Stellar populations in the dwarf spheroidal galaxy Leo I

We present a detailed study of the color magnitude diagram (CMD) of the dwarf spheroidal galaxy Leo I, based on archival Hubble Space Telescope data. Our photometric analysis, confirming previous results on the brighter portion of the CMD, allow us to obtain an accurate sampling of the stellar populations also at the faint magnitudes corresponding to the Main Sequence. By adopting a homogeneous and consistent theoretical scenario for both hydrogen and central helium-burning evolutionary phases, the various features observed in the CMD are interpreted and reliable estimations for both the distance modulus and the age(s) for the main stellar components of Leo I are derived. More in details, from the upper luminosity of the Red Giant Branch and the lower luminosity of the Subgiant Branch we simultaneously constrain the galaxy distance and the age of the oldest stellar population in Leo I. In this way we obtain a distance modulus (m-M)_V=22.00$\pm$0.15 mag and an age of 10--15 Gyr or 9--13 Gyr, adopting a metallicity Z=0.0001 and 0.0004, respectively. The reliability of this distance modulus has been tested by comparing the observed distribution of the Leo I anomalous Cepheids in the period-magnitude diagram with the predicted boundaries of the instability strip, as given by convective pulsating models.Comment: 19 pages, 3 tables, 14 figures To be published in A

Upgrade of the CMS muon system with Triple-GEM detectors

The CMS collaboration considers upgrading the muon forward region which is particularly affected by the high-luminosity conditions at the LHC. The proposal involves Gas ElectronMultiplier (GEM) chambers, which are able to handle the extreme particle rates expected in this region along with a high spatial resolution. This allows to combine tracking and triggering capabilities, which will improve the CMS muon High Level Trigger, the muon identification and the track reconstruction. Intense research and development has been done since 2009 and it has lead to the development of several GEM prototypes and the associated detector electronics. All GEM prototypes have been put to extensive tests in the lab and in test beams at the CERN SPS. The contribution will review the status of the CMS upgrade project with the usage of GEM detector, discussing also the trigger performance

Nuclear DNA contents, rDNAs, and karyotype evolution in subgenus Vicia: III. The heterogeneous section Hypechusa.

Abstract: Nuclear DNA contents, automated karyotype analyses, and sequences of internal transcribed spacers from ribosomal genes have been determined in the species belonging to section Hypechusa of the sub-genus Vicia. Karyomorphological results and phylogenetic data generated from the comparison of rDNA ( genes coding for rRNA) sequences showed that sect. Hypechusa is not monophyletic; however, some monophyletic units are apparent ( one including Vicia galeata, V. hyrcanica, V. noeana, and V. tigridis, another including V. assyriaca, V. hybrida, V. melanops, V. mollis, and V. sericocarpa), which partly correspond to morphology-based infrasectional groups. The relationships among these species and the species in sections Faba, Narbonensis, Bithynicae, and Peregrinae have been also investigated. Nuclear DNA contents, automated karyotype analyses, and sequences of internal transcribed spacers from ribosomal genes have been determined in the species belonging to section Hypechusa of the subgenus Vicia. Karyomorphological results and phylogenetic data generated from the comparison of rDNA (genes coding for rRNA) sequences showed that sect. Hypechusa is not monophyletic; however, some monophyletic units are apparent (one including Vicia galeata, V. hyrcanica, V. noeana, and V. tigridis, another including V. assyriaca, V. hybrida, V. melanops, V. mollis, and V. sericocarpa), which partly correspond to morphology-based infrasectional groups. The relationships among these species and the species in sections Faba, Narbonensis, Bithynicae, and Peregrinae have been also investigated

Fourier mode dynamics for the nonlinear Schroedinger equation in one-dimensional bounded domains

We analyze the 1D focusing nonlinear Schr\"{o}dinger equation in a finite interval with homogeneous Dirichlet or Neumann boundary conditions. There are two main dynamics, the collapse which is very fast and a slow cascade of Fourier modes. For the cubic nonlinearity the calculations show no long term energy exchange between Fourier modes as opposed to higher nonlinearities. This slow dynamics is explained by fairly simple amplitude equations for the resonant Fourier modes. Their solutions are well behaved so filtering high frequencies prevents collapse. Finally these equations elucidate the unique role of the zero mode for the Neumann boundary conditions

Monitoring the performance of residents during training in off-pump coronary surgery.

OBJECTIVE: Control charts (eg, cumulative sum charts) plot changes in performance with time and can alert a surgeon to suboptimal performance. They were used to compare performance of off-pump coronary artery bypass surgery between a consultant and four resident surgeons and to compare performance of off-pump coronary artery bypass surgery and conventional coronary artery bypass grafting within surgeons. METHODS: Data were analyzed for consecutive patients undergoing coronary artery bypass grafting who were operated on by one consultant or one of four residents. Conversions were analyzed by intention to treat. Perioperative death or one or more of 10 adverse events constituted failure. Predicted risks of failure for individual patients were derived from the study population. Variable life-adjusted displays and risk-adjusted sequential probability ratio test charts were plotted. RESULTS: Data for 1372 patients were analyzed; 769 of the procedures were off-pump coronary artery bypass operations (56.0%). The consultant operated on 382 patients (293 off-pump, 76.7%), and the residents operated on 990 (474 off-pump, 47.9%). Patients operated on by residents tended to be older, more obese, more likely to require an urgent operation, and more likely to need a circumflex artery graft but less likely to have triple-vessel disease. There were 7 conversions (consultant 5, residents 2). The overall failure rate was 8.5% (9.2% for consultant's operations and 8.2% for residents' operations), including 10 deaths (0.7%). Predicted and observed risks of failure were similar for all five surgeons. After 100 off-pump coronary artery bypass operations, performance was the same or better for the residents as for the consultant. For all surgeons, performance was the same or better for off-pump as for conventional coronary artery bypass grafting. CONCLUSIONS: Off-pump coronary artery bypass surgery can be safely taught to cardiothoracic residents. Implementation of continuous performance monitoring for residents is practicable

Portable dynamic fundus instrument

A portable diagnostic image analysis instrument is disclosed for retinal funduscopy in which an eye fundus image is optically processed by a lens system to a charge coupled device (CCD) which produces recordable and viewable output data and is simultaneously viewable on an electronic view finder. The fundus image is processed to develop a representation of the vessel or vessels from the output data

Triggering the Formation of Halo Globular Clusters with Galaxy Outflows

We investigate the interactions of high-redshift galaxy outflows with low-mass virialized (Tvir < 10,000K) clouds of primordial composition. While atomic cooling allows star formation in larger primordial objects, such "minihalos" are generally unable to form stars by themselves. However, the large population of high-redshift starburst galaxies may have induced widespread star formation in these objects, via shocks that caused intense cooling both through nonequilibrium H2 formation and metal-line emission. Using a simple analytic model, we show that the resulting star clusters naturally reproduce three key features of the observed population of halo globular clusters (GCs). First, the 10,000 K maximum virial temperature corresponds to the ~ 10^6 solar mass upper limit on the stellar mass of GCs. Secondly, the momentum imparted in such interactions is sufficient to strip the gas from its associated dark matter halo, explaining why GCs do not reside in dark matter potential wells. Finally, the mixing of ejected metals into the primordial gas is able to explain the ~ 0.1 dex homogeneity of stellar metallicities within a given GC, while at the same time allowing for a large spread in metallicity between different clusters. To study this possibility in detail, we use a simple 1D numerical model of turbulence transport to simulate mixing in cloud-outflow interactions. We find that as the shock shears across the side of the cloud, Kelvin-Helmholtz instabilities arise, which cause mixing of enriched material into > 20% of the cloud. Such estimates ignore the likely presence of large-scale vortices, however, which would further enhance turbulence generation. Thus quantitative mixing predictions must await more detailed numerical studies.Comment: 21 pages, 11 figures, Apj in pres

Analyzing real options and flexibility in engineering systems design using decision rules and deep reinforcement learning

Engineering systems provide essential services to society e.g., power generation, transportation. Their performance, however, is directly affected by their ability to cope with uncertainty, especially given the realities of climate change and pandemics. Standard design methods often fail to recognize uncertainty in early conceptual activities, leading to rigid systems that are vulnerable to change. Real Options and Flexibility in Design are important paradigms to improve a system’s ability to adapt and respond to unforeseen conditions. Existing approaches to analyze flexibility, however, do not leverage sufficiently recent developments in machine learning enabling deeper exploration of the computational design space. There is untapped potential for new solutions that are not readily accessible using existing methods. Here, a novel approach to analyze flexibility is proposed based on Deep Reinforcement Learning (DRL). It explores available datasets systematically and considers a wider range of adaptability strategies. The methodology is evaluated on an example waste-toenergy system. Low and high flexibility DRL models are compared against stochastically optimal inflexible and flexible solutions using decision rules. The results show highly dynamic solutions, with action space parametrized via artificial neural network. They show improved expected economic value up to 69% compared to previous solutions. Combining information from action space probability distributions along expert insights and risk tolerance helps make better decisions in real-world design and system operations. Out of sample testing shows that the policies are generalizable, but subject to tradeoffs between flexibility and inherent limitations of the learning process