scholarly journals Nuclear coalescence and collective behaviour in small interacting systems

2022 ◽  
Author(s):  
Jonas Tjemsland ◽  
M. Kachelriess ◽  
S. Ostapchenko
Keyword(s):  
Collective Behaviour ◽  
Interacting Systems

scholarly journals Effects of energy extensivity on the quantum phases of long-range interacting systems

2021 ◽  
Vol 103 (15) ◽  
Author(s):  
T. Botzung ◽  
D. Hagenmüller ◽  
G. Masella ◽  
J. Dubail ◽  
N. Defenu ◽  
...  
Keyword(s):  
Long Range ◽  
Quantum Phases ◽  
Interacting Systems

Collective behaviour can stabilize ecosystems

2021 ◽  
Author(s):  
Benjamin D. Dalziel ◽  
Mark Novak ◽  
James R. Watson ◽  
Stephen P. Ellner
Keyword(s):  
Collective Behaviour

scholarly journals Fishing out collective memory of migratory schools

2014 ◽  
Vol 11 (95) ◽  
pp. 20140043 ◽  
Author(s):  
Giancarlo De Luca ◽  
Patrizio Mariani ◽  
Brian R. MacKenzie ◽  
Matteo Marsili
Keyword(s):  
Collective Memory ◽  
Large Scale ◽  
Group Formation ◽  
Individual Preference ◽  
Relative Number ◽  
Collective Behaviour ◽  
Control Group ◽  
Adaptive Networks ◽  
Modelling Framework ◽  
Migration Pathways

Animals form groups for many reasons, but there are costs and benefits associated with group formation. One of the benefits is collective memory. In groups on the move, social interactions play a crucial role in the cohesion and the ability to make consensus decisions. When migrating from spawning to feeding areas, fish schools need to retain a collective memory of the destination site over thousands of kilometres, and changes in group formation or individual preference can produce sudden changes in migration pathways. We propose a modelling framework, based on stochastic adaptive networks, that can reproduce this collective behaviour. We assume that three factors control group formation and school migration behaviour: the intensity of social interaction, the relative number of informed individuals and the strength of preference that informed individuals have for a particular migration area. We treat these factors independently and relate the individuals’ preferences to the experience and memory for certain migration sites. We demonstrate that removal of knowledgeable individuals or alteration of individual preference can produce rapid changes in group formation and collective behaviour. For example, intensive fishing targeting the migratory species and also their preferred prey can reduce both terms to a point at which migration to the destination sites is suddenly stopped. The conceptual approaches represented by our modelling framework may therefore be able to explain large-scale changes in fish migration and spatial distribution.

scholarly journals Collective Losses of Low Power Cage Induction Motors—A New Approach

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1749
Author(s):  
Elzbieta Szychta ◽  
Leszek Szychta
Keyword(s):  
Control System ◽  
Experimental Studies ◽  
Complex Problem ◽  
Accurate Estimation ◽  
New Approach ◽  
Water Pumping ◽  
Efficiency Control ◽  
Interacting Systems ◽  
Cage Induction Motor ◽  
Selection Of

Energy efficiency of systems of water pumping is a complex problem since efficiency of two distinct interacting systems needs to be combined: water and power supply. This paper introduces a non-intrusive method of calculating the so-called “collective losses” of a cage induction motor. The term “collective losses”, which the authors define, allows for accurate estimation of motor efficiency. Control system of a pump determines operating point of a pumping station, and thus its efficiency. General estimated performance characteristics of a motor, components of a control system, are assumed to serve selection of a range of pumping speed variations. Rotational speed has a direct effect on motor load torque, pump power and head, and thus on motor performance. Hellwig’s statistical method was used to specify characteristics of estimated collective losses on the basis of experimental studies of 21 motors rated at up to 2.2 kW. The results of simulations and experiments are used to verify validity and efficiency of the suggested method. The method is non-intrusive, simple to use, and requires minimum data.

scholarly journals Reflective and Impulsive Determinants of Social Behavior

2004 ◽  
Vol 8 (3) ◽  
pp. 220-247 ◽  
Author(s):  
Fritz Strack ◽  
Roland Deutsch
Keyword(s):  
Social Behavior ◽  
Impulsive System ◽  
Dual Process ◽  
Mental Functioning ◽  
Systems Model ◽  
Proposed Model ◽  
Interacting Systems ◽  
Impulsive Model ◽  
Impulsive Processes ◽  
Behavioral Mechanisms

This article describes a 2-systems model that explains social behavior as a joint function of reflective and impulsive processes. In particular, it is assumed that social behavior is controlled by 2 interacting systems that follow different operating principles. The reflective system generates behavioral decisions that are based on knowledge about facts and values, whereas the impulsive system elicits behavior through associative links and motivational orientations. The proposed model describes how the 2 systems interact at various stages of processing, and how their outputs may determine behavior in a synergistic or antagonistic fashion. It extends previous models by integrating motivational components that allow more precise predictions of behavior. The implications of this reflective-impulsive model are applied to various phenomena from social psychology and beyond. Extending previous dual-process accounts, this model is not limited to specific domains of mental functioning and attempts to integrate cognitive, motivational, and behavioral mechanisms.

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