69 research outputs found
Conditional statistics of electron transport in interacting nanoscale conductors
Interactions between nanoscale semiconductor structures form the basis for
charge detectors in the solid state. Recent experimental advances have
demonstrated the on-chip detection of single electron transport through a
quantum dot (QD). The discreteness of charge in units of e leads to intrinsic
fluctuations in the electrical current, known as shot noise. To measure these
single-electron fluctuations a nearby coherent conductor, called a quantum
point contact (QPC), interacts with the QD and acts as a detector. An important
property of the QPC charge detector is noninvasiveness: the system physically
affects the detector, not visa-versa. Here we predict that even for ideal
noninvasive detectors such as the QPC, when a particular detector result is
observed, the system suffers an informational backaction, radically altering
the statistics of transport through the QD as compared to the unconditional
shot noise. We develop a theoretical model to make predictions about the joint
current probability distributions and conditional transport statistics. The
experimental findings reported here demonstrate the reality of informational
backaction in nanoscale systems as well as a variety of new effects, such as
conditional noise enhancement, which are in essentially perfect agreement with
our model calculations. This type of switching telegraph process occurs
abundantly in nature, indicating that these results are applicable to a wide
variety of systems.Comment: 16 pages, 3 figures, to appear in Nature Physic
Exploring the Free Energy Landscape: From Dynamics to Networks and Back
The knowledge of the Free Energy Landscape topology is the essential key to
understand many biochemical processes. The determination of the conformers of a
protein and their basins of attraction takes a central role for studying
molecular isomerization reactions. In this work, we present a novel framework
to unveil the features of a Free Energy Landscape answering questions such as
how many meta-stable conformers are, how the hierarchical relationship among
them is, or what the structure and kinetics of the transition paths are.
Exploring the landscape by molecular dynamics simulations, the microscopic data
of the trajectory are encoded into a Conformational Markov Network. The
structure of this graph reveals the regions of the conformational space
corresponding to the basins of attraction. In addition, handling the
Conformational Markov Network, relevant kinetic magnitudes as dwell times or
rate constants, and the hierarchical relationship among basins, complete the
global picture of the landscape. We show the power of the analysis studying a
toy model of a funnel-like potential and computing efficiently the conformers
of a short peptide, the dialanine, paving the way to a systematic study of the
Free Energy Landscape in large peptides.Comment: PLoS Computational Biology (in press
An experimentally-achieved information-driven Brownian motor shows maximum power at the relaxation time
We present an experimental realization of an information-driven Brownian motor by periodically cooling a Brownian particle trapped in a harmonic potential connected to a single heat bath, where cooling is carried out by the information process consisting of measurement and feedback control. We show that the random motion of the particle is rectified by symmetry-broken feedback cooling where the particle is cooled only when it resides on the specific side of the potential center at the instant of measurement. Studying how the motor thermodynamics depends on cycle period tau relative to the relaxation time tau(B) of the Brownian particle, we find that the ratcheting of thermal noise produces the maximum work extraction when tau >= 5 tau(B) while the extracted power is maximum near tau= tau(B), implying the optimal operating time for the ratcheting process. In addition, we find that the average transport velocity is monotonically decreased as tau increases and present the upper bound for the velocity
What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology
Stochastic resonance is said to be observed when increases in levels of unpredictable fluctuations—e.g., random noise—cause an increase in a metric of the quality of signal transmission or detection performance, rather than a decrease. This counterintuitive effect relies on system nonlinearities and on some parameter ranges being “suboptimal”. Stochastic resonance has been observed, quantified, and described in a plethora of physical and biological systems, including neurons. Being a topic of widespread multidisciplinary interest, the definition of stochastic resonance has evolved significantly over the last decade or so, leading to a number of debates, misunderstandings, and controversies. Perhaps the most important debate is whether the brain has evolved to utilize random noise in vivo, as part of the “neural code”. Surprisingly, this debate has been for the most part ignored by neuroscientists, despite much indirect evidence of a positive role for noise in the brain. We explore some of the reasons for this and argue why it would be more surprising if the brain did not exploit randomness provided by noise—via stochastic resonance or otherwise—than if it did. We also challenge neuroscientists and biologists, both computational and experimental, to embrace a very broad definition of stochastic resonance in terms of signal-processing “noise benefits”, and to devise experiments aimed at verifying that random variability can play a functional role in the brain, nervous system, or other areas of biology
Effects of a pulmonary rehabilitation program on physical capacity, peripheral muscle function and inflammatory markers in asthmatic children and adolescents: study protocol for a randomized controlled trial
Efficacy and cost-effectiveness of a web-based and mobile stress-management intervention for employees: design of a randomized controlled trial
Background: Work-related stress is associated with a variety of mental and emotional problems and can lead to substantial economic costs due to lost productivity, absenteeism or the inability to work. There is a considerable amount of evidence on the effectiveness of traditional face-to-face stress-management interventions for employees; however, they are often costly, time-consuming, and characterized by a high access threshold. Web-based interventions may overcome some of these problems yet the evidence in this field is scarce. This paper describes the protocol for a study that will examine the efficacy and cost-effectiveness of a web-based guided stress-management training which is based on problem solving and emotion regulation and aimed at reducing stress in adult employees. Methods. The study will target stressed employees aged 18 and older. A randomized controlled trial (RCT) design will be applied. Based on a power calculation of d=.35 (1-β of 80%, α =.05), 264 participants will be recruited and randomly assigned to either the intervention group or a six-month waitlist control group. Inclusion criteria include an elevated stress level (Cohen's Perceived Stress Scale-10 ≥ 22) and current employment. Exclusion criteria include risk of suicide or previously diagnosed psychosis or dissociative symptoms. The primary outcome will be perceived stress, and secondary outcomes include depression and anxiety. Data will be collected at baseline and seven weeks and six months after randomization. An extended follow up at 12 months is planned for the intervention group. Moreover, a cost-effectiveness analysis will be conducted from a societal perspective and will include both direct and indirect health care costs. Data will be analyzed on an intention-to-treat basis and per protocol. Discussion. The substantial negative consequences of work-related stress emphasize the necessity for effective stress-management trainings. If the proposed internet intervention proves to be (cost-) effective, a preventative, economical stress-management tool will be conceivable. The strengths and limitations of the present study are discussed. Trial registration. German Register of Clinical Studies (DRKS): DRKS00004749. © 2013 Heber et al.; licensee BioMed Central Ltd
Developmental dyscalculia: a dysconnection syndrome?
Numerical understanding is important for everyday life. For children with developmental dyscalculia (DD), numbers and magnitudes present profound problems which are thought to be based upon neuronal impairments of key regions for numerical understanding. The aim of the present study was to investigate possible differences in white matter fibre integrity between children with DD and controls using diffusion tensor imaging. White matter integrity and behavioural measures were evaluated in 15 children with developmental dyscalculia aged around 10 years and 15 matched controls. The main finding, obtained by a whole brain group comparison, revealed reduced fractional anisotropy in the superior longitudinal fasciculus in children with developmental dyscalculia. In addition, a region of interest analysis exhibited prominent deficits in fibres of the superior longitudinal fasciculus adjacent to the intraparietal sulcus, which is thought to be the core region for number processing. To conclude, our results outline deficient fibre projection between parietal, temporal and frontal regions in children with developmental dyscalculia, and therefore raise the question of whether dyscalculia can be seen as a dysconnection syndrome. Since the superior longitudinal fasciculus is involved in the integration and control of distributed brain processes, the present results highlight the importance of considering broader domain-general mechanisms in the diagnosis and therapy of dyscalculia
Sedentary behavior in children by wearable vameras: Development of an annotation protocol
Introduction
There is increasing evidence that not all types of sedentary behavior have the same harmful effects on children's health. Hence, there has been a growing interest in the use of wearable cameras. The aim of this study is to develop a protocol to categorize children's wearable camera data into sedentary behavior components.
Methods
Wearable camera data were collected in 3 different samples of children in 2014. A development sample (3 children aged 4–8 years) was used to design the annotation protocol. A training sample (4 children aged 10 years) was used to train 3 different coders. The independent reliability sample (14 children aged 9–11 years) was used for independent coding of wearable camera images and to estimate inter-rater agreement. Data were analyzed in 2018. Cohen's κ was calculated for every rater pair on a per-participant basis. Means and SDs were then calculated across per-participant κ scores.
Results
A total of 41,651 images from 14 participants were considered for analysis. Inter-rater agreement over all raters over all the sedentary behavior components was almost perfect (mean κ=0.85, 95% CI=0.83, 0.87). Inter-rater reliability for screen-based sedentary behavior (mean κ=0.72, 95% CI=0.62, 0.82) and nonscreen sedentary behavior (κ=0.69, 95% CI=0.65, 0.72) showed substantial agreement. Inter-rater reliability for location (κ=0.91, 95% CI=0.88, 0.93) showed almost perfect agreement.
Conclusions
A reliable annotation protocol to categorize wearable camera data of children into sedentary behavior components was developed. Once applied to larger samples in children, this protocol can ultimately help to better understand the potential harms of screen time and sedentary behavior in children
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