The validity of the rotational formula used to compute E1 and E3 transition strengths in even-even nuclei is analyzed within the Generator Coordinate Method framework based on mean field wave functions.
The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, little effort has been invested toward feature selection and the features’ corresponding medical interpretation.
A new scenario for energy distribution, security and shareability is presented that assumes the availability of quantum information heat engines and a thermal bath. It is based on the convertibility between entropy and work in the presence of a thermal reservoir.
We examine the properties of the galaxies and dark matter haloes residing in the cluster infall region surrounding the simulated Λ cold dark matter galaxy cluster studied by Elahi et al. at z = 0. The 1.1 × 1015h−1 M⊙ galaxy cluster has been simulated with eight different hydrodynamical codes containing a variety of hydrodynamic solvers and sub-grid schemes.
We analyze predator–prey models in which the movement of predator searching for prey is the superposition of random dispersal and taxis directed toward the gradient of concentration of some chemical released by prey (e.g. pheromone), Model II, or released from damaged or injured prey due to predation (e.g. blood), Model I.
Healthcare associated infections (HAIS) can be acquired by patients during their stay in a hospital. HAIS are very endemic, causing a huge burden for the patients and for the health care system. We propose a machine learning approach to predict HAIS in an intensive care unit (ICU), combining heterogeneous data from longitudinal electronic health records and from microbiology laboratory.