In neonatal intensive care units (NICUs), hygiene and disinfection measures are pivotal to protect neonates from nosocomial infections. This study aimed to evaluate the efficacy of the classical incubators disinfection procedure and to follow-up neonates housed in the incubators for the development of late-onset sepsis (LOS). In a tertiary NICU, 20 incubators were monitored for bacterial contamination at three times before disinfection, after disinfection, and 24 h after turning on and housing a new neonate. Clinical data of neonates housed in these incubators were retrieved from the medical records. All 20 incubators were contaminated at the 3 times of the study, mainly on mattresses and balances. Coagulase-negative Staphylococci, Enterococcus, and Bacillus-resisted disinfection while enterobacteria and Staphylococcus aureus were eradicated. After 24 h, the bacterial colonisation was similar to the one observed before disinfection. The bacteria isolated on incubators were also found on the caregivers' CUs requires further researches concerning mechanisms of bacterial persistence and ways to fight against environmental colonisation. The aim of this study was to identify factors predicting outcome in patients with mitochondrial disease admitted to pediatric intensive care units (PICU). Retrospective study of 2434 patients (age <21 years) admitted to a PICU from 1 January 2006 through 31 March 2016 and captured in the Virtual Pediatric Systems database with ICD9 diagnosis 277.87, disorders of mitochondrial metabolism. Factors influencing mortality and prolonged length of stay (≥14 days) were analyzed using logistic regression. Predictors independently affecting mortality (adjusted odds ratios and 95% confidence intervals, p < 0.05) age 1-23 months 3.4 (1.7-6.6) and mechanical ventilation 4.7 (2.6-8.6) were risk factors; post-operative 0.2 (0.1-0.6), readmission 0.5 (0.3-0.9), and neurologic reason for admittance 0.3 (0.1-0.9) were factors reducing risk. Predictors affecting prolonged length of stay mechanical ventilation 7.4 (5.2-10.3) and infectious reason for admittance 2.0 (1.3-3.2) were risk factors, post-operative patients risk for prolonged length of stay PRISM3 and PIM2 are not as accurate in patients with mitochondrial disease as in a mixed patient population.The fundamental building blocks of the proton-quarks and gluons-have been known for decades. However, we still have an incomplete theoretical and experimental understanding of how these particles and their dynamics give rise to the quantum bound state of the proton and its physical properties, such as its spin1. The two up quarks and the single down quark that comprise the proton in the simplest picture account only for a few per cent of the proton mass, the bulk of which is in the form of quark kinetic and potential energy and gluon energy from the strong force2. An essential feature of this force, as described by quantum chromodynamics, is its ability to create matter-antimatter quark pairs inside the proton that exist only for a very short time. Their fleeting existence makes the antimatter quarks within protons difficult to study, but their existence is discernible in reactions in which a matter-antimatter quark pair annihilates. In this picture of quark-antiquark creation by the strong force, the probability distributions as a function of momentum for the presence of up and down antimatter quarks should be nearly identical, given that their masses are very similar and small compared to the mass of the proton3. Here we provide evidence from muon pair production measurements that these distributions are considerably different, with more abundant down antimatter quarks than up antimatter quarks over a wide range of momenta. These results are expected to revive interest in several proposed mechanisms for the origin of this antimatter asymmetry in the proton that had been disfavoured by previous results4, and point to future measurements that can distinguish between these mechanisms.Reinforcement learning promises to solve complex sequential-decision problems autonomously by specifying a high-level reward function only. However, reinforcement learning algorithms struggle when, as is often the case, simple and intuitive rewards provide sparse1 and deceptive2 feedback. Avoiding these pitfalls requires a thorough exploration of the environment, but creating algorithms that can do so remains one of the central challenges of the field. Here we hypothesize that the main impediment to effective exploration originates from algorithms forgetting how to reach previously visited states (detachment) and failing to first return to a state before exploring from it (derailment). We introduce Go-Explore, a family of algorithms that addresses these two challenges directly through the simple principles of explicitly 'remembering' promising states and returning to such states before intentionally exploring. Go-Explore solves all previously unsolved Atari games and surpasses the state of the art on all hard-exploration games1, with orders-of-magnitude improvements on the grand challenges of Montezuma's Revenge and Pitfall. We also demonstrate the practical potential of Go-Explore on a sparse-reward pick-and-place robotics task. Additionally, we show that adding a goal-conditioned policy can further improve Go-Explore's exploration efficiency and enable it to handle stochasticity throughout training. GDC-0199 The substantial performance gains from Go-Explore suggest that the simple principles of remembering states, returning to them, and exploring from them are a powerful and general approach to exploration-an insight that may prove critical to the creation of truly intelligent learning agents.Natural load-bearing materials such as tendons have a high water content of about 70 per cent but are still strong and tough, even when used for over one million cycles per year, owing to the hierarchical assembly of anisotropic structures across multiple length scales1. Synthetic hydrogels have been created using methods such as electro-spinning2, extrusion3, compositing4,5, freeze-casting6,7, self-assembly8 and mechanical stretching9,10 for improved mechanical performance. However, in contrast to tendons, many hydrogels with the same high water content do not show high strength, toughness or fatigue resistance. Here we present a strategy to produce a multi-length-scale hierarchical hydrogel architecture using a freezing-assisted salting-out treatment. The produced poly(vinyl alcohol) hydrogels are highly anisotropic, comprising micrometre-scale honeycomb-like pore walls, which in turn comprise interconnected nanofibril meshes. These hydrogels have a water content of 70-95 per cent and properties that compare favourably to those of other tough hydrogels and even natural tendons; for example, an ultimate stress of 23.