scholarly journals Phyllotactic patterning of gerbera flower heads

2021 ◽  
Vol 118 (13) ◽  
pp. e2016304118
Author(s):  
Teng Zhang ◽  
Mikolaj Cieslak ◽  
Andrew Owens ◽  
Feng Wang ◽  
Suvi K. Broholm ◽  
...  
Keyword(s):  
Active Zone ◽  
Computational Models ◽  
Lateral Displacement ◽  
Fibonacci Number ◽  
Gradual Transition ◽  
Gerbera Hybrida ◽  
Circular Pattern ◽  
Zigzag Pattern ◽  
Geometric Regularity

Phyllotaxis, the distribution of organs such as leaves and flowers on their support, is a key attribute of plant architecture. The geometric regularity of phyllotaxis has attracted multidisciplinary interest for centuries, resulting in an understanding of the patterns in the model plants Arabidopsis and tomato down to the molecular level. Nevertheless, the iconic example of phyllotaxis, the arrangement of individual florets into spirals in the heads of the daisy family of plants (Asteraceae), has not been fully explained. We integrate experimental data and computational models to explain phyllotaxis in Gerbera hybrida. We show that phyllotactic patterning in gerbera is governed by changes in the size of the morphogenetically active zone coordinated with the growth of the head. The dynamics of these changes divides the patterning process into three phases: the development of an approximately circular pattern with a Fibonacci number of primordia near the head rim, its gradual transition to a zigzag pattern, and the development of a spiral pattern that fills the head on the template of this zigzag pattern. Fibonacci spiral numbers arise due to the intercalary insertion and lateral displacement of incipient primordia in the first phase. Our results demonstrate the essential role of the growth and active zone dynamics in the patterning of flower heads.

Lung Computational Models and the Role of the Small Airways in Asthma

PEDIATRICS ◽  
2020 ◽  
Vol 146 (Supplement 4) ◽  
pp. S359.2-S360
Author(s):  
Jennilee Eppley ◽  
Todd Mahr
Keyword(s):  
Computational Models ◽  
Small Airways

LANDSLIDE RISK MANAGEMENT IN THE COASTAL ZONE OF THE KUIBYSHEV RESERVOIR DUE THE DESIGN OF HIGH-SPEED LINE "MOSCOW-KAZAN"

2017 ◽  
Author(s):  
Nikolai Petrov ◽  
Nikolai Petrov ◽  
Inna Nikonorova ◽  
Inna Nikonorova ◽  
Vladimir Mashin ◽  
...  
Keyword(s):  
High Speed ◽  
Computational Models ◽  
Stable State ◽  
Landslide Risk ◽  
Kuibyshev Reservoir ◽  
Stepped Surface ◽  
The Stability ◽  
Landslide Slope ◽  
The Village

High-speed railway "Moscow-Kazan" by the draft crosses the Volga (Kuibyshev reservoir) in Chuvashia region 500 m below the village of New Kushnikovo. The crossing plot is a right-bank landslide slope with a stepped surface. Its height is 80 m; the slope steepness -15-16o. The authors should assess the risk of landslides and recommend anti-landslide measures to ensure the safety of the future bridge. For this landslide factors have been analyzed, slope stability assessment has been performed and recommendations have been suggested. The role of the following factors have been analyzed: 1) hydrologic - erosion and abrasion reservoir and runoff role; 2) lithologyc (the presence of Urzhum and Northern Dvina horizons of plastically deformable rocks, displacement areas); 3) hydrogeological (the role of perched, ground and interstratal water); 4) geomorphological (presence of the elemental composition of sliding systems and their structure in the relief); 5) exogeodynamic (cycles and stages of landslide systems development, mechanisms and relationship between landslide tiers of different generations and blocks contained in tiers). As a result 6-7 computational models at each of the three engineering-geological sections were made. The stability was evaluated by the method “of the leaning slope”. It is proved that the slope is in a very stable state and requires the following measures: 1) unloading (truncation) of active heads blocks of landslide tiers) and the edge of the plateau, 2) regulation of the surface and groundwater flow, 3) concrete dam, if necessary.

scholarly journals Role of body stiffness in undulatory swimming: Insights from robotic and computational models

2016 ◽  
Vol 1 (7) ◽  
Author(s):  
Eric D. Tytell ◽  
Megan C. Leftwich ◽  
Chia-Yu Hsu ◽  
Boyce E. Griffith ◽  
Avis H. Cohen ◽  
...  
Keyword(s):  
Computational Models ◽  
Undulatory Swimming

scholarly journals Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Computational Models ◽  
Data Driven ◽  
Urban Systems ◽  
Out Of The Loop ◽  
Urban Futures ◽  
Urban Behaviour ◽  
The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

scholarly journals A Neurocomputational Theory of Nightmares: The role of formal properties of nightmare images

2021 ◽  
Author(s):  
Patrick McNamara ◽  
Wesley J Wildman ◽  
George Hodulik ◽  
David Rohr
Keyword(s):  
Individual Difference ◽  
Parameter Space ◽  
Computational Models ◽  
Computational Simulation ◽  
Time Varying ◽  
Individual Difference Variables ◽  
Image Characteristics ◽  
Nightmare Disorder ◽  
Formal Properties

Abstract Study Objectives To test and extend Levin & Nielsen’s (2007) Affective Network Dysfunction (AND) model with nightmare disorder (ND) image characteristics, and then to implement the extension as a computational simulation, the Disturbed Dreaming Model (DDM). Methods We used AnyLogic V7.2 to computationally implement an extended AND model incorporating quantitative effects of image characteristics including valence, dominance, and arousal. We explored the DDM parameter space by varying parameters, running approximately one million runs, each for one month of model time, varying pathway bifurcation thresholds, image characteristics, and individual-difference variables to quantitively evaluate their combinatory effects on nightmare symptomology. Results The DDM shows that the AND model extended with pathway bifurcations and image properties is computationally coherent. Varying levels of image properties we found that when nightmare images exhibit lower dominance and arousal levels, the ND agent will choose to sleep but then has a traumatic nightmare, whereas, when images exhibit greater than average dominance and arousal levels, the nightmares trigger sleep-avoidant behavior, but lower overall nightmare distress at the price of exacerbating nightmare effects during waking hours. Conclusions Computational simulation of nightmare symptomology within the AND framework suggests that nightmare image properties significantly influence nightmare symptomology. Computational models for sleep and dream studies are powerful tools for testing quantitative effects of variables affecting nightmare symptomology and confirms the value of extending the Levin & Nielsen AND model of disturbed dreaming/ND.

scholarly journals Indirect associations in learning semantic and syntactic lexical relationships

2019 ◽  
Author(s):  
M. Alex Kelly ◽  
David Reitter ◽  
Robert West ◽  
Moojan Ghafurian
Keyword(s):  
Computational Models ◽  
Human Memory ◽  
Learning Support ◽  
Distributional Semantics ◽  
Grammatical Structure ◽  
Word Associations ◽  
Part Of Speech ◽  
Degree Of Separation ◽  
Mechanisms Of Memory

Computational models of distributional semantics (a.k.a. word embeddings) represent a word's meaning in terms of its relationships with all other words. We examine what grammatical information is encoded in distributional models and investigate the role of indirect associations. Distributional models are sensitive to associations between words at one degree of separation, such as 'tiger' and 'stripes', or two degrees of separation, such as 'soar' and 'fly'. By recursively adding higher levels of representations to a computational, holographic model of semantic memory, we construct a distributional model sensitive to associations between words at arbitrary degrees of separation. We find that word associations at four degrees of separation increase the similarity assigned by the model to English words that share part-of-speech or syntactic type. Word associations at four degrees of separation also improve the ability of the model to construct grammatical English sentences. Our model proposes that human memory uses indirect associations to learn part-of-speech and that the basic associative mechanisms of memory and learning support knowledge of both semantics and grammatical structure.

scholarly journals Tonal priming is resistant to changes in pitch height

2020 ◽  
Author(s):  
Jon Prince ◽  
Dominique T Vuvan ◽  
Mark A. Schmuckler ◽  
Thomas T. Scott-Clark
Keyword(s):  
Reaction Time ◽  
Computational Models ◽  
Ceiling Effect ◽  
Behavioral Study ◽  
Pitch Height ◽  
Chord Sequence ◽  
Tonal Context

Research on tonal priming has consistently shown that tonally expected events are processed more efficiently and has confirmed that the locus of the effect is cognitive rather than sensory. However, it is also important to investigate the role of pitch height, because models of tonal priming collapse across octaves, yet it is possible that pitch height may modulate the effectiveness of tonal priming. We systematically tested this issue by varying the pitch heights of a related (tonic) or a less-related (subdominant) target chord following a tonal context. Musically untrained participants (N = 30) made speeded consonant/dissonant judgments of the final chord of an eight-chord sequence. The effects of tonal priming emerged in accuracy and reaction time measures for all octaves, except for a ceiling effect on accuracy in the matching (original pitch height) condition. In a second experiment, we increased the shift to two octaves and compressed the chords to eliminate overlap between the target and context chords; again, tonal priming emerged. These findings have implications for the behavioral study of tonal priming and support the assumption of octave equivalence in computational models.

scholarly journals The role of taking into account the interatomic interaction in predicting the complex of structurally-sensitive properties of steels and alloys for special purpose

2018 ◽  
pp. 361-370
Author(s):  
I.R. Snihura ◽  
D.N. Togobitskaya
Keyword(s):  
Computational Models ◽  
State Parameter ◽  
Interatomic Interaction ◽  
Homogeneous System ◽  
Experimental Information ◽  
Structure Property ◽  
Chain Composition ◽  
Forecast Models ◽  
Composition Structure

The aim of the work is to identify the influence of the chemical composition of steels and special-purpose alloys on the formation of their physicochemical and structural-sensitive properties. This problem is solved by mathematical modeling of the inseparable chain «composition - structure – property» taking into account the parameters of interatomic interaction in the melt based on the concept of a directed chemical bond. A steel melt is considered as a chemically homogeneous system, and the state of the melts is expressed through a set of integral parameters, the main of which are: Zy - system charge state parameter (e); r - statistically average internuclear distance (10-1nm); tgα is a constant for each element, which characterizes the change in the radius of the ion as its charge changes. On the basis of experimental information on properties and using the parameters of interatomic interaction, computational models are proposed for predicting the properties of steels and alloys. The forecast models took into account the parameters of micro-inhomogeneity of steel, which ensured a high accuracy of the operational forecast. A comparative analysis of the results of steel melting with the corresponding calculations based on the JMatPro software package confirmed the effectiveness of using the interatomic interaction parameters as models. The proposed models for determining the melting of chromium-nickel steels are recommended for use with the content of basic elements Cr, Ni from 0 to 30%. The research results are recommended for use in industrial environments through the integration of the developed models in the process control system of steelmaking, which will contribute to the directed formation of the composition and properties of smelting products, as well as reducing energy costs.

scholarly journals What is the role of computational models in Cognitive Science? A quantitative and qualitative analysis of the history of the TRACE model of speech segmentation

2019 ◽  
Author(s):  
Manisha Chawla ◽  
Richard Shillcock
Keyword(s):  
Qualitative Analysis ◽  
Cognitive Science ◽  
Computational Models ◽  
Computational Modelling ◽  
Speech Segmentation ◽  
Cognitive Modelling ◽  
Trace Model ◽  
History Of ◽  
Central Paradigm

Implemented computational models are a central paradigm of Cognitive Science. How do cognitive scientists really use such models? We take the example of one of the most successful and influential cognitive models, TRACE (McClelland & Elman, 1986), and we map its impact on the field in terms of published, electronically available documents that cite the original TRACE paper over a period of 25 years since its publication. We draw conclusions about the general status of computational cognitive modelling and make critical suggestions regarding the nature of abstraction in computational modelling.

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