especially near folded-node singularities, give an essential generating mechanism for mixed-mode oscillations (MMOs) in the framework of smooth multiple timescale systems. There is a wealth of literature on such slow-fast dynamical systems and many models displaying canard-induced MMOs, particularly in neuroscience. In parallel, since the late 1990s several papers have shown that the canard phenomenon can be faithfully reproduced with piecewise-linear (PWL) systems in two dimensions, although very few results are available in the three-dimensional case. The present paper aims to bridge this gap by analyzing canonical PWL systems that display folded singularities, primary and secondary canards, with a similar control of the maximal winding number as in the smooth case. We also show that the singular phase portraits are compatible in both frameworks. Finally, we show using an example how to construct a (linear) global return and obtain robust PWL MMOs

Observational evidence for matter propagation in accretion flows

We study simultaneous X-ray and optical observations of three intermediate polars EX Hya, V1223 Sgr and TV Col with the aim to understand the propagation of matter in their accretion flows. We show that in all cases the power spectra of flux variability of binary systems in X-rays and in optical band are similar to each other and the majority of X-ray and optical fluxes are correlated with time lag <1 sec. These findings support the idea that optical emission of accretion disks, in these binary systems,largely originates as reprocessing of X-ray luminosity of their white dwarfs. In the best obtained dataset of EX Hya we see that the optical lightcurve unambiguously contains some component, which leads the X-ray emission by ~7 sec. We interpret this in the framework of the model of propagating fluctuations and thus deduce the time of travel of the matter from the innermost part of the truncated accretion disk to the white dwarf surface. This value agrees very well with the time expected for matter threaded onto the magnetosphere of the white dwarf to fall to its surface. The datasets of V1223 Sgr and TV Col in general confirm these findings,but have poorer quality.Comment: 7 pages, 6 figures. Accepted for publication in MNRA