233 research outputs found
New aspects of the continuous phase transition in the scalar noise model (SNM) of collective motion
In this paper we present our detailed investigations on the nature of the
phase transition in the scalar noise model (SNM) of collective motion. Our
results confirm the original findings of Vicsek et al. [Phys. Rev. Lett. 75
(1995) 1226] that the disorder-order transition in the SNM is a continuous,
second order phase transition for small particle velocities ().
However, for large velocities () we find a strong anisotropy in the
particle diffusion in contrast with the isotropic diffusion for small
velocities. The interplay between the anisotropic diffusion and the periodic
boundary conditions leads to an artificial symmetry breaking of the solutions
(directionally quantized density waves) and a consequent first order transition
like behavior. Thus, it is not possible to draw any conclusion about the
physical behavior in the large particle velocity regime of the SNM.Comment: 13 pages, 11 figure
Towards a Process Algebra for Shared Processors
AbstractWe present initial work on a timed process algebra that models sharing of processor resources allowing preemption at arbitrary points in time. This enables us to model both the functional and the timely behaviour of concurrent processes executed on a single processor. We give a refinement relation that describes that one process is more deterministic than another. Applications of the model for process scheduling, programming language semantics, and kernel development are outlined
Accelerating consensus of self-driven swarm via adaptive speed
In resent years, Vicsek model has attracted more and more attention and been
well developed. However, the in-depth analysis on the convergence time are
scarce thus far. In this paper, we study some certain factors that mainly
govern the convergence time of Vicsek model. By extensively numerical
simulations, we find the convergence time scales in a power law with
in the noise-free case, where and are horizon radius and the number of
particles. Furthermore, to accelerate the convergence, we propose a new model
in which the speed of each particle is variable. The convergence time can be
remarkably shortened compared with the standard Vicsek model.Comment: 11 pages, 6 figure
Wireless Neurosensor for Full-Spectrum Electrophysiology Recordings during Free Behavior
SummaryBrain recordings in large animal models and humans typically rely on a tethered connection, which has restricted the spectrum of accessible experimental and clinical applications. To overcome this limitation, we have engineered a compact, lightweight, high data rate wireless neurosensor capable of recording the full spectrum of electrophysiological signals from the cortex of mobile subjects. The wireless communication system exploits a spatially distributed network of synchronized receivers that is scalable to hundreds of channels and vast environments. To demonstrate the versatility of our wireless neurosensor, we monitored cortical neuron populations in freely behaving nonhuman primates during natural locomotion and sleep-wake transitions in ecologically equivalent settings. The interface is electrically safe and compatible with the majority of existing neural probes, which may support previously inaccessible experimental and clinical research
Can we estimate catchment-scale biomass production from sedimentary biomarkers? An attempt with miliacin in Late Bronze Age levels from Lake le Bourget (French Alps).
International audienceThe evaluation of demography for proto- and prehistoric times remains complex due to the rareness of human remains. Here we propose an original approach based on the combination of geophysical and organic geochemical techniques applied to the Late Bronze Age sedimentary infill of Lake le Bourget. Deep sediments were mapped and their volume estimated by sub-bottom seismic profiling calibrated (accoustically and chronologically) on piston cores. Multibeam bathymetry combined to a subaquatic archaeological survey allowed to precisely identify the extension of Late Bronze Age palafittic stations in shallow waters and to determine the volume of the associated organic rich deposits
Modeling Vortex Swarming In Daphnia
Based on experimental observations in \textit{Daphnia}, we introduce an
agent-based model for the motion of single and swarms of animals. Each agent is
described by a stochastic equation that also considers the conditions for
active biological motion. An environmental potential further reflects local
conditions for \textit{Daphnia}, such as attraction to light sources. This
model is sufficient to describe the observed cycling behavior of single
\textit{Daphnia}. To simulate vortex swarming of many \textit{Daphnia}, i.e.
the collective rotation of the swarm in one direction, we extend the model by
considering avoidance of collisions. Two different ansatzes to model such a
behavior are developed and compared. By means of computer simulations of a
multi-agent system we show that local avoidance - as a special form of
asymmetric repulsion between animals - leads to the emergence of a vortex
swarm. The transition from uncorrelated rotation of single agents to the vortex
swarming as a function of the swarm size is investigated. Eventually, some
evidence of avoidance behavior in \textit{Daphnia} is provided by comparing
experimental and simulation results for two animals.Comment: 24 pages including 11 multi-part figs. Major revisions compared to
version 1, new results on transition from uncorrelated rotation to vortex
swarming. Extended discussion. For related publications see
http://www.sg.ethz.ch/people/scfrank/Publication
Association between cannabis use and symptom dimensions in schizophrenia spectrum disorders: an individual participant data meta-analysis on 3053 individuals
Background: The association between cannabis use and positive symptoms in schizophrenia spectrum disorders is well documented, especially via meta-analyses. Yet, findings are inconsistent regarding negative symptoms, while other dimensions such as disorganization, depression, and excitement, have not been investigated. In addition, meta-analyses use aggregated data discarding important confounding variables which is a source of bias.
Methods: PubMed, ScienceDirect and PsycINFO were used to search for publications from inception to September 27, 2022. We contacted the authors of relevant studies to extract raw datasets and perform an Individual Participant Data meta-analysis (IPDMA). Inclusion criteria were: psychopathology of individuals with schizophrenia spectrum disorders assessed by the Positive and Negative Syndrome Scale (PANSS); cannabis-users had to either have a diagnosis of cannabis use disorder or use cannabis at least twice a week. The main outcomes were the PANSS subscores extracted via the 3-factor (positive, negative and general) and 5-factor (positive, negative, disorganization, depression, excitement) structures. Preregistration is accessible via Prospero: ID CRD42022329172.
Findings: Among the 1149 identified studies, 65 were eligible and 21 datasets were shared, totaling 3677 IPD and 3053 complete cases. The adjusted multivariate analysis revealed that relative to non-use, cannabis use was associated with higher severity of positive dimension (3-factor: Adjusted Mean Difference, aMD = 0.34, 95% Confidence Interval, CI = [0.03; 0.66]; 5-factor: aMD = 0.38, 95% CI = [0.08; 0.63]), lower severity of negative dimension (3-factor: aMD = -0.49, 95% CI [-0.90; -0.09]; 5-factor: aMD = -0.50, 95% CI = [-0.91; -0.08]), higher severity of excitement dimension (aMD = 0.16, 95% CI = [0.03; 0.28]). No association was found between cannabis use and disorganization (aMD = -0.13, 95% CI = [-0.42; 0.17]) or depression (aMD = -0.14, 95% CI = [-0.34; 0.06]).
Interpretation: No causal relationship can be inferred from the current results. The findings could be in favor of both a detrimental and beneficial effect of cannabis on positive and negative symptoms, respectively. Longitudinal designs are needed to understand the role of cannabis is this association. The reported effect sizes are small and CIs are wide, the interpretation of findings should be taken with caution
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