Learning from humans: combining imitation and deep reinforcement learning to accomplish human-level performance on a virtual foraging task

We develop a method to learn bio-inspired foraging policies using human data. We conduct an experiment where humans are virtually immersed in an open field foraging environment and are trained to collect the highest amount of rewards. A Markov Decision Process (MDP) framework is introduced to model the human decision dynamics. Then, Imitation Learning (IL) based on maximum likelihood estimation is used to train Neural Networks (NN) that map human decisions to observed states. The results show that passive imitation substantially underperforms humans. We further refine the human-inspired policies via Reinforcement Learning (RL), using on-policy algorithms that are more suitable to learn from pre-trained networks. We show that the combination of IL and RL can match human results and that good performance strongly depends on an egocentric representation of the environment. The developed methodology can be used to efficiently learn policies for unmanned vehicles which have to solve missions in an open field environment.Comment: 24 pages, 15 figure

Comparison of in vivo and in vitro digestibility in donkeys

We compared in vivo and in vitro dry matter (DM) and neutral detergent fiber (NDF) digestibility in donkeys using feces as microbial inoculum. Four donkeys were used in a 4 × 4 Latin square design with a 2 × 2 factorial arrangement of treatments. The animals were fed two types of hay, with or without flaked barley. For the in vivo procedure, total feces were collected for 6 days from each donkey; digestibility was calculated as the difference between ingested and excreted DM and NDF. For the in vitro procedure, donkey feces were buffered and used as microbial inoculum in an Ankom DaisyII Incubator; digestibility was estimated after 60 h of incubation. In vivo results showed that the addition of barley to hays did not change the digestibility values. In vivo estimates were higher than in vitro ones. The equations used to predict in vivo estimates from in vitro data were not reliable (R2 = 0.47 and 0.21; P = 0.003 and 0.078 for NDF and DM digestibility, respectively). Further studies need to evaluate different sample size and digestion times

Long-QT mutations in KCNE1 modulate the 17β-estradiol response of Kv7.1/KCNE1.

Estradiol (17[Formula: see text]-E2) is implicated in higher arrhythmia risk of women with congenital or acquired long-QT syndrome (LQTS) compared to men. However, the underlying mechanisms remain poorly understood, and little is known about the impact of LQTS-associated mutations. We show that 17[Formula: see text]-E2 inhibits the human cardiac Kv7.1/KCNE1 channel expressed in Xenopus oocytes. We find that the 17[Formula: see text]-E2 effect depends on the Kv7.1 to KCNE1 stoichiometry, and we reveal a critical function of the KCNE1 carboxyl terminus for the effect. LQTS-associated mutations in the KCNE1 carboxyl terminus show a range of responses to 17[Formula: see text]-E2, from a wild-type like response to impaired or abolished response. Together, this study increases our understanding of the mechanistic basis for 17[Formula: see text]-E2 inhibition of Kv7.1/KCNE1 and demonstrates mutation-dependent responses to 17[Formula: see text]-E2. These findings suggest that the 17[Formula: see text]-E2 effect on Kv7.1/KCNE1 might contribute to the higher arrhythmia risk of women, particularly in carriers with specific LQTS-associated mutations

Mare Embryonic Resorption and Homocysteine

Early embryonic death in the mare is one of the main causes of subfertility in horses(Woods et al., 1987). Pregnancy loss in women has been correlated with hyperhomocysteinaemia(Steegers-Theunissem et al., 1997) and seems to be caused by an alterationof placental angiogenesis (Nagai et al., 2001). Hyperhomocysteinaemia isconsidered an important marker of obstetric and gynaecological conditions (Scholland Johnson, 2000).The aim of the present study was to test the levels of homocysteine in maressuffering from embryonic death.[...

Point prevalence survey on antibiotic use in a Croatian Infectious Disease Hospital

Antibiotic use is the driving force for increasing antibiotic resistance. A large proportion of antibiotics in hospitals are used inadequately. The objective of this study was to evaluate antibiotic use at the Hospital for Infectious Diseases through point-prevalence surveys conducted in 2006, 2008, and 2009. Point prevalence surveys were part of the European Surveillance on Antimicrobial Consumption (ESAC) Hospital Care Subproject and patients' data were collected following ESAC protocol. Additionally, the adequacy of antimicrobial therapy and administration of the first line antibiotic according to the local guidelines were assessed by an infectious disease doctor and a clinical microbiologist. In the study period among the 599 patients admitted to hospital, 352 (58·8%) received antibiotics. Out of 448 antimicrobial treatments, 313 (69·9%) were administered parenterally and 135 (30·1%) orally. Altogether in years 2006, 2008, and 2009 the most commonly prescribed antibiotics were ceftriaxone (19·9%), co-amoxiclav (15·4%), ciprofloxacin (12·3%), narrow spectrum penicillins (6·5%), and penicillinase resistant penicillins (5·6%). Most (82·6%) of the treated infections were community acquired infections. The predominating diagnoses were urinary tract infections and infections with no primary site defined, followed by skin, soft tissue and bone and joint infections. The overall adequacy of antimicrobial therapy was 82% and the first line antibiotic according to the local guidelines was administered with high frequency for central nervous system and cardiovascular infections (100%), and low for ear, nose, and throat infections, urinary tract infections, lower respiratory tract and bone and joint infections (23·0%, 51·6%, 52·5%, 65·0%, respectively) which indicates a significant overuse of antibiotics for diagnoses listed. The results of an individual point prevalence survey provided reliable and representative data for the hospital. Point-prevalence surveys proved to be a valuable method for detecting targets for antibiotic prescribing improvement and they clearly showed that our local hospital guidelines offered too many choices of antibiotic treatment for each clinical indication and needed revision