Simple gestalts: Emergent features in two-line stimulus space

2009 ◽  
Author(s):  
James R. Pomerantz ◽  
Anna I. Stupina
Keyword(s):  
Stimulus Space ◽  
Line Stimulus ◽  
Emergent Features

Visual Attention Within the Generation of Emergent Features for Novel Metaphors

2014 ◽  
Author(s):  
Asuka Terai ◽  
Masanori Nakagawa ◽  
Takashi Kusumi ◽  
Yasuharu Koike ◽  
Koji Jimura
Keyword(s):  
Visual Attention ◽  
Emergent Features

scholarly journals Actin and Microtubules Differently Contribute to Vacuolar Targeting Specificity during the Export from the ER

Membranes ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 299
Author(s):  
Monica De Caroli ◽  
Fabrizio Barozzi ◽  
Luciana Renna ◽  
Gabriella Piro ◽  
Gian-Pietro Di Sansebastiano
Keyword(s):  
Spatial Targeting ◽  
Traffic Regulation ◽  
Emergent Features ◽  
Vacuolar Sorting ◽  
Er Export ◽  
Golgi Network ◽  
Relationship Of ◽  
The Relationship ◽  
Fine Tune

Plants rely on both actin and microtubule cytoskeletons to fine-tune sorting and spatial targeting of membranes during cell growth and stress adaptation. Considerable advances have been made in recent years in the comprehension of the relationship between the trans-Golgi network/early endosome (TGN/EE) and cytoskeletons, but studies have mainly focused on the transport to and from the plasma membrane. We address here the relationship of the cytoskeleton with different endoplasmic reticulum (ER) export mechanisms toward vacuoles. These emergent features of the plant endomembrane traffic are explored with an in vivo approach, providing clues on the traffic regulation at different levels beyond known proteins’ functions and interactions. We show how traffic of vacuolar markers, characterized by different vacuolar sorting determinants, diverges at the export from the ER, clearly involving different components of the cytoskeleton.

scholarly journals On the Many-Body Expansion of an Interaction Energy of Some Supramolecular Halogen-Containing Capsules

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4431
Author(s):  
Jiří Czernek ◽  
Jiří Brus
Keyword(s):  
Density Functional ◽  
Condensed Phases ◽  
Multicomponent Mixtures ◽  
Many Body ◽  
Symmetric Form ◽  
Functional Theory ◽  
Emergent Features ◽  
The Many ◽  
Surprising Fact ◽  
Dimethyl Benzene

A tetramer model was investigated of a remarkably stable iodine-containing supramolecular capsule that was most recently characterized by other authors, who described emergent features of the capsule’s formation. In an attempt to address the surprising fact that no strong pair-wise interactions between any of the respective components were experimentally detected in condensed phases, the DFT (density-functional theory) computational model was used to decompose the total stabilization energy as a sum of two-, three- and four-body contributions. This model considers complexes formed between either iodine or bromine and the crucial D4h-symmetric form of octaaryl macrocyclic compound cyclo[8](1,3-(4,6-dimethyl)benzene that is surrounded by arenes of a suitable size, namely, either corannulene or coronene. A significant enthalpic gain associated with the formation of investigated tetramers was revealed. Furthermore, it is shown that the total stabilization of these complexes is dominated by binary interactions. Based on these findings, comments are made regarding the experimentally observed behavior of related multicomponent mixtures.

scholarly journals Automated Framework for the Inclusion of a His–Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology

2021 ◽  
Author(s):  
Karli Gillette ◽  
Matthias A. F. Gsell ◽  
Julien Bouyssier ◽  
Anton J. Prassl ◽  
Aurel Neic ◽  
...  
Keyword(s):  
Cardiac Electrophysiology ◽  
Ventricular Myocardium ◽  
Activation Patterns ◽  
Purkinje System ◽  
Digital Twins ◽  
Emergent Features ◽  
Ventricular Activation ◽  
Endocardial Layer ◽  
Right Ventricular Apical Pacing ◽  
Electrocardiogram Ecg

AbstractPersonalized models of cardiac electrophysiology (EP) that match clinical observation with high fidelity, referred to as cardiac digital twins (CDTs), show promise as a tool for tailoring cardiac precision therapies. Building CDTs of cardiac EP relies on the ability of models to replicate the ventricular activation sequence under a broad range of conditions. Of pivotal importance is the His–Purkinje system (HPS) within the ventricles. Workflows for the generation and incorporation of HPS models are needed for use in cardiac digital twinning pipelines that aim to minimize the misfit between model predictions and clinical data such as the 12 lead electrocardiogram (ECG). We thus develop an automated two stage approach for HPS personalization. A fascicular-based model is first introduced that modulates the endocardial Purkinje network. Only emergent features of sites of earliest activation within the ventricular myocardium and a fast-conducting sub-endocardial layer are accounted for. It is then replaced by a topologically realistic Purkinje-based representation of the HPS. Feasibility of the approach is demonstrated. Equivalence between both HPS model representations is investigated by comparing activation patterns and 12 lead ECGs under both sinus rhythm and right-ventricular apical pacing. Predominant ECG morphology is preserved by both HPS models under sinus conditions, but elucidates differences during pacing.

Boundary spanning tactics and “traceable” connections in cross-organizational virtual alliances

2014 ◽  
Vol 27 (2) ◽  
pp. 197-227 ◽  
Author(s):  
Demosthenes Akoumianakis
Keyword(s):  
Boundary Spanning ◽  
Online Collaboration ◽  
Knowledge Visualization ◽  
Content Type ◽  
Trace Data ◽  
Emergent Features ◽  
Hidden Knowledge ◽  
Practice Knowledge ◽  
Visualization Techniques ◽  
Social Collective

Purpose – The purpose of this paper is to investigate boundary spanning tactics in a cross-organizational virtual alliance and discuss the analytical value of “digging” into technology for excavating boundaries and understanding their dynamic and emergent features. Design/methodology/approach – Although boundaries, their role and implications have been extensively investigated across a variety of online settings, the results are inconclusive as to the features of technology that create, dissolve or re-locate boundaries. This is attributed to the fact that in most cases technology is addressed as a black box – a discrete artefact of practice – without seeking justification for the inscribed functions that enable or constrain use. The paper overcomes these shortcomings by analysing digital trace data compiled through a virtual ethnographic assessment of a cross-organizational tourism alliance. Data comprise electronic traces of online collaboration whose interpretive capacity is augmented using knowledge visualization techniques capable of revealing dynamic and emergent features of boundary spanning. Findings – Boundary spanning in virtual settings entails micro-negotiations around several types of boundaries. Some of them are either enforced by or inscribed into technology, while others are enacted in practice. Knowledge visualization of digital trace data allows “excavation” of these boundaries, assessment of their implications on distributed organizing of online ensembles and discovery of “hidden” knowledge that drives boundary spanning tactics of collaborators. Practical implications – In cross-organizational collaborative settings, boundary spanning represents an enacted capability stemming from the intertwining between material and social/collective agencies. Consequently, boundaries surface as first class design constructs, directing design attention not only to features inscribed in technology (i.e. user profiles, registration mechanisms, moderation policies) but also the way such features are appropriated to re-shape, re-locate or dissolve boundaries. Originality/value – An empirical data pool compiled through virtual ethnographic assessment of online collaboration is revisited and augmented with knowledge visualization techniques that enhance the interpretive capacity of the data and reveal “hidden” aspects of the collaborators’ boundary spanning behaviour and tactics.

scholarly journals 'n Multidimensionele skaleringstudie van personeelkonsultantgroepe in Suid Afrika

1988 ◽  
Vol 14 (2) ◽  
Author(s):  
C. C. Theron ◽  
L. C. De Jager
Keyword(s):  
South Africa ◽  
Multidimensional Scaling ◽  
Ideal Point ◽  
Stimulus Space

A multidimentional scaling study of personnel consultancy groups in South Africa. Ten 12x12 symetric dissimilarity matrices of inter personnel consultant comparisons were submitted to weigthed multidimensional scaling. Vector and ideal point models were used to relate preference and con- sultant attributes to the group stimulus space. Results indicate that the hypothetical ideal consultant differs significantly from existing consultancies and that there exists a partial incongruence between the attributes used spontaneously when comparing a number of consultancies and the critical consultant attributes identified in the literature. Recommendations for further research are made. Opsomming Tien 12x12 simmetriese dissimilariteitsmatrikse van interpersoneelkonsultante-beoordelings is onderwerp aan matriksgeweegde multidimensionele skating. Vektor n "ideal point" modelle is gebruik om voorkeur en konsultantattribute met die groepstimulusruimte in verband te bring. Resultate dui daarop dat die hipotetiese ideate konsultant betekenisvol verskil van bestaande konsultantaanbiedinge en dat daar 'n element van inkongruensie bestaan tussen die attribute wat spontaan na vore tree by onderlinge vergelyking van konsultantgroepe en die kritieke attribute soos deur die literatuur geidentifiseer. Aanbevelings vir verdere studie word gemaak.

scholarly journals Comparing continual task learning in minds and machines

2018 ◽  
Vol 115 (44) ◽  
pp. E10313-E10322 ◽  
Author(s):  
Timo Flesch ◽  
Jan Balaguer ◽  
Ronald Dekker ◽  
Hamed Nili ◽  
Christopher Summerfield
Keyword(s):  
Human Error ◽  
Human Performance ◽  
Deep Neural Networks ◽  
Artificial Agents ◽  
Trial And Error ◽  
Stimulus Space ◽  
Cognitive Mechanisms ◽  
Error Training ◽  
Multiple Tasks ◽  
Continual Learning

Humans can learn to perform multiple tasks in succession over the lifespan (“continual” learning), whereas current machine learning systems fail. Here, we investigated the cognitive mechanisms that permit successful continual learning in humans and harnessed our behavioral findings for neural network design. Humans categorized naturalistic images of trees according to one of two orthogonal task rules that were learned by trial and error. Training regimes that focused on individual rules for prolonged periods (blocked training) improved human performance on a later test involving randomly interleaved rules, compared with control regimes that trained in an interleaved fashion. Analysis of human error patterns suggested that blocked training encouraged humans to form “factorized” representation that optimally segregated the tasks, especially for those individuals with a strong prior bias to represent the stimulus space in a well-structured way. By contrast, standard supervised deep neural networks trained on the same tasks suffered catastrophic forgetting under blocked training, due to representational interference in the deeper layers. However, augmenting deep networks with an unsupervised generative model that allowed it to first learn a good embedding of the stimulus space (similar to that observed in humans) reduced catastrophic forgetting under blocked training. Building artificial agents that first learn a model of the world may be one promising route to solving continual task performance in artificial intelligence research.

scholarly journals A one-dimensional modified TASEP model on a track of variable length: analytical and computational results

2021 ◽  
Vol 2090 (1) ◽  
pp. 012025
Author(s):  
B. Reed ◽  
E. Aldrich ◽  
L. Stoleriu ◽  
D.A. Mazilu ◽  
I. Mazilu
Keyword(s):  
Monte Carlo ◽  
Molecular Motors ◽  
Mean Field Theory ◽  
Mean Field ◽  
Limited Range ◽  
Field Methods ◽  
One Dimensional ◽  
Emergent Features ◽  
Simulation Results ◽  
Mean Field Methods

Abstract We present analytical solutions and Monte Carlo simulation results for a one-dimensional modified TASEP model inspired by the interplay between molecular motors and their cellular tracks of variable lengths, known as microtubules. Our TASEP model incorporates rules for changes in the length of the track based on the occupation of the first two sites. Using mean-field theory, we derive analytical results for the particle densities and particle currents and compare them with Monte Carlo simulations. These results show the limited range of mean-field methods for models with localized high correlation between particles. The variability in length adds to the complexity of the model, leading to emergent features for the evolution of particle densities and particle currents compared to the traditional TASEP model.

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