Harmonization of the American College of Cardiology/American Heart Association and European Society of Cardiology/European Society of Hypertension Blood Pressure/Hypertension Guidelines: Comparisons, Reflections, and Recommendations

The 2017 American College of Cardiology/American Heart Association and 2018 European Society of Cardiology/European Society of Hypertension clinical practice guidelines for management of high blood pressure/hypertension are influential documents. Both guidelines are comprehensive, were developed using rigorous processes, and underwent extensive peer review. The most notable difference between the 2 guidelines is the blood pressure cut points recommended for the diagnosis of hypertension. There are also differences in the timing and intensity of treatment, with the American College of Cardiology/American Heart Association guideline recommending a somewhat more intensive approach. Overall, there is substantial concordance in the recommendations provided by the 2 guideline-writing committees, with greater congruity between them than their predecessors. Additional harmonization of future guidelines would help to underscore the commonality of their core recommendations and could serve to catalyze changes in practice that would lead to improved prevention, awareness, treatment, and control of hypertension, worldwide

Estimated Impact of Achieving Optimal Cardiovascular Health Among US Adults on Cardiovascular Disease Events

Background Better cardiovascular health (CVH) scores are associated with lower risk of cardiovascular disease (CVD). However, estimates of the potential population-level impact of improving CVH on US CVD event rates are not currently available. Methods and Results Using data from the National Health and Nutrition Examination Survey 2011 to 2016 (n=11 696), we estimated the proportions of US adults in CVH groups. Levels of 7 American Heart Association CVH metrics were scored as ideal (2 points), intermediate (1 point), or poor (0 points), and summed to define overall CVH (low, 0-8 points; moderate, 9-11 points; or high, 12-14 points). Using individual-level data from 7 US community-based cohort studies (n=30 447), we estimated annual incidence rates of major CVD events by levels of CVH. Using the combined data sources, we estimated population attributable fractions of CVD and the number of CVD events that could be prevented annually if all US adults achieved high CVH. High CVH was identified in 7.3% (95% CI, 6.3%-8.3%) of US adults. We estimated that 70.0% (95% CI, 56.5%-79.9%) of CVD events were attributable to low and moderate CVH. If all US adults attained high CVH, we estimated that 2.0 (95% CI, 1.6-2.3) million CVD events could be prevented annually. If all US adults with low CVH attained moderate CVH, we estimated that 1.2 (95% CI, 1.0-1.4) million CVD events could be prevented annually. Conclusions The potential benefits of achieving high CVH in all US adults are considerable, and even a partial improvement in CVH scores would be highly beneficial

The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence

Recent advances in machine learning and AI, including Generative AI and LLMs, are disrupting technological innovation, product development, and society as a whole. AI's contribution to technology can come from multiple approaches that require access to large training data sets and clear performance evaluation criteria, ranging from pattern recognition and classification to generative models. Yet, AI has contributed less to fundamental science in part because large data sets of high-quality data for scientific practice and model discovery are more difficult to access. Generative AI, in general, and Large Language Models in particular, may represent an opportunity to augment and accelerate the scientific discovery of fundamental deep science with quantitative models. Here we explore and investigate aspects of an AI-driven, automated, closed-loop approach to scientific discovery, including self-driven hypothesis generation and open-ended autonomous exploration of the hypothesis space. Integrating AI-driven automation into the practice of science would mitigate current problems, including the replication of findings, systematic production of data, and ultimately democratisation of the scientific process. Realising these possibilities requires a vision for augmented AI coupled with a diversity of AI approaches able to deal with fundamental aspects of causality analysis and model discovery while enabling unbiased search across the space of putative explanations. These advances hold the promise to unleash AI's potential for searching and discovering the fundamental structure of our world beyond what human scientists have been able to achieve. Such a vision would push the boundaries of new fundamental science rather than automatize current workflows and instead open doors for technological innovation to tackle some of the greatest challenges facing humanity today.Comment: 35 pages, first draft of the final report from the Alan Turing Institute on AI for Scientific Discover

Mergers, AGN, and 'Normal' Galaxies: Contributions to the Distribution of Star Formation Rates and Infrared Luminosity Functions

We use a novel method to predict the contribution of normal star-forming galaxies, merger-induced bursts, and obscured AGN, to IR luminosity functions (LFs) and global SFR densities. We use empirical halo occupation constraints to populate halos with galaxies and determine the distribution of normal and merging galaxies. Each system can then be associated with high-resolution hydrodynamic simulations. We predict the distribution of observed luminosities and SFRs, from different galaxy classes, as a function of redshift from z=0-6. We provide fitting functions for the predicted LFs, quantify the uncertainties, and compare with observations. At all redshifts, 'normal' galaxies dominate the LF at moderate luminosities ~L* (the 'knee'). Merger-induced bursts increasingly dominate at L>>L*; at the most extreme luminosities, AGN are important. However, all populations increase in luminosity at higher redshifts, owing to increasing gas fractions. Thus the 'transition' between normal and merger-dominated sources increases from the LIRG-ULIRG threshold at z~0 to bright Hyper-LIRG thresholds at z~2. The transition to dominance by obscured AGN evolves similarly, at factor of several higher L_IR. At all redshifts, non-merging systems dominate the total luminosity/SFR density, with merger-induced bursts constituting ~5-10% and AGN ~1-5%. Bursts contribute little to scatter in the SFR-stellar mass relation. In fact, many systems identified as 'ongoing' mergers will be forming stars in their 'normal' (non-burst) mode. Counting this as 'merger-induced' star formation leads to a stronger apparent redshift evolution in the contribution of mergers to the SFR density.Comment: 16 pages, 9 figures (+appendices), accepted to MNRAS. A routine to return the galaxy merger rates discussed here is available at http://www.cfa.harvard.edu/~phopkins/Site/mergercalc.htm

A physical model for the origin of the diffuse cosmic infrared background

We present a physical model for origin of the cosmic diffuse infrared background (CDIRB). By utilizing the observed stellar mass function and its evolution as input to a semi-empirical model of galaxy formation, we isolate the physics driving diffuse IR emission. The model includes contributions from three primary sources of IR emission: steady-state star formation owing to isolated disk galaxies, interaction-driven bursts of star formation owing to close encounters and mergers, and obscured active galactic nuclei (AGN). We find that most of the CDIRB is produced by equal contributions from objects at z=0.5-1 and z>1, as suggested by recent observations. Of those sources, the vast majority of the emission originates in systems with low to moderate IR luminosities (L_{IR}<10^{12} $L_sun); the most luminous objects contribute significant flux only at high-redshifts (z>2). All star formation in ongoing mergers accounts for <10% of the total at all wavelengths and redshifts, while emission directly attributable to the interaction-driven burst itself accounts for <5%. We furthermore find that obscured AGN contribute <1-2% of the CDIRB at all wavelengths and redshifts, with a strong upper limit of less than 4% of the total emission. Finally, since electron-positron pair production interactions with the CDIRB represent the primary source of opacity to very high energy (VHE: E_\gamma > 1 TeV) \gamma-rays, the model provides predictions for the optical depth of the Universe to the most energetic photons. We find that these predictions agree with observations of high-energy cutoffs at TeV energies in nearby blazars, and suggest that while the Universe is extremely optically thick at >10 TeV, the next generation of VHE \gamma-ray telescopes can reasonably expect detections from out to 50-150 Mpc.Comment: 14 pages, 13 figures, submitted to MNRA

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr

Mergers in Lambda-CDM: Uncertainties in Theoretical Predictions and Interpretations of the Merger Rate

Different methodologies lead to order-of-magnitude variations in predicted galaxy merger rates. We examine and quantify the dominant uncertainties. Different halo merger rates and subhalo 'destruction' rates agree to within a factor ~2 given proper care in definitions. If however (sub)halo masses are not appropriately defined or are under-resolved, the major merger rate can be dramatically suppressed. The dominant differences in galaxy merger rates owe to baryonic physics. Hydrodynamic simulations without feedback and older models that do not agree with the observed galaxy mass function propagate factor ~5 bias in the resulting merger rates. However, if the model matches the galaxy mass function, properties of central galaxies are sufficiently converged to give small differences in merger rates. But variations in baryonic physics of satellites also have dramatic effects. The known problem of satellite 'over-quenching' in most semi-analytic models (SAMs), whereby SAM satellites are too efficiently stripped of gas, could lead to order-of-magnitude under-estimates of merger rates for low-mass, gas-rich galaxies. Fixing the satellite properties to observations tends to predict higher merger rates, but with factor ~2 empirical uncertainties. Choice of mass ratio definition matters: at low masses, most true major mergers (in baryonic/dynamical galaxy mass) will appear to be minor mergers in their stellar or luminosity mass ratio. Observations and models using these criteria may underestimate major merger rates by factors ~5. Orbital parameters and gas fractions also introduce factor ~3 differences in amount of bulge formed by mergers, even for fixed mass ratio encounters.Comment: 32 Pages, 15 figures, accepted to ApJ (revised to match accepted version and correct Fig. 12

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median $z\sim 0.03$). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between $z\sim 0.6$ and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July

The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg2 of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg2 of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg2; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra. \ua9 2015. The American Astronomical Society