Simulating three dimensional self-assembly of shape modified particles using magnetic dipolar forces

The feasibility of 3D self-assembly of milli-magnetic particles that interact via magnetic dipolar forces is investigated. Typically magnetic particles, such as isotropic spheres, self-organize in stable 2D configurations. By modifying the shape of the particles, 3D self-assembly may be enabled. The design of the particles and the experimental setup are presented. The magnetic configurations of simple particle arrangements are obtained via energy minimization in simulations. The simulations show that a 3D configuration can become energetically favourable over 2D configurations, if the shape of the particle is modified

Forward models demonstrate that repetition suppression is best modelled by local neural scaling

Inferring neural mechanisms from functional magnetic resonance imaging (fMRI) is challenging because the fMRI signal integrates over millions of neurons. One approach is to compare computational models that map neural activity to fMRI responses, to see which best predicts fMRI data. We use this approach to compare four possible neural mechanisms of fMRI adaptation to repeated stimuli (scaling, sharpening, repulsive shifting and attractive shifting), acting across three domains (global, local and remote). Six features of fMRI repetition effects are identified, both univariate and multivariate, from two independent fMRI experiments. After searching over parameter values, only the local scaling model can simultaneously fit all data features from both experiments. Thus fMRI stimulus repetition effects are best captured by down-scaling neuronal tuning curves in proportion to the difference between the stimulus and neuronal preference. These results emphasize the importance of formal modelling for bridging neuronal and fMRI levels of investigation.This work was supported by British Academy postdoctoral fellowship and a Marie Curie fellowship (753441) to A.A., a Cambridge University international scholarship and IDB merit scholarship award to H.A., and Medical Research Council programme grant (SUAG/010 RG91365) to R.N.H

The attentional blink modulates activity in the early visual cortex

The attentional blink (AB) documents a particularly strong case of visual attentional competition, in which subjects' ability to identify a second target (T2) is significantly impaired when it is presented with a short SOA after a first target (T1). We used functional magnetic resonance imaging to investigate the impact of the AB on visual activity in individually defined retinotopic representations of the target stimuli. Our results show reduction of neural response in V3 and marginally in V2 and V1, paralleling the behavioral AB effect. Reduction of visual activity was accompanied by reduced neural response in the inferior parietal cortex. This indicates that attentional competition modulates activity in higher-order parietal regions and the early visual cortex, providing a plausible neural basis of the behavioral AB effect

Humane risicobeoordeling in zicht : een inventarisatie van de mogelijkheden voor het optimaliseren van het gebruik van humane data bij de risicobeoordeling van chemische stoffen in de voeding

Het doel van deze studie was het identificeren van visies op het huidige risicobeoordelingsproces, het optimaliseren van het gebruik van humane data en de samenwerking tussen toxicologie en epidemiologie. Gegevens zijn verkregen middels 23 semigestructureerde interview

RF Circuit linearity optimization using a general weak nonlinearity model

This paper focuses on optimizing the linearity in known RF circuits, by exploring the circuit design space that is usually available in today’s deep submicron CMOS technologies. Instead of using brute force numerical optimizers we apply a generalized weak nonlinearity model that only involves AC transfer functions to derive simple equations for obtaining design insights. The generalized weak nonlinearity model is applied to three known RF circuits: a cascode common source amplifier, a common gate LNA and a CMOS attenuator. It is shown that in deep submicron CMOS technologies the cascode transistor in both the common source amplifier and in the common gate amplifier significantly contributes IM3 distortion. Some design insights are presented for reducing the cascode transistor related distortion, among which moderate inversion biasing that improves IIP3 by 10 dB up to 5 GHz in a 90 nm CMOS process. For the attenuator, a wideband IM3 cancellation technique is introduced and demonstrated using simulations

Measuring and monitoring national prevalence of child maltreatment: A practical handbook

n/

The assimilation of novel information into schemata and its efficient consolidation

Schemata enhance memory formation for related novel information. This is true even when this information is neutral with respect to schema-driven expectations. This assimilation of novel information into schemata has been attributed to more effective organizational processing that leads to more referential connections with the activated associative schema network. Animal data suggest that systems consolidation of novel assimilated information is also accelerated. In the current study, we used both multivariate and univariate fMRI analyses to provide further support for these proposals and to elucidate the neural underpinning of these processes. 28 Participants (5 male) over-learned fictitious schemata for seven weeks and then encoded novel related and control facts in the scanner. These facts were retrieved both immediately and two weeks later, also in the scanner. Our results conceptually replicate previous findings with respect to enhanced vmPFC-hippocampus coupling during encoding of novel related information and point to a prior knowledge-effect that is distinct from situations where novel information is experienced as congruent or incongruent with a schema. Moreover, the combination of both multi- and univariate results further specified the proposed contributions of the vmPFC, precuneus and angular gyrus-network to the more efficient encoding of schema-related information. In addition, our data provide further evidence for more efficient systems consolidation of such novel schema-related and potentially assimilated information

The effectiveness of Video-feedback Intervention to promote Positive Parenting for Foster Care (VIPP-FC)

Background: Foster children are at higher risk of the development of behavior and emotional problems, which can contribute to the development of insecure attachment bonds with their foster parents and (subsequently) to placement breakdown. Sensitive parenting might minimize the adverse effects of the behavior and emotional problems. Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline in Foster Care (VIPP-FC) is an adaptation of the evidence-based Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD) and aims at increasing sensitive parenting and the use of sensitive discipline strategies of foster parents. The current study is the first to examine the effectiveness of VIPP-FC. Methods: A randomized controlled trial is used with 60 foster parent-child dyads (intervention group n=30, control group n=30). The primary outcomes are parental sensitivity, parental disciplining, and parental attitudes towards parenting. Data about attachment (in)security, behavioral and emotional problems, neurobiological parameters, and possible confounders is additionally collected. Discussion: Examining the effectiveness of VIPP-FC contributes to the knowledge of evidence-based prevention and intervention programs needed in foster care practice

Estimation of conditional laws given an extreme component

Let $(X,Y)$ be a bivariate random vector. The estimation of a probability of the form $P(Y\leq y \mid X >t)$ is challenging when $t$ is large, and a fruitful approach consists in studying, if it exists, the limiting conditional distribution of the random vector $(X,Y)$, suitably normalized, given that $X$ is large. There already exists a wide literature on bivariate models for which this limiting distribution exists. In this paper, a statistical analysis of this problem is done. Estimators of the limiting distribution (which is assumed to exist) and the normalizing functions are provided, as well as an estimator of the conditional quantile function when the conditioning event is extreme. Consistency of the estimators is proved and a functional central limit theorem for the estimator of the limiting distribution is obtained. The small sample behavior of the estimator of the conditional quantile function is illustrated through simulations.Comment: 32 pages, 5 figur