3,593 research outputs found
Measurement of rolling friction by a damped oscillator
An experimental method for measuring rolling friction is proposed. The method is mechanically simple. It is based on an oscillator in a uniform magnetic field and does not involve any mechanical forces except for the measured friction. The measured pickup voltage is Fourier analyzed and yields the friction spectral response. The proposed experiment is not tailored for a particular case. Instead, various modes of operation, suitable to different experimental conditions, are discussed
Characterizing the firing properties of an adaptive analog VLSI neuron
Ben Dayan Rubin D, Chicca E, Indiveri G. Characterizing the firing properties of an adaptive analog VLSI neuron. Biologically Inspired Approaches to Advanced Information Technology. 2004;3141:189-200.We describe the response properties of a compact, low power, analog circuit that implements a model of a leaky-Integrate & Fire (I&F) neuron, with spike-frequency adaptation, refractory period and voltage threshold modulation properties. We investigate the statistics of the circuit's output response by modulating its operating parameters, like refractory period and adaptation level and by changing the statistics of the input current. The results show a clear match with theoretical prediction and neurophysiological data in a given range of the parameter space. This analysis defines the chip's parameter working range and predicts its behavior in case of integration into large massively parallel very-large-scale-integration (VLSI) networks
Neuronal assembly dynamics in supervised and unsupervised learning scenarios
The dynamic formation of groups of neurons—neuronal assemblies—is believed to mediate cognitive phenomena at many levels, but their detailed operation and mechanisms of interaction are still to be uncovered. One hypothesis suggests that synchronized oscillations underpin their formation and functioning, with a focus on the temporal structure of neuronal signals. In this context, we investigate neuronal assembly dynamics in two complementary scenarios: the first, a supervised spike pattern classification task, in which noisy variations of a collection of spikes have to be correctly labeled; the second, an unsupervised, minimally cognitive evolutionary robotics tasks, in which an evolved agent has to cope with multiple, possibly conflicting, objectives. In both cases, the more traditional dynamical analysis of the system’s variables is paired with information-theoretic techniques in order to get a broader picture of the ongoing interactions with and within the network. The neural network model is inspired by the Kuramoto model of coupled phase oscillators and allows one to fine-tune the network synchronization dynamics and assembly configuration. The experiments explore the computational power, redundancy, and generalization capability of neuronal circuits, demonstrating that performance depends nonlinearly on the number of assemblies and neurons in the network and showing that the framework can be exploited to generate minimally cognitive behaviors, with dynamic assembly formation accounting for varying degrees of stimuli modulation of the sensorimotor interactions
Insular carnivore biogeography: island area and mammalian optimal body size.
Published versio
Learning by message-passing in networks of discrete synapses
We show that a message-passing process allows to store in binary "material"
synapses a number of random patterns which almost saturates the information
theoretic bounds. We apply the learning algorithm to networks characterized by
a wide range of different connection topologies and of size comparable with
that of biological systems (e.g. ). The algorithm can be
turned into an on-line --fault tolerant-- learning protocol of potential
interest in modeling aspects of synaptic plasticity and in building
neuromorphic devices.Comment: 4 pages, 3 figures; references updated and minor corrections;
accepted in PR
Prior preferences beneficially influence social and non-social learning
Our personal preferences affect a broad array of social behaviors. This includes the way we learn the preferences of others, an ability that often relies on limited or ambiguous information. Here we report an egocentric influence on this type of social learning that is reflected in both performance and response times. Using computational models that combine inter-trial learning and intra-trial choice, we find transient effects of participants' preferences on the learning process, through the influence of priors, and persistent effects on the choice process. A second experiment shows that these effects generalize to non-social learning, though participants in the social learning experiment appeared to additionally benefit by using their knowledge about the popularity of certain preferences. We further find that the domain-general egocentric influences we identify can yield performance advantages in uncertain environments.People often assume that other people share their preferences, but how exactly this bias manifests itself in learning and decision-making is unclear. Here, authors show that a person's own preferences influence learning in both social and non-social situations, and that this bias improves performance
Current state of antimicrobial stewardship in children’s hospital emergency departments
BACKGROUND Antimicrobial stewardship programs (ASPs) effectively optimize antibiotic use for inpatients; however, the extent of emergency department (ED) involvement in ASPs has not been described. OBJECTIVE To determine current ED involvement in children's hospital ASPs and to assess beliefs and preferred methods of implementation for ED-based ASPs. METHODS A cross-sectional survey of 37 children's hospitals participating in the Sharing Antimicrobial Resistance Practices collaboration was conducted. Surveys were distributed to ASP leaders and ED medical directors at each institution. Items assessed included beliefs regarding ED antibiotic prescribing, ED prescribing resources, ASP methods used in the ED such as clinical decision support and clinical care guidelines, ED participation in ASP activities, and preferred methods for ED-based ASP implementation. RESULTS A total of 36 ASP leaders (97.3%) and 32 ED directors (86.5%) responded; the overall response rate was 91.9%. Most ASP leaders (97.8%) and ED directors (93.7%) agreed that creation of ED-based ASPs was necessary. ED resources for antibiotic prescribing were obtained via the Internet or electronic health records (EHRs) for 29 hospitals (81.3%). The main ASP activities for the ED included production of antibiograms (77.8%) and creation of clinical care guidelines for pneumonia (83.3%). The ED was represented on 3 hospital ASP committees (8.3%). No hospital ASPs actively monitored outpatient ED prescribing. Most ASP leaders (77.8%) and ED directors (81.3%) preferred implementation of ED-based ASPs using clinical decision support integrated into the EHR. CONCLUSIONS Although ED involvement in ASPs is limited, both ASP and ED leaders believe that ED-based ASPs are necessary. Many children's hospitals have the capability to implement ED-based ASPs via the preferred method: EHR clinical decision support. Infect Control Hosp Epidemiol 2017;38:469-475
Supergravity Higgs Inflation and Shift Symmetry in Electroweak Theory
We present a model of inflation in a supergravity framework in the Einstein
frame where the Higgs field of the next to minimal supersymmetric standard
model (NMSSM) plays the role of the inflaton. Previous attempts which assumed
non-minimal coupling to gravity failed due to a tachyonic instability of the
singlet field during inflation. A canonical K\"{a}hler potential with
\textit{minimal coupling} to gravity can resolve the tachyonic instability but
runs into the -problem. We suggest a model which is free of the
-problem due to an additional coupling in the K\"{a}hler potential which
is allowed by the Standard Model gauge group. This induces directions in the
potential which we call K-flat. For a certain value of the new coupling in the
(N)MSSM, the K\"{a}hler potential is special, because it can be associated with
a certain shift symmetry for the Higgs doublets, a generalization of the shift
symmetry for singlets in earlier models. We find that K-flat direction has
This shift symmetry is broken by interactions coming from
the superpotential and gauge fields. This direction fails to produce successful
inflation in the MSSM but produces a viable model in the NMSSM. The model is
specifically interesting in the Peccei-Quinn (PQ) limit of the NMSSM. In this
limit the model can be confirmed or ruled-out not just by cosmic microwave
background observations but also by axion searches.Comment: matches the published version at JCA
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