781 research outputs found

    Electromagnetics from a quasistatic perspective

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    Quasistatics is introduced so that it fits smoothly into the standard textbook presentation of electrodynamics. The usual path from statics to general electrodynamics is rather short and surprisingly simple. A closer look reveals however that it is not without confusing issues as has been illustrated by many contributions to this Journal. Quasistatic theory is conceptually useful by providing an intermediate level in between statics and the full set of Maxwell's equations. Quasistatics is easier than general electrodynamics and in some ways more similar to statics. It is however, in terms of interesting physics and important applications, far richer than statics. Quasistatics is much used in electromagnetic modeling, an activity that today is possible on a PC and which also has great pedagogical potential. The use of electromagnetic simulations in teaching gives additional support for the importance of quasistatics. This activity may also motivate some change of focus in the presentation of basic electrodynamics

    Analytical reasoning task reveals limits of social learning in networks

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    Social learning -by observing and copying others- is a highly successful cultural mechanism for adaptation, outperforming individual information acquisition and experience. Here, we investigate social learning in the context of the uniquely human capacity for reflective, analytical reasoning. A hallmark of the human mind is our ability to engage analytical reasoning, and suppress false associative intuitions. Through a set of lab-based network experiments, we find that social learning fails to propagate this cognitive strategy. When people make false intuitive conclusions, and are exposed to the analytic output of their peers, they recognize and adopt this correct output. But they fail to engage analytical reasoning in similar subsequent tasks. Thus, humans exhibit an 'unreflective copying bias,' which limits their social learning to the output, rather than the process, of their peers' reasoning -even when doing so requires minimal effort and no technical skill. In contrast to much recent work on observation-based social learning, which emphasizes the propagation of successful behavior through copying, our findings identify a limit on the power of social networks in situations that require analytical reasoning

    An efficient and principled method for detecting communities in networks

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    A fundamental problem in the analysis of network data is the detection of network communities, groups of densely interconnected nodes, which may be overlapping or disjoint. Here we describe a method for finding overlapping communities based on a principled statistical approach using generative network models. We show how the method can be implemented using a fast, closed-form expectation-maximization algorithm that allows us to analyze networks of millions of nodes in reasonable running times. We test the method both on real-world networks and on synthetic benchmarks and find that it gives results competitive with previous methods. We also show that the same approach can be used to extract nonoverlapping community divisions via a relaxation method, and demonstrate that the algorithm is competitively fast and accurate for the nonoverlapping problem.Comment: 14 pages, 5 figures, 1 tabl

    Mesoscopic structure and social aspects of human mobility

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    The individual movements of large numbers of people are important in many contexts, from urban planning to disease spreading. Datasets that capture human mobility are now available and many interesting features have been discovered, including the ultra-slow spatial growth of individual mobility. However, the detailed substructures and spatiotemporal flows of mobility - the sets and sequences of visited locations - have not been well studied. We show that individual mobility is dominated by small groups of frequently visited, dynamically close locations, forming primary "habitats" capturing typical daily activity, along with subsidiary habitats representing additional travel. These habitats do not correspond to typical contexts such as home or work. The temporal evolution of mobility within habitats, which constitutes most motion, is universal across habitats and exhibits scaling patterns both distinct from all previous observations and unpredicted by current models. The delay to enter subsidiary habitats is a primary factor in the spatiotemporal growth of human travel. Interestingly, habitats correlate with non-mobility dynamics such as communication activity, implying that habitats may influence processes such as information spreading and revealing new connections between human mobility and social networks.Comment: 7 pages, 5 figures (main text); 11 pages, 9 figures, 1 table (supporting information

    Incidence, management, and outcomes of cardiovascular insufficiency in critically ill term and late preterm newborn infants

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    OBJECTIVE: The objective of this study was to characterize the incidence, management, and short-term outcomes of cardiovascular insufficiency (CVI) in mechanically ventilated newborns, evaluating four separate prespecified definitions. STUDY DESIGN: Multicenter, prospective cohort study of infants ≥34 weeks gestational age (GA) and on mechanical ventilation during the first 72 hours. CVI was prospectively defined as either (1) mean arterial pressure (MAP) < GA; (2) MAP < GA + signs of inadequate perfusion; (3) any therapy for CVI; or (4) inotropic therapy. Short-term outcomes included death, days on ventilation, oxygen, and to full feedings and discharge. RESULTS: Of 647 who met inclusion criteria, 419 (65%) met ≥1 definition of CVI. Of these, 98% received fluid boluses, 36% inotropes, and 17% corticosteroids. Of treated infants, 46% did not have CVI as defined by a MAP < GA ± signs of inadequate perfusion. Inotropic therapy was associated with increased mortality (11.1 vs. 1.3%; p < 0.05). CONCLUSION: More than half of the infants met at least one definition of CVI. However, almost half of the treated infants met none of the definitions. Inotropic therapy was associated with increased mortality. These findings can help guide the design of future studies of CVI in newborn

    Safety and pharmacokinetics of multiple dose myo-inositol in preterm infants

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    BACKGROUND: Preterm infants with respiratory distress syndrome (RDS) given inositol had reduced bronchopulmonary dysplasia (BPD), death and severe retinopathy of prematurity (ROP). We assessed the safety and pharmacokinetics of daily inositol to select a dose providing serum levels previously associated with benefit, and to learn if accumulation occurred when administered throughout the normal period of retinal vascularization. METHODS: Infants ≤ 29 wk GA (n = 122, 14 centers) were randomized and treated with placebo or inositol at 10, 40, or 80 mg/kg/d. Intravenous administration converted to enteral when feedings were established, and continued to the first of 10 wk, 34 wk postmenstrual age (PMA) or discharge. Serum collection employed a sparse sampling population pharmacokinetics design. Inositol urine losses and feeding intakes were measured. Safety was prospectively monitored. RESULTS: At 80 mg/kg/d mean serum levels reached 140 mg/l, similar to Hallman's findings. Levels declined after 2 wk, converging in all groups by 6 wk. Analyses showed a mean volume of distribution 0.657 l/kg, clearance 0.058 l/kg/h, and half-life 7.90 h. Adverse events and comorbidities were fewer in the inositol groups, but not significantly so. CONCLUSION: Multiple dose inositol at 80 mg/kg/d was not associated with increased adverse events, achieves previously effective serum levels, and is appropriate for investigation in a phase III trial

    Understanding the interplay between social and spatial behaviour

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    According to personality psychology, personality traits determine many aspects of human behaviour. However, validating this insight in large groups has been challenging so far, due to the scarcity of multi-channel data. Here, we focus on the relationship between mobility and social behaviour by analysing trajectories and mobile phone interactions of ∼1000 individuals from two high-resolution longitudinal datasets. We identify a connection between the way in which individuals explore new resources and exploit known assets in the social and spatial spheres. We show that different individuals balance the exploration-exploitation trade-off in different ways and we explain part of the variability in the data by the big five personality traits. We point out that, in both realms, extraversion correlates with the attitude towards exploration and routine diversity, while neuroticism and openness account for the tendency to evolve routine over long time-scales. We find no evidence for the existence of classes of individuals across the spatio-social domains. Our results bridge the fields of human geography, sociology and personality psychology and can help improve current models of mobility and tie formation

    Metabotropic glutamate receptor 5 as a potential target for smoking cessation

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    Rationale Most habitual smokers find it difficult to quit smoking because they are dependent upon the nicotine present in tobacco smoke. Tobacco dependence is commonly treated pharmacologically using nicotine replacement therapy or drugs, such as varenicline, that target the nicotinic receptor. Relapse rates, however, remain high and there remains a need to develop novel non-nicotinic pharmacotherapies for the dependence that are more effective than existing treatments. Objective The purpose of this paper is to review the evidence from preclinical and clinical studies that drugs that antagonise the metabotropic glutamate receptor 5 (mGluR5) in the brain are likely to be efficacious as treatments for tobacco dependence. Results Imaging studies reveal that chronic exposure to tobacco smoke reduces the density of mGluR5s in human brain. Preclinical results demonstrate that negative allosteric modulators (NAMs) at mGluR5 attenuate both nicotine self-administration and the reinstatement of responding evoked by exposure to conditioned cues paired with nicotine delivery. They also attenuate the effects of nicotine on brain dopamine pathways implicated in addiction. Conclusions Although mGluR5 NAMs attenuate most of the key facets of nicotine dependence they potentiate the symptoms of nicotine withdrawal. This may limit their value as smoking cessation aids. The NAMs that have been employed most widely in preclinical studies of nicotine dependence have too many \u201coff target\u201d effects to be used clinically. However newer mGluR5 NAMs have been developed for clinical use in other indications. Future studies will determine if these agents can also be used effectively and safely to treat tobacco dependence

    Meta-Reinforcement Learning for the Tuning of PI Controllers: An Offline Approach

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    Meta-learning is a branch of machine learning which trains neural network models to synthesize a wide variety of data in order to rapidly solve new problems. In process control, many systems have similar and well-understood dynamics, which suggests it is feasible to create a generalizable controller through meta-learning. In this work, we formulate a meta reinforcement learning (meta-RL) control strategy that can be used to tune proportional--integral controllers. Our meta-RL agent has a recurrent structure that accumulates "context" to learn a system's dynamics through a hidden state variable in closed-loop. This architecture enables the agent to automatically adapt to changes in the process dynamics. In tests reported here, the meta-RL agent was trained entirely offline on first order plus time delay systems, and produced excellent results on novel systems drawn from the same distribution of process dynamics used for training. A key design element is the ability to leverage model-based information offline during training in simulated environments while maintaining a model-free policy structure for interacting with novel processes where there is uncertainty regarding the true process dynamics. Meta-learning is a promising approach for constructing sample-efficient intelligent controllers.Comment: 23 pages; postprin
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