Self-organization principles of intracellular pattern formation.

PubMed

Halatek, J; Brauns, F; Frey, E

2018-05-26

Dynamic patterning of specific proteins is essential for the spatio-temporal regulation of many important intracellular processes in prokaryotes, eukaryotes and multicellular organisms. The emergence of patterns generated by interactions of diffusing proteins is a paradigmatic example for self-organization. In this article, we review quantitative models for intracellular Min protein patterns in Escherichia coli , Cdc42 polarization in Saccharomyces cerevisiae and the bipolar PAR protein patterns found in Caenorhabditis elegans By analysing the molecular processes driving these systems we derive a theoretical perspective on general principles underlying self-organized pattern formation. We argue that intracellular pattern formation is not captured by concepts such as 'activators', 'inhibitors' or 'substrate depletion'. Instead, intracellular pattern formation is based on the redistribution of proteins by cytosolic diffusion, and the cycling of proteins between distinct conformational states. Therefore, mass-conserving reaction-diffusion equations provide the most appropriate framework to study intracellular pattern formation. We conclude that directed transport, e.g. cytosolic diffusion along an actively maintained cytosolic gradient, is the key process underlying pattern formation. Thus the basic principle of self-organization is the establishment and maintenance of directed transport by intracellular protein dynamics.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Authors.

Phase separation driven by density-dependent movement: A novel mechanism for ecological patterns.

PubMed

Liu, Quan-Xing; Rietkerk, Max; Herman, Peter M J; Piersma, Theunis; Fryxell, John M; van de Koppel, Johan

2016-12-01

Many ecosystems develop strikingly regular spatial patterns because of small-scale interactions between organisms, a process generally referred to as spatial self-organization. Self-organized spatial patterns are important determinants of the functioning of ecosystems, promoting the growth and survival of the involved organisms, and affecting the capacity of the organisms to cope with changing environmental conditions. The predominant explanation for self-organized pattern formation is spatial heterogeneity in establishment, growth and mortality, resulting from the self-organization processes. A number of recent studies, however, have revealed that movement of organisms can be an important driving process creating extensive spatial patterning in many ecosystems. Here, we review studies that detail movement-based pattern formation in contrasting ecological settings. Our review highlights that a common principle, where movement of organisms is density-dependent, explains observed spatial regular patterns in all of these studies. This principle, well known to physics as the Cahn-Hilliard principle of phase separation, has so-far remained unrecognized as a general mechanism for self-organized complexity in ecology. Using the examples presented in this paper, we explain how this movement principle can be discerned in ecological settings, and clarify how to test this mechanism experimentally. Our study highlights that animal movement, both in isolation and in unison with other processes, is an important mechanism for regular pattern formation in ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

Organizer and axes formation as a self-organizing process.

PubMed

Meinhardt, H

2001-01-01

It is a widely held view that axis formation is based essentially on pre-localized determinants. However, the robustness of early development, the pattern regulation observed after experimental interferences and the existence of systems that don't require maternal determinants suggest that self-regulating pattern forming systems are also involved. A model is proposed that allows axes formation by a chain of reactions based on local self-enhancement and long-range inhibition. Their appropriate linkage ensures that the intermediary patterns emerge in the correct sequence and have the correct spatial relation to each other. Specifically, the model comprises the following events: the generation of a pole by a pattern-forming process, the formation of a second organizer eccentric to the pole (e.g. the Nieuwkoop center), the ecto-meso-endo subdivision, the generation of the Spemann-Mangold organizer with its anterior-posterior subdivision under the influence of the Nieuwkoop center, the conversion of the Spemann-Mangold organizer (a hot spot) into the notochord (a hot stripe), and the marking of the left side of the organism by a patterning reaction influenced by the midline. The pattern forming reactions do not depend on but can make use of maternally pre-localized determinants or asymmetries. Comparison with known genes and molecules reveals that many of the expected ingredients are present. Computer simulations show that the model accounts for many regulatory features reported in the literature. The computer simulations are available in an animated form at.

Predicting supramolecular self-assembly on reconstructed metal surfaces

NASA Astrophysics Data System (ADS)

Roussel, Thomas J.; Barrena, Esther; Ocal, Carmen; Faraudo, Jordi

2014-06-01

The prediction of supramolecular self-assembly onto solid surfaces is still challenging in many situations of interest for nanoscience. In particular, no previous simulation approach has been capable to simulate large self-assembly patterns of organic molecules over reconstructed surfaces (which have periodicities over large distances) due to the large number of surface atoms and adsorbing molecules involved. Using a novel simulation technique, we report here large scale simulations of the self-assembly patterns of an organic molecule (DIP) over different reconstructions of the Au(111) surface. We show that on particular reconstructions, the molecule-molecule interactions are enhanced in a way that long-range order is promoted. Also, the presence of a distortion in a reconstructed surface pattern not only induces the presence of long-range order but also is able to drive the organization of DIP into two coexisting homochiral domains, in quantitative agreement with STM experiments. On the other hand, only short range order is obtained in other reconstructions of the Au(111) surface. The simulation strategy opens interesting perspectives to tune the supramolecular structure by simulation design and surface engineering if choosing the right molecular building blocks and stabilising the chosen reconstruction pattern.The prediction of supramolecular self-assembly onto solid surfaces is still challenging in many situations of interest for nanoscience. In particular, no previous simulation approach has been capable to simulate large self-assembly patterns of organic molecules over reconstructed surfaces (which have periodicities over large distances) due to the large number of surface atoms and adsorbing molecules involved. Using a novel simulation technique, we report here large scale simulations of the self-assembly patterns of an organic molecule (DIP) over different reconstructions of the Au(111) surface. We show that on particular reconstructions, the molecule-molecule interactions are enhanced in a way that long-range order is promoted. Also, the presence of a distortion in a reconstructed surface pattern not only induces the presence of long-range order but also is able to drive the organization of DIP into two coexisting homochiral domains, in quantitative agreement with STM experiments. On the other hand, only short range order is obtained in other reconstructions of the Au(111) surface. The simulation strategy opens interesting perspectives to tune the supramolecular structure by simulation design and surface engineering if choosing the right molecular building blocks and stabilising the chosen reconstruction pattern. GA image adapted from refs: (a) Phys. Chem. Chem. Phys., 2001, 3, 3399-3404, with permission from the PCCP Owner Societies, and (b) J. Phys. Chem. C, 2008, 112 (18), 7168-7172, reprinted with permission from the American Chemical Society, copyright © 2008.

Self-organization in a diversity induced thermodynamics.

PubMed

Scirè, Alessandro; Annovazzi-Lodi, Valerio

2017-01-01

In this work we show how global self-organized patterns can come out of a disordered ensemble of point oscillators, as a result of a deterministic, and not of a random, cooperative process. The resulting system dynamics has many characteristics of classical thermodynamics. To this end, a modified Kuramoto model is introduced, by including Euclidean degrees of freedom and particle polarity. The standard deviation of the frequency distribution is the disorder parameter, diversity, acting as temperature, which is both a source of motion and of disorder. For zero and low diversity, robust static phase-synchronized patterns (crystals) appear, and the problem reverts to a generic dissipative many-body problem. From small to moderate diversity crystals display vibrations followed by structure disintegration in a competition of smaller dynamic patterns, internally synchronized, each of which is capable to manage its internal diversity. In this process a huge variety of self-organized dynamic shapes is formed. Such patterns can be seen again as (more complex) oscillators, where the same description can be applied in turn, renormalizing the problem to a bigger scale, opening the possibility of pattern evolution. The interaction functions are kept local because our idea is to build a system able to produce global patterns when its constituents only interact at the bond scale. By further increasing the oscillator diversity, the dynamics becomes erratic, dynamic patterns show short lifetime, and finally disappear for high diversity. Results are neither qualitatively dependent on the specific choice of the interaction functions nor on the shape of the probability function assumed for the frequencies. The system shows a phase transition and a critical behaviour for a specific value of diversity.

Self-organizing actin patterns shape membrane architecture but not cell mechanics

NASA Astrophysics Data System (ADS)

Fritzsche, M.; Li, D.; Colin-York, H.; Chang, V. T.; Moeendarbary, E.; Felce, J. H.; Sezgin, E.; Charras, G.; Betzig, E.; Eggeling, C.

2017-02-01

Cell-free studies have demonstrated how collective action of actin-associated proteins can organize actin filaments into dynamic patterns, such as vortices, asters and stars. Using complementary microscopic techniques, we here show evidence of such self-organization of the actin cortex in living HeLa cells. During cell adhesion, an active multistage process naturally leads to pattern transitions from actin vortices over stars into asters. This process is primarily driven by Arp2/3 complex nucleation, but not by myosin motors, which is in contrast to what has been theoretically predicted and observed in vitro. Concomitant measurements of mechanics and plasma membrane fluidity demonstrate that changes in actin patterning alter membrane architecture but occur functionally independent of macroscopic cortex elasticity. Consequently, tuning the activity of the Arp2/3 complex to alter filament assembly may thus be a mechanism allowing cells to adjust their membrane architecture without affecting their macroscopic mechanical properties.

Self-organizing actin patterns shape membrane architecture but not cell mechanics

PubMed Central

Fritzsche, M.; Li, D.; Colin-York, H.; Chang, V. T.; Moeendarbary, E.; Felce, J. H.; Sezgin, E.; Charras, G.; Betzig, E.; Eggeling, C.

2017-01-01

Cell-free studies have demonstrated how collective action of actin-associated proteins can organize actin filaments into dynamic patterns, such as vortices, asters and stars. Using complementary microscopic techniques, we here show evidence of such self-organization of the actin cortex in living HeLa cells. During cell adhesion, an active multistage process naturally leads to pattern transitions from actin vortices over stars into asters. This process is primarily driven by Arp2/3 complex nucleation, but not by myosin motors, which is in contrast to what has been theoretically predicted and observed in vitro. Concomitant measurements of mechanics and plasma membrane fluidity demonstrate that changes in actin patterning alter membrane architecture but occur functionally independent of macroscopic cortex elasticity. Consequently, tuning the activity of the Arp2/3 complex to alter filament assembly may thus be a mechanism allowing cells to adjust their membrane architecture without affecting their macroscopic mechanical properties. PMID:28194011

Pattern formation and self-organization in plasmas interacting with surfaces

NASA Astrophysics Data System (ADS)

Trelles, Juan Pablo

2016-10-01

Pattern formation and self-organization are fascinating phenomena commonly observed in diverse types of biological, chemical and physical systems, including plasmas. These phenomena are often responsible for the occurrence of coherent structures found in nature, such as recirculation cells and spot arrangements; and their understanding and control can have important implications in technology, e.g. from determining the uniformity of plasma surface treatments to electrode erosion rates. This review comprises theoretical, computational and experimental investigations of the formation of spatiotemporal patterns that result from self-organization events due to the interaction of low-temperature plasmas in contact with confining or intervening surfaces, particularly electrodes. The basic definitions associated to pattern formation and self-organization are provided, as well as some of the characteristics of these phenomena within natural and technological contexts, especially those specific to plasmas. Phenomenological aspects of pattern formation include the competition between production/forcing and dissipation/transport processes, as well as nonequilibrium, stability, bifurcation and nonlinear interactions. The mathematical modeling of pattern formation in plasmas has encompassed from theoretical approaches and canonical models, such as reaction-diffusion systems, to drift-diffusion and nonequilibrium fluid flow models. The computational simulation of pattern formation phenomena imposes distinct challenges to numerical methods, such as high sensitivity to numerical approximations and the occurrence of multiple solutions. Representative experimental and numerical investigations of pattern formation and self-organization in diverse types of low-temperature electrical discharges (low and high pressure glow, dielectric barrier and arc discharges, etc) in contact with solid and liquid electrodes are reviewed. Notably, plasmas in contact with liquids, found in diverse emerging applications ranging from nanomaterial synthesis to medicine, show marked sensitivity to pattern formation and a broadened range of controlling parameters. The results related to the characteristics of the patterns, such as their geometric configuration and static or dynamic nature; as well as their controlling factors, including gas composition, driving voltage and current, electrode cooling, and imposed gas flow, are summarized and discussed. The article finalizes with an outlook of the research area, including theoretical, computational, and experimental needs to advance the field.

Diatom-sedimentation feedback generates a self-organized geomorphic landscape on intertidal mudflats (Invited)

NASA Astrophysics Data System (ADS)

van de Koppel, J.; Weerman, E.; Herman, P.

2010-12-01

During spring, intertidal flats can exhibit strikingly regular spatial patterns of diatom-covered hummocks alternating with almost bare, water-filled hollows. We hypothesize that 1) the formation of this geomorphic landscape is caused by a strong interaction between benthic diatoms and sediment dynamics, inducing spatial self-organization, and 2) that self-organization affects ecosystem functioning by increasing the net average sedimentation on the tidal flat. We present a combined empirical and mathematical study to test the first hypothesis. We determined how the sediment erosion threshold varied with diatom cover and elevation. Our results were incorporated into a mathematical model to investigate whether the proposed mechanism could explain the formation of the observed patterns. Our mathematical model confirmed that the interaction between sedimentation, diatom growth and water redistribution could induce the formation of regular patterns on the intertidal mudflat. The model predicts that areas exhibiting spatially-self-organized patterns have increased sediment accretion and diatom biomass compared with areas lacking spatial patterns. We tested this prediction by following the sediment elevation during the season on both patterned and unpatterned parts of the mudflat. The results of our study confirmed our model prediction, as more sediment was found to accumulate in patterned parts of the mudflat, revealing how self-organization affected the functioning of mudflat ecosystems. Our study on intertidal mudflats provides a simple but clear-cut example of how the interaction between biological and geomorphological processes, through the process of self-organization, induces a self-organized geomorphic landscape.

Landscapes of facilitation: how self-organized patchiness of aquatic macrophytes promotes diversity in streams.

PubMed

Cornacchia, Loreta; van de Koppel, Johan; van der Wal, Daphne; Wharton, Geraldene; Puijalon, Sara; Bouma, Tjeerd J

2018-04-01

Spatial heterogeneity plays a crucial role in the coexistence of species. Despite recognition of the importance of self-organization in creating environmental heterogeneity in otherwise uniform landscapes, the effects of such self-organized pattern formation in promoting coexistence through facilitation are still unknown. In this study, we investigated the effects of pattern formation on species interactions and community spatial structure in ecosystems with limited underlying environmental heterogeneity, using self-organized patchiness of the aquatic macrophyte Callitriche platycarpa in streams as a model system. Our theoretical model predicted that pattern formation in aquatic vegetation - due to feedback interactions between plant growth, water flow and sedimentation processes - could promote species coexistence, by creating heterogeneous flow conditions inside and around the plant patches. The spatial plant patterns predicted by our model agreed with field observations at the reach scale in naturally vegetated rivers, where we found a significant spatial aggregation of two macrophyte species around C. platycarpa. Field transplantation experiments showed that C. platycarpa had a positive effect on the growth of both beneficiary species, and the intensity of this facilitative effect was correlated with the heterogeneous hydrodynamic conditions created within and around C. platycarpa patches. Our results emphasize the importance of self-organized patchiness in promoting species coexistence by creating a landscape of facilitation, where new niches and facilitative effects arise in different locations. Understanding the interplay between competition and facilitation is therefore essential for successful management of biodiversity in many ecosystems. © 2018 The Authors Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.

Integrative understanding of macular morphologic patterns in diabetic retinopathy based on self-organizing map.

PubMed

Murakami, Tomoaki; Ueda-Arakawa, Naoko; Nishijima, Kazuaki; Uji, Akihito; Horii, Takahiro; Ogino, Ken; Yoshimura, Nagahisa

2014-03-28

To integrate parameters on spectral-domain optical coherence tomography (SD-OCT) in diabetic retinopathy (DR) based on the self-organizing map and objectively describe the macular morphologic patterns. A total of 336 consecutive eyes of 216 patients with DR for whom clear SD-OCT images were available were retrospectively reviewed. Eleven OCT parameters and the logarithm of the minimal angle of resolution (logMAR) were measured. These multidimensional data were analyzed based on the self-organizing map on which similar cases were near each other according to the degree of their similarities, followed by the objective clustering. Self-organizing maps indicated that eyes with greater retinal thickness in the central subfield had greater thicknesses in the superior and temporal subfields. Eyes with foveal serous retinal detachment (SRD) had greater thickness in the nasal or inferior subfield. Eyes with foveal cystoid spaces were arranged to the left upper corner on the two-dimensional map; eyes with foveal SRD to the left lower corner; eyes with thickened retinal parenchyma to the lower area. The following objective clustering demonstrated the unsupervised pattern recognition of macular morphologies in diabetic macular edema (DME) as well as the higher-resolution discrimination of DME per se. Multiple regression analyses showed better association of logMAR with retinal thickness in the inferior subfield in eyes with SRD and with external limiting membrane disruption in eyes with foveal cystoid spaces or thickened retinal parenchyma. The self-organizing map facilitates integrative understanding of the macular morphologic patterns and the structural/functional relationship in DR.

Cellular chirality arising from the self-organization of the actin cytoskeleton.

PubMed

Tee, Yee Han; Shemesh, Tom; Thiagarajan, Visalatchi; Hariadi, Rizal Fajar; Anderson, Karen L; Page, Christopher; Volkmann, Niels; Hanein, Dorit; Sivaramakrishnan, Sivaraj; Kozlov, Michael M; Bershadsky, Alexander D

2015-04-01

Cellular mechanisms underlying the development of left-right asymmetry in tissues and embryos remain obscure. Here, the development of a chiral pattern of actomyosin was revealed by studying actin cytoskeleton self-organization in cells with isotropic circular shape. A radially symmetrical system of actin bundles consisting of α-actinin-enriched radial fibres (RFs) and myosin-IIA-enriched transverse fibres (TFs) evolved spontaneously into the chiral system as a result of the unidirectional tilting of all RFs, which was accompanied by a tangential shift in the retrograde movement of TFs. We showed that myosin-IIA-dependent contractile stresses within TFs drive their movement along RFs, which grow centripetally in a formin-dependent fashion. The handedness of the chiral pattern was shown to be regulated by α-actinin-1. Computational modelling demonstrated that the dynamics of the RF-TF system can explain the pattern transition from radial to chiral. Thus, actin cytoskeleton self-organization provides built-in machinery that potentially allows cells to develop left-right asymmetry.

Morphology-Induced Collective Behaviors: Dynamic Pattern Formation in Water-Floating Elements

PubMed Central

Nakajima, Kohei; Ngouabeu, Aubery Marchel Tientcheu; Miyashita, Shuhei; Göldi, Maurice; Füchslin, Rudolf Marcel; Pfeifer, Rolf

2012-01-01

Complex systems involving many interacting elements often organize into patterns. Two types of pattern formation can be distinguished, static and dynamic. Static pattern formation means that the resulting structure constitutes a thermodynamic equilibrium whose pattern formation can be understood in terms of the minimization of free energy, while dynamic pattern formation indicates that the system is permanently dissipating energy and not in equilibrium. In this paper, we report experimental results showing that the morphology of elements plays a significant role in dynamic pattern formation. We prepared three different shapes of elements (circles, squares, and triangles) floating in a water-filled container, in which each of the shapes has two types: active elements that were capable of self-agitation with vibration motors, and passive elements that were mere floating tiles. The system was purely decentralized: that is, elements interacted locally, and subsequently elicited global patterns in a process called self-organized segregation. We showed that, according to the morphology of the selected elements, a different type of segregation occurs. Also, we quantitatively characterized both the local interaction regime and the resulting global behavior for each type of segregation by means of information theoretic quantities, and showed the difference for each case in detail, while offering speculation on the mechanism causing this phenomenon. PMID:22715370

Self-organized pattern on the surface of a metal anode in low-pressure DC discharge

NASA Astrophysics Data System (ADS)

Yaqi, YANG; Weiguo, LI

2018-03-01

Self-organization phenomena on the surface of a metal electrode in low-pressure DC discharge is studied. In this paper, we carry out laboratory investigations of self-organization in a low-pressure test platform for 100-200 mm rod-plane gaps with a needle tip, conical tip and hemispherical tip within 1-10 kPa. The factors influencing the pattern profile are the pressure value, gap length and shape of the electrode, and a variety of pattern structures are observed by changing these factors. With increasing pressure, first the pattern diameter increases and then decreases. With the needle tip, layer structure, single-ring structure and double-ring structure are displayed successively with increasing pressure. With the conical tip, the ring-like structure gradually forms separate spots with increasing pressure. With the hemispherical tip, there are anode spots inside the ring structure. With the increase of gap length, the diameter of the self-organized pattern increases and the profile of the pattern changes. The development process of the pattern contains three key stages: pattern enlargement, pattern stabilization and pattern shrink.

Modeling digits. Digit patterning is controlled by a Bmp-Sox9-Wnt Turing network modulated by morphogen gradients.

PubMed

Raspopovic, J; Marcon, L; Russo, L; Sharpe, J

2014-08-01

During limb development, digits emerge from the undifferentiated mesenchymal tissue that constitutes the limb bud. It has been proposed that this process is controlled by a self-organizing Turing mechanism, whereby diffusible molecules interact to produce a periodic pattern of digital and interdigital fates. However, the identities of the molecules remain unknown. By combining experiments and modeling, we reveal evidence that a Turing network implemented by Bmp, Sox9, and Wnt drives digit specification. We develop a realistic two-dimensional simulation of digit patterning and show that this network, when modulated by morphogen gradients, recapitulates the expression patterns of Sox9 in the wild type and in perturbation experiments. Our systems biology approach reveals how a combination of growth, morphogen gradients, and a self-organizing Turing network can achieve robust and reproducible pattern formation. Copyright © 2014, American Association for the Advancement of Science.

Large-Scale Patterns in a Minimal Cognitive Flocking Model: Incidental Leaders, Nematic Patterns, and Aggregates

NASA Astrophysics Data System (ADS)

Barberis, Lucas; Peruani, Fernando

2016-12-01

We study a minimal cognitive flocking model, which assumes that the moving entities navigate using the available instantaneous visual information exclusively. The model consists of active particles, with no memory, that interact by a short-ranged, position-based, attractive force, which acts inside a vision cone (VC), and lack velocity-velocity alignment. We show that this active system can exhibit—due to the VC that breaks Newton's third law—various complex, large-scale, self-organized patterns. Depending on parameter values, we observe the emergence of aggregates or millinglike patterns, the formation of moving—locally polar—files with particles at the front of these structures acting as effective leaders, and the self-organization of particles into macroscopic nematic structures leading to long-ranged nematic order. Combining simulations and nonlinear field equations, we show that position-based active models, as the one analyzed here, represent a new class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems. The reported results are of prime importance in the study, interpretation, and modeling of collective motion patterns in living and nonliving active systems.

Large-Scale Patterns in a Minimal Cognitive Flocking Model: Incidental Leaders, Nematic Patterns, and Aggregates.

PubMed

Barberis, Lucas; Peruani, Fernando

2016-12-09

We study a minimal cognitive flocking model, which assumes that the moving entities navigate using the available instantaneous visual information exclusively. The model consists of active particles, with no memory, that interact by a short-ranged, position-based, attractive force, which acts inside a vision cone (VC), and lack velocity-velocity alignment. We show that this active system can exhibit-due to the VC that breaks Newton's third law-various complex, large-scale, self-organized patterns. Depending on parameter values, we observe the emergence of aggregates or millinglike patterns, the formation of moving-locally polar-files with particles at the front of these structures acting as effective leaders, and the self-organization of particles into macroscopic nematic structures leading to long-ranged nematic order. Combining simulations and nonlinear field equations, we show that position-based active models, as the one analyzed here, represent a new class of active systems fundamentally different from other active systems, including velocity-alignment-based flocking systems. The reported results are of prime importance in the study, interpretation, and modeling of collective motion patterns in living and nonliving active systems.

Analysis of 2D Phase Contrast MRI in Renal Arteries by Self Organizing Maps

NASA Astrophysics Data System (ADS)

Zöllner, Frank G.; Schad, Lothar R.

We present an approach based on self organizing maps to segment renal arteries from 2D PC Cine MR, images to measure blood velocity and flow. Such information are important in grading renal artery stenosis and support the decision on surgical interventions like percu-tan transluminal angioplasty. Results show that the renal arteries could be extracted automatically. The corresponding velocity profiles show high correlation (r=0.99) compared those from manual delineated vessels. Furthermore, the method could detect possible blood flow patterns within the vessel.

Self-organization of network dynamics into local quantized states

DOE PAGES

Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

2016-02-17

Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of themore » Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Thus, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.« less

Self-organization of network dynamics into local quantized states.

PubMed

Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

2016-02-17

Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model-a minimal-ingredients model of nodal activation and interaction within a complex network-is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.

Self-organization of network dynamics into local quantized states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of themore » Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Thus, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.« less

Inhibition of Shh signalling in the chick wing gives insights into digit patterning and evolution.

PubMed

Pickering, Joseph; Towers, Matthew

2016-10-01

In an influential model of pattern formation, a gradient of Sonic hedgehog (Shh) signalling in the chick wing bud specifies cells with three antero-posterior positional values, which give rise to three morphologically different digits by a self-organizing mechanism with Turing-like properties. However, as four of the five digits of the mouse limb are morphologically similar in terms of phalangeal pattern, it has been suggested that self-organization alone could be sufficient. Here, we show that inhibition of Shh signalling at a specific stage of chick wing development results in a pattern of four digits, three of which can have the same number of phalanges. These patterning changes are dependent on a posterior extension of the apical ectodermal ridge, and this also allows the additional digit to arise from the Shh-producing cells of the polarizing region - an ability lost in ancestral theropod dinosaurs. Our analyses reveal that, if the specification of antero-posterior positional values is curtailed, self-organization can then produce several digits with the same number of phalanges. We present a model that may give important insights into how the number of digits and phalanges has diverged during the evolution of avian and mammalian limbs. © 2016. Published by The Company of Biologists Ltd.

Self-organized phenomena of pedestrian counterflow through a wide bottleneck in a channel

NASA Astrophysics Data System (ADS)

Dong, Li-Yun; Lan, Dong-Kai; Li, Xiang

2016-09-01

The pedestrian counterflow through a bottleneck in a channel shows a variety of flow patterns due to self-organization. In order to reveal the underlying mechanism, a cellular automaton model was proposed by incorporating the floor field and the view field which reflects the global information of the studied area and local interactions with others. The presented model can well reproduce typical collective behaviors, such as lane formation. Numerical simulations were performed in the case of a wide bottleneck and typical flow patterns at different density ranges were identified as rarefied flow, laminar flow, interrupted bidirectional flow, oscillatory flow, intermittent flow, and choked flow. The effects of several parameters, such as the size of view field and the width of opening, on the bottleneck flow are also analyzed in detail. The view field plays a vital role in reproducing self-organized phenomena of pedestrian. Numerical results showed that the presented model can capture key characteristics of bottleneck flows. Project supported by the National Basic Research Program of China (Grant No. 2012CB725404) and the National Natural Science Foundation of China (Grant Nos. 11172164 and 11572184).

Architectural Patterns for Self-Organizing Systems-of-Systems

DTIC Science & Technology

2011-05-01

show that they are necessary for self-organization to occur. Common Purpose Abraham Maslow proposed a theory on human motivation based on a hierarchy...http://www.hole-in-the-wall.com/abouthiwel.html (accessed October 28, 2010). 21. Maslow , Abraham . 1943. A theory of human motivation. In Psychological...in-the-wall Education Ltd. http://www.hole- in-the-wall.com/abouthiwel.html (accessed October 28, 2010). 22. Maslow , Abraham . 1943. A theory of human

Transformations of the dislocation structure of nickel single crystals

NASA Astrophysics Data System (ADS)

Alfyorova, E. A.; Lychagin, D. V.; Lychagina, L. L.; Tsvetkov, N. A.

2017-12-01

A relationship between different-scale deformations of crystals has not been established yet. In order to solve this task, we investigate the development of a deformation relief and dislocation structure in nickel single crystals after deformation. The stress tensor, crystallography, and geometry of specimens affect the organization of some shear along corresponding systems of sliding. The organization of shear shows some features of self-organization. It is associated with the self-organization in the dislocation subsystem analyzed previously. The effectiveness of reducing external and internal stresses determines patterns of deformation processes at different scale levels.

Predicting spiral wave patterns from cell properties in a model of biological self-organization.

PubMed

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

Predicting spiral wave patterns from cell properties in a model of biological self-organization

NASA Astrophysics Data System (ADS)

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

Landform elevation suggests ecohydrologic footprints in subsurface geomorphology

NASA Astrophysics Data System (ADS)

Watts, A. C.; Watts, D.; Kaplan, D. A.; Mclaughlin, D. L.; Heffernan, J. B.; Martin, J. B.; Murray, A.; Osborne, T.; Cohen, M. J.; Kobziar, L. N.

2012-12-01

Many landscapes exhibit patterns in their arrangement of biota, or in their surface geomorphology as a result of biotic activity. Examples occur around the globe and include northern peatlands, Sahelian savannas, and shallow marine reefs. Such self-organized patterning is strongly suggestive of coupled, reciprocal feedbacks (i.e. locally positive, and distally negative) among biota and their environment. Much research on patterned landscapes has concerned emergent biogeomorphologic surfaces such as those found in peatlands, or the influence of biota on soil formation or transport. Our research concerns ecohydrologic feedbacks hypothesized to produce patterned occurrence of depressions in a subtropical limestone karst landscape. Our findings show strong evidence of self-organized patterning, in the form of overdispersed dissolution basins. Distributions of randomized bedrock elevation measurements on the landscape are bimodal, with means clustered about either higher- or lower-elevation modes. Measurements on the thin mantle of soil overlying this landscape, however, display reduced bimodality and mode separation. These observations indicate abiotic processes in diametric opposition to the biogenic forces which may be responsible for generating landscape pattern. Correlograms show higher spatial autocorrelation among soil measurements compared to bedrock measurements, and measurements of soil-layer thickness show high negative correlation with bedrock elevation. Our results are consistent with predictions of direct ecohydrologic feedbacks that would produce patterned "footprints" directly on bedrock, and of abiotic processes operating to obfuscate this pattern. The study suggests new steps to identify biogeochemical mechanisms for landscape patterning: an "ecological drill" by which plant communities modify geology.

Secure steganographic communication algorithm based on self-organizing patterns.

PubMed

Saunoriene, Loreta; Ragulskis, Minvydas

2011-11-01

A secure steganographic communication algorithm based on patterns evolving in a Beddington-de Angelis-type predator-prey model with self- and cross-diffusion is proposed in this paper. Small perturbations of initial states of the system around the state of equilibrium result in the evolution of self-organizing patterns. Small differences between initial perturbations result in slight differences also in the evolving patterns. It is shown that the generation of interpretable target patterns cannot be considered as a secure mean of communication because contours of the secret image can be retrieved from the cover image using statistical techniques if only it represents small perturbations of the initial states of the system. An alternative approach when the cover image represents the self-organizing pattern that has evolved from initial states perturbed using the dot-skeleton representation of the secret image can be considered as a safe visual communication technique protecting both the secret image and communicating parties.

Long-range correlations and patterns of recurrence in children and adults' attention to hierarchical displays

PubMed Central

Castillo, Ramon D.; Kloos, Heidi; Holden, John G.; Richardson, Michael J.

2015-01-01

In order to make sense of a scene, a person must pay attention to several levels of nested order, ranging from the most differentiated details of the display to the integrated whole. In adults, research shows that the processes of integration and differentiation have the signature of self-organization. Does the same hold for children? The current study addresses this question with children between 6 and 9 years of age, using two tasks that require attention to hierarchical displays. A group of adults were tested as well, for control purposes. To get at the question of self-organization, reaction times were submitted to a detrended fluctuation analysis and a recurrence quantification analysis. H exponents show a long-range correlations (1/f noise), and recurrence measures (percent determinism, maximum line, entropy, and trend), show a deterministic structure of variability being characteristic of self-organizing systems. Findings are discussed in terms of organism-environment coupling that gives rise to fluid attention to hierarchical displays. PMID:25999862

Periodic Grating-like Patterns Induced by Self-Assembly of Gelator Fibres in Nematic Gels.

PubMed

Topnani, Neha B; Prutha, N; Pratibha, R

2018-03-15

Periodic orientation patterns occurring in nematic gels, revealed by optical and scanning electron microscopy, are found to be formed by spontaneous self-assembly of fibrous aggregates of a low-molecular-weight organogelator in an aligned thermotropic liquid crystal (LC). Self-organization into periodic structures is also reflected in a calorimetric study, which shows the occurrence of three thermoreversible states, namely, isotropic liquid, nematic and nematic gel. The segregation and self-assembly of the fibrous aggregates leading to pattern formation are attributed to the highly polar LC and to hydrogen bonding between gelator molecules, as shown by X-ray diffraction and vibrational spectroscopy. This study aims to investigate in detail the effect of the chemical nature and alignment of an anisotropic solvent on the morphology of the gelator fibres and the resulting gelation process. The periodic organization of LC-rich and fibre-rich regions can also provide a way to obtain templates for positioning nanoparticle arrays in an LC matrix, which can lead to novel devices. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Starfish Behavior as an Anticipatory System: Its Flexibility in Obstacle Avoidance

NASA Astrophysics Data System (ADS)

Migita, Masao

2006-06-01

As starfish do not have central nervous systems, their behaviors such as walking, righting, feeding, and so on, must be produced by some processes of self-organization of many motor organs. It has been noticed that self-organized behavioral patterns are not strictly determined by external stimuli, though such stimuli may elicit the very self-organization processes. In this sense, starfish are not only reactive like a conventional discourse of comparative psychology have presupposed. In this study, I will show diversity in self-organized behavior of a starfish exhibited under experiments on obstacle avoidance. The starfish may be considered as an anticipatory system, because it usually appeared to be free from serious deadlock at the obstacles. I will also discuss that to view the animal as an anticipatory system may have an interesting implication on the fields of behavioral biology and comparative psychology.

Mechanochemical Symmetry Breaking in Hydra Aggregates

PubMed Central

Mercker, Moritz; Köthe, Alexandra; Marciniak-Czochra, Anna

2015-01-01

Tissue morphogenesis comprises the self-organized creation of various patterns and shapes. Although detailed underlying mechanisms are still elusive in many cases, an increasing amount of experimental data suggests that chemical morphogen and mechanical processes are strongly coupled. Here, we develop and test a minimal model of the axis-defining step (i.e., symmetry breaking) in aggregates of the Hydra polyp. Based on previous findings, we combine osmotically driven shape oscillations with tissue mechanics and morphogen dynamics. We show that the model incorporating a simple feedback loop between morphogen patterning and tissue stretch reproduces a wide range of experimental data. Finally, we compare different hypothetical morphogen patterning mechanisms (Turing, tissue-curvature, and self-organized criticality). Our results suggest the experimental investigation of bigger (i.e., multiple head) aggregates as a key step for a deeper understanding of mechanochemical symmetry breaking in Hydra. PMID:25954896

Neurodynamics With Spatial Self-Organization

NASA Technical Reports Server (NTRS)

Zak, Michail A.

1993-01-01

Report presents theoretical study of dynamics of neural network organizing own response in both phase space and in position space. Postulates several mathematical models of dynamics including spatial derivatives representing local interconnections among neurons. Shows how neural responses propagate via these interconnections and how spatial pattern of neural responses formed in homogeneous biological neural network.

Process-morphology scaling relations quantify self-organization in capillary densified nanofiber arrays.

PubMed

Kaiser, Ashley L; Stein, Itai Y; Cui, Kehang; Wardle, Brian L

2018-02-07

Capillary-mediated densification is an inexpensive and versatile approach to tune the application-specific properties and packing morphology of bulk nanofiber (NF) arrays, such as aligned carbon nanotubes. While NF length governs elasto-capillary self-assembly, the geometry of cellular patterns formed by capillary densified NFs cannot be precisely predicted by existing theories. This originates from the recently quantified orders of magnitude lower than expected NF array effective axial elastic modulus (E), and here we show via parametric experimentation and modeling that E determines the width, area, and wall thickness of the resulting cellular pattern. Both experiments and models show that further tuning of the cellular pattern is possible by altering the NF-substrate adhesion strength, which could enable the broad use of this facile approach to predictably pattern NF arrays for high value applications.

Habitual Sleep Duration and Self-Perceptions of the Need to Achieve.

ERIC Educational Resources Information Center

Pellegrini, Robert J.; And Others

Two hypotheses were developed in an attempt to organize and clarify the conceptual basis for studies of relationships between patterns of habitual sleep duration and self-perceptions of the need to achieve. A non-specific arousal (N-SA) hypothesis presumes that short sleepers show more vigor, more general anxiety, incline more toward development…

Topics in the mechanics of self-organizing systems

NASA Astrophysics Data System (ADS)

Tambe, Dhananjay

Self-organization, in one of its accepted definitions, is the appearance of non-random structures in a system without explicit constraints from forces outside the system. In this thesis two self-organizing systems are studied from the viewpoint of mechanics. In the first system---semiconductor crystal surfaces---the internal constraints that lead to self-assembly of nanoscale structures on silicon-germanium (SiGe) films are studied. In the second system---actin cytoskeleton---a consequence of dynamic self-organization of actin filaments in the form of motion of micron-sized beads through a cytoplasmic medium is studied. When Ge film is deposited on Si(001) substrate, nanoscale features form on the surface and self-organize by minimizing energy contributions from the surface and the strain resulting from difference in lattice constants of the film and the substrate. Clean Si(001) and Ge(001) surfaces are very similar, but experiments to date have shown that atomic scale defects such as dimer-vacancies self-organize into vacancy lines only on Si(001). Through atomic simulations, we show that the observed difference originate from the magnitude of compressive surface strain which reduces formation energy of the dimer-vacancies. During initial stages of the film deposition, the surface is composed of steps and vacancy lines organized in periodic patterns. Using theory of elasticity and atomic simulations we show that these line defects self-organize due to monopolar nature of steps and dipolar nature of the vacancy lines. This self-organized pattern further develops to form pyramidal islands bounded with (105) facets and high Ge content. Mismatch strain of the island is then reduced by incorporation of Si from the substrate surrounding the island leaving behind trenches whose depth is proportional to the basewidth of the island. Using finite element simulations we show that such a relationship is an outcome of competition between elastic energy and surface energy. Some experimental studies also report observation of steeper (103) and (104) facets on pyramidal islands. Using numerical simulations we derive a phase diagram which shows that the steeper facets are stabilized because they provide better relaxation of mismatch strain with only slight increase in surface energy. In the second system, the actin cytoskeleton is a key structural and propulsion element of eukaryotic cells. Micron-sized "cargoes", which under pathological conditions include bacteria, are propelled by dynamic self-organization of the actin filaments. Recently it is shown that the trajectories of a bacterium, Listeria monocytogenes, propelled by actin filaments are periodic; implying that the organization of actin filaments impart an effective force that spins about the axis of the bacterium. We show that the motion of spherical beads is also non-random; the effective force has an additional degree of freedom due to the spherical symmetry of the bead. Agreement of the theoretical trajectories with experimental observations suggest that the actin-based motility can be generally described using deterministic equations. We also propose microscopic basis for the effective force model which can guide development of microscopic theory to predict the long term trajectories of actin propelled objects.

Simulation of stationary glow patterns in dielectric barrier discharges at atmospheric pressure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Fucheng, E-mail: hdlfc@hbu.cn; He, Yafeng; Dong, Lifang

2014-12-15

Self-organized stationary patterns in dielectric barrier discharges operating in glow regime at atmospheric pressure are investigated by a self-consistent two-dimensional fluid model. The simulation results show that two different modes, namely, the diffuse mode and the static patterned mode, can be formed in different ranges of the driving frequency. The discharge operates in Townsend regime in the diffuse mode, while it operates in a glow regime inside the filaments and in a Townsend regime outside the filaments in the stable pattered mode. The forming process of the stationary filaments can be divided into three stages, namely, destabilizing stage, self-assembling stage,more » and stable stage. The space charge associated with residual electron density and surface charge is responsible for the formation of these stationary glow patterns.« less

Self-organization: the fundament of cell biology

PubMed Central

Betz, Timo

2018-01-01

Self-organization refers to the emergence of an overall order in time and space of a given system that results from the collective interactions of its individual components. This concept has been widely recognized as a core principle in pattern formation for multi-component systems of the physical, chemical and biological world. It can be distinguished from self-assembly by the constant input of energy required to maintain order—and self-organization therefore typically occurs in non-equilibrium or dissipative systems. Cells, with their constant energy consumption and myriads of local interactions between distinct proteins, lipids, carbohydrates and nucleic acids, represent the perfect playground for self-organization. It therefore comes as no surprise that many properties and features of self-organized systems, such as spontaneous formation of patterns, nonlinear coupling of reactions, bi-stable switches, waves and oscillations, are found in all aspects of modern cell biology. Ultimately, self-organization lies at the heart of the robustness and adaptability found in cellular and organismal organization, and hence constitutes a fundamental basis for natural selection and evolution. This article is part of the theme issue ‘Self-organization in cell biology’. PMID:29632257

Spatial self-organization in hybrid models of multicellular adhesion

NASA Astrophysics Data System (ADS)

Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

2016-10-01

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

Light-driven dynamic Archimedes spirals and periodic oscillatory patterns of topological solitons in anisotropic soft matter

DOE PAGES

Martinez, Angel; Smalyukh, Ivan I.

2015-02-12

Oscillatory and excitable systems very commonly exhibit formation of dynamic non-equilibrium patterns. For example, rotating spiral patterns are observed in biological, chemical, and physical systems ranging from organization of slime mold cells to Belousov-Zhabotinsky reactions, and to crystal growth from nuclei with screw dislocations. Here we describe spontaneous formation of spiral waves and a large variety of other dynamic patterns in anisotropic soft matter driven by low-intensity light. The unstructured ambient or microscope light illumination of thin liquid crystal films in contact with a self-assembled azobenzene monolayer causes spontaneous formation, rich spatial organization, and dynamics of twisted domains and topologicalmore » solitons accompanied by the dynamic patterning of azobenzene group orientations within the monolayer. Linearly polarized incident light interacts with the twisted liquid crystalline domains, mimicking their dynamics and yielding patterns in the polarization state of transmitted light, which can be transformed to similar dynamic patterns in its intensity and interference color. This shows that the delicate light-soft-matter interaction can yield complex self-patterning of both. Finally, we uncover underpinning physical mechanisms and discuss potential uses.« less

A new mechanism for spatial pattern formation via lateral and protrusion-mediated lateral signalling

PubMed Central

Hunter, Ginger L.; Baum, Buzz

2016-01-01

Tissue organization and patterning are critical during development when genetically identical cells take on different fates. Lateral signalling plays an important role in this process by helping to generate self-organized spatial patterns in an otherwise uniform collection of cells. Recent data suggest that lateral signalling can be mediated both by junctional contacts between neighbouring cells and via cellular protrusions that allow non-neighbouring cells to interact with one another at a distance. However, it remains unclear precisely how signalling mediated by these distinct types of cell–cell contact can physically contribute to the generation of complex patterns without the assistance of diffusible morphogens or pre-patterns. To explore this question, in this work we develop a model of lateral signalling based on a single receptor/ligand pair as exemplified by Notch and Delta. We show that allowing the signalling kinetics to differ at junctional versus protrusion-mediated contacts, an assumption inspired by recent data which show that the cleavage of Notch in several systems requires both Delta binding and the application of mechanical force, permits individual cells to act to promote both lateral activation and lateral inhibition. Strikingly, under this model, in which Delta can sequester Notch, a variety of patterns resembling those typical of reaction–diffusion systems is observed, together with more unusual patterns that arise when we consider changes in signalling kinetics, and in the length and distribution of protrusions. Importantly, these patterns are self-organizing—so that local interactions drive tissue-scale patterning. Together, these data show that protrusions can, in principle, generate different types of patterns in addition to contributing to long-range signalling and to pattern refinement. PMID:27807273

Regular and irregular patterns of self-localized excitation in arrays of coupled phase oscillators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolfrum, Matthias; Omel'chenko, Oleh E.; Sieber, Jan

We study a system of phase oscillators with nonlocal coupling in a ring that supports self-organized patterns of coherence and incoherence, called chimera states. Introducing a global feedback loop, connecting the phase lag to the order parameter, we can observe chimera states also for systems with a small number of oscillators. Numerical simulations show a huge variety of regular and irregular patterns composed of localized phase slipping events of single oscillators. Using methods of classical finite dimensional chaos and bifurcation theory, we can identify the emergence of chaotic chimera states as a result of transitions to chaos via period doublingmore » cascades, torus breakup, and intermittency. We can explain the observed phenomena by a mechanism of self-modulated excitability in a discrete excitable medium.« less

Femtosecond self-reconfiguration of laser-induced plasma patterns in dielectrics

NASA Astrophysics Data System (ADS)

Déziel, Jean-Luc; Dubé, Louis J.; Messaddeq, Sandra H.; Messaddeq, Younès; Varin, Charles

2018-05-01

Laser-induced modification of transparent solids by intense femtosecond laser pulses allows fast integration of nanophotonic and nanofluidic devices with controlled optical properties. Experimental observations suggest that the local and dynamic nature of the interactions between light and the transient plasma plays an important role during fabrication. Current analytical models neglect these aspects and offer limited coverage of nanograting formation on dielectric surfaces. In this paper, we present a self-consistent dynamic treatment of the plasma buildup and its interaction with light within a three-dimensional electromagnetic framework. The main finding of this work is that local light-plasma interactions are responsible for the reorientation of laser-induced periodic plasma patterns with respect to the incident light polarization, when a certain energy density threshold is reached. Plasma reconfiguration occurs within a single laser pulse, on a femtosecond time scale. Moreover, we show that the reconfigured subwavelength plasma structures actually grow into the bulk of the sample, which agrees with the experimental observations of self-organized volume nanogratings. We find that mode coupling of the incident and transversely scattered light with the periodic plasma structures is sufficient to initiate the growth and self-organization of the pattern inside the medium with a characteristic half-wavelength periodicity.

Self-organizing periodicity in development: organ positioning in plants.

PubMed

Bhatia, Neha; Heisler, Marcus G

2018-02-08

Periodic patterns during development often occur spontaneously through a process of self-organization. While reaction-diffusion mechanisms are often invoked, other types of mechanisms that involve cell-cell interactions and mechanical buckling have also been identified. Phyllotaxis, or the positioning of plant organs, has emerged as an excellent model system to study the self-organization of periodic patterns. At the macro scale, the regular spacing of organs on the growing plant shoot gives rise to the typical spiral and whorled arrangements of plant organs found in nature. In turn, this spacing relies on complex patterns of cell polarity that involve feedback between a signaling molecule - the plant hormone auxin - and its polar, cell-to-cell transport. Here, we review recent progress in understanding phyllotaxis and plant cell polarity and highlight the development of new tools that can help address the remaining gaps in our understanding. © 2018. Published by The Company of Biologists Ltd.

Modeling habits as self-sustaining patterns of sensorimotor behavior

PubMed Central

Egbert, Matthew D.; Barandiaran, Xabier E.

2014-01-01

In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation. In this paper we use a computational model to present an alternative theoretical view (with some philosophical implications), where habits are seen as self-maintaining patterns of behavior that share properties in common with self-maintaining biological processes, and that inhabit a complex ecological context, including the presence and influence of other habits. Far from mechanical automatisms, this organismic and self-organizing concept of habit can overcome the dominating atomistic and statistical conceptions, and the high temporal resolution effects of situatedness, embodiment and sensorimotor loops emerge as playing a more central, subtle and complex role in the organization of behavior. The model is based on a novel “iterant deformable sensorimotor medium (IDSM),” designed such that trajectories taken through sensorimotor-space increase the likelihood that in the future, similar trajectories will be taken. We couple the IDSM to sensors and motors of a simulated robot, and show that under certain conditions, the IDSM conditions, the IDSM forms self-maintaining patterns of activity that operate across the IDSM, the robot's body, and the environment. We present various environments and the resulting habits that form in them. The model acts as an abstraction of habits at a much needed sensorimotor “meso-scale” between microscopic neuron-based models and macroscopic descriptions of behavior. Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks. PMID:25152724

How a life-like system emerges from a simplistic particle motion law.

PubMed

Schmickl, Thomas; Stefanec, Martin; Crailsheim, Karl

2016-11-30

Self-structuring patterns can be observed all over the universe, from galaxies to molecules to living matter, yet their emergence is waiting for full understanding. We discovered a simple motion law for moving and interacting self-propelled particles leading to a self-structuring, self-reproducing and self-sustaining life-like system. The patterns emerging within this system resemble patterns found in living organisms. The emergent cells we found show a distinct life cycle and even create their own ecosystem from scratch. These structures grow and reproduce on their own, show self-driven behavior and interact with each other. Here we analyze the macroscopic properties of the emerging ecology, as well as the microscopic properties of the mechanism that leads to it. Basic properties of the emerging structures (size distributions, longevity) are analyzed as well as their resilience against sensor or actuation noise. Finally, we explore parameter space for potential other candidates of life. The generality and simplicity of the motion law provokes the thought that one fundamental rule, described by one simple equation yields various structures in nature: it may work on different time- and size scales, ranging from the self-structuring universe, to emergence of living beings, down to the emergent subatomic formation of matter.

How a life-like system emerges from a simple particle motion law

PubMed Central

Schmickl, Thomas; Stefanec, Martin; Crailsheim, Karl

2016-01-01

Self-structuring patterns can be observed all over the universe, from galaxies to molecules to living matter, yet their emergence is waiting for full understanding. We discovered a simple motion law for moving and interacting self-propelled particles leading to a self-structuring, self-reproducing and self-sustaining life-like system. The patterns emerging within this system resemble patterns found in living organisms. The emergent cells we found show a distinct life cycle and even create their own ecosystem from scratch. These structures grow and reproduce on their own, show self-driven behavior and interact with each other. Here we analyze the macroscopic properties of the emerging ecology, as well as the microscopic properties of the mechanism that leads to it. Basic properties of the emerging structures (size distributions, longevity) are analyzed as well as their resilience against sensor or actuation noise. Finally, we explore parameter space for potential other candidates of life. The generality and simplicity of the motion law provokes the thought that one fundamental rule, described by one simple equation yields various structures in nature: it may work on different time- and size scales, ranging from the self-structuring universe, to emergence of living beings, down to the emergent subatomic formation of matter. PMID:27901107

Coupled local facilitation and global hydrologic inhibition drive landscape geometry in a patterned peatland

NASA Astrophysics Data System (ADS)

Acharya, S.; Kaplan, D. A.; Casey, S.; Cohen, M. J.; Jawitz, J. W.

2015-05-01

Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing-canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.

Coupled local facilitation and global hydrologic inhibition drive landscape geometry in a patterned peatland

NASA Astrophysics Data System (ADS)

Acharya, S.; Kaplan, D. A.; Casey, S.; Cohen, M. J.; Jawitz, J. W.

2015-01-01

Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types: ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape: patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks.

Variability of Changjiang Diluted Water revealed by a 45-year long-term ocean hindcast and Self-Organizing Maps analysis

NASA Astrophysics Data System (ADS)

Zeng, Xiangming; He, Ruoying; Zong, Haibo

2017-08-01

Based on long-term realistic ocean circulation hindcast for in the Bohai, Yellow, and East China Seas, 45 years (1961-2005) of sea surface salinity data were analyzed using Self-Organizing Maps (SOM) to have a better understanding of the Changjiang Diluted Water (CDW) variation. Three spatial patterns were revealed by the SOM: normal, transition, and extension. The normal pattern mainly occurs from December to May while the CDW hugs China's east coast closely and flows southward. The extension pattern is dominant from June to October when the CDW extends northwestward toward Jeju Island in an omega shape. The transition pattern prevails for the rest of the year. Pattern-averaged temperature, circulation, and chlorophyll-a concentration show significant differences. CDW area and its eastern most extension were explored as a function of the Changjiang runoff and regional upwelling index. We found that Changjiang runoff and upwelling index can be reasonable predictors for the overall CDW area, while ambient circulation determines the distribution and structure of the CDW, and thus the CDW eastern most extension.

Spatial pattern formation of microbes at the soil microscale affect soil C and N turnover in an individual-based microbial community model

NASA Astrophysics Data System (ADS)

Kaiser, Christina; Evans, Sarah; Dieckmann, Ulf; Widder, Stefanie

2016-04-01

At the μm-scale, soil is a highly structured and complex environment, both in physical as well as in biological terms, characterized by non-linear interactions between microbes, substrates and minerals. As known from mathematics and theoretical ecology, spatial structure significantly affects the system's behaviour by enabling synergistic dynamics, facilitating diversity, and leading to emergent phenomena such as self-organisation and self-regulation. Such phenomena, however, are rarely considered when investigating mechanisms of microbial soil organic matter turnover. Soil organic matter is the largest terrestrial reservoir for organic carbon (C) and nitrogen (N) and plays a pivotal role in global biogeochemical cycles. Still, the underlying mechanisms of microbial soil organic matter buildup and turnover remain elusive. We explored mechanisms of microbial soil organic matter turnover using an individual-based, stoichiometrically and spatially explicit computer model, which simulates the microbial de-composer system at the soil microscale (i.e. on a grid of 100 x 100 soil microsites). Soil organic matter dynamics in our model emerge as the result of interactions among individual microbes with certain functional traits (f.e. enzyme production rates, growth rates, cell stoichiometry) at the microscale. By degrading complex substrates, and releasing labile substances microbes in our model continusly shape their environment, which in turn feeds back to spatiotemporal dynamics of the microbial community. In order to test the effect of microbial functional traits and organic matter input rate on soil organic matter turnover and C and N storage, we ran the model into steady state using continuous inputs of fresh organic material. Surprisingly, certain parameter settings that induce resource limitation of microbes lead to regular spatial pattern formation (f.e. moving spiral waves) of microbes and substrate at the μm-scale at steady-state. The occurrence of these pattern can be explained by the Turing mechanism. These pattern formation had strong consequences for process rates, as well as for C and N storage in the soil at the steady state: Scenarios that exhibited pattern formation were generally associated with higher C storage at steady state compared to those without pattern formation (i.e. at non-limiting conditions for microbes). Moreover, pattern formation lead to a spatial decoupling of C and N turnover processes, and to a spatial decoupling of microbial N mineralization and N immobilization. Taken together, our theoretical analysis shows that self-organisation may be a feature of the soil decomposer system, with consequences for process rates of microbial C and N turnover. Pattern formation through spatial self-organization, which has been observed on larger spatial scales in other resource-limited communities (e.g., vegetation patterns in arid or wetland eco-systems), may also occur at the soil microscale, leaving its mark on the soil's storage capacity for C and N.

Self-organization: the fundament of cell biology.

PubMed

Wedlich-Söldner, Roland; Betz, Timo

2018-05-26

Self-organization refers to the emergence of an overall order in time and space of a given system that results from the collective interactions of its individual components. This concept has been widely recognized as a core principle in pattern formation for multi-component systems of the physical, chemical and biological world. It can be distinguished from self-assembly by the constant input of energy required to maintain order-and self-organization therefore typically occurs in non-equilibrium or dissipative systems. Cells, with their constant energy consumption and myriads of local interactions between distinct proteins, lipids, carbohydrates and nucleic acids, represent the perfect playground for self-organization. It therefore comes as no surprise that many properties and features of self-organized systems, such as spontaneous formation of patterns, nonlinear coupling of reactions, bi-stable switches, waves and oscillations, are found in all aspects of modern cell biology. Ultimately, self-organization lies at the heart of the robustness and adaptability found in cellular and organismal organization, and hence constitutes a fundamental basis for natural selection and evolution.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Author(s).

Do ecohydrology and community dynamics feed back to banded-ecosystem structure and productivity?

NASA Astrophysics Data System (ADS)

Callegaro, Chiara; Ursino, Nadia

2016-04-01

Mixed communities including grass, shrubs and trees are often reported to populate self-organized vegetation patterns. Patterns of survey data suggest that species diversity and complementarity strengthen the dynamics of banded environments. Resource scarcity and local facilitation trigger self organization, whereas coexistence of multiple species in vegetated self-organizing patches, implying competition for water and nutrients and favorable reproduction sites, is made possible by differing adaptation strategies. Mixed community spatial self-organization has so far received relatively little attention, compared with local net facilitation of isolated species. We assumed that soil moisture availability is a proxy for the environmental niche of plant species according to Ursino and Callegaro (2016). Our modelling effort was focused on niche differentiation of coexisting species within a tiger bush type ecosystem. By minimal numerical modelling and stability analysis we try to answer a few open scientific questions: Is there an adaptation strategy that increases biodiversity and ecosystem functioning? Does specific adaptation to environmental niches influence the structure of self-organizing vegetation pattern? What specific niche distribution along the environmental gradient gives the highest global productivity?

Self-Organized Criticality, Plasticity and Sensorimotor Coupling. Explorations with a Neurorobotic Model in a Behavioural Preference Task

PubMed Central

Aguilera, Miguel; Barandiaran, Xabier E.; Bedia, Manuel G.; Seron, Francisco

2015-01-01

During the last two decades, analysis of 1/ƒ noise in cognitive science has led to a considerable progress in the way we understand the organization of our mental life. However, there is still a lack of specific models providing explanations of how 1/ƒ noise is generated in coupled brain-body-environment systems, since existing models and experiments typically target either externally observable behaviour or isolated neuronal systems but do not address the interplay between neuronal mechanisms and sensorimotor dynamics. We present a conceptual model of a minimal neurorobotic agent solving a behavioural task that makes it possible to relate mechanistic (neurodynamic) and behavioural levels of description. The model consists of a simulated robot controlled by a network of Kuramoto oscillators with homeostatic plasticity and the ability to develop behavioural preferences mediated by sensorimotor patterns. With only three oscillators, this simple model displays self-organized criticality in the form of robust 1/ƒ noise and a wide multifractal spectrum. We show that the emergence of self-organized criticality and 1/ƒ noise in our model is the result of three simultaneous conditions: a) non-linear interaction dynamics capable of generating stable collective patterns, b) internal plastic mechanisms modulating the sensorimotor flows, and c) strong sensorimotor coupling with the environment that induces transient metastable neurodynamic regimes. We carry out a number of experiments to show that both synaptic plasticity and strong sensorimotor coupling play a necessary role, as constituents of self-organized criticality, in the generation of 1/ƒ noise. The experiments also shown to be useful to test the robustness of 1/ƒ scaling comparing the results of different techniques. We finally discuss the role of conceptual models as mediators between nomothetic and mechanistic models and how they can inform future experimental research where self-organized critically includes sensorimotor coupling among the essential interaction-dominant process giving rise to 1/ƒ noise. PMID:25706744

Scanning tunneling microscopy of the formation, transformation, and property of oligothiophene self-organizations on graphite and gold surfaces.

PubMed

Yang, Zhi-Yong; Zhang, Hui-Min; Yan, Cun-Ji; Li, Shan-Shan; Yan, Hui-Juan; Song, Wei-Guo; Wan, Li-Jun

2007-03-06

Two alkyl-substituted dual oligothiophenes, quarterthiophene (4T)-trimethylene (tm)-octithiophene (8T) and 4T-tm-4T, were used to fabricate molecular structures on highly oriented pyrolytic graphite and Au(111) surfaces. The resulted structures were investigated by scanning tunneling microscopy. The 4T-tm-8T and 4T-tm-4T molecules self-organize into long-range ordered structures with linear and/or quasi-hexagonal patterns on highly oriented pyrolytic graphite at ambient temperature. Thermal annealing induced a phase transformation from quasi-hexagonal to linear in 4T-tm-8T adlayer. The molecules adsorbed on Au(111) surface in randomly folded and linear conformation. Based on scanning tunneling microscopy results, the structural models for different self-organizations were proposed. Scanning tunneling spectroscopy measurement showed the electronic property of individual molecules in the patterns. These results are significant in understanding the chemistry of molecular structure, including its formation, transformation, and electronic properties. They also help to fabricate oligothiophene assemblies with desired structures for future molecular devices.

Self-organized structures in a superorganism: do ants “behave” like molecules?

NASA Astrophysics Data System (ADS)

Detrain, Claire; Deneubourg, Jean-Louis

2006-09-01

While the striking structures (e.g. nest architecture, trail networks) of insect societies may seem familiar to many of us, the understanding of pattern formation still constitutes a challenging problem. Over the last two decades, self-organization has dramatically changed our view on how collective decision-making and structures may emerge out of a population of ant workers having each their own individuality as well as a limited access to information. A variety of collective behaviour spontaneously outcome from multiple interactions between nestmates, even when there is no directing influence imposed by an external template, a pacemaker or a leader. By focussing this review on foraging structures, we show that ant societies display some properties which are usually considered in physico-chemical systems, as typical signatures of self-organization. We detail the key role played by feed-back loops, fluctuations, number of interacting units and sensitivity to environmental factors in the emergence of a structured collective behaviour. Nonetheless, going beyond simple analogies with non-living self-organized patterns, we stress on the specificities of social structures made of complex living units of which the biological features have been selected throughout the evolution depending on their adaptive value. In particular, we consider the ability of each ant individual to process information about environmental and social parameters, to accordingly tune its interactions with nestmates and ultimately to determine the final pattern emerging at the collective level. We emphasize on the parsimony and simplicity of behavioural rules at the individual level which allow an efficient processing of information, energy and matter within the whole colony.

Predictability of spatio-temporal patterns in a lattice of coupled FitzHugh–Nagumo oscillators

PubMed Central

Grace, Miriam; Hütt, Marc-Thorsten

2013-01-01

In many biological systems, variability of the components can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In pioneering work in the late 1990s, it was hypothesized that a drift of cellular parameters (along a ‘developmental path’), together with differences in cell properties (‘desynchronization’ of cells on the developmental path) can establish self-organized spatio-temporal patterns (in their example, spiral waves of cAMP in a colony of Dictyostelium discoideum cells) starting from a homogeneous state. Here, we embed a generic model of an excitable medium, a lattice of diffusively coupled FitzHugh–Nagumo oscillators, into a developmental-path framework. In this minimal model of spiral wave generation, we can now study the predictability of spatio-temporal patterns from cell properties as a function of desynchronization (or ‘spread’) of cells along the developmental path and the drift speed of cell properties on the path. As a function of drift speed and desynchronization, we observe systematically different routes towards fully established patterns, as well as strikingly different correlations between cell properties and pattern features. We show that the predictability of spatio-temporal patterns from cell properties contains important information on the pattern formation process as well as on the underlying dynamical system. PMID:23349439

Study of large nonlinear change phase in Hibiscus Sabdariffa

NASA Astrophysics Data System (ADS)

Trejo-Durán, M.; Alvarado-Méndez, E.; Andrade-Lucio, J. A.; Rojas-Laguna, R.; Vázquez-Guevara, M. A.

2015-09-01

High intensities electromagnetic energy interacting with organic media gives rise to nonlinear optical effects. Hibiscus Sabdariffa is a flower whose concentrated solution presents interesting nonlinear optical properties. This organic material shows an important self-phase modulation with changes bigger than 2π. We present a diffraction ring patterns study of the Hibiscus Sabdariffa solution. Numerical results of transmittance, with refraction and simultaneous absorption, are shown.

Work routines moderate the association between eveningness and poor psychological well-being

PubMed Central

de Souza, Camila Morelatto; Hidalgo, Maria Paz Loayza

2018-01-01

Well-being is a useful screening method for the detection of mood disorders. Evidence associating psychological well-being with sleep-wake patterns exists, as well as associations with sleep-wake patterns, work-related parameters, and perceived self-efficacy. Despite the growing research regarding the relationship between these factors and mental health, there are few studies that analyze them together. OBJECTIVE: To investigate if the association between sleep-wake patterns and psychological well-being is mediated or moderated by perceived self-efficacy, work flexibility and work routines. MATERIAL AND METHODS: This cohort study was performed in southern Brazil. A sample of 987 individuals was analyzed (66.9% women; mean age = 43.9 years). Work routines parameters and work schedule flexibility were evaluated, most participants were farmers (46%) and most worked 7 days a week (69.1%). Munich Chronotype Questionnaire (MCTQ) was administered for evaluation of sleep-wake patterns, General Self-Efficacy Scale (GSE) for assessment the participants’ beliefs about how they coped with daily hassles, and World Health Organization Five-item Well-being Index (WHO-5) for evaluation of psychological well-being levels. Moderation and mediation models were tested. RESULTS: The moderation model showed influences of work end time on the relationship between sleep onset time and psychological well-being (R2 = 0.147; F = 24.16; p<0.001). The final regression model showed an association of psychological well-being with sex (Beta = -0.086; p = 0.004), sleep onset time (Beta = -0.086; p = 0.006), and self-efficacy (Beta = 0.316; p<0.001); the work end time showed association in the interaction with sleep onset time (Beta = -0.075; p = 0.016). CONCLUSION: The findings support the direct association of psychological well-being with sleep-wake patterns and self-efficacy, and show an interaction between work routines and sleep-wake patterns. Our results draw attention to the importance of the interplay between individual and social rhythms in relation to psychological well-being. PMID:29624593

Local pH oscillations witness autocatalytic self-organization of biomorphic nanostructures

NASA Astrophysics Data System (ADS)

Montalti, M.; Zhang, G.; Genovese, D.; Morales, J.; Kellermeier, M.; García-Ruiz, J. M.

2017-02-01

Bottom-up self-assembly of simple molecular compounds is a prime pathway to complex materials with interesting structures and functions. Coupled reaction systems are known to spontaneously produce highly ordered patterns, so far observed in soft matter. Here we show that similar phenomena can occur during silica-carbonate crystallization, the emerging order being preserved. The resulting materials, called silica biomorphs, exhibit non-crystallographic curved morphologies and hierarchical textures, much reminiscent of structural principles found in natural biominerals. We have used a fluorescent chemosensor to probe local conditions during the growth of such self-organized nanostructures. We demonstrate that the pH oscillates in the local microenvironment near the growth front due to chemical coupling, which becomes manifest in the final mineralized architectures as intrinsic banding patterns with the same periodicity. A better understanding of dynamic autocatalytic crystallization processes in such simple model systems is key to the rational development of advanced materials and to unravel the mechanisms of biomineralization.

Cellular self-organization by autocatalytic alignment feedback

PubMed Central

Junkin, Michael; Leung, Siu Ling; Whitman, Samantha; Gregorio, Carol C.; Wong, Pak Kin

2011-01-01

Myoblasts aggregate, differentiate and fuse to form skeletal muscle during both embryogenesis and tissue regeneration. For proper muscle function, long-range self-organization of myoblasts is required to create organized muscle architecture globally aligned to neighboring tissue. However, how the cells process geometric information over distances considerably longer than individual cells to self-organize into well-ordered, aligned and multinucleated myofibers remains a central question in developmental biology and regenerative medicine. Using plasma lithography micropatterning to create spatial cues for cell guidance, we show a physical mechanism by which orientation information can propagate for a long distance from a geometric boundary to guide development of muscle tissue. This long-range alignment occurs only in differentiating myoblasts, but not in non-fusing myoblasts perturbed by microfluidic disturbances or other non-fusing cell types. Computational cellular automata analysis of the spatiotemporal evolution of the self-organization process reveals that myogenic fusion in conjunction with rotational inertia functions in a self-reinforcing manner to enhance long-range propagation of alignment information. With this autocatalytic alignment feedback, well-ordered alignment of muscle could reinforce existing orientations and help promote proper arrangement with neighboring tissue and overall organization. Such physical self-enhancement might represent a fundamental mechanism for long-range pattern formation during tissue morphogenesis. PMID:22193956

Relationship of self-management to personality types and indices.

PubMed

Williams, R L; Verble, J S; Price, D E; Layne, B H

1995-06-01

This study addressed the relationship between self-management (as measured by the Lifestyle Approaches Inventory, Williams, Moore, Pettibone, & Thomas, 1992) and personality types and indexes (as measured by the Myers-Briggs Type Indicator, Myers & McCaulley, 1985) in a sample of 347 university students. Correlational analyses indicated that the self-management factor most consistently linked to the Myers-Briggs indices was Organization of Physical Space. The Myers-Briggs index most consistently correlated with the self-management factors was Judgment-Perception. Overall, male and female subjects showed similar patterns of relationships between the self-management and personality indices. When the self-management scores were compared for the various Myers-Briggs types, the analysis indicated that types having a J (planful and organized) or S (precise and practical) in the typology tended to score higher than those having a P (spontaneous and flexible) or N (imaginative and insightful).

Precisely cyclic sand: self-organization of periodically sheared frictional grains.

PubMed

Royer, John R; Chaikin, Paul M

2015-01-06

The disordered static structure and chaotic dynamics of frictional granular matter has occupied scientists for centuries, yet there are few organizational principles or guiding rules for this highly hysteretic, dissipative material. We show that cyclic shear of a granular material leads to dynamic self-organization into several phases with different spatial and temporal order. Using numerical simulations, we present a phase diagram in strain-friction space that shows chaotic dispersion, crystal formation, vortex patterns, and most unusually a disordered phase in which each particle precisely retraces its unique path. However, the system is not reversible. Rather, the trajectory of each particle, and the entire frictional, many-degrees-of-freedom system, organizes itself into a limit cycle absorbing state. Of particular note is that fact that the cyclic states are spatially disordered, whereas the ordered states are chaotic.

Precisely cyclic sand: Self-organization of periodically sheared frictional grains

PubMed Central

Royer, John R.; Chaikin, Paul M.

2015-01-01

The disordered static structure and chaotic dynamics of frictional granular matter has occupied scientists for centuries, yet there are few organizational principles or guiding rules for this highly hysteretic, dissipative material. We show that cyclic shear of a granular material leads to dynamic self-organization into several phases with different spatial and temporal order. Using numerical simulations, we present a phase diagram in strain–friction space that shows chaotic dispersion, crystal formation, vortex patterns, and most unusually a disordered phase in which each particle precisely retraces its unique path. However, the system is not reversible. Rather, the trajectory of each particle, and the entire frictional, many–degrees-of-freedom system, organizes itself into a limit cycle absorbing state. Of particular note is that fact that the cyclic states are spatially disordered, whereas the ordered states are chaotic. PMID:25538298

Modeling of Instabilities and Self-organization at the Frictional Interface

NASA Astrophysics Data System (ADS)

Mortazavi, Vahid

The field of friction-induced self-organization and its practical importance remains unknown territory to many tribologists. Friction is usually thought of as irreversible dissipation of energy and deterioration; however, under certain conditions, friction can lead to the formation of new structures at the interface, including in-situ tribofilms and various patterns at the interface. This thesis studies self-organization and instabilities at the frictional interface, including the instability due to the temperature-dependency of the coefficient of friction, the transient process of frictional running-in, frictional Turing systems, the stick-and-slip phenomenon, and, finally, contact angle (CA) hysteresis as an example of solid-liquid friction and dissipation. All these problems are chosen to bridge the gap between fundamental interest in understanding the conditions leading to self-organization and practical motivation. We study the relationship between friction-induced instabilities and friction-induced self-organization. Friction is usually thought of as a stabilizing factor; however, sometimes it leads to the instability of sliding, in particular when friction is coupled with another process. Instabilities constitute the main mechanism for pattern formation. At first, a stationary structure loses its stability; after that, vibrations with increasing amplitude occur, leading to a limit cycle corresponding to a periodic pattern. The self-organization is usually beneficial for friction and wear reduction because the tribological systems tend to enter a state with the lowest energy dissipation. The introductory chapter starts with basic definitions related to self-organization, instabilities and friction, literature review, and objectives. We discuss fundamental concepts that provide a methodological tool to investigate, understand and enhance beneficial processes in tribosystems which might lead to self-organization. These processes could result in the ability of a frictional surface to exhibit "self-protection" and "self-healing" properties. Hence, this research is dealing with the fundamental concepts that allow the possibility of the development of a new generation of tribosystem and materials that reinforce such properties. In chapter 2, we investigate instabilities due to the temperature-dependency of the coefficient of friction. The temperature-dependency of the coefficient of friction can have a significant effect on the frictional sliding stability, by leading to the formation of "hot" and "cold" spots on the contacting surfaces. We formulate a stability criterion and perform a case study of a brake disk. In chapter 3, we study frictional running-in. Running-in is a transient period on the onset of the frictional sliding, in which friction and wear decrease to their stationary values. In this research, running-in is interpreted as friction-induced self-organization process. We introduce a theoretical model of running-in and investigate rough profile evolution assuming that its kinetics is driven by two opposite processes or events, i.e., smoothening which is typical for the deformation-driven friction and wear, and roughening which is typical for the adhesion-driven friction and wear. In chapter 4, we investigate the possibility of the so-called Turing-type pattern formation during friction. Turing or reaction-diffusion systems describe variations of spatial concentrations of chemical components with time due to local chemical reactions coupled with diffusion. During friction, the patterns can form at the sliding interface due to the mass transfer (diffusion), heat transfer, various tribochemical reactions, and wear. In chapter 5, we investigate how interfacial patterns including propagating trains of stick and slip zones form due to dynamic sliding instabilities. These can be categorized as self-organized patterns. We treat stick and slip as two phases at the interface, and study the effects related to phase transitions. Our results show how interfacial patterns form, how the transition between stick and slip zones occurs, and which parameters affect them. In chapter 6, we use Cellular Potts Model to study contact angle (CA) hysteresis as a measure of solid-liquid energy dissipation. We simulate CA hysteresis for a droplet over the tilted patterned surface, and a bubble placed under the surface immersed in liquid. We discuss the dependency of CA hysteresis on the surface structure and other parameters. This analysis allows decoupling of the 1D (pinning of the triple line) and 2D effects (adhesion hysteresis in the contact area) and obtain new insights on the nature of CA hysteresis. To summarize, we examine different cases in frictional interface and observe similar trends. We investigate and discus how these trends could be beneficial in design, synthesis and characterization of different materials and tribosystems. Furthermore, we describe how to utilize fundamental concepts for specific engineering applications. Finally, the main theme of this research is to find new applications of concept of self-organization to tribology and the role played by different physical and chemical interactions in modifying and controlling friction and wear. (Abstract shortened by UMI.)

Modeling how shark and dolphin skin patterns control transitional wall-turbulence vorticity patterns using spatiotemporal phase reset mechanisms

PubMed Central

Bandyopadhyay, Promode R.; Hellum, Aren M.

2014-01-01

Many slow-moving biological systems like seashells and zebrafish that do not contend with wall turbulence have somewhat organized pigmentation patterns flush with their outer surfaces that are formed by underlying autonomous reaction-diffusion (RD) mechanisms. In contrast, sharks and dolphins contend with wall turbulence, are fast swimmers, and have more organized skin patterns that are proud and sometimes vibrate. A nonlinear spatiotemporal analytical model is not available that explains the mechanism underlying control of flow with such proud patterns, despite the fact that shark and dolphin skins are major targets of reverse engineering mechanisms of drag and noise reduction. Comparable to RD, a minimal self-regulation model is given for wall turbulence regeneration in the transitional regime—laterally coupled, diffusively—which, although restricted to pre-breakdown durations and to a plane close and parallel to the wall, correctly reproduces many experimentally observed spatiotemporal organizations of vorticity in both laminar-to-turbulence transitioning and very low Reynolds number but turbulent regions. We further show that the onset of vorticity disorganization is delayed if the skin organization is treated as a spatiotemporal template of olivo-cerebellar phase reset mechanism. The model shows that the adaptation mechanisms of sharks and dolphins to their fluid environment have much in common. PMID:25338940

Modeling how shark and dolphin skin patterns control transitional wall-turbulence vorticity patterns using spatiotemporal phase reset mechanisms.

PubMed

Bandyopadhyay, Promode R; Hellum, Aren M

2014-10-23

Many slow-moving biological systems like seashells and zebrafish that do not contend with wall turbulence have somewhat organized pigmentation patterns flush with their outer surfaces that are formed by underlying autonomous reaction-diffusion (RD) mechanisms. In contrast, sharks and dolphins contend with wall turbulence, are fast swimmers, and have more organized skin patterns that are proud and sometimes vibrate. A nonlinear spatiotemporal analytical model is not available that explains the mechanism underlying control of flow with such proud patterns, despite the fact that shark and dolphin skins are major targets of reverse engineering mechanisms of drag and noise reduction. Comparable to RD, a minimal self-regulation model is given for wall turbulence regeneration in the transitional regime--laterally coupled, diffusively--which, although restricted to pre-breakdown durations and to a plane close and parallel to the wall, correctly reproduces many experimentally observed spatiotemporal organizations of vorticity in both laminar-to-turbulence transitioning and very low Reynolds number but turbulent regions. We further show that the onset of vorticity disorganization is delayed if the skin organization is treated as a spatiotemporal template of olivo-cerebellar phase reset mechanism. The model shows that the adaptation mechanisms of sharks and dolphins to their fluid environment have much in common.

Self-organization and complexity in historical landscape patterns

Treesearch

Janine Bolliger; Julien C. Sprott; David J. Mladenoff

2003-01-01

Self-organization describes the evolution process of complex structures where systems emerge spontaneously, driven internally by variations of the system itself. Self-organization to the critical state is manifested by scale-free behavior across many orders of magnitude (Bak et al. 1987, Bak 1996, Sole et a1. 1999). Spatial scale-free behavior implies fractal...

Self-organization and forcing templates in coastal barrier response to storms

NASA Astrophysics Data System (ADS)

Lazarus, E.

2015-12-01

When a storm event pushes water up and over a coastal barrier, cross-shore flow transports sediment from the barrier face to the back-barrier environment. This natural physical process is called "overwash", and "washover" is the sedimentary deposit it forms. Overwash and washover support critical coastal habitats, and enable barriers to maintain their height and width relative to rising sea level. On developed barrier coasts, overwash constitutes a natural hazard, which sea-level rise will exacerbate. Overwash is also a prerequisite for barrier breaching and coastal flooding. Predicting occurrence and characteristics of overwash and washover has significant societal value. Hazard models typically assume that pre-storm barrier morphology determines how the barrier changes during a storm. However, classic work has documented the absence of a relationship between pre/post-storm topography in some cases, and has also identified rhythmic patterns in washover alongshore. Previous explanations for these spatial patterns have looked to forcing templates, forms that get imprinted in the barrier shape. An alternative explanation is that washover patterns self-organize, emerging from feedbacks between water flow and sediment transport. Self-organization and forcing templates are often framed as mutually exclusive, but patterns likely form across a continuum of conditions. Here, I use data from a new physical experiment to suggest that spatial patterns in washover can self-organize within the limit of a forcing template of some critical "strength", beyond which pre/post-storm morphologies are highly correlated. Quantifying spatial patterns in washover deposits opens exciting questions regarding coastal morphodynamic response to storms. Measurement of relative template strength over extended spatial (and temporal) scales has the potential to improve hazard assessment and prediction, particularly where template strength is low and self-organization dominates barrier change.

Mechanical models for the self-organization of tubular patterns.

PubMed

Guo, Chin-Lin

2013-01-01

Organogenesis, such as long tubule self-organization, requires long-range coordination of cell mechanics to arrange cell positions and to remodel the extracellular matrix. While the current mainstream in the field of tissue morphogenesis focuses primarily on genetics and chemical signaling, the influence of cell mechanics on the programming of patterning cues in tissue morphogenesis has not been adequately addressed. Here, we review experimental evidence and propose quantitative mechanical models by which cells can create tubular patterns.

Reverse and forward engineering of protein pattern formation.

PubMed

Kretschmer, Simon; Harrington, Leon; Schwille, Petra

2018-05-26

Living systems employ protein pattern formation to regulate important life processes in space and time. Although pattern-forming protein networks have been identified in various prokaryotes and eukaryotes, their systematic experimental characterization is challenging owing to the complex environment of living cells. In turn, cell-free systems are ideally suited for this goal, as they offer defined molecular environments that can be precisely controlled and manipulated. Towards revealing the molecular basis of protein pattern formation, we outline two complementary approaches: the biochemical reverse engineering of reconstituted networks and the de novo design, or forward engineering, of artificial self-organizing systems. We first illustrate the reverse engineering approach by the example of the Escherichia coli Min system, a model system for protein self-organization based on the reversible and energy-dependent interaction of the ATPase MinD and its activating protein MinE with a lipid membrane. By reconstituting MinE mutants impaired in ATPase stimulation, we demonstrate how large-scale Min protein patterns are modulated by MinE activity and concentration. We then provide a perspective on the de novo design of self-organizing protein networks. Tightly integrated reverse and forward engineering approaches will be key to understanding and engineering the intriguing phenomenon of protein pattern formation.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Author(s).

Alternative mechanisms alter the emergent properties of self-organization in mussel beds

PubMed Central

Liu, Quan-Xing; Weerman, Ellen J.; Herman, Peter M. J.; Olff, Han; van de Koppel, Johan

2012-01-01

Theoretical models predict that spatial self-organization can have important, unexpected implications by affecting the functioning of ecosystems in terms of resilience and productivity. Whether and how these emergent effects depend on specific formulations of the underlying mechanisms are questions that are often ignored. Here, we compare two alternative models of regular spatial pattern formation in mussel beds that have different mechanistic descriptions of the facilitative interactions between mussels. The first mechanism involves a reduced mussel loss rate at high density owing to mutual protection between the mussels, which is the basis of prior studies on the pattern formation in mussels. The second mechanism assumes, based on novel experimental evidence, that mussels feed more efficiently on top of mussel-generated hummocks. Model simulations point out that the second mechanism produces very similar types of spatial patterns in mussel beds. Yet the mechanisms predict a strikingly contrasting effect of these spatial patterns on ecosystem functioning, in terms of productivity and resilience. In the first model, where high mussel densities reduce mussel loss rates, patterns are predicted to strongly increase productivity and decrease the recovery time of the bed following a disturbance. When pattern formation is generated by increased feeding efficiency on hummocks, only minor emergent effects of pattern formation on ecosystem functioning are predicted. Our results provide a warning against predictions of the implications and emergent properties of spatial self-organization, when the mechanisms that underlie self-organization are incompletely understood and not based on the experimental study. PMID:22418256

Sugar-Based Polyamides: Self-Organization in Strong Polar Organic Solvents.

PubMed

Rosu, Cornelia; Russo, Paul S; Daly, William H; Cueto, Rafael; Pople, John A; Laine, Roger A; Negulescu, Ioan I

2015-09-14

Periodic patterns resembling spirals were observed to form spontaneously upon unassisted cooling of d-glucaric acid- and d-galactaric acid-based polyamide solutions in N-methyl-N-morpholine oxide (NMMO) monohydrate. Similar observations were made in d-galactaric acid-based polyamide/ionic liquid (IL) solutions. The morphologies were investigated by optical, polarized light and confocal microscopy assays to reveal pattern details. Differential scanning calorimetry was used to monitor solution thermal behavior. Small- and wide-angle X-ray scattering data reflected the complex and heterogeneous nature of the self-organized patterns. Factors such as concentration and temperature were found to influence spiral dimensions and geometry. The distance between rings followed a first-order exponential decay as a function of polymer concentration. Fourier-Transform Infrared Microspectroscopy analysis of spirals pointed to H-bonding between the solvent and the pendant hydroxyl groups of the glucose units from the polymer backbone. Tests on self-organization into spirals of ketal-protected d-galactaric acid polyamides in NMMO monohydrate confirmed the importance of the monosaccharide's pendant free hydroxyl groups on the formation of these patterns. Rheology performed on d-galactaric-based polyamides at high concentration in NMMO monohydrate solution revealed the optimum conditions necessary to process these materials as fibers by spinning. The self-organization of these sugar-based polyamides mimics certain biological materials.

Adaptive self-organization in the embryo: its importance to adult anatomy and to tissue engineering.

PubMed

Davies, Jamie A

2018-04-01

The anatomy of healthy humans shows much minor variation, and twin-studies reveal at least some of this variation cannot be explained genetically. A plausible explanation is that fine-scale anatomy is not specified directly in a genetic programme, but emerges from self-organizing behaviours of cells that, for example, place a new capillary where it happens to be needed to prevent local hypoxia. Self-organizing behaviour can be identified by manipulating growing tissues (e.g. putting them under a spatial constraint) and observing an adaptive change that conserves the character of the normal tissue while altering its precise anatomy. Self-organization can be practically useful in tissue engineering but it is limited; generally, it is good for producing realistic small-scale anatomy but large-scale features will be missing. This is because self-organizing organoids miss critical symmetry-breaking influences present in the embryo: simulating these artificially, for example, with local signal sources, makes anatomy realistic even at large scales. A growing understanding of the mechanisms of self-organization is now allowing synthetic biologists to take their first tentative steps towards constructing artificial multicellular systems that spontaneously organize themselves into patterns, which may soon be extended into three-dimensional shapes. © 2017 The Authors Journal of Anatomy published by John Wiley & Sons Ltd on behalf of Anatomical Society.

Characterizing Communication Networks in a Web-Based Classroom: Cognitive Styles and Linguistic Behavior of Self-Organizing Groups in Online Discussions

ERIC Educational Resources Information Center

Vercellone-Smith, Pamela; Jablokow, Kathryn; Friedel, Curtis

2012-01-01

In this study, we explore the cognitive style profiles and linguistic patterns of self-organizing groups within a web-based graduate education course to determine how cognitive preferences and individual behaviors influence the patterns of information exchange and the formation of communication hierarchies in an online classroom. Network analysis…

Positive Maladjustment as a Transition from Chaos to Order

ERIC Educational Resources Information Center

Laycraft, Krystyna

2009-01-01

Dabrowski's theory of positive disintegration describes patterns and explains mechanisms of human development and has been successfully applied to understanding of gifted individuals. This article shows how the concepts of chaos theory and self-organization such as the sensitivity to initial conditions, positive and negative feedback, bifurcation…

Pattern formation and collective effects in populations of magnetic microswimmers

NASA Astrophysics Data System (ADS)

Vach, Peter J.; Walker, Debora; Fischer, Peer; Fratzl, Peter; Faivre, Damien

2017-03-01

Self-propelled particles are one prototype of synthetic active matter used to understand complex biological processes, such as the coordination of movement in bacterial colonies or schools of fishes. Collective patterns such as clusters were observed for such systems, reproducing features of biological organization. However, one limitation of this model is that the synthetic assemblies are made of identical individuals. Here we introduce an active system based on magnetic particles at colloidal scales. We use identical but also randomly-shaped magnetic micropropellers and show that they exhibit dynamic and reversible pattern formation.

Feedback, Lineages and Self-Organizing Morphogenesis

PubMed Central

Calof, Anne L.; Lowengrub, John S.; Lander, Arthur D.

2016-01-01

Feedback regulation of cell lineage progression plays an important role in tissue size homeostasis, but whether such feedback also plays an important role in tissue morphogenesis has yet to be explored. Here we use mathematical modeling to show that a particular feedback architecture in which both positive and negative diffusible signals act on stem and/or progenitor cells leads to the appearance of bistable or bi-modal growth behaviors, ultrasensitivity to external growth cues, local growth-driven budding, self-sustaining elongation, and the triggering of self-organization in the form of lamellar fingers. Such behaviors arise not through regulation of cell cycle speeds, but through the control of stem or progenitor self-renewal. Even though the spatial patterns that arise in this setting are the result of interactions between diffusible factors with antagonistic effects, morphogenesis is not the consequence of Turing-type instabilities. PMID:26989903

Data Mining in Cyber Operations

DTIC Science & Technology

2014-07-01

information processing units intended to mimic the network of neurons in the human brain for performing pattern recognition  Self- organizing maps (SOM...patterns are mined from in order to influence the learning model . An exploratory attack does not alter the training process , but rather uses other...New Jersey: Prentice Hall. 21) Kohonen, T. (1982). Self- organized formation of topologically correct feature maps. Biological Cybernetics , 43, 59–69

SPM Investigation of Thiolated Gold Nanoparticle Patterns Deposited on Different Self-Assembled Substrates

NASA Astrophysics Data System (ADS)

Sbrana, F.; Parodi, M. T.; Ricci, D.; Di Zitti, E.

We present the results of a Scanning Probe Microscopy (SPM) investigation of ordered nanosized metallo-organic structures. Our aim is to investigate the organization and stability of thiolated gold nanoparticles in a compact pattern when deposited onto gold substrates functionalized with self-assembled monolayers made from two molecules that differ essentially in their terminating group: 1,4-benzenedimethanethiol and 4-methylbenzylthiol.

Machine-learned analysis of quantitative sensory testing responses to noxious cold stimulation in healthy subjects.

PubMed

Weyer-Menkhoff, I; Thrun, M C; Lötsch, J

2018-05-01

Pain in response to noxious cold has a complex molecular background probably involving several types of sensors. A recent observation has been the multimodal distribution of human cold pain thresholds. This study aimed at analysing reproducibility and stability of this observation and further exploration of data patterns supporting a complex background. Pain thresholds to noxious cold stimuli (range 32-0 °C, tonic: temperature decrease -1 °C/s, phasic: temperature decrease -8 °C/s) were acquired in 148 healthy volunteers. The probability density distribution was analysed using machine-learning derived methods implemented as Gaussian mixture modeling (GMM), emergent self-organizing maps and self-organizing swarms of data agents. The probability density function of pain responses was trimodal (mean thresholds at 25.9, 18.4 and 8.0 °C for tonic and 24.5, 18.1 and 7.5 °C for phasic stimuli). Subjects' association with Gaussian modes was consistent between both types of stimuli (weighted Cohen's κ = 0.91). Patterns emerging in self-organizing neuronal maps and swarms could be associated with different trends towards decreasing cold pain sensitivity in different Gaussian modes. On self-organizing maps, the third Gaussian mode emerged as particularly distinct. Thresholds at, roughly, 25 and 18 °C agree with known working temperatures of TRPM8 and TRPA1 ion channels, respectively, and hint at relative local dominance of either channel in respective subjects. Data patterns suggest involvement of further distinct mechanisms in cold pain perception at lower temperatures. Findings support data science approaches to identify biologically plausible hints at complex molecular mechanisms underlying human pain phenotypes. Sensitivity to pain is heterogeneous. Data-driven computational research approaches allow the identification of subgroups of subjects with a distinct pattern of sensitivity to cold stimuli. The subgroups are reproducible with different types of noxious cold stimuli. Subgroups show pattern that hints at distinct and inter-individually different types of the underlying molecular background. © 2018 European Pain Federation - EFIC®.

How complexity science can inform scale-up and spread in health care: understanding the role of self-organization in variation across local contexts.

PubMed

Lanham, Holly Jordan; Leykum, Luci K; Taylor, Barbara S; McCannon, C Joseph; Lindberg, Curt; Lester, Richard T

2013-09-01

Health care systems struggle to scale-up and spread effective practices across diverse settings. Failures in scale-up and spread (SUS) are often attributed to a lack of consideration for variation in local contexts among different health care delivery settings. We argue that SUS occurs within complex systems and that self-organization plays an important role in the success, or failure, of SUS. Self-organization is a process whereby local interactions give rise to patterns of organizing. These patterns may be stable or unstable, and they evolve over time. Self-organization is a major contributor to local variations across health care delivery settings. Thus, better understanding of self-organization in the context of SUS is needed. We re-examine two cases of successful SUS: 1) the application of a mobile phone short message service intervention to improve adherence to medications during HIV treatment scale up in resource-limited settings, and 2) MRSA prevention in hospital inpatient settings in the United States. Based on insights from these cases, we discuss the role of interdependencies and sensemaking in leveraging self-organization in SUS initiatives. We argue that self-organization, while not completely controllable, can be influenced, and that improving interdependencies and sensemaking among SUS stakeholders is a strategy for facilitating self-organization processes that increase the probability of spreading effective practices across diverse settings. Published by Elsevier Ltd.

Patterning Self-Assembled Monolayers on Gold: Green Materials Chemistry in the Teaching Laboratory

ERIC Educational Resources Information Center

McFarland, Adam D.; Huffman, Lauren M.; Parent, Kathryn, E.; Hutchison, James E.; Thompson, John E.

2004-01-01

An experiment demonstrating self-assembled monolayer (SAM) chemistry, organic thin-film patterning and the use of molecular functionality to control macroscopic properties is described. Several important green chemistry principles are introduced.

Drying bacterial biosaline patterns capable of vital reanimation upon rehydration: novel hibernating biomineralogical life formations.

PubMed

Gómez Gómez, José María; Medina, Jesús; Hochberg, David; Mateo-Martí, Eva; Martínez-Frías, Jesús; Rull, Fernando

2014-07-01

Water is the fundamental molecule for life on Earth. Thus, the search for hibernating life-forms in waterless environments is an important research topic for astrobiology. To date, however, the organizational patterns containing microbial life in extremely dry places, such as the deserts of Earth, the Dry Valleys of Antarctica, or Mars analog regolith, have been poorly characterized. Here, we report on the formation of bacterial biosaline self-organized drying patterns formed over plastic surfaces. These emerge during the evaporation of sessile droplets of aqueous NaCl salt 0.15 M solutions containing Escherichia coli cells. In the present study, scanning electron microscopy (SEM) and energy dispersive X-ray spectrometry (EDS) analyses indicated that the bacterial cells and the NaCl in these biosaline formations are organized in a two-layered characteristic 3-D architectural morphology. A thin filmlike top layer formed by NaCl conjugated to, and intermingled with, "mineralized" bacterial cells covers a bottom layer constructed by the bulk of the nonmineralized bacterial cells; both layers have the same morphological pattern. In addition, optical microscopic time-lapsed movies show that the formation of these patterns is a kinetically fast process that requires the coupled interaction between the salt and the bacterial cells. Apparently, this mutual interaction drives the generative process of self-assembly that underlies the drying pattern formation. Most notably, the bacterial cells inside these drying self-assembled patterns enter into a quiescent suspended anhydrobiotic state resistant to complete desiccation and capable of vital reanimation upon rehydration. We propose that these E. coli biosaline drying patterns represent an excellent experimental model for understanding different aspects of anhydrobiosis phenomena in bacteria as well as for revealing the mechanisms of bacterially induced biomineralization, both highly relevant topics for the search of life in extraterrestrial locations.

Cell adhesion and mechanics as drivers of tissue organization and differentiation: local cues for large scale organization.

PubMed

Wickström, Sara A; Niessen, Carien M

2018-06-01

Biological patterns emerge through specialization of genetically identical cells to take up distinct fates according to their position within the organism. How initial symmetry is broken to give rise to these patterns remains an intriguing open question. Several theories of patterning have been proposed, most prominently Turing's reaction-diffusion model of a slowly diffusing activator and a fast diffusing inhibitor generating periodic patterns. Although these reaction-diffusion systems can generate diverse patterns, it is becoming increasingly evident that cell shape and tension anisotropies, mediated via cell-cell and/or cell-matrix contacts, also facilitate symmetry breaking and subsequent self-organized tissue patterning. This review will highlight recent studies that implicate local changes in adhesion and/or tension as key drivers of cell rearrangements. We will also discuss recent studies on the role of cadherin and integrin adhesive receptors in mediating and responding to local tissue tension asymmetries to coordinate cell fate, position and behavior essential for tissue self-organization and maintenance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Self-organized pattern formation at organic-inorganic interfaces during deposition: Experiment versus modeling

NASA Astrophysics Data System (ADS)

Szillat, F.; Mayr, S. G.

2011-09-01

Self-organized pattern formation during physical vapor deposition of organic materials onto rough inorganic substrates is characterized by a complex morphological evolution as a function of film thickness. We employ a combined experimental-theoretical study using atomic force microscopy and numerically solved continuum rate equations to address morphological evolution in the model system: poly(bisphenol A carbonate) on polycrystalline Cu. As the key ingredients for pattern formation, (i) curvature and interface potential driven surface diffusion, (ii) deposition noise, and (iii) interface boundary effects are identified. Good agreement of experiments and theory, fitting only the Hamaker constant and diffusivity within narrow physical parameter windows, corroborates the underlying physics and paves the way for computer-assisted interface engineering.

Mesoscale pattern formation of self-propelled rods with velocity reversal

NASA Astrophysics Data System (ADS)

Großmann, Robert; Peruani, Fernando; Bär, Markus

2016-11-01

We study self-propelled particles with velocity reversal interacting by uniaxial (nematic) alignment within a coarse-grained hydrodynamic theory. Combining analytical and numerical continuation techniques, we show that the physics of this active system is essentially controlled by the reversal frequency. In particular, we find that elongated, high-density, ordered patterns, called bands, emerge via subcritical bifurcations from spatially homogeneous states. Our analysis reveals further that the interaction of bands is weakly attractive and, consequently, bands fuse upon collision in analogy with nonequilibrium nucleation processes. Moreover, we demonstrate that a renormalized positive line tension can be assigned to stable bands below a critical reversal rate, beyond which they are transversally unstable. In addition, we discuss the kinetic roughening of bands as well as their nonlinear dynamics close to the threshold of transversal instability. Altogether, the reduction of the multiparticle system onto the dynamics of bands provides a unified framework to understand the emergence and stability of nonequilibrium patterns in this self-propelled particle system. In this regard, our results constitute a proof of principle in favor of the hypothesis in microbiology that velocity reversal of gliding rod-shaped bacteria regulates the transitions between various self-organized patterns observed during the bacterial life cycle.

Self-organizing human cardiac microchambers mediated by geometric confinement

NASA Astrophysics Data System (ADS)

Ma, Zhen; Wang, Jason; Loskill, Peter; Huebsch, Nathaniel; Koo, Sangmo; Svedlund, Felicia L.; Marks, Natalie C.; Hua, Ethan W.; Grigoropoulos, Costas P.; Conklin, Bruce R.; Healy, Kevin E.

2015-07-01

Tissue morphogenesis and organ formation are the consequences of biochemical and biophysical cues that lead to cellular spatial patterning in development. To model such events in vitro, we use PEG-patterned substrates to geometrically confine human pluripotent stem cell colonies and spatially present mechanical stress. Modulation of the WNT/β-catenin pathway promotes spatial patterning via geometric confinement of the cell condensation process during epithelial-mesenchymal transition, forcing cells at the perimeter to express an OCT4+ annulus, which is coincident with a region of higher cell density and E-cadherin expression. The biochemical and biophysical cues synergistically induce self-organizing lineage specification and creation of a beating human cardiac microchamber confined by the pattern geometry. These highly defined human cardiac microchambers can be used to study aspects of embryonic spatial patterning, early cardiac development and drug-induced developmental toxicity.

Self-consistent modeling of self-organized patterns of spots on anodes of DC glow discharges

NASA Astrophysics Data System (ADS)

Bieniek, M. S.; Almeida, P. G. C.; Benilov, M. S.

2018-05-01

Self-organized patterns of spots on a flat metallic anode in a cylindrical glow discharge tube are simulated. A standard model of glow discharges is used, comprising conservation and transport equations for a single species of ion and electrons, written with the use of the drift-diffusion and local-field approximations, and the Poisson equation. Only processes in the near-anode region are considered and the computation domain is the region between the anode and the discharge column. Multiple solutions, existing in the same range of discharge current and describing modes with and without anode spots, are computed for the first time. A reversal of the local anode current density in the spots was found, i.e. mini-cathodes are formed inside the spots or, as one could say, anode spots operate as a unipolar glow discharge. The solutions do not fit into the conventional pattern of self-organization in bistable nonlinear dissipative systems; In particular, the modes are not joined by bifurcations.

Regulation of Spatiotemporal Patterns by Biological Variability: General Principles and Applications to Dictyostelium discoideum

PubMed Central

Grace, Miriam; Hütt, Marc-Thorsten

2015-01-01

Spatiotemporal patterns often emerge from local interactions in a self-organizing fashion. In biology, the resulting patterns are also subject to the influence of the systematic differences between the system’s constituents (biological variability). This regulation of spatiotemporal patterns by biological variability is the topic of our review. We discuss several examples of correlations between cell properties and the self-organized spatiotemporal patterns, together with their relevance for biology. Our guiding, illustrative example will be spiral waves of cAMP in a colony of Dictyostelium discoideum cells. Analogous processes take place in diverse situations (such as cardiac tissue, where spiral waves occur in potentially fatal ventricular fibrillation) so a deeper understanding of this additional layer of self-organized pattern formation would be beneficial to a wide range of applications. One of the most striking differences between pattern-forming systems in physics or chemistry and those in biology is the potential importance of variability. In the former, system components are essentially identical with random fluctuations determining the details of the self-organization process and the resulting patterns. In biology, due to variability, the properties of potentially very few cells can have a driving influence on the resulting asymptotic collective state of the colony. Variability is one means of implementing a few-element control on the collective mode. Regulatory architectures, parameters of signaling cascades, and properties of structure formation processes can be "reverse-engineered" from observed spatiotemporal patterns, as different types of regulation and forms of interactions between the constituents can lead to markedly different correlations. The power of this biology-inspired view of pattern formation lies in building a bridge between two scales: the patterns as a collective state of a very large number of cells on the one hand, and the internal parameters of the single cells on the other. PMID:26562406

Organically Grown Architectures: Creating Decentralized, Autonomous Systems by Embryomorphic Engineering

NASA Astrophysics Data System (ADS)

Doursat, René

Exploding growth growth in computational systems forces us to gradually replace rigid design and control with decentralization and autonomy. Information technologies will progress, instead, by"meta-designing" mechanisms of system self-assembly, self-regulation and evolution. Nature offers a great variety of efficient complex systems, in which numerous small elements form large-scale, adaptive patterns. The new engineering challenge is to recreate this self-organization and let it freely generate innovative designs under guidance. This article presents an original model of artificial system growth inspired by embryogenesis. A virtual organism is a lattice of cells that proliferate, migrate and self-pattern into differentiated domains. Each cell's fate is controlled by an internal gene regulatory network network. Embryomorphic engineering emphasizes hyperdistributed architectures, and their development as a prerequisite of evolutionary design.

Trophic interactions induce spatial self-organization of microbial consortia on rough surfaces.

PubMed

Wang, Gang; Or, Dani

2014-10-24

The spatial context of microbial interactions common in natural systems is largely absent in traditional pure culture-based microbiology. The understanding of how interdependent microbial communities assemble and coexist in limited spatial domains remains sketchy. A mechanistic model of cell-level interactions among multispecies microbial populations grown on hydrated rough surfaces facilitated systematic evaluation of how trophic dependencies shape spatial self-organization of microbial consortia in complex diffusion fields. The emerging patterns were persistent irrespective of initial conditions and resilient to spatial and temporal perturbations. Surprisingly, the hydration conditions conducive for self-assembly are extremely narrow and last only while microbial cells remain motile within thin aqueous films. The resulting self-organized microbial consortia patterns could represent optimal ecological templates for the architecture that underlie sessile microbial colonies on natural surfaces. Understanding microbial spatial self-organization offers new insights into mechanisms that sustain small-scale soil microbial diversity; and may guide the engineering of functional artificial microbial consortia.

Centro-Apical Self-Organization of Organic Semiconductors in a Line-Printed Organic Semiconductor: Polymer Blend for One-Step Printing Fabrication of Organic Field-Effect Transistors

PubMed Central

Jin Lee, Su; Kim, Yong-Jae; Young Yeo, So; Lee, Eunji; Sun Lim, Ho; Kim, Min; Song, Yong-Won; Cho, Jinhan; Ah Lim, Jung

2015-01-01

Here we report the first demonstration for centro-apical self-organization of organic semiconductors in a line-printed organic semiconductor: polymer blend. Key feature of this work is that organic semiconductor molecules were vertically segregated on top of the polymer phase and simultaneously crystallized at the center of the printed line pattern after solvent evaporation without an additive process. The thickness and width of the centro-apically segregated organic semiconductor crystalline stripe in the printed blend pattern were controlled by varying the relative content of the organic semiconductors, printing speed, and solution concentrations. The centro-apical self-organization of organic semiconductor molecules in a printed polymer blend may be attributed to the combination of an energetically favorable vertical phase-separation and hydrodynamic fluids inside the droplet during solvent evaporation. Finally, a centro-apically phase-separated bilayer structure of organic semiconductor: polymer blend was successfully demonstrated as a facile method to form the semiconductor and dielectric layer for OFETs in one- step. PMID:26359068

Centro-Apical Self-Organization of Organic Semiconductors in a Line-Printed Organic Semiconductor: Polymer Blend for One-Step Printing Fabrication of Organic Field-Effect Transistors.

PubMed

Lee, Su Jin; Kim, Yong-Jae; Yeo, So Young; Lee, Eunji; Lim, Ho Sun; Kim, Min; Song, Yong-Won; Cho, Jinhan; Lim, Jung Ah

2015-09-11

Here we report the first demonstration for centro-apical self-organization of organic semiconductors in a line-printed organic semiconductor: polymer blend. Key feature of this work is that organic semiconductor molecules were vertically segregated on top of the polymer phase and simultaneously crystallized at the center of the printed line pattern after solvent evaporation without an additive process. The thickness and width of the centro-apically segregated organic semiconductor crystalline stripe in the printed blend pattern were controlled by varying the relative content of the organic semiconductors, printing speed, and solution concentrations. The centro-apical self-organization of organic semiconductor molecules in a printed polymer blend may be attributed to the combination of an energetically favorable vertical phase-separation and hydrodynamic fluids inside the droplet during solvent evaporation. Finally, a centro-apically phase-separated bilayer structure of organic semiconductor: polymer blend was successfully demonstrated as a facile method to form the semiconductor and dielectric layer for OFETs in one- step.

Directed ordering of phase separated domains and dewetting of thin polymer blend films on a topographically patterned substrate.

PubMed

Bhandaru, Nandini; Karim, Alamgir; Mukherjee, Rabibrata

2017-07-21

Substrate pattern guided self-organization of ultrathin and confined polymeric films on a topographically patterned substrate is a useful approach for obtaining ordered meso and nano structures over large areas, particularly if the ordering is achieved during film preparation itself, eliminating any post-processing such as thermal or solvent vapor annealing. By casting a dilute solution of two immiscible polymers, polystyrene (PS) and polymethylmethacrylate (PMMA), from a common solvent (toluene) on a topographically patterned substrate with a grating geometry, we show the formation of self-organized meso patterns with various degrees of ordering. The morphology depends on both the concentration of the dispensed solution (C n ) and the blend composition (R B ). Depending on the extent of dewetting during spin coating, the final morphologies can be classified into three distinct categories. At a very low C n the solution dewets fully, resulting in isolated polymer droplets aligned along substrate grooves (Type 1). Type 2 structures comprising isolated threads with aligned phase separated domains along each substrate groove are observed at intermediate C n . A continuous film (Type 3) is obtained above a critical concentration (C n *) that depends on R B . While the extent of ordering of the domains gradually diminishes with an increase in film thickness for Type 3 patterns, the size of the domains remains much smaller than that on a flat substrate, resulting in significant downsizing of the features due to the lateral confinement imposed on the phase separation process by the topographic patterns. Finally, we show that some of these structures exhibit excellent broadband anti-reflection (AR) properties.

Exploring the patterns and evolution of self-organized urban street networks through modeling

NASA Astrophysics Data System (ADS)

Rui, Yikang; Ban, Yifang; Wang, Jiechen; Haas, Jan

2013-03-01

As one of the most important subsystems in cities, urban street networks have recently been well studied by using the approach of complex networks. This paper proposes a growing model for self-organized urban street networks. The model involves a competition among new centers with different values of attraction radius and a local optimal principle of both geometrical and topological factors. We find that with the model growth, the local optimization in the connection process and appropriate probability for the loop construction well reflect the evolution strategy in real-world cities. Moreover, different values of attraction radius in centers competition process lead to morphological change in patterns including urban network, polycentric and monocentric structures. The model succeeds in reproducing a large diversity of road network patterns by varying parameters. The similarity between the properties of our model and empirical results implies that a simple universal growth mechanism exists in self-organized cities.

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template

PubMed Central

Dong, Xiaoli; Grimm, Nancy B.

2017-01-01

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, “wetland”) system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995–2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns. PMID:28559326

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template.

PubMed

Dong, Xiaoli; Ruhí, Albert; Grimm, Nancy B

2017-06-13

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, "wetland") system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995-2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns.

Self-Organizing Global Gene Expression Regulated through Criticality: Mechanism of the Cell-Fate Change

PubMed Central

Tsuchiya, Masa; Giuliani, Alessandro; Hashimoto, Midori; Erenpreisa, Jekaterina; Yoshikawa, Kenichi

2016-01-01

Background A fundamental issue in bioscience is to understand the mechanism that underlies the dynamic control of genome-wide expression through the complex temporal-spatial self-organization of the genome to regulate the change in cell fate. We address this issue by elucidating a physically motivated mechanism of self-organization. Principal Findings Building upon transcriptome experimental data for seven distinct cell fates, including early embryonic development, we demonstrate that self-organized criticality (SOC) plays an essential role in the dynamic control of global gene expression regulation at both the population and single-cell levels. The novel findings are as follows: i) Mechanism of cell-fate changes: A sandpile-type critical transition self-organizes overall expression into a few transcription response domains (critical states). A cell-fate change occurs by means of a dissipative pulse-like global perturbation in self-organization through the erasure of initial-state critical behaviors (criticality). Most notably, the reprogramming of early embryo cells destroys the zygote SOC control to initiate self-organization in the new embryonal genome, which passes through a stochastic overall expression pattern. ii) Mechanism of perturbation of SOC controls: Global perturbations in self-organization involve the temporal regulation of critical states. Quantitative evaluation of this perturbation in terminal cell fates reveals that dynamic interactions between critical states determine the critical-state coherent regulation. The occurrence of a temporal change in criticality perturbs this between-states interaction, which directly affects the entire genomic system. Surprisingly, a sub-critical state, corresponding to an ensemble of genes that shows only marginal changes in expression and consequently are considered to be devoid of any interest, plays an essential role in generating a global perturbation in self-organization directed toward the cell-fate change. Conclusion and Significance ‘Whole-genome’ regulation of gene expression through self-regulatory SOC control complements gene-by-gene fine tuning and represents a still largely unexplored non-equilibrium statistical mechanism that is responsible for the massive reprogramming of genome expression. PMID:27997556

Universality in the Evolution of Orientation Columns in the Visual Cortex

PubMed Central

Kaschube, Matthias; Schnabel, Michael; Löwel, Siegrid; Coppola, David M.; White, Leonard E.; Wolf, Fred

2011-01-01

The brain’s visual cortex processes information concerning form, pattern, and motion within functional maps that reflect the layout of neuronal circuits. We analyzed functional maps of orientation preference in the ferret, tree shrew, and galago—three species separated since the basal radiation of placental mammals more than 65 million years ago—and found a common organizing principle. A symmetry-based class of models for the self-organization of cortical networks predicts all essential features of the layout of these neuronal circuits, but only if suppressive long-range interactions dominate development. We show mathematically that orientation-selective long-range connectivity can mediate the required interactions. Our results suggest that self-organization has canalized the evolution of the neuronal circuitry underlying orientation preference maps into a single common design. PMID:21051599

Self-dissimilar landscapes: Revealing the signature of geologic constraints on landscape dissection via topologic and multi-scale analysis

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Mohammad; Tejedor, Alejandro; Foufoula-Georgiou, Efi

2017-10-01

Climatic or geologic controls, such as tectonics or glacial drainage, might impose constraints on landscape self-organization resulting in spatial patterns of rivers and valleys which do not obey the typical self-similar relationships found in most landscapes. The goal of this study is to quantify how such geologic constraints express themselves on channel network topology, spatial heterogeneity of drainage patterns, and emergence of preferred scales of landscape dissection. We use as an example a basin located in the Upper Midwestern United States where successive glaciations over the past thousand years have led to a pronounced spatially anisotropic channel network structure which defeats most scaling laws of fluvial landscapes. This is contrasted with another river basin in the North-Central U.S. which has been organized under the absence of major geologic influences and follows a typical self-similar channel network organization. We show how the geologic constraints have imposed a competition for space which is captured in the slope-local drainage density probabilistic structure, in the failure of self-similarity in basin-wide river network topology, and in the length-area scaling relationship being not typical of fluvial landscapes. Via a two-dimensional wavelet analysis and synthesis, we demonstrate the occurrence of a gap in the power spectrum which corresponds to the presence of preferred scales of organization, and characterize them through multi-scale detrending. The developed methodologies can be useful in advancing our geomorphologic understanding of how external controls might manifest themselves in creating a landscape dissection that is outside the norm and how this dissection can be studied objectively for understanding cause and effect.

Pattern formation--A missing link in the study of ecosystem response to environmental changes.

PubMed

Meron, Ehud

2016-01-01

Environmental changes can affect the functioning of an ecosystem directly, through the response of individual life forms, or indirectly, through interspecific interactions and community dynamics. The feasibility of a community-level response has motivated numerous studies aimed at understanding the mutual relationships between three elements of ecosystem dynamics: the abiotic environment, biodiversity and ecosystem function. Since ecosystems are inherently nonlinear and spatially extended, environmental changes can also induce pattern-forming instabilities that result in spatial self-organization of life forms and resources. This, in turn, can affect the relationships between these three elements, and make the response of ecosystems to environmental changes far more complex. Responses of this kind can be expected in dryland ecosystems, which show a variety of self-organizing vegetation patterns along the rainfall gradient. This paper describes the progress that has been made in understanding vegetation patterning in dryland ecosystems, and the roles it plays in ecosystem response to environmental variability. The progress has been achieved by modeling pattern-forming feedbacks at small spatial scales and up-scaling their effects to large scales through model studies. This approach sets the basis for integrating pattern formation theory into the study of ecosystem dynamics and addressing ecologically significant questions such as the dynamics of desertification, restoration of degraded landscapes, biodiversity changes along environmental gradients, and shrubland-grassland transitions. Copyright © 2015 Elsevier Inc. All rights reserved.

Polymer-stabilized liquid crystalline topological defect network for micro-pixelated optical devices

NASA Astrophysics Data System (ADS)

Araoka, Fumito; Le, Khoa V.; Fujii, Shuji; Orihara, Hiroshi; Sasaki, Yuji

2018-02-01

Spatially and temporally controlled topological defects in nematic liquid crystals (NLCs) are promising for its potential in optical applications. Utilization of self-organization is a key to fabricate complex micro- and nano-structures which are often difficult to obtain by conventional lithographic tools. Using photo-polymerization technique, here we show a polymer-stabilized NLC having a micro-pixelated structure of regularly ordered umbilical defects which are induced by an electric field. Due to the formation of polymer network, the self-organized pattern is kept stable without deterioration. Moreover, the polymer network allows to template other LCs whose optical properties can be tuned with external stimuli such as temperature and electric fields.

Generating self-organizing collective behavior using separation dynamics from experimental data

NASA Astrophysics Data System (ADS)

Dieck Kattas, Graciano; Xu, Xiao-Ke; Small, Michael

2012-09-01

Mathematical models for systems of interacting agents using simple local rules have been proposed and shown to exhibit emergent swarming behavior. Most of these models are constructed by intuition or manual observations of real phenomena, and later tuned or verified to simulate desired dynamics. In contrast to this approach, we propose using a model that attempts to follow an averaged rule of the essential distance-dependent collective behavior of real pigeon flocks, which was abstracted from experimental data. By using a simple model to follow the behavioral tendencies of real data, we show that our model can exhibit a wide range of emergent self-organizing dynamics such as flocking, pattern formation, and counter-rotating vortices.

Generating self-organizing collective behavior using separation dynamics from experimental data.

PubMed

Dieck Kattas, Graciano; Xu, Xiao-Ke; Small, Michael

2012-09-01

Mathematical models for systems of interacting agents using simple local rules have been proposed and shown to exhibit emergent swarming behavior. Most of these models are constructed by intuition or manual observations of real phenomena, and later tuned or verified to simulate desired dynamics. In contrast to this approach, we propose using a model that attempts to follow an averaged rule of the essential distance-dependent collective behavior of real pigeon flocks, which was abstracted from experimental data. By using a simple model to follow the behavioral tendencies of real data, we show that our model can exhibit a wide range of emergent self-organizing dynamics such as flocking, pattern formation, and counter-rotating vortices.

Self-organization of spatial patterning in human embryonic stem cells

PubMed Central

Deglincerti, Alessia; Etoc, Fred; Ozair, M. Zeeshan; Brivanlou, Ali H.

2017-01-01

The developing embryo is a remarkable example of self-organization, where functional units are created in a complex spatio-temporal choreography. Recently, human embryonic stem cells (ESCs) have been used to recapitulate in vitro the self-organization programs that are executed in the embryo in vivo. This represents a unique opportunity to address self-organization in humans that is otherwise not addressable with current technologies. In this essay, we review the recent literature on self-organization of human ESCs, with a particular focus on two examples: formation of embryonic germ layers and neural rosettes. Intriguingly, both activation and elimination of TGFβ signaling can initiate self-organization, albeit with different molecular underpinnings. We discuss the mechanisms underlying the formation of these structures in vitro and explore future challenges in the field. PMID:26970615

Two-dimensional patterning of colloidal crystals by means of lateral autocloning in edge-patterned cells

NASA Astrophysics Data System (ADS)

Emoto, Akira; Kamei, Tadayoshi; Shioda, Tatsutoshi; Kawatsuki, Nobuhiro; Ono, Hiroshi

2009-06-01

We report the experimental results of two-dimensional patterning of colloidal crystals using edge-patterned cells. Solvent evaporation of a colloidal suspension from the edge of the cell induces self-organized crystallization of spherical colloidal particles. From a reservoir of colloidal suspension in the cell, different colloidal suspensions are injected repetitively. An edge-patterned substrate is introduced into the cell as an upper substrate. As a result, different colloidal crystals are alternately stacked in the lateral direction according to the edge pattern. The characteristics of cloning formation are specifically showed including deformations from the original pattern. This two-dimensional patterning of three-dimensional colloidal crystals by means of lateral autocloning is promising for the development of photonic crystal arrays for use in optic and photonic devices.

Customization and design of directed self-assembly using hybrid prepatterns

NASA Astrophysics Data System (ADS)

Cheng, Joy; Doerk, Gregory S.; Rettner, Charles T.; Singh, Gurpreet; Tjio, Melia; Truong, Hoa; Arellano, Noel; Balakrishnan, Srinivasan; Brink, Markus; Tsai, Hsinyu; Liu, Chi-Chun; Guillorn, Michael; Sanders, Daniel P.

2015-03-01

Diminishing error tolerance renders the customization of patterns created through directed self-assembly (DSA) extremely challenging at tighter pitch. A self-aligned customization scheme can be achieved using a hybrid prepattern comprising both organic and inorganic regions that serves as a guiding prepattern to direct the self-assembly of the block copolymers as well as a cut mask pattern for the DSA arrays aligned to it. In this paper, chemoepitaxy-based self-aligned customization is demonstrated using two types of organic-inorganic prepatterns. CHEETAH prepattern for "CHemoepitaxy Etch Trim using a self-Aligned Hardmask" of preferential hydrogen silsesquioxane (HSQ, inorganic resist), non-preferential organic underlayer is fabricated using electron beam lithography. Customized trench or hole arrays can be achieved through co-transfer of DSA-formed arrays and CHEETAH prepattern. Herein, we also introduce a tone-reversed version called reverse-CHEETAH (or rCHEETAH) in which customized line segments can be achieved through co-transfer of DSA-formed arrays formed on a prepattern wherein the inorganic HSQ regions are nonpreferential and the organic regions are PMMA preferential. Examples of two-dimensional self-aligned customization including 25nm pitch fin structures and an 8-bar "IBM" illustrate the versatility of this customization scheme using rCHEETAH.

Discovery of fairy circles in Australia supports self-organization theory

PubMed Central

Getzin, Stephan; Yizhaq, Hezi; Bell, Bronwyn; Erickson, Todd E.; Postle, Anthony C.; Katra, Itzhak; Tzuk, Omer; Zelnik, Yuval R.; Wiegand, Kerstin; Wiegand, Thorsten; Meron, Ehud

2016-01-01

Vegetation gap patterns in arid grasslands, such as the “fairy circles” of Namibia, are one of nature’s greatest mysteries and subject to a lively debate on their origin. They are characterized by small-scale hexagonal ordering of circular bare-soil gaps that persists uniformly in the landscape scale to form a homogeneous distribution. Pattern-formation theory predicts that such highly ordered gap patterns should be found also in other water-limited systems across the globe, even if the mechanisms of their formation are different. Here we report that so far unknown fairy circles with the same spatial structure exist 10,000 km away from Namibia in the remote outback of Australia. Combining fieldwork, remote sensing, spatial pattern analysis, and process-based mathematical modeling, we demonstrate that these patterns emerge by self-organization, with no correlation with termite activity; the driving mechanism is a positive biomass–water feedback associated with water runoff and biomass-dependent infiltration rates. The remarkable match between the patterns of Australian and Namibian fairy circles and model results indicate that both patterns emerge from a nonuniform stationary instability, supporting a central universality principle of pattern-formation theory. Applied to the context of dryland vegetation, this principle predicts that different systems that go through the same instability type will show similar vegetation patterns even if the feedback mechanisms and resulting soil–water distributions are different, as we indeed found by comparing the Australian and the Namibian fairy-circle ecosystems. These results suggest that biomass–water feedbacks and resultant vegetation gap patterns are likely more common in remote drylands than is currently known. PMID:26976567

Novel High-Activity Organic Piezoelectric Materials - From Single-Molecule Response to Energy Harvesting Films

DTIC Science & Technology

2015-08-24

microcontact printing techniques to deposit and pattern intrinsically polar self - assembled monolayers (SAMs) on smooth template-stripped gold films...and large piezoresponse. Stamp Stamp Gold Gold 10 μm 10 μ m 1.5 1.0 0.5 0.0 -0.5 -1.0 -1.5 nm Fig. 7. Patterned self - assembled monolayers of...SAM. Importantly, deposition and patterning of thiol self - assembled monolayers on gold surfaces is facile, creating in intrinsically polar film for

Self-organization in psychotherapy: testing the synergetic model of change processes

PubMed Central

Schiepek, Günter K.; Tominschek, Igor; Heinzel, Stephan

2014-01-01

In recent years, models have been developed that conceive psychotherapy as a self-organizing process of bio-psycho-social systems. These models originate from the theory of self-organization (Synergetics), from the theory of deterministic chaos, or from the approach of self-organized criticality. This process-outcome study examines several hypotheses mainly derived from Synergetics, including the assumption of discontinuous changes in psychotherapy (instead of linear incremental gains), the occurrence of critical instabilities in temporal proximity of pattern transitions, the hypothesis of necessary stable boundary conditions during destabilization processes, and of motivation to change playing the role of a control parameter for psychotherapeutic self-organization. Our study was realized at a day treatment center; 23 patients with obsessive compulsive disorder (OCD) were included. Client self-assessment was performed by an Internet-based process monitoring (referred to as the Synergetic Navigation System), whereby daily ratings were recorded through administering the Therapy Process Questionnaire (TPQ). The process measures of the study were extracted from the subscale dynamics (including the dynamic complexity of their time series) of the TPQ. The outcome criterion was measured by the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) which was completed pre-post and on a bi-weekly schedule by all patients. A second outcome criterion was based on the symptom severity subscale of the TPQ. Results supported the hypothesis of discontinuous changes (pattern transitions), the occurrence of critical instabilities preparing pattern transitions, and of stable boundary conditions as prerequisites for such transitions, but not the assumption of motivation to change as a control parameter. PMID:25324801

Self-organization in psychotherapy: testing the synergetic model of change processes.

PubMed

Schiepek, Günter K; Tominschek, Igor; Heinzel, Stephan

2014-01-01

In recent years, models have been developed that conceive psychotherapy as a self-organizing process of bio-psycho-social systems. These models originate from the theory of self-organization (Synergetics), from the theory of deterministic chaos, or from the approach of self-organized criticality. This process-outcome study examines several hypotheses mainly derived from Synergetics, including the assumption of discontinuous changes in psychotherapy (instead of linear incremental gains), the occurrence of critical instabilities in temporal proximity of pattern transitions, the hypothesis of necessary stable boundary conditions during destabilization processes, and of motivation to change playing the role of a control parameter for psychotherapeutic self-organization. Our study was realized at a day treatment center; 23 patients with obsessive compulsive disorder (OCD) were included. Client self-assessment was performed by an Internet-based process monitoring (referred to as the Synergetic Navigation System), whereby daily ratings were recorded through administering the Therapy Process Questionnaire (TPQ). The process measures of the study were extracted from the subscale dynamics (including the dynamic complexity of their time series) of the TPQ. The outcome criterion was measured by the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) which was completed pre-post and on a bi-weekly schedule by all patients. A second outcome criterion was based on the symptom severity subscale of the TPQ. Results supported the hypothesis of discontinuous changes (pattern transitions), the occurrence of critical instabilities preparing pattern transitions, and of stable boundary conditions as prerequisites for such transitions, but not the assumption of motivation to change as a control parameter.

Communication-based regulated freedom of response in bacterial colonies

NASA Astrophysics Data System (ADS)

Ben-Jacob, Eshel; Shapira, Yoash; Becker, Israela; Raichman, Nadav; Volman, Vladislav; Hulata, Eyal; Baruchi, Itay

2003-12-01

Bacteria have developed intricate communication capabilities on all levels-the genome, the individual bacteria, the colony, and multi-colonial eco-systems of different bacterial species. All manner of biochemical messages are utilized for communication, including simple and complex abiotic molecules, peptides, proteins and even genetic sequences. These communication capabilities are required for bacterial cooperative self-organization into multicellular hierarchically structured colonies with complex spatio-temporal patterning. A colonial higher complexity is required for better colonial adaptability in a dynamic environment. The communication-based cooperative self-organization goes hand in hand with changes in cell structure and behavior. We identify two classes of such changes: (1) automatic and predetermined changes, which are triggered by inducive messages. (2) Regulated “decision-making” changes, which represent cellular regulated freedom of response to informative (semantic) messages. Each bacterium has internal degrees of freedom and informatics capabilities (storage, processing and interpretation of information). These features are required for the freedom of response in self-alteration (self-plasticity). Additionally, the cell can send messages to alter other bacteria in a self-regulated manner. To convert the above seemingly blurred notions into testable concepts we present the first steps towards quantification of colonial features associated with “regulated freedom”. For this we extract a binary representation of the observed patterns to show the existence of Lévy distributions with parameters that range from near the Cauchy limit to the Gaussian limit. The assumption about bacterial “regulated freedom” or “decision-making” appears in contradict the fundamental principle of time causality. We propose, that this apparent difficulty might be resolved by applying the recent understandings of biotic and abiotic self-organization, to the dynamics of the cells’ internal biochemical gel.

Microtubules and motor proteins: Mechanically regulated self-organization in vivo

NASA Astrophysics Data System (ADS)

Vogel, S. K.; Pavin, N.; Maghelli, N.; Jülicher, F.; Tolić-Nørrelykke, I. M.

2009-11-01

A key aspect of life is sexual reproduction, which requires concerted movement. For successful mixing of the genetic material, molecular motors move the nucleus back and forth inside the cell. How motors work together to produce these large-scale movements, however, remains a mystery. To answer this question, we studied nuclear movement in fission yeast, which is driven by motor proteins pulling on microtubules. We show that motor proteins dynamically redistribute from one part of the cell to the other, generating asymmetric patterns of motors and, consequently, of forces that generate movement. By combining quantitative live cell imaging and laser ablation with a theoretical model, we find that this dynamic motor redistribution occurs purely as a result of changes in the mechanical strain sensed by the motor proteins. Our work therefore demonstrates that spatio-temporal pattern formation within a cell can occur as a result of mechanical cues (Vogel et al., 2009), which differs from conventional molecular signaling, as well as from self-organization based on a combination of biochemical reactions and diffusion.

Lead spatio-temporal pattern identification in urban microenvironments using moss bags and the Kohonen self-organizing maps

NASA Astrophysics Data System (ADS)

Deljanin, Isidora; Antanasijević, Davor; Vuković, Gordana; Urošević, Mira Aničić; Tomašević, Milica; Perić-Grujić, Aleksandra; Ristić, Mirjana

2015-09-01

The first investigation of the use of the Kohonen self-organizing map (SOM) which includes lead concentration and its isotopic composition in moss bags to assess the spatial and temporal patterns of lead in the urban microenvironments is presented in this paper. The moss bags experiment was carried out during 2011 in the city tunnel in Belgrade, as well as in street canyons at different heights (4, 8 and 16 m) and in public garages. The moss bags were exposed for 5 and 10 weeks. The results revealed that the 10 weeks period represents suitable exposure time in screening Pb isotopic composition in active biomonitoring analysis. The obtained results showed that the SOM analysis, by recognizing slight differences among moss samples regarding exposure time, horizontal and vertical spatial distribution, with both, contribution of stable lead isotopes and Pb concentration, could be recommended in biomonitoring analysis of lead distribution in urban microenvironments.

Self-Organization of Spatial Patterning in Human Embryonic Stem Cells.

PubMed

Deglincerti, Alessia; Etoc, Fred; Ozair, M Zeeshan; Brivanlou, Ali H

2016-01-01

The developing embryo is a remarkable example of self-organization, where functional units are created in a complex spatiotemporal choreography. Recently, human embryonic stem cells (ESCs) have been used to recapitulate in vitro the self-organization programs that are executed in the embryo in vivo. This represents an unique opportunity to address self-organization in humans that is otherwise not addressable with current technologies. In this chapter, we review the recent literature on self-organization of human ESCs, with a particular focus on two examples: formation of embryonic germ layers and neural rosettes. Intriguingly, both activation and elimination of TGFβ signaling can initiate self-organization, albeit with different molecular underpinnings. We discuss the mechanisms underlying the formation of these structures in vitro and explore future challenges in the field. © 2016 Elsevier Inc. All rights reserved.

A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis

PubMed Central

Refahi, Yassin; Brunoud, Géraldine; Farcot, Etienne; Jean-Marie, Alain; Pulkkinen, Minna; Vernoux, Teva; Godin, Christophe

2016-01-01

Exploration of developmental mechanisms classically relies on analysis of pattern regularities. Whether disorders induced by biological noise may carry information on building principles of developmental systems is an important debated question. Here, we addressed theoretically this question using phyllotaxis, the geometric arrangement of plant aerial organs, as a model system. Phyllotaxis arises from reiterative organogenesis driven by lateral inhibitions at the shoot apex. Motivated by recurrent observations of disorders in phyllotaxis patterns, we revisited in depth the classical deterministic view of phyllotaxis. We developed a stochastic model of primordia initiation at the shoot apex, integrating locality and stochasticity in the patterning system. This stochastic model recapitulates phyllotactic patterns, both regular and irregular, and makes quantitative predictions on the nature of disorders arising from noise. We further show that disorders in phyllotaxis instruct us on the parameters governing phyllotaxis dynamics, thus that disorders can reveal biological watermarks of developmental systems. DOI: http://dx.doi.org/10.7554/eLife.14093.001 PMID:27380805

Self-organization of neural tissue architectures from pluripotent stem cells.

PubMed

Karus, Michael; Blaess, Sandra; Brüstle, Oliver

2014-08-15

Despite being a subject of intensive research, the mechanisms underlying the formation of neural tissue architectures during development of the central nervous system remain largely enigmatic. So far, studies into neural pattern formation have been restricted mainly to animal experiments. With the advent of pluripotent stem cells it has become possible to explore early steps of nervous system development in vitro. These studies have unraveled a remarkable propensity of primitive neural cells to self-organize into primitive patterns such as neural tube-like rosettes in vitro. Data from more advanced 3D culture systems indicate that this intrinsic propensity for self-organization can even extend to the formation of complex architectures such as a multilayered cortical neuroepithelium or an entire optic cup. These novel experimental paradigms not only demonstrate the enormous self-organization capacity of neural stem cells, they also provide exciting prospects for studying the earliest steps of human neural tissue development and the pathogenesis of brain malformations in reductionist in vitro paradigms. © 2014 Wiley Periodicals, Inc.

Hierarchical random walks in trace fossils and the origin of optimal search behavior

PubMed Central

Sims, David W.; Reynolds, Andrew M.; Humphries, Nicolas E.; Southall, Emily J.; Wearmouth, Victoria J.; Metcalfe, Brett; Twitchett, Richard J.

2014-01-01

Efficient searching is crucial for timely location of food and other resources. Recent studies show that diverse living animals use a theoretically optimal scale-free random search for sparse resources known as a Lévy walk, but little is known of the origins and evolution of foraging behavior and the search strategies of extinct organisms. Here, using simulations of self-avoiding trace fossil trails, we show that randomly introduced strophotaxis (U-turns)—initiated by obstructions such as self-trail avoidance or innate cueing—leads to random looping patterns with clustering across increasing scales that is consistent with the presence of Lévy walks. This predicts that optimal Lévy searches may emerge from simple behaviors observed in fossil trails. We then analyzed fossilized trails of benthic marine organisms by using a novel path analysis technique and find the first evidence, to our knowledge, of Lévy-like search strategies in extinct animals. Our results show that simple search behaviors of extinct animals in heterogeneous environments give rise to hierarchically nested Brownian walk clusters that converge to optimal Lévy patterns. Primary productivity collapse and large-scale food scarcity characterizing mass extinctions evident in the fossil record may have triggered adaptation of optimal Lévy-like searches. The findings suggest that Lévy-like behavior has been used by foragers since at least the Eocene but may have a more ancient origin, which might explain recent widespread observations of such patterns among modern taxa. PMID:25024221

Effect of self-organized interdependence between populations on the evolution of cooperation

NASA Astrophysics Data System (ADS)

Luo, Chao; Zhang, Xiaolin

2017-01-01

In this article, based on interdependent networks, the effect of self-organized interdependence on the evolution of cooperation is studied. Different from the previous works, the interdependent strength, which can effectively improve the fitness of players, is taken as a kind of limited resources and co-evolves with players' strategy. We show that the self-organization of interdependent strength would spontaneously lead to power law distribution at the stationary state, where the level of cooperation in system can be significantly promoted. Furthermore, when intermediate quantity of interdependence resources existing in system, the power law distribution is most evident with the power β ≈ 1.72, meanwhile the level of cooperation also reaches the maximum value. We discuss the related microscopic system properties which are responsible for the observed results and also demonstrate that the power law distribution of interdependence resources is an elementary property which is robust against the governing repeated games and the initial resources allocation patterns.

Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

PubMed

Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

2015-11-01

In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Hui; Song, Yongduan; Xue, Fangzheng

In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than themore » SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.« less

Network approach to patterns in stratocumulus clouds

NASA Astrophysics Data System (ADS)

Glassmeier, Franziska; Feingold, Graham

2017-10-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Network approach to patterns in stratocumulus clouds.

PubMed

Glassmeier, Franziska; Feingold, Graham

2017-10-03

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth's climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis's Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Network approach to patterns in stratocumulus clouds

PubMed Central

Feingold, Graham

2017-01-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav–Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes. PMID:28904097

On the Correlation Between the Self-Organized Island Pattern and Substrate Elastic Anisotropy

DTIC Science & Technology

2007-04-01

eters would be most useful to experimentalists. The kinetic Monte Carlo KMC has been proposed re- cently to study QD island self-organization by many...time ti. 21,25 Based on a proposed coupled KMC , the authors simu- lated the island ordering and narrow size distribution in two dimensions and further...100, 013527 2006pattern has not been studied so far within the coupled KMC algorithm where the long-range strain energy field is in- cluded

Patterning technology for solution-processed organic crystal field-effect transistors

PubMed Central

Li, Yun; Sun, Huabin; Shi, Yi; Tsukagoshi, Kazuhito

2014-01-01

Organic field-effect transistors (OFETs) are fundamental building blocks for various state-of-the-art electronic devices. Solution-processed organic crystals are appreciable materials for these applications because they facilitate large-scale, low-cost fabrication of devices with high performance. Patterning organic crystal transistors into well-defined geometric features is necessary to develop these crystals into practical semiconductors. This review provides an update on recentdevelopment in patterning technology for solution-processed organic crystals and their applications in field-effect transistors. Typical demonstrations are discussed and examined. In particular, our latest research progress on the spin-coating technique from mixture solutions is presented as a promising method to efficiently produce large organic semiconducting crystals on various substrates for high-performance OFETs. This solution-based process also has other excellent advantages, such as phase separation for self-assembled interfaces via one-step spin-coating, self-flattening of rough interfaces, and in situ purification that eliminates the impurity influences. Furthermore, recommendations for future perspectives are presented, and key issues for further development are discussed. PMID:27877656

Spatiotemporal Organization of Energy Release Events in the Quiet Solar Corona

NASA Technical Reports Server (NTRS)

Uritsky, Vadim M.; Davila, Joseph M.

2014-01-01

Using data from the STEREO and SOHO spacecraft, we show that temporal organization of energy release events in the quiet solar corona is close to random, in contrast to the clustered behavior of flaring times in solar active regions. The locations of the quiet-Sun events follow the meso- and supergranulation pattern of the underling photosphere. Together with earlier reports of the scale-free event size statistics, our findings suggest that quiet solar regions responsible for bulk coronal heating operate in a driven self-organized critical state, possibly involving long-range Alfvenic interactions.

Rules and Self-Organizing Properties of Post-embryonic Plant Organ Cell Division Patterns.

PubMed

von Wangenheim, Daniel; Fangerau, Jens; Schmitz, Alexander; Smith, Richard S; Leitte, Heike; Stelzer, Ernst H K; Maizel, Alexis

2016-02-22

Plants form new organs with patterned tissue organization throughout their lifespan. It is unknown whether this robust post-embryonic organ formation results from stereotypic dynamic processes, in which the arrangement of cells follows rigid rules. Here, we combine modeling with empirical observations of whole-organ development to identify the principles governing lateral root formation in Arabidopsis. Lateral roots derive from a small pool of founder cells in which some take a dominant role as seen by lineage tracing. The first division of the founders is asymmetric, tightly regulated, and determines the formation of a layered structure. Whereas the pattern of subsequent cell divisions is not stereotypic between different samples, it is characterized by a regular switch in division plane orientation. This switch is also necessary for the appearance of patterned layers as a result of the apical growth of the primordium. Our data suggest that lateral root morphogenesis is based on a limited set of rules. They determine cell growth and division orientation. The organ-level coupling of the cell behavior ensures the emergence of the lateral root's characteristic features. We propose that self-organizing, non-deterministic modes of development account for the robustness of plant organ morphogenesis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network

PubMed Central

Del Papa, Bruno; Priesemann, Viola

2017-01-01

Many experiments have suggested that the brain operates close to a critical state, based on signatures of criticality such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes information processing capacities, e.g. sensitivity to input, dynamical range and storage capacity, which makes it a favorable candidate state for brain function. Although models that self-organize towards a critical state have been proposed, the relation between criticality signatures and learning is still unclear. Here, we investigate signatures of criticality in a self-organizing recurrent neural network (SORN). Investigating criticality in the SORN is of particular interest because it has not been developed to show criticality. Instead, the SORN has been shown to exhibit spatio-temporal pattern learning through a combination of neural plasticity mechanisms and it reproduces a number of biological findings on neural variability and the statistics and fluctuations of synaptic efficacies. We show that, after a transient, the SORN spontaneously self-organizes into a dynamical state that shows criticality signatures comparable to those found in experiments. The plasticity mechanisms are necessary to attain that dynamical state, but not to maintain it. Furthermore, onset of external input transiently changes the slope of the avalanche distributions – matching recent experimental findings. Interestingly, the membrane noise level necessary for the occurrence of the criticality signatures reduces the model’s performance in simple learning tasks. Overall, our work shows that the biologically inspired plasticity and homeostasis mechanisms responsible for the SORN’s spatio-temporal learning abilities can give rise to criticality signatures in its activity when driven by random input, but these break down under the structured input of short repeating sequences. PMID:28552964

Feasibility of a feedback control of atomic self-organization in an optical cavity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivanov, D. A., E-mail: ivanov-den@yandex.ru; Ivanova, T. Yu.

Many interesting nonlinear effects are based on the strong interaction of motional degrees of freedom of atoms with an optical cavity field. Among them is the spatial self-organization of atoms in a pattern where the atoms group in either odd or even sites of the cavity-induced optical potential. An experimental observation of this effect can be simplified by using, along with the original cavity-induced feedback, an additional electronic feedback based on the detection of light leaking the cavity and the control of the optical potential for the atoms. Following our previous study, we show that this approach is more efficientmore » from the laser power perspective than the original scheme without the electronic feedback.« less

Self-organization of progress across the century of physics

NASA Astrophysics Data System (ADS)

Perc, Matjaž

2013-04-01

We make use of information provided in the titles and abstracts of over half a million publications that were published by the American Physical Society during the past 119 years. By identifying all unique words and phrases and determining their monthly usage patterns, we obtain quantifiable insights into the trends of physics discovery from the end of the 19th century to today. We show that the magnitudes of upward and downward trends yield heavy-tailed distributions, and that their emergence is due to the Matthew effect. This indicates that both the rise and fall of scientific paradigms is driven by robust principles of self-organization. Data also confirm that periods of war decelerate scientific progress, and that the later is very much subject to globalisation.

Pattern recognition with "materials that compute".

PubMed

Fang, Yan; Yashin, Victor V; Levitan, Steven P; Balazs, Anna C

2016-09-01

Driven by advances in materials and computer science, researchers are attempting to design systems where the computer and material are one and the same entity. Using theoretical and computational modeling, we design a hybrid material system that can autonomously transduce chemical, mechanical, and electrical energy to perform a computational task in a self-organized manner, without the need for external electrical power sources. Each unit in this system integrates a self-oscillating gel, which undergoes the Belousov-Zhabotinsky (BZ) reaction, with an overlaying piezoelectric (PZ) cantilever. The chemomechanical oscillations of the BZ gels deflect the PZ layer, which consequently generates a voltage across the material. When these BZ-PZ units are connected in series by electrical wires, the oscillations of these units become synchronized across the network, where the mode of synchronization depends on the polarity of the PZ. We show that the network of coupled, synchronizing BZ-PZ oscillators can perform pattern recognition. The "stored" patterns are set of polarities of the individual BZ-PZ units, and the "input" patterns are coded through the initial phase of the oscillations imposed on these units. The results of the modeling show that the input pattern closest to the stored pattern exhibits the fastest convergence time to stable synchronization behavior. In this way, networks of coupled BZ-PZ oscillators achieve pattern recognition. Further, we show that the convergence time to stable synchronization provides a robust measure of the degree of match between the input and stored patterns. Through these studies, we establish experimentally realizable design rules for creating "materials that compute."

Pattern recognition with “materials that compute”

PubMed Central

Fang, Yan; Yashin, Victor V.; Levitan, Steven P.; Balazs, Anna C.

2016-01-01

Driven by advances in materials and computer science, researchers are attempting to design systems where the computer and material are one and the same entity. Using theoretical and computational modeling, we design a hybrid material system that can autonomously transduce chemical, mechanical, and electrical energy to perform a computational task in a self-organized manner, without the need for external electrical power sources. Each unit in this system integrates a self-oscillating gel, which undergoes the Belousov-Zhabotinsky (BZ) reaction, with an overlaying piezoelectric (PZ) cantilever. The chemomechanical oscillations of the BZ gels deflect the PZ layer, which consequently generates a voltage across the material. When these BZ-PZ units are connected in series by electrical wires, the oscillations of these units become synchronized across the network, where the mode of synchronization depends on the polarity of the PZ. We show that the network of coupled, synchronizing BZ-PZ oscillators can perform pattern recognition. The “stored” patterns are set of polarities of the individual BZ-PZ units, and the “input” patterns are coded through the initial phase of the oscillations imposed on these units. The results of the modeling show that the input pattern closest to the stored pattern exhibits the fastest convergence time to stable synchronization behavior. In this way, networks of coupled BZ-PZ oscillators achieve pattern recognition. Further, we show that the convergence time to stable synchronization provides a robust measure of the degree of match between the input and stored patterns. Through these studies, we establish experimentally realizable design rules for creating “materials that compute.” PMID:27617290

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology.

PubMed

Rubenstein, Michael; Sai, Ying; Chuong, Cheng-Ming; Shen, Wei-Min

2009-01-01

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. Self here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering.

Self-Organized Behavior Generation for Musculoskeletal Robots.

PubMed

Der, Ralf; Martius, Georg

2017-01-01

With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors "waiting" to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics.

Self-Organized Behavior Generation for Musculoskeletal Robots

PubMed Central

Der, Ralf; Martius, Georg

2017-01-01

With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors “waiting” to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics. PMID:28360852

Self-Healing and Self-Care for Nurses.

PubMed

Crane, Patricia J; Ward, Suzanne F

2016-11-01

The potential effects of self-care techniques to increase nurses' effectiveness and influence positive patient care outcomes have often been underestimated. Today, nurses experience increased stress as a result of more work hours and greater patient loads. Research studies demonstrate the value to an organization and to individuals of educating nurses about self-care. Studies also show that how being aware of individual reaction patterns is vital to learning more effective coping mechanisms. In this article, we discuss the aspects of body, mind, emotions, and spirit as they relate to self-care; present self-care change techniques; and offer some practical self-care exercises. Most self-care skills can be learned and implemented in a short period of time. Nurses are encouraged to experiment with the various techniques to determine the most effective ones for them. Copyright © 2016 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Self-assembly and hierarchical patterning of aligned organic nanowire arrays by solvent evaporation on substrates with patterned wettability.

PubMed

Bao, Rong-Rong; Zhang, Cheng-Yi; Zhang, Xiu-Juan; Ou, Xue-Mei; Lee, Chun-Sing; Jie, Jian-Sheng; Zhang, Xiao-Hong

2013-06-26

The controlled growth and alignment of one-dimensional organic nanostructures at well-defined locations considerably hinders the integration of nanostructures for electronic and optoelectronic applications. Here, we demonstrate a simple process to achieve the growth, alignment, and hierarchical patterning of organic nanowires on substrates with controlled patterns of surface wettability. The first-level pattern is confined by the substrate patterns of wettability. Organic nanostructures are preferentially grown on solvent wettable regions. The second-level pattern is the patterning of aligned organic nanowires deposited by controlling the shape and movement of the solution contact lines during evaporation on the wettable regions. This process is controlled by the cover-hat-controlled method or vertical evaportation method. Therefore, various new patterns of organic nanostructures can be obtained by combing these two levels of patterns. This simple method proves to be a general approach that can be applied to other organic nanostructure systems. Using the as-prepared patterned nanowire arrays, an optoelectronic device (photodetector) is easily fabricated. Hence, the proposed simple, large-scale, low-cost method of preparing patterns of highly ordered organic nanostructures has high potential applications in various electronic and optoelectronic devices.

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology

PubMed Central

RUBENSTEIN, MICHAEL; SAI, YING; CHUONG, CHENG-MING; SHEN, WEI-MIN

2010-01-01

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. “Self” here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering. PMID:19557691

Characterization of Wind Patterns over Texas Using Self-Organizing Maps: Impact on Dallas-Fort Worth Long Term Ozone Trends

NASA Astrophysics Data System (ADS)

Kotsakis, A.; Choi, Y.; Souri, A.; Jeon, W.; Flynn, J. H., III

2017-12-01

From the years 2000 to 2014, Dallas-Fort Worth (DFW) has seen a decrease in ozone exceedances due to decreased emissions of ozone precursors. In this study, a wind pattern analysis was done to gain a better understanding of the meteorological patterns that have historically contributed to ozone exceedances over the DFW area. Long-term trends in ozone and the seasonal distribution of ozone exceedances were analyzed using surface monitoring data. Using a clustering algorithm called self-organizing maps, characteristic regional wind patterns from 2000-2014 were determined. For each of the wind pattern clusters, the frequency over the last 15 years and average ozone from monitors across DFW was analyzed. Finally, model simulations were performed to determine if pollution transported out of Houston affected incoming background ozone into DFW.

Solvent-free directed patterning of a highly ordered liquid crystalline organic semiconductor via template-assisted self-assembly for organic transistors.

PubMed

Kim, Aryeon; Jang, Kwang-Suk; Kim, Jinsoo; Won, Jong Chan; Yi, Mi Hye; Kim, Hanim; Yoon, Dong Ki; Shin, Tae Joo; Lee, Myong-Hoon; Ka, Jae-Won; Kim, Yun Ho

2013-11-20

Highly ordered organic semiconductor micropatterns of the liquid-crystalline small molecule 2,7-didecylbenzothienobenzothiophene (C10 -BTBT) are fabricated using a simple method based on template-assisted self-assembly (TASA). The liquid crystallinity of C10 -BTBT allows solvent-free fabrication of high-performance printed organic field-effect transistors (OFETs). © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Quantifying Postural Control during Exergaming Using Multivariate Whole-Body Movement Data: A Self-Organizing Maps Approach

PubMed Central

van Diest, Mike; Stegenga, Jan; Wörtche, Heinrich J.; Roerdink, Jos B. T. M; Verkerke, Gijsbertus J.; Lamoth, Claudine J. C.

2015-01-01

Background Exergames are becoming an increasingly popular tool for training balance ability, thereby preventing falls in older adults. Automatic, real time, assessment of the user’s balance control offers opportunities in terms of providing targeted feedback and dynamically adjusting the gameplay to the individual user, yet algorithms for quantification of balance control remain to be developed. The aim of the present study was to identify movement patterns, and variability therein, of young and older adults playing a custom-made weight-shifting (ice-skating) exergame. Methods Twenty older adults and twenty young adults played a weight-shifting exergame under five conditions of varying complexity, while multi-segmental whole-body movement data were captured using Kinect. Movement coordination patterns expressed during gameplay were identified using Self Organizing Maps (SOM), an artificial neural network, and variability in these patterns was quantified by computing Total Trajectory Variability (TTvar). Additionally a k Nearest Neighbor (kNN) classifier was trained to discriminate between young and older adults based on the SOM features. Results Results showed that TTvar was significantly higher in older adults than in young adults, when playing the exergame under complex task conditions. The kNN classifier showed a classification accuracy of 65.8%. Conclusions Older adults display more variable sway behavior than young adults, when playing the exergame under complex task conditions. The SOM features characterizing movement patterns expressed during exergaming allow for discriminating between young and older adults with limited accuracy. Our findings contribute to the development of algorithms for quantification of balance ability during home-based exergaming for balance training. PMID:26230655

Quantifying Postural Control during Exergaming Using Multivariate Whole-Body Movement Data: A Self-Organizing Maps Approach.

PubMed

van Diest, Mike; Stegenga, Jan; Wörtche, Heinrich J; Roerdink, Jos B T M; Verkerke, Gijsbertus J; Lamoth, Claudine J C

2015-01-01

Exergames are becoming an increasingly popular tool for training balance ability, thereby preventing falls in older adults. Automatic, real time, assessment of the user's balance control offers opportunities in terms of providing targeted feedback and dynamically adjusting the gameplay to the individual user, yet algorithms for quantification of balance control remain to be developed. The aim of the present study was to identify movement patterns, and variability therein, of young and older adults playing a custom-made weight-shifting (ice-skating) exergame. Twenty older adults and twenty young adults played a weight-shifting exergame under five conditions of varying complexity, while multi-segmental whole-body movement data were captured using Kinect. Movement coordination patterns expressed during gameplay were identified using Self Organizing Maps (SOM), an artificial neural network, and variability in these patterns was quantified by computing Total Trajectory Variability (TTvar). Additionally a k Nearest Neighbor (kNN) classifier was trained to discriminate between young and older adults based on the SOM features. Results showed that TTvar was significantly higher in older adults than in young adults, when playing the exergame under complex task conditions. The kNN classifier showed a classification accuracy of 65.8%. Older adults display more variable sway behavior than young adults, when playing the exergame under complex task conditions. The SOM features characterizing movement patterns expressed during exergaming allow for discriminating between young and older adults with limited accuracy. Our findings contribute to the development of algorithms for quantification of balance ability during home-based exergaming for balance training.

Spike-train communities: finding groups of similar spike trains.

PubMed

Humphries, Mark D

2011-02-09

Identifying similar spike-train patterns is a key element in understanding neural coding and computation. For single neurons, similar spike patterns evoked by stimuli are evidence of common coding. Across multiple neurons, similar spike trains indicate potential cell assemblies. As recording technology advances, so does the urgent need for grouping methods to make sense of large-scale datasets of spike trains. Existing methods require specifying the number of groups in advance, limiting their use in exploratory analyses. I derive a new method from network theory that solves this key difficulty: it self-determines the maximum number of groups in any set of spike trains, and groups them to maximize intragroup similarity. This method brings us revealing new insights into the encoding of aversive stimuli by dopaminergic neurons, and the organization of spontaneous neural activity in cortex. I show that the characteristic pause response of a rat's dopaminergic neuron depends on the state of the superior colliculus: when it is inactive, aversive stimuli invoke a single pattern of dopaminergic neuron spiking; when active, multiple patterns occur, yet the spike timing in each is reliable. In spontaneous multineuron activity from the cortex of anesthetized cat, I show the existence of neural ensembles that evolve in membership and characteristic timescale of organization during global slow oscillations. I validate these findings by showing that the method both is remarkably reliable at detecting known groups and can detect large-scale organization of dynamics in a model of the striatum.

Coordination of Cell Polarity, Mechanics and Fate in Tissue Self-organization.

PubMed

Kim, Esther Jeong Yoon; Korotkevich, Ekaterina; Hiiragi, Takashi

2018-07-01

Self-organization guides robust, spatiotemporally ordered formation of complex tissues and ultimately whole organisms. While products of gene expression serve as building blocks of living matter, how these interact to give rise to tissues of distinct patterns and function remains a central question in biology. Tissue self-organization relies on dynamic interactions between constituents spanning a range of spatiotemporal scales with tuneable chemical and mechanical parameters. This review highlights recent studies dissecting mechanisms of these interactions. We propose that feedback interactions between cell polarity, mechanics, and fate are a key principle underlying tissue self-organization. We also provide a glimpse into how such processes can be studied in future endeavors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Self-enhancement learning: target-creating learning and its application to self-organizing maps.

PubMed

Kamimura, Ryotaro

2011-05-01

In this article, we propose a new learning method called "self-enhancement learning." In this method, targets for learning are not given from the outside, but they can be spontaneously created within a neural network. To realize the method, we consider a neural network with two different states, namely, an enhanced and a relaxed state. The enhanced state is one in which the network responds very selectively to input patterns, while in the relaxed state, the network responds almost equally to input patterns. The gap between the two states can be reduced by minimizing the Kullback-Leibler divergence between the two states with free energy. To demonstrate the effectiveness of this method, we applied self-enhancement learning to the self-organizing maps, or SOM, in which lateral interactions were added to an enhanced state. We applied the method to the well-known Iris, wine, housing and cancer machine learning database problems. In addition, we applied the method to real-life data, a student survey. Experimental results showed that the U-matrices obtained were similar to those produced by the conventional SOM. Class boundaries were made clearer in the housing and cancer data. For all the data, except for the cancer data, better performance could be obtained in terms of quantitative and topological errors. In addition, we could see that the trustworthiness and continuity, referring to the quality of neighborhood preservation, could be improved by the self-enhancement learning. Finally, we used modern dimensionality reduction methods and compared their results with those obtained by the self-enhancement learning. The results obtained by the self-enhancement were not superior to but comparable with those obtained by the modern dimensionality reduction methods.

Molecular self-assembly approaches for supramolecular electronic and organic electronic devices

NASA Astrophysics Data System (ADS)

Yip, Hin-Lap

Molecular self-assembly represents an efficient bottom-up strategy to generate structurally well-defined aggregates of semiconducting pi-conjugated materials. The capability of tuning the chemical structures, intermolecular interactions and nanostructures through molecular engineering and novel materials processing renders it possible to tailor a large number of unprecedented properties such as charge transport, energy transfer and light harvesting. This approach does not only benefit traditional electronic devices based on bulk materials, but also generate a new research area so called "supramolecular electronics" in which electronic devices are built up with individual supramolecular nanostructures with size in the sub-hundred nanometers range. My work combined molecular self-assembly together with several novel materials processing techniques to control the nucleation and growth of organic semiconducting nanostructures from different type of pi-conjugated materials. By tailoring the interactions between the molecules using hydrogen bonds and pi-pi stacking, semiconducting nanoplatelets and nanowires with tunable sizes can be fabricated in solution. These supramolecular nanostructures were further patterned and aligned on solid substrates through printing and chemical templating methods. The capability to control the different hierarchies of organization on surface provides an important platform to study their structural-induced electronic properties. In addition to using molecular self-assembly to create different organic nanostructures, functional self-assembled monolayer (SAM) formed by spontaneous chemisorption on surfaces was used to tune the interfacial property in organic solar cells. Devices showed dramatically improved performance when appropriate SAMs were applied to optimize the contact property for efficiency charge collection.

Pattern reverberation in networks of excitable systems with connection delays

NASA Astrophysics Data System (ADS)

Lücken, Leonhard; Rosin, David P.; Worlitzer, Vasco M.; Yanchuk, Serhiy

2017-01-01

We consider the recurrent pulse-coupled networks of excitable elements with delayed connections, which are inspired by the biological neural networks. If the delays are tuned appropriately, the network can either stay in the steady resting state, or alternatively, exhibit a desired spiking pattern. It is shown that such a network can be used as a pattern-recognition system. More specifically, the application of the correct pattern as an external input to the network leads to a self-sustained reverberation of the encoded pattern. In terms of the coupling structure, the tolerance and the refractory time of the individual systems, we determine the conditions for the uniqueness of the sustained activity, i.e., for the functionality of the network as an unambiguous pattern detector. We point out the relation of the considered systems with cyclic polychronous groups and show how the assumed delay configurations may arise in a self-organized manner when a spike-time dependent plasticity of the connection delays is assumed. As excitable elements, we employ the simplistic coincidence detector models as well as the Hodgkin-Huxley neuron models. Moreover, the system is implemented experimentally on a Field-Programmable Gate Array.

78 FR 50123 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of a Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-16

...-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of a Proposed Rule Change to Assume... NASDAQ Stock Market LLC (``NASDAQ'' or the ``Exchange'') filed with the Securities and Exchange...: Manipulation patterns that monitor solely NASDAQ activity, including patterns that monitor the Exchange's...

78 FR 62814 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving a Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-22

...-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Approving a Proposed Rule Change To Assume... Authority and Supervision September 30, 2013. On July 31, 2013, The NASDAQ Stock Market LLC (``NASDAQ'' or...) Manipulation patterns that monitor solely NASDAQ activity, including patterns that monitor the Exchange's...

The neural network classification of false killer whale (Pseudorca crassidens) vocalizations.

PubMed

Murray, S O; Mercado, E; Roitblat, H L

1998-12-01

This study reports the use of unsupervised, self-organizing neural network to categorize the repertoire of false killer whale vocalizations. Self-organizing networks are capable of detecting patterns in their input and partitioning those patterns into categories without requiring that the number or types of categories be predefined. The inputs for the neural networks were two-dimensional characterization of false killer whale vocalization, where each vocalization was characterized by a sequence of short-time measurements of duty cycle and peak frequency. The first neural network used competitive learning, where units in a competitive layer distributed themselves to recognize frequently presented input vectors. This network resulted in classes representing typical patterns in the vocalizations. The second network was a Kohonen feature map which organized the outputs topologically, providing a graphical organization of pattern relationships. The networks performed well as measured by (1) the average correlation between the input vectors and the weight vectors for each category, and (2) the ability of the networks to classify novel vocalizations. The techniques used in this study could easily be applied to other species and facilitate the development of objective, comprehensive repertoire models.

Vegetation pattern formation in a fog-dependent ecosystem.

PubMed

Borthagaray, Ana I; Fuentes, Miguel A; Marquet, Pablo A

2010-07-07

Vegetation pattern formation is a striking characteristic of several water-limited ecosystems around the world. Typically, they have been described on runoff-based ecosystems emphasizing local interactions between water, biomass interception, growth and dispersal. Here, we show that this situation is by no means general, as banded patterns in vegetation can emerge in areas without rainfall and in plants without functional root (the Bromeliad Tillandsia landbeckii) and where fog is the principal source of moisture. We show that a simple model based on the advection of fog-water by wind and its interception by the vegetation can reproduce banded patterns which agree with empirical patterns observed in the Coastal Atacama Desert. Our model predicts how the parameters may affect the conditions to form the banded pattern, showing a transition from a uniform vegetated state, at high water input or terrain slope to a desert state throughout intermediate banded states. Moreover, the model predicts that the pattern wavelength is a decreasing non-linear function of fog-water input and slope, and an increasing function of plant loss and fog-water flow speed. Finally, we show that the vegetation density is increased by the formation of the regular pattern compared to the density expected by the spatially homogeneous model emphasizing the importance of self-organization in arid ecosystems. (c) 2010 Elsevier Ltd. All rights reserved.

Characteristics of pattern formation and evolution in approximations of Physarum transport networks.

PubMed

Jones, Jeff

2010-01-01

Most studies of pattern formation place particular emphasis on its role in the development of complex multicellular body plans. In simpler organisms, however, pattern formation is intrinsic to growth and behavior. Inspired by one such organism, the true slime mold Physarum polycephalum, we present examples of complex emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on chemotaxis, the mobile agent population spontaneously forms complex and dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained. Certain areas of the parameter mapping yield particularly complex long term behaviors, including the circular contraction of network lacunae and bifurcation of network paths to maintain network connectivity. We demonstrate the formation of irregular spots and labyrinthine and reticulated patterns by chemoattraction. Other Turing-like patterning schemes were obtained by using chemorepulsion behaviors, including the self-organization of regular periodic arrays of spots, and striped patterns. We show that complex pattern types can be produced without resorting to the hierarchical coupling of reaction-diffusion mechanisms. We also present network behaviors arising from simple pre-patterning cues, giving simple examples of how the emergent pattern formation processes evolve into networks with functional and quasi-physical properties including tensionlike effects, network minimization behavior, and repair to network damage. The results are interpreted in relation to classical theories of biological pattern formation in natural systems, and we suggest mechanisms by which emergent pattern formation processes may be used as a method for spatially represented unconventional computation.

Corticosterone and pace of life in two life-history ecotypes of the garter snake Thamnophis elegans.

PubMed

Palacios, Maria G; Sparkman, Amanda M; Bronikowski, Anne M

2012-02-01

Glucocorticoids are main candidates for mediating life-history trade-offs by regulating the balance between current reproduction and survival. It has been proposed that slow-living organisms should show higher stress-induced glucocorticoid levels that favor self-maintenance rather than current reproduction when compared to fast-living organisms. We tested this hypothesis in replicate populations of two ecotypes of the garter snake (Thamnophis elegans) that exhibit slow and fast pace of life strategies. We subjected free-ranging snakes to a capture-restraint protocol and compared the stress-induced corticosterone levels between slow- and fast-living snakes. We also used a five-year dataset to assess whether baseline corticosterone levels followed the same pattern as stress-induced levels in relation to pace of life. In accordance with the hypothesis, slow-living snakes showed higher stress-induced corticosterone levels than fast-living snakes. Baseline corticosterone levels showed a similar pattern with ecotype, although differences depended on the year of study. Overall, however, levels of glucocorticoids are higher in slow-living than fast-living snakes, which should favor self-maintenance and survival at the expense of current reproduction. The results of the present study are the first to relate glucocorticoid levels and pace of life in a reptilian system and contribute to our understanding of the physiological mechanisms involved in life-history evolution. Copyright © 2011 Elsevier Inc. All rights reserved.

A limit-cycle self-organizing map architecture for stable arm control.

PubMed

Huang, Di-Wei; Gentili, Rodolphe J; Katz, Garrett E; Reggia, James A

2017-01-01

Inspired by the oscillatory nature of cerebral cortex activity, we recently proposed and studied self-organizing maps (SOMs) based on limit cycle neural activity in an attempt to improve the information efficiency and robustness of conventional single-node, single-pattern representations. Here we explore for the first time the use of limit cycle SOMs to build a neural architecture that controls a robotic arm by solving inverse kinematics in reach-and-hold tasks. This multi-map architecture integrates open-loop and closed-loop controls that learn to self-organize oscillatory neural representations and to harness non-fixed-point neural activity even for fixed-point arm reaching tasks. We show through computer simulations that our architecture generalizes well, achieves accurate, fast, and smooth arm movements, and is robust in the face of arm perturbations, map damage, and variations of internal timing parameters controlling the flow of activity. A robotic implementation is evaluated successfully without further training, demonstrating for the first time that limit cycle maps can control a physical robot arm. We conclude that architectures based on limit cycle maps can be organized to function effectively as neural controllers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Light-mediated self-organization of sunflower stands increases oil yield in the field

PubMed Central

López Pereira, Mónica; Sadras, Victor O.; Batista, William; Casal, Jorge J.; Hall, Antonio J.

2017-01-01

Here, we show a unique crop response to intraspecific interference, whereby neighboring sunflower plants in a row avoid each other by growing toward a more favorable light environment and collectively increase production per unit land area. In high-density stands, a given plant inclined toward one side of the interrow space, and the immediate neighbors inclined in the opposite direction. This process started early as an incipient inclination of pioneer plants, and the arrangement propagated gradually as a “wave” of alternate inclination that persisted until maturity. Measurements and experimental manipulation of light spectral composition indicate that these responses are mediated by changes in the red/far-red ratio of the light, which is perceived by phytochrome. Cellular automata simulations reproduced the patterns of stem inclination in field experiments, supporting the proposition of self-organization of stand structure. Under high crop population densities (10 and 14 plants per m2), as yet unachievable in commercial farms with current hybrids due to lodging and diseases, self-organized crops yielded between 19 and 47% more oil than crops forced to remain erect. PMID:28696316

Light-mediated self-organization of sunflower stands increases oil yield in the field.

PubMed

López Pereira, Mónica; Sadras, Victor O; Batista, William; Casal, Jorge J; Hall, Antonio J

2017-07-25

Here, we show a unique crop response to intraspecific interference, whereby neighboring sunflower plants in a row avoid each other by growing toward a more favorable light environment and collectively increase production per unit land area. In high-density stands, a given plant inclined toward one side of the interrow space, and the immediate neighbors inclined in the opposite direction. This process started early as an incipient inclination of pioneer plants, and the arrangement propagated gradually as a "wave" of alternate inclination that persisted until maturity. Measurements and experimental manipulation of light spectral composition indicate that these responses are mediated by changes in the red/far-red ratio of the light, which is perceived by phytochrome. Cellular automata simulations reproduced the patterns of stem inclination in field experiments, supporting the proposition of self-organization of stand structure. Under high crop population densities (10 and 14 plants per m 2 ), as yet unachievable in commercial farms with current hybrids due to lodging and diseases, self-organized crops yielded between 19 and 47% more oil than crops forced to remain erect.

Implementation of Fractal Dimension and Self-Organizing Map to Detect Toxic Effects of Toluene on Movement Tracks of Daphnia magna.

PubMed

Liu, Yuedan; Xia, Chunlei; Fan, Zhongya; Wu, Renren; Chen, Xianglin; Liu, Zuoyi

2018-01-01

Movement behaviors of an indicator species, Daphnia magna , in response to contaminants have been implemented to monitor environmental disturbances. Complexity in movement tracks of Daphnia magna was characterized by use of fractal dimension and self-organizing map. The individual movement tracks of D. magna were continuously recorded for 24 hours before and after treatments with toluene at the concentration of 10 mg/L, respectively. The general complexity in movement tracks (10 minutes) was characterized by fractal dimension. Results showed that average fractal dimension of movement tracks was decreased from 1.62 to 1.22 after treatments. The instantaneous movement parameters of movement segments in 5 s were input into the self-organizing map to investigate the swimming pattern changes under stresses of toluene. Abnormal behaviors of D. magna are more frequently observed after treatments than before treatments. Computational methods in ecological informatics could be utilized to obtain the useful information in behavioral data of D. magna and would be further applied as an in situ monitoring tool in water environment.

Self-organization at the frictional interface for green tribology.

PubMed

Nosonovsky, Michael

2010-10-28

Despite the fact that self-organization during friction has received relatively little attention from tribologists so far, it has the potential for the creation of self-healing and self-lubricating materials, which are important for green or environment-friendly tribology. The principles of the thermodynamics of irreversible processes and of the nonlinear theory of dynamical systems are used to investigate the formation of spatial and temporal structures during friction. The transition to the self-organized state with low friction and wear occurs through destabilization of steady-state (stationary) sliding. The criterion for destabilization is formulated and several examples are discussed: the formation of a protective film, microtopography evolution and slip waves. The pattern formation may involve self-organized criticality and reaction-diffusion systems. A special self-healing mechanism may be embedded into the material by coupling the corresponding required forces. The analysis provides the structure-property relationship, which can be applied for the design optimization of composite self-lubricating and self-healing materials for various ecologically friendly applications and green tribology.

Self-organized MBE growth of II VI epilayers on patterned GaSb substrates

NASA Astrophysics Data System (ADS)

Wissmann, H.; Tran Anh, T.; Rogaschewski, S.; von Ortenberg, M.

1999-05-01

We report on the self-organized MBE growth of II-VI epilayers on patterned and unpatterned GaSb substrates resulting in quantum wires and quantum wells, respectively. The HgSe : Fe quantum wires were grown on (0 0 1)GaSb substrates with a buffer of lattice-matched ZnTe 1- xSe x. Due to the anisotropic growth of HgSe on the A-oriented stripes roof-like overgrowth with a definite ridge was obtained. Additional Fe doping in the direct vicinity of the ridge results in a highly conductive quantum wire.

Patterned FePt nanostructures using ultrathin self-organized templates

NASA Astrophysics Data System (ADS)

Deng, Chen Hua; Zhang, Min; Wang, Fang; Xu, Xiao Hong

2018-02-01

Patterned magnetic thin films are both scientifically interesting and technologically useful. Ultrathin self-organized anodic aluminum oxide (AAO) template can be used to fabricate large area nanodot and antidot arrays. The magnetic properties of these nanostructures may be tuned by the morphology of the AAO template, which in turn can be controlled by synthetic parameters. In this work, ultrathin AAO templates were used as etching masks for the fabrication of both FePt nanodot and antidot arrays with high areal density. The perpendicular magnetic anisotropy of L10 FePt thin films are preserved in the nanostructures.

Low cost solution-based materials processing methods for large area OLEDs and OFETs

NASA Astrophysics Data System (ADS)

Jeong, Jonghwa

In Part 1, we demonstrate the fabrication of organic light-emitting devices (OLEDs) with precisely patterned pixels by the spin-casting of Alq3 and rubrene thin films with dimensions as small as 10 mum. The solution-based patterning technique produces pixels via the segregation of organic molecules into microfabricated channels or wells. Segregation is controlled by a combination of weak adsorbing characteristics of aliphatic terminated self-assembled monolayers (SAMs) and by centrifugal force, which directs the organic solution into the channel or well. This novel patterning technique may resolve the limitations of pixel resolution in the method of thermal evaporation using shadow masks, and is applicable to the fabrication of large area displays. Furthermore, the patterning technique has the potential to produce pixel sizes down to the limitation of photolithography and micromachining techniques, thereby enabling the fabrication of high-resolution microdisplays. The patterned OLEDs, based upon a confined structure with low refractive index of SiO2, exhibited higher current density than an unpatterned OLED, which results in higher electroluminescence intensity and eventually more efficient device operation at low applied voltages. We discuss the patterning method and device fabrication, and characterize the morphological, optical, and electrical properties of the organic pixels. In part 2, we demonstrate a new growth technique for organic single crystals based on solvent vapor assisted recrystallization. We show that, by controlling the polarity of the solvent vapor and the exposure time in a closed system, we obtain rubrene in orthorhombic to monoclinic crystal structures. This novel technique for growing single crystals can induce phase shifting and alteration of crystal structure and lattice parameters. The organic molecules showed structural change from orthorhombic to monoclinic, which also provided additional optical transition of hypsochromic shift from that of the orthorhombic form. An intermediate form of the crystal exhibits an optical transition to the lowest vibrational energy level that is otherwise disallowed in the single-crystal orthorhombic form. The monoclinic form exhibits entirely new optical transitions and showed a possible structural rearrangement for increasing charge carrier mobility, making it promising for organic devices. These phenomena can be explained and proved by the chemical structure and molecular packing of the monoclinic form, transformed from orthorhombic crystalline structure.

Patterns of adolescents' participation in organized activities: are sports best when combined with other activities?

PubMed

Linver, Miriam R; Roth, Jodie L; Brooks-Gunn, Jeanne

2009-03-01

Although many adolescents participate in sports and other types of organized activities, little extant research explores how youth development outcomes may vary for youth involved in different combinations of activities. The present study uses the Child Development Supplement of the Panel Study of Income Dynamics, a large, nationally representative sample, to compare activity patterns of adolescents ages 10-18 years (n = 1,711). A cluster analytic technique revealed 5 activity clusters: sports-focused, sports plus other activities, primarily school-based activities, primarily religious youth groups, and low activity involvement. Activity patterns were examined in conjunction with 5 categories of youth development outcomes, including competence (e.g., academic ability), confidence (e.g., self-concept of ability), connections (e.g., talking with friends), character (e.g., externalizing behavior problems), and caring (e.g., prosocial behavior). Results showed that those who participated only in sports had more positive outcomes compared with those who had little or no involvement in organized activities, but less positive outcomes compared with those who participated in sports plus other activities.

Topology assisted self-organization of colloidal nanoparticles: application to 2D large-scale nanomastering.

PubMed

Kadiri, Hind; Kostcheev, Serguei; Turover, Daniel; Salas-Montiel, Rafael; Nomenyo, Komla; Gokarna, Anisha; Lerondel, Gilles

2014-01-01

Our aim was to elaborate a novel method for fully controllable large-scale nanopatterning. We investigated the influence of the surface topology, i.e., a pre-pattern of hydrogen silsesquioxane (HSQ) posts, on the self-organization of polystyrene beads (PS) dispersed over a large surface. Depending on the post size and spacing, long-range ordering of self-organized polystyrene beads is observed wherein guide posts were used leading to single crystal structure. Topology assisted self-organization has proved to be one of the solutions to obtain large-scale ordering. Besides post size and spacing, the colloidal concentration and the nature of solvent were found to have a significant effect on the self-organization of the PS beads. Scanning electron microscope and associated Fourier transform analysis were used to characterize the morphology of the ordered surfaces. Finally, the production of silicon molds is demonstrated by using the beads as a template for dry etching.

Self-assembly patterning of organic molecules on a surface

DOEpatents

Pan, Minghu; Fuentes-Cabrera, Miguel; Maksymovych, Petro; Sumpter, Bobby G.; Li, Qing

2017-04-04

The embodiments disclosed herein include all-electron control over a chemical attachment and the subsequent self-assembly of an organic molecule into a well-ordered three-dimensional monolayer on a metal surface. The ordering or assembly of the organic molecule may be through electron excitation. Hot-electron and hot-hole excitation enables tethering of the organic molecule to a metal substrate, such as an alkyne group to a gold surface. All-electron reactions may allow a direct control over the size and shape of the self-assembly, defect structures and the reverse process of molecular disassembly from single molecular level to mesoscopic scale.

Antarctic Sea Ice-Atmosphere Interactions: A Self-organizing Map-based Perspective

NASA Astrophysics Data System (ADS)

Reusch, D. B.

2005-12-01

Interactions between the ocean, sea ice and the atmosphere are a significant component of the dynamic nature of the Earth's climate system. Self-organizing maps (SOMs), an analysis tool from the field of artificial neural networks, have been used to study variability in Antarctic sea ice extent and the West Antarctic atmospheric circulation, plus the relationship and interactions between these two systems. Self-organizing maps enable unsupervised classification of large, multivariate/multidimensional data sets, e.g., time series of the atmospheric circulation or sea-ice extent, into a fixed number of distinct generalized states or modes, organized spatially as a two-dimensional grid, that are representative of the input data. When applied to atmospheric data, the analysis yields a nonlinear classification of the continuum of atmospheric conditions. In contrast to principal component analysis, SOMs do not force orthogonality or require subjective rotations to produce interpretable patterns. Twenty four years (1973-96) of monthly sea ice extent data (10 deg longitude bands; Simmonds and Jacka, 1995) were analyzed with a 30-node SOM. The resulting set of generalized patterns concisely captures the spatial and temporal variability in this data. An example of the former is variability in the longitudinal region of greatest extent. The SOM patterns readily show that there are multiple spatial patterns corresponding to "greatest extent conditions". Temporal variability is examined by creating frequency maps (i.e., which patterns occur most often) by month. With the annual cycle still in the data, the monthly frequency maps show a cycle moving from least extent, through expansion to greatest extent and back through retreat. When plotted in "SOM space", month-to-month transitions occur at different rates of change, suggesting that there is variability in the rate of change in extent at different times of the year, e.g., retreat in January is faster than November. Twenty five years (1977-2001) of monthly 500 mb temperature and pressure data (from the ECMWF 40-year reanalysis, ERA-40) from a region centered on the Antarctic Peninsula were analyzed independently for a separate SOMs-based study. Dominant SOM temperature patterns include the expected summer warmth and winter cold, plus "dipoles" of warm Atlantic (Pacific) and cold Pacific (Atlantic) sectors (with corresponding pressure patterns). Temporally, there is the expected annual progression from warmth, through cooling and back to warmth, with no particularly predominant patterns in many of the monthly frequency maps when the full record is used. Stratifying by high/low values of the Southern Oscillation Index (SOI) suggests that the spatial patterns of cooling and warming may be related to conditions in the tropical Pacific: in a low SOI year (1987), cooling and warming both begin in the Atlantic sector, with the opposite true in a high SOI year (1989). Further study of this aspect is planned. In addition to direct comparisons of the SOM analysis results from each study, a joint SOM analysis will be done on the combined data sets, exploiting the flexibility and power of this technique. We anticipate additional useful insights into the joint variability and relationships between Antarctic sea ice and the overlying atmosphere through this expanded analysis.

A self-organized learning strategy for object recognition by an embedded line of attraction

NASA Astrophysics Data System (ADS)

Seow, Ming-Jung; Alex, Ann T.; Asari, Vijayan K.

2012-04-01

For humans, a picture is worth a thousand words, but to a machine, it is just a seemingly random array of numbers. Although machines are very fast and efficient, they are vastly inferior to humans for everyday information processing. Algorithms that mimic the way the human brain computes and learns may be the solution. In this paper we present a theoretical model based on the observation that images of similar visual perceptions reside in a complex manifold in an image space. The perceived features are often highly structured and hidden in a complex set of relationships or high-dimensional abstractions. To model the pattern manifold, we present a novel learning algorithm using a recurrent neural network. The brain memorizes information using a dynamical system made of interconnected neurons. Retrieval of information is accomplished in an associative sense. It starts from an arbitrary state that might be an encoded representation of a visual image and converges to another state that is stable. The stable state is what the brain remembers. In designing a recurrent neural network, it is usually of prime importance to guarantee the convergence in the dynamics of the network. We propose to modify this picture: if the brain remembers by converging to the state representing familiar patterns, it should also diverge from such states when presented with an unknown encoded representation of a visual image belonging to a different category. That is, the identification of an instability mode is an indication that a presented pattern is far away from any stored pattern and therefore cannot be associated with current memories. These properties can be used to circumvent the plasticity-stability dilemma by using the fluctuating mode as an indicator to create new states. We capture this behavior using a novel neural architecture and learning algorithm, in which the system performs self-organization utilizing a stability mode and an instability mode for the dynamical system. Based on this observation we developed a self- organizing line attractor, which is capable of generating new lines in the feature space to learn unrecognized patterns. Experiments performed on UMIST pose database and CMU face expression variant database for face recognition have shown that the proposed nonlinear line attractor is able to successfully identify the individuals and it provided better recognition rate when compared to the state of the art face recognition techniques. Experiments on FRGC version 2 database has also provided excellent recognition rate in images captured in complex lighting environments. Experiments performed on the Japanese female face expression database and Essex Grimace database using the self organizing line attractor have also shown successful expression invariant face recognition. These results show that the proposed model is able to create nonlinear manifolds in a multidimensional feature space to distinguish complex patterns.

Morphogenesis of polycrystalline dendritic patterns from evaporation of a reactive nanofluid sessile drop

NASA Astrophysics Data System (ADS)

Wu, Hua; Briscoe, Wuge H.

2018-04-01

We report polycrystalline residual patterns with dendritic micromorphologies upon fast evaporation of a mixed-solvent sessile drop containing reactive ZnO nanoparticles. The molecular and particulate species generated in situ upon evaporative drying collude with and modify the Marangoni solvent flows and Bénard-Marangoni instabilities, as they undergo self-assembly and self-organization under conditions far from equilibrium, leading to the ultimate hierarchical central cellular patterns surrounded by a peripheral coffee ring upon drying.

Solution-processed, Self-organized Organic Single Crystal Arrays with Controlled Crystal Orientation

PubMed Central

Kumatani, Akichika; Liu, Chuan; Li, Yun; Darmawan, Peter; Takimiya, Kazuo; Minari, Takeo; Tsukagoshi, Kazuhito

2012-01-01

A facile solution process for the fabrication of organic single crystal semiconductor devices which meets the demand for low-cost and large-area fabrication of high performance electronic devices is demonstrated. In this paper, we develop a bottom-up method which enables direct formation of organic semiconductor single crystals at selected locations with desired orientations. Here oriented growth of one-dimensional organic crystals is achieved by using self-assembly of organic molecules as the driving force to align these crystals in patterned regions. Based upon the self-organized organic single crystals, we fabricate organic field effect transistor arrays which exhibit an average field-effect mobility of 1.1 cm2V−1s−1. This method can be carried out under ambient atmosphere at room temperature, thus particularly promising for production of future plastic electronics. PMID:22563523

Magnetic Nanostructures Patterned by Self-Organized Materials

DTIC Science & Technology

2016-01-05

solvent composition on the structural and magnetic properties of MnZn ferrite nanoparticles obtained by hydrothermal synthesis Microfluid...techniques such as chemical synthesis , self-organized methods, sputtering, lithography and atomic layer deposition (ALD). We also performed micromagnetic...range of temperatures (1.8 to 300 K) and at high fields (up to 5 T). The low temperature measurements of magnetic nanoparticles allowed us to

Dynamic Self-Organization and Early Lexical Development in Children

ERIC Educational Resources Information Center

Li, Ping; Zhao, Xiaowei; Whinney, Brian Mac

2007-01-01

In this study we present a self-organizing connectionist model of early lexical development. We call this model DevLex-II, based on the earlier DevLex model. DevLex-II can simulate a variety of empirical patterns in children's acquisition of words. These include a clear vocabulary spurt, effects of word frequency and length on age of acquisition,…

Self-organization and positioning of bacterial protein clusters

NASA Astrophysics Data System (ADS)

Murray, Seán M.; Sourjik, Victor

2017-10-01

Many cellular processes require proteins to be precisely positioned within the cell. In some cases this can be attributed to passive mechanisms such as recruitment by other proteins in the cell or by exploiting the curvature of the membrane. However, in bacteria, active self-positioning is likely to play a role in multiple processes, including the positioning of the future site of cell division and cytoplasmic protein clusters. How can such dynamic clusters be formed and positioned? Here, we present a model for the self-organization and positioning of dynamic protein clusters into regularly repeating patterns based on a phase-locked Turing pattern. A single peak in the concentration is always positioned at the midpoint of the model cell, and two peaks are positioned at the midpoint of each half. Furthermore, domain growth results in peak splitting and pattern doubling. We argue that the model may explain the regular positioning of the highly conserved structural maintenance of chromosomes complexes on the bacterial nucleoid and that it provides an attractive mechanism for the self-positioning of dynamic protein clusters in other systems.

Cooperation prevails when individuals adjust their social ties.

PubMed

Santos, Francisco C; Pacheco, Jorge M; Lenaerts, Tom

2006-10-20

Conventional evolutionary game theory predicts that natural selection favours the selfish and strong even though cooperative interactions thrive at all levels of organization in living systems. Recent investigations demonstrated that a limiting factor for the evolution of cooperative interactions is the way in which they are organized, cooperators becoming evolutionarily competitive whenever individuals are constrained to interact with few others along the edges of networks with low average connectivity. Despite this insight, the conundrum of cooperation remains since recent empirical data shows that real networks exhibit typically high average connectivity and associated single-to-broad-scale heterogeneity. Here, a computational model is constructed in which individuals are able to self-organize both their strategy and their social ties throughout evolution, based exclusively on their self-interest. We show that the entangled evolution of individual strategy and network structure constitutes a key mechanism for the sustainability of cooperation in social networks. For a given average connectivity of the population, there is a critical value for the ratio W between the time scales associated with the evolution of strategy and of structure above which cooperators wipe out defectors. Moreover, the emerging social networks exhibit an overall heterogeneity that accounts very well for the diversity of patterns recently found in acquired data on social networks. Finally, heterogeneity is found to become maximal when W reaches its critical value. These results show that simple topological dynamics reflecting the individual capacity for self-organization of social ties can produce realistic networks of high average connectivity with associated single-to-broad-scale heterogeneity. On the other hand, they show that cooperation cannot evolve as a result of "social viscosity" alone in heterogeneous networks with high average connectivity, requiring the additional mechanism of topological co-evolution to ensure the survival of cooperative behaviour.

Tissue culture on a chip: Developmental biology applications of self-organized capillary networks in microfluidic devices.

PubMed

Miura, Takashi; Yokokawa, Ryuji

2016-08-01

Organ culture systems are used to elucidate the mechanisms of pattern formation in developmental biology. Various organ culture techniques have been used, but the lack of microcirculation in such cultures impedes the long-term maintenance of larger tissues. Recent advances in microfluidic devices now enable us to utilize self-organized perfusable capillary networks in organ cultures. In this review, we will overview past approaches to organ culture and current technical advances in microfluidic devices, and discuss possible applications of microfluidics towards the study of developmental biology. © 2016 Japanese Society of Developmental Biologists.

Dewetting-mediated pattern formation in nanoparticle assemblies

NASA Astrophysics Data System (ADS)

Stannard, Andrew

2011-03-01

The deposition of nanoparticles from solution onto solid substrates is a diverse subfield of current nanoscience research. Complex physical and chemical processes underpin the self-assembly and self-organization of colloidal nanoparticles at two-phase (solid-liquid, liquid-air) interfaces and three-phase (solid-liquid-air) contact lines. This review discusses key recent advances made in the understanding of nonequilibrium dewetting processes of nanoparticle-containing solutions, detailing how such an apparently simple experimental system can give rise to such a strikingly varied palette of two-dimensional self-organized nanoparticle array morphologies. Patterns discussed include worm-like domains, cellular networks, microscale rings, and fractal-like fingering structures. There remain many unresolved issues regarding the role of the solvent dewetting dynamics in assembly processes of this type, with a significant focus on how dewetting can be coerced to produce nanoparticle arrays with desirable characteristics such as long-range order. In addition to these topics, methods developed to control nanofluid dewetting through routes such as confining the geometries of drying solutions, depositing onto pre-patterned heterogeneous substrates, and post-dewetting pattern evolution via local or global manipulation are covered.

Dewetting-mediated pattern formation in nanoparticle assemblies.

PubMed

Stannard, Andrew

2011-03-02

The deposition of nanoparticles from solution onto solid substrates is a diverse subfield of current nanoscience research. Complex physical and chemical processes underpin the self-assembly and self-organization of colloidal nanoparticles at two-phase (solid-liquid, liquid-air) interfaces and three-phase (solid-liquid-air) contact lines. This review discusses key recent advances made in the understanding of nonequilibrium dewetting processes of nanoparticle-containing solutions, detailing how such an apparently simple experimental system can give rise to such a strikingly varied palette of two-dimensional self-organized nanoparticle array morphologies. Patterns discussed include worm-like domains, cellular networks, microscale rings, and fractal-like fingering structures. There remain many unresolved issues regarding the role of the solvent dewetting dynamics in assembly processes of this type, with a significant focus on how dewetting can be coerced to produce nanoparticle arrays with desirable characteristics such as long-range order. In addition to these topics, methods developed to control nanofluid dewetting through routes such as confining the geometries of drying solutions, depositing onto pre-patterned heterogeneous substrates, and post-dewetting pattern evolution via local or global manipulation are covered.

Self-organized centripetal movement of corneal epithelium in the absence of external cues

NASA Astrophysics Data System (ADS)

Lobo, Erwin P.; Delic, Naomi C.; Richardson, Alex; Raviraj, Vanisri; Halliday, Gary M.; di Girolamo, Nick; Myerscough, Mary R.; Lyons, J. Guy

2016-08-01

Maintaining the structure of the cornea is essential for high-quality vision. In adult mammals, corneal epithelial cells emanate from stem cells in the limbus, driven by an unknown mechanism towards the centre of the cornea as cohesive clonal groups. Here we use complementary mathematical and biological models to show that corneal epithelial cells can self-organize into a cohesive, centripetal growth pattern in the absence of external physiological cues. Three conditions are required: a circumferential location of stem cells, a limited number of cell divisions and mobility in response to population pressure. We have used these complementary models to provide explanations for the increased rate of centripetal migration caused by wounding and the potential for stem cell leakage to account for stable transplants derived from central corneal tissue, despite the predominantly limbal location of stem cells.

Self-organization of human embryonic stem cells on micropatterns

PubMed Central

Deglincerti, Alessia; Etoc, Fred; Guerra, M. Cecilia; Martyn, Iain; Metzger, Jakob; Ruzo, Albert; Simunovic, Mijo; Yoney, Anna; Brivanlou, Ali H.; Siggia, Eric; Warmflash, Aryeh

2018-01-01

Fate allocation in the gastrulating embryo is spatially organized as cells differentiate to specialized cell types depending on their positions with respect to the body axes. There is a need for in vitro protocols that allow the study of spatial organization associated with this developmental transition. While embryoid bodies and organoids can exhibit some spatial organization of differentiated cells, these methods do not yield consistent and fully reproducible results. Here, we describe a micropatterning approach where human embryonic stem cells are confined to disk-shaped, sub-millimeter colonies. After 42 hours of BMP4 stimulation, cells form self-organized differentiation patterns in concentric radial domains, which express specific markers associated with the embryonic germ layers, reminiscent of gastrulating embryos. Our protocol takes 3 days; it uses commercial microfabricated slides (CYTOO), human laminin-521 (LN-521) as extra-cellular matrix coating, and either conditioned or chemically-defined medium (mTeSR). Differentiation patterns within individual colonies can be determined by immunofluorescence and analyzed with cellular resolution. Both the size of the micropattern and the type of medium affect the patterning outcome. The protocol is appropriate for personnel with basic stem cell culture training. This protocol describes a robust platform for quantitative analysis of the mechanisms associated with pattern formation at the onset of gastrulation. PMID:27735934

Topological patterns in street networks of self-organized urban settlements

NASA Astrophysics Data System (ADS)

Buhl, J.; Gautrais, J.; Reeves, N.; Solé, R. V.; Valverde, S.; Kuntz, P.; Theraulaz, G.

2006-02-01

Many urban settlements result from a spatially distributed, decentralized building process. Here we analyze the topological patterns of organization of a large collection of such settlements using the approach of complex networks. The global efficiency (based on the inverse of shortest-path lengths), robustness to disconnections and cost (in terms of length) of these graphs is studied and their possible origins analyzed. A wide range of patterns is found, from tree-like settlements (highly vulnerable to random failures) to meshed urban patterns. The latter are shown to be more robust and efficient.

Organizations as machines, organizations as conversations: two core metaphors and their consequences.

PubMed

Suchman, Anthony L

2011-12-01

One factor contributing to the limited success of organizational change initiatives is the use of an outmoded conceptual model: the organization as machine. This metaphor leads to the creation of detailed blueprints for desired changes; invites unrealistic expectations of control; and creates anxiety, blame and defensiveness when events inevitably do not proceed according to plan, thus hindering the work. An alternative conceptualization--the organization as conversation--portrays an organization not as a reified object upon which we can act but as self-organizing patterns of thinking (organizational identity and knowledge) and relating (organizational culture) that exist in the medium of human interaction in which we participate. Principles of complexity dynamics (self-organization) have important implications for organizational change practices. (1) Organizational change requires mindful participation--reflecting on and talking about what we are doing together here and now, what patterns of thinking and interacting we are enacting, and what new behaviors might interrupt old patterns or give rise to new ones. (2) Diversity and responsiveness favor the emergence of novel patterns. Skilled facilitation can enhance these characteristics when novelty is desirable; checklists and protocols can diminish these characteristics when consistency and reliability are needed. (3) We cannot know in advance the outcomes of our actions so we need to hold plans lightly, value "not knowing" and practice emergent design. The organization-as-conversation perspective also has important implications for T3 translational research, redefining its purpose, suggesting new methodologies, and requiring new approaches for evaluating proposed and completed projects.

Logical NAND and NOR Operations Using Algorithmic Self-assembly of DNA Molecules

NASA Astrophysics Data System (ADS)

Wang, Yanfeng; Cui, Guangzhao; Zhang, Xuncai; Zheng, Yan

DNA self-assembly is the most advanced and versatile system that has been experimentally demonstrated for programmable construction of patterned systems on the molecular scale. It has been demonstrated that the simple binary arithmetic and logical operations can be computed by the process of self assembly of DNA tiles. Here we report a one-dimensional algorithmic self-assembly of DNA triple-crossover molecules that can be used to execute five steps of a logical NAND and NOR operations on a string of binary bits. To achieve this, abstract tiles were translated into DNA tiles based on triple-crossover motifs. Serving as input for the computation, long single stranded DNA molecules were used to nucleate growth of tiles into algorithmic crystals. Our method shows that engineered DNA self-assembly can be treated as a bottom-up design techniques, and can be capable of designing DNA computer organization and architecture.

Dissipative and Autonomous Square-Wave Self-Oscillation of a Macroscopic Hybrid Self-Assembly under Continuous Light Irradiation.

PubMed

Ikegami, Tomonori; Kageyama, Yoshiyuki; Obara, Kazuma; Takeda, Sadamu

2016-07-11

Building a bottom-up supramolecular system to perform continuously autonomous motions will pave the way for the next generation of biomimetic mechanical systems. In biological systems, hierarchical molecular synchronization underlies the generation of spatio-temporal patterns with dissipative structures. However, it remains difficult to build such self-organized working objects via artificial techniques. Herein, we show the first example of a square-wave limit-cycle self-oscillatory motion of a noncovalent assembly of oleic acid and an azobenzene derivative. The assembly steadily flips under continuous blue-light irradiation. Mechanical self-oscillation is established by successively alternating photoisomerization processes and multi-stable phase transitions. These results offer a fundamental strategy for creating a supramolecular motor that works progressively under the operation of molecule-based machines. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Reconstitution of a Patterned Neural Tube from Single Mouse Embryonic Stem Cells.

PubMed

Ishihara, Keisuke; Ranga, Adrian; Lutolf, Matthias P; Tanaka, Elly M; Meinhardt, Andrea

2017-01-01

The recapitulation of tissue development and patterning in three-dimensional (3D) culture is an important dimension of stem cell research. Here, we describe a 3D culture protocol in which single mouse ES cells embedded in Matrigel under neural induction conditions clonally form a lumen containing, oval-shaped epithelial structure within 3 days. By Day 7 an apicobasally polarized neuroepithelium with uniformly dorsal cell identity forms. Treatment with retinoic acid at Day 2 results in posteriorization and self-organization of dorsal-ventral neural tube patterning. Neural tube organoid growth is also supported by pure laminin gels as well as poly(ethylene glycol) (PEG)-based artificial extracellular matrix hydrogels, which can be fine-tuned for key microenvironment characteristics. The rapid generation of a simple, patterned tissue in well-defined culture conditions makes the neural tube organoid a tractable model for studying neural stem cell self-organization.

Nanogrids and Beehive-Like Nanostructures Formed by Plasma Etching the Self-Organized SiGe Islands

NASA Astrophysics Data System (ADS)

Chang, Yuan-Ming; Jian, Sheng-Rui; Juang, Jenh-Yih

2010-09-01

A lithography-free method for fabricating the nanogrids and quasi-beehive nanostructures on Si substrates is developed. It combines sequential treatments of thermal annealing with reactive ion etching (RIE) on SiGe thin films grown on (100)-Si substrates. The SiGe thin films deposited by ultrahigh vacuum chemical vapor deposition form self-assembled nanoislands via the strain-induced surface roughening (Asaro-Tiller-Grinfeld instability) during thermal annealing, which, in turn, serve as patterned sacrifice regions for subsequent RIE process carried out for fabricating nanogrids and beehive-like nanostructures on Si substrates. The scanning electron microscopy and atomic force microscopy observations confirmed that the resultant pattern of the obtained structures can be manipulated by tuning the treatment conditions, suggesting an interesting alternative route of producing self-organized nanostructures.

Directed self-assembly of virus particles at nanoscale chemical templates

NASA Astrophysics Data System (ADS)

Chung, Sung-Wook; Cheung, Chin Li; Chatterji, Anju; Lin, Tianwei; Johnson, Jack; de Yoreo, Jim

2006-03-01

Because viruses can be site-specifically engineered to present catalytic, electronic, and optical moieties, they are attractive as building blocks for hierarchical nanostructures. We report results using scanned probe nanolithography to direct virus organization into 1D and 2D patterns and in situ AFM investigations of organization dynamics as pattern geometry, inter-viral potential, virus flux, and virus-pattern interaction are varied. Cowpea Mosaic Virus was modified to present surface sites with histidine (His) or cysteine (Cys) groups. Flat gold substrates were patterned with 10-100nm features of alkyl thiols terminated by Ni-NTA or meleimide groups to reversibly and irreversibly bind to the Hys and Cys groups, respectively. We show how assembly kinetics, degree of ordering and cluster-size distribution at these templates depend on the control parameters and present a physical picture of virus assembly at templates that incorporates growth dynamics of small-molecule epitaxial systems and condensation dynamics of colloidal systems. This work was performed under the auspices of the U. S. Department of Energy by the University of California, Lawrence Livermore National Laboratory under Contract No. W-7405-Eng-48.

Molecular structure of self-assembled chiral nanoribbons and nanotubules revealed in the hydrated state.

PubMed

Oda, Reiko; Artzner, Franck; Laguerre, Michel; Huc, Ivan

2008-11-05

A detailed molecular organization of racemic 16-2-16 tartrate self-assembled multi-bilayer ribbons in the hydrated state is proposed where 16-2-16 amphiphiles, tartrate ions, and water molecules are all accurately positioned by comparing experimental X-ray powder diffraction and diffraction patterns derived from modeling studies. X-ray diffuse scattering studies show that molecular organization is not fundamentally altered when comparing the flat ribbons of the racemate to chirally twisted or helical ribbons of the pure tartrate enantiomer. Essential features of the three-dimensional molecular organizations of these structures include interdigitation of alkyl chains within each bilayer and well-defined networks of ionic and hydrogen bonds between cations, anions, and water molecules between bilayers. The detailed study of diffraction patterns also indicated that the gemini headgroups are oriented parallel to the long edge of the ribbons. The structure thus possesses a high cohesion and good crystallinity, and for the first time, we could relate the packing of the chiral molecules to the expression of the chirality at a mesoscopic scale. The organization of the ribbons at the molecular level sheds light on a number of their macroscopic features. Among these are the reason why enantiomerically pure 16-2-16 tartrate forms ribbons that consist of exactly two bilayers, and a plausible mechanism by which a chirally twisted or helical shape may emerge from the packing of chiral tartrate ions. Importantly, the distinction between commonly observed helical and twisted morphologies could be related to a subtle symmetry breaking. These results demonstrate that accurately solving the molecular structure of self-assembled soft materials--a process rarely achieved--is within reach, that it is a valid approach to correlate molecular parameters to macroscopic properties, and thus that it offers opportunities to modulate properties through molecular design.

Multiciliated cell basal bodies align in stereotypical patterns coordinated by the apical cytoskeleton

PubMed Central

Herawati, Elisa; Kanoh, Hatsuho

2016-01-01

Multiciliated cells (MCCs) promote fluid flow through coordinated ciliary beating, which requires properly organized basal bodies (BBs). Airway MCCs have large numbers of BBs, which are uniformly oriented and, as we show here, align linearly. The mechanism for BB alignment is unexplored. To study this mechanism, we developed a long-term and high-resolution live-imaging system and used it to observe green fluorescent protein–centrin2–labeled BBs in cultured mouse tracheal MCCs. During MCC differentiation, the BB array adopted four stereotypical patterns, from a clustering “floret” pattern to the linear “alignment.” This alignment process was correlated with BB orientations, revealed by double immunostaining for BBs and their asymmetrically associated basal feet (BF). The BB alignment was disrupted by disturbing apical microtubules with nocodazole and by a BF-depleting Odf2 mutation. We constructed a theoretical model, which indicated that the apical cytoskeleton, acting like a viscoelastic fluid, provides a self-organizing mechanism in tracheal MCCs to align BBs linearly for mucociliary transport. PMID:27573463

Extensive T-Cell Epitope Repertoire Sharing among Human Proteome, Gastrointestinal Microbiome, and Pathogenic Bacteria: Implications for the Definition of Self

PubMed Central

Bremel, Robert D.; Homan, E. Jane

2015-01-01

T-cell receptor binding to MHC-bound peptides plays a key role in discrimination between self and non-self. Only a subset, typically a pentamer, of amino acids in a MHC-bound peptide form the motif exposed to the T-cell receptor. We categorize and compare the T-cell exposed amino acid motif repertoire of the total proteomes of two groups of bacteria, comprising pathogens and gastrointestinal microbiome organisms, with the human proteome and immunoglobulins. Given the maximum 205, or 3.2 million of such motifs that bind T-cell receptors, there is considerable overlap in motif usage. We show that the human proteome, exclusive of immunoglobulins, only comprises three quarters of the possible motifs, of which 65.3% are also present in both composite bacterial proteomes. Very few motifs are unique to the human proteome. Immunoglobulin variable regions carry a broad diversity of T-cell exposed motifs (TCEMs) that provides a stratified random sample of the motifs found in pathogens, microbiome, and the human proteome. Individual bacterial genera and species vary in the content of immunoglobulin and human proteome matched motifs that they carry. Mycobacteria and Burkholderia spp carry a particularly high content of such matched motifs. Some bacteria retain a unique motif signature and motif sharing pattern with the human proteome. The implication is that distinguishing self from non-self does not depend on individual TCEMs, but on a complex and dynamic overlay of signals wherein the same TCEM may play different roles in different organisms, and the frequency with which a particular TCEM appears influences its effect. The patterns observed provide clues to bacterial immune evasion and to strategies for intervention, including vaccine design. The breadth and distinct frequency patterns of the immunoglobulin-derived peptides suggest a role of immunoglobulins in maintaining a broadly responsive T-cell repertoire. PMID:26557118

Stability and transitions in mother-infant face-to-face communication during the first 6 months: a microhistorical approach.

PubMed

Hsu, Hui-Chin; Fogel, Alan

2003-11-01

In this study the authors attempted to unravel the relational, dynamical, and historical nature of mother-infant communication during the first 6 months. Thirteen mothers and their infants were videotaped weekly from 4 to 24 weeks during face-to-face interactions. Three distinct patterns of mother-infant communication were identified: symmetrical, asymmetrical, and unilateral. Guided by a dynamic systems perspective, the authors explored the stability of and transitions between these communication patterns. Findings from event history analysis showed that (a) there are regularly recurring dyadic communication patterns in early infancy, (b) these recurring patterns show differential stabilities and likelihoods of transitions, (c) dynamic stability in dyadic communication is shaped not only by individual characteristics (e.g., infant sex and maternal parity) but also by the dyad's communication history, and (d) depending on their recency, communication histories varying in temporal proximity exert differential effects on the self-organization processes of a dyadic system. ((c) 2003 APA, all rights reserved)

Self-organizing maps based on limit cycle attractors.

PubMed

Huang, Di-Wei; Gentili, Rodolphe J; Reggia, James A

2015-03-01

Recent efforts to develop large-scale brain and neurocognitive architectures have paid relatively little attention to the use of self-organizing maps (SOMs). Part of the reason for this is that most conventional SOMs use a static encoding representation: each input pattern or sequence is effectively represented as a fixed point activation pattern in the map layer, something that is inconsistent with the rhythmic oscillatory activity observed in the brain. Here we develop and study an alternative encoding scheme that instead uses sparsely-coded limit cycles to represent external input patterns/sequences. We establish conditions under which learned limit cycle representations arise reliably and dominate the dynamics in a SOM. These limit cycles tend to be relatively unique for different inputs, robust to perturbations, and fairly insensitive to timing. In spite of the continually changing activity in the map layer when a limit cycle representation is used, map formation continues to occur reliably. In a two-SOM architecture where each SOM represents a different sensory modality, we also show that after learning, limit cycles in one SOM can correctly evoke corresponding limit cycles in the other, and thus there is the potential for multi-SOM systems using limit cycles to work effectively as hetero-associative memories. While the results presented here are only first steps, they establish the viability of SOM models based on limit cycle activity patterns, and suggest that such models merit further study. Copyright © 2014 Elsevier Ltd. All rights reserved.

Self-organization of a periodic structure between amorphous and crystalline phases in a GeTe thin film induced by femtosecond laser pulse amorphization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Katsumata, Y.; Morita, T.; Morimoto, Y.

A self-organized fringe pattern in a single amorphous mark of a GeTe thin film was formed by multiple femtosecond pulse amorphization. Micro Raman measurement indicates that the fringe is a periodic alternation between crystalline and amorphous phases. The period of the fringe is smaller than the irradiation wavelength and the direction is parallel to the polarization direction. Snapshot observation revealed that the fringe pattern manifests itself via a complex but coherent process, which is attributed to crystallization properties unique to a nonthermally amorphized phase and the distinct optical contrast between crystalline and amorphous phases.

Self-organization of sorted patterned ground.

PubMed

Kessler, M A; Werner, B T

2003-01-17

Striking circular, labyrinthine, polygonal, and striped patterns of stones and soil self-organize in many polar and high alpine environments. These forms emerge because freeze-thaw cycles drive an interplay between two feedback mechanisms. First, formation of ice lenses in freezing soil sorts stones and soil by displacing soil toward soil-rich domains and stones toward stone-rich domains. Second, stones are transported along the axis of elongate stone domains, which are squeezed and confined as freezing soil domains expand. In a numerical model implementing these feedbacks, circles, labyrinths, and islands form when sorting dominates; polygonal networks form when stone domain squeezing and confinement dominate; and stripes form as hillslope gradient is increased.

Love flows downstream: mothers' and children's neural representation similarity in perceiving distress of self and family.

PubMed

Lee, Tae-Ho; Qu, Yang; Telzer, Eva H

2017-12-01

The current study aimed to capture empathy processing in an interpersonal context. Mother-adolescent dyads (N = 22) each completed an empathy task during fMRI, in which they imagined the target person in distressing scenes as either themselves or their family (i.e. child for the mother, mother for the child). Using multi-voxel pattern approach, we compared neural pattern similarity for the self and family conditions and found that mothers showed greater perceptual similarity between self and child in the fusiform face area (FFA), representing high self-child overlap, whereas adolescents showed significantly less self-mother overlap. Adolescents' pattern similarity was dependent upon family relationship quality, such that they showed greater self-mother overlap with higher relationship quality, whereas mothers' pattern similarity was independent of relationship quality. Furthermore, adolescents' perceptual similarity in the FFA was associated with increased social brain activation (e.g. temporal parietal junction). Mediation analyses indicated that high relationship quality was associated with greater social brain activation, which was mediated by greater self-mother overlap in the FFA. Our findings suggest that adolescents show more distinct neural patterns in perceiving their own vs their mother's distress, and such distinction is sensitive to mother-child relationship quality. In contrast, mothers' perception for their own and child's distress is highly similar and unconditional. © The Author (2017). Published by Oxford University Press.

High-performance vertical organic transistors.

PubMed

Kleemann, Hans; Günther, Alrun A; Leo, Karl; Lüssem, Björn

2013-11-11

Vertical organic thin-film transistors (VOTFTs) are promising devices to overcome the transconductance and cut-off frequency restrictions of horizontal organic thin-film transistors. The basic physical mechanisms of VOTFT operation, however, are not well understood and VOTFTs often require complex patterning techniques using self-assembly processes which impedes a future large-area production. In this contribution, high-performance vertical organic transistors comprising pentacene for p-type operation and C60 for n-type operation are presented. The static current-voltage behavior as well as the fundamental scaling laws of such transistors are studied, disclosing a remarkable transistor operation with a behavior limited by injection of charge carriers. The transistors are manufactured by photolithography, in contrast to other VOTFT concepts using self-assembled source electrodes. Fluorinated photoresist and solvent compounds allow for photolithographical patterning directly and strongly onto the organic materials, simplifying the fabrication protocol and making VOTFTs a prospective candidate for future high-performance applications of organic transistors. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Art, outreach and geopattern formation

NASA Astrophysics Data System (ADS)

Morris, S. W.; Chen, A. S. H.; Rogers, M. C.; Goehring, L.

2014-12-01

For the past several years, I have been exhibiting images and videos of natural and laboratory geopatterns in art galleries and outdoor shows. I have also brought artists into my research lab for hands-on workshops. My experience shows that scientific images can be well received as art and generate wide-ranging discussions across traditionally separate disciplines. The art world offers an interesting new venue for outreach activities, as well as being a lot of fun to explore. Artists Statement:I am interested in self-organized, emergent patterns and textures. I take photos of patterns both from the natural world and of experiments in my laboratory in the department of Physics at the University of Toronto. Patterns naturally attract casual attention but are also the subject of serious scientific research. Some things just evolve all by themselves into strikingly regular shapes and textures. Why? These shapes emerge spontaneously from a dynamic process of growing, folding, cracking, wrinkling, branching, flowing and other kinds of morphological development. My photos are informed by the scientific aesthetic of nonlinear physics, and mathematics lurks behind every image for those who know where to look for it. But no special knowledge is required to appreciate the results. Each image shows an object, sometimes quite small and often familiar, with a self-composed regular structure. Some images are from laboratory physics experiments and some are from Nature, and all celebrate the subtle interplay of order and complexity in emergent patterns.

Computer-based self-organized tectonic zoning: a tentative pattern recognition for Iran

NASA Astrophysics Data System (ADS)

Zamani, Ahmad; Hashemi, Naser

2004-08-01

Conventional methods of tectonic zoning are frequently characterized by two deficiencies. The first one is the large uncertainty involved in tectonic zoning based on non-quantitative and subjective analysis. Failure to interpret accurately a large amount of data "by eye" is the second. In order to alleviate each of these deficiencies, the multivariate statistical method of cluster analysis has been utilized to seek and separate zones with similar tectonic pattern and construct automated self-organized multivariate tectonic zoning maps. This analytical method of tectonic regionalization is particularly useful for showing trends in tectonic evolution of a region that could not be discovered by any other means. To illustrate, this method has been applied for producing a general-purpose numerical tectonic zoning map of Iran. While there are some similarities between the self-organized multivariate numerical maps and the conventional maps, the cluster solution maps reveal some remarkable features that cannot be observed on the current tectonic maps. The following specific examples need to be noted: (1) The much disputed extent and rigidity of the Lut Rigid Block, described as the microplate of east Iran, is clearly revealed on the self-organized numerical maps. (2) The cluster solution maps reveal a striking similarity between this microplate and the northern Central Iran—including the Great Kavir region. (3) Contrary to the conventional map, the cluster solution maps make a clear distinction between the East Iranian Ranges and the Makran Mountains. (4) Moreover, an interesting similarity between the Azarbaijan region in the northwest and the Makran Mountains in the southeast and between the Kopet Dagh Ranges in the northeast and the Zagros Folded Belt in the southwest of Iran are revealed in the clustering process. This new approach to tectonic zoning is a starting point and is expected to be improved and refined by collection of new data. The method is also a useful tool in studying neotectonics, seismotectonics, seismic zoning, and hazard estimation of the seismogenic regions.

Defining functional groups based on running kinematics using Self-Organizing Maps and Support Vector Machines.

PubMed

Hoerzer, Stefan; von Tscharner, Vinzenz; Jacob, Christian; Nigg, Benno M

2015-07-16

A functional group is a collection of individuals who react in a similar way to a specific intervention/product such as a sport shoe. Matching footwear features to a functional group can possibly enhance footwear-related comfort, improve running performance, and decrease the risk of movement-related injuries. To match footwear features to a functional group, one has to first define the different groups using their distinctive movement patterns. Therefore, the main objective of this study was to propose and apply a methodological approach to define functional groups with different movement patterns using Self-Organizing Maps and Support Vector Machines. Further study objectives were to identify differences in age, gender and footwear-related comfort preferences between the functional groups. Kinematic data and subjective comfort preferences of 88 subjects (16-76 years; 45 m/43 f) were analysed. Eight functional groups with distinctive movement patterns were defined. The findings revealed that most of the groups differed in age or gender. Certain functional groups differed in their comfort preferences and, therefore, had group-specific footwear requirements to enhance footwear-related comfort. Some of the groups, which had group-specific footwear requirements, did not show any differences in age or gender. This is important because when defining functional groups simply using common grouping criteria like age or gender, certain functional groups with group-specific movement patterns and footwear requirements might not be detected. This emphasises the power of the proposed pattern recognition approach to automatically define groups by their distinctive movement patterns in order to be able to address their group-specific product requirements. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ecological feedbacks. Termite mounds can increase the robustness of dryland ecosystems to climatic change.

PubMed

Bonachela, Juan A; Pringle, Robert M; Sheffer, Efrat; Coverdale, Tyler C; Guyton, Jennifer A; Caylor, Kelly K; Levin, Simon A; Tarnita, Corina E

2015-02-06

Self-organized spatial vegetation patterning is widespread and has been described using models of scale-dependent feedback between plants and water on homogeneous substrates. As rainfall decreases, these models yield a characteristic sequence of patterns with increasingly sparse vegetation, followed by sudden collapse to desert. Thus, the final, spot-like pattern may provide early warning for such catastrophic shifts. In many arid ecosystems, however, termite nests impart substrate heterogeneity by altering soil properties, thereby enhancing plant growth. We show that termite-induced heterogeneity interacts with scale-dependent feedbacks to produce vegetation patterns at different spatial grains. Although the coarse-grained patterning resembles that created by scale-dependent feedback alone, it does not indicate imminent desertification. Rather, mound-field landscapes are more robust to aridity, suggesting that termites may help stabilize ecosystems under global change. Copyright © 2015, American Association for the Advancement of Science.

Sequential pattern formation governed by signaling gradients

NASA Astrophysics Data System (ADS)

Jörg, David J.; Oates, Andrew C.; Jülicher, Frank

2016-10-01

Rhythmic and sequential segmentation of the embryonic body plan is a vital developmental patterning process in all vertebrate species. However, a theoretical framework capturing the emergence of dynamic patterns of gene expression from the interplay of cell oscillations with tissue elongation and shortening and with signaling gradients, is still missing. Here we show that a set of coupled genetic oscillators in an elongating tissue that is regulated by diffusing and advected signaling molecules can account for segmentation as a self-organized patterning process. This system can form a finite number of segments and the dynamics of segmentation and the total number of segments formed depend strongly on kinetic parameters describing tissue elongation and signaling molecules. The model accounts for existing experimental perturbations to signaling gradients, and makes testable predictions about novel perturbations. The variety of different patterns formed in our model can account for the variability of segmentation between different animal species.

78 FR 62884 - Self-Regulatory Organizations; NASDAQ OMX BX, Inc.; Order Approving a Proposed Rule Change To...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-22

... review functions focused on: (1) Manipulation patterns that monitor solely BX activity, including patterns that monitor the opening and closing crosses on The NASDAQ Stock Market LLC (``NASDAQ'') and...

A two-step patterning process increases the robustness of periodic patterning in the fly eye.

PubMed

Gavish, Avishai; Barkai, Naama

2016-06-01

Complex periodic patterns can self-organize through dynamic interactions between diffusible activators and inhibitors. In the biological context, self-organized patterning is challenged by spatial heterogeneities ('noise') inherent to biological systems. How spatial variability impacts the periodic patterning mechanism and how it can be buffered to ensure precise patterning is not well understood. We examine the effect of spatial heterogeneity on the periodic patterning of the fruit fly eye, an organ composed of ∼800 miniature eye units (ommatidia) whose periodic arrangement along a hexagonal lattice self-organizes during early stages of fly development. The patterning follows a two-step process, with an initial formation of evenly spaced clusters of ∼10 cells followed by a subsequent refinement of each cluster into a single selected cell. Using a probabilistic approach, we calculate the rate of patterning errors resulting from spatial heterogeneities in cell size, position and biosynthetic capacity. Notably, error rates were largely independent of the desired cluster size but followed the distributions of signaling speeds. Pre-formation of large clusters therefore greatly increases the reproducibility of the overall periodic arrangement, suggesting that the two-stage patterning process functions to guard the pattern against errors caused by spatial heterogeneities. Our results emphasize the constraints imposed on self-organized patterning mechanisms by the need to buffer stochastic effects. Author summary Complex periodic patterns are common in nature and are observed in physical, chemical and biological systems. Understanding how these patterns are generated in a precise manner is a key challenge. Biological patterns are especially intriguing, as they are generated in a noisy environment; cell position and cell size, for example, are subject to stochastic variations, as are the strengths of the chemical signals mediating cell-to-cell communication. The need to generate a precise and robust pattern in this 'noisy' environment restricts the space of patterning mechanisms that can function in the biological setting. Mathematical modeling is useful in comparing the sensitivity of different mechanisms to such variations, thereby highlighting key aspects of their design.We use mathematical modeling to study the periodic patterning of the fruit fly eye. In this system, a highly ordered lattice of differentiated cells is generated in a two-dimensional cell epithelium. The pattern is first observed by the appearance of evenly spaced clusters of ∼10 cells that express specific genes. Each cluster is subsequently refined into a single cell, which initiates the formation and differentiation of a miniature eye unit, the ommatidium. We formulate a mathematical model based on the known molecular properties of the patterning mechanism, and use a probabilistic approach to calculate the errors in cluster formation and refinement resulting from stochastic cell-to-cell variations ('noise') in different quantitative parameters. This enables us to define the parameters most influencing noise sensitivity. Notably, we find that this error is roughly independent of the desired cluster size, suggesting that large clusters are beneficial for ensuring the overall reproducibility of the periodic cluster arrangement. For the stage of cluster refinement, we find that rapid communication between cells is critical for reducing error. Our work provides new insights into the constraints imposed on mechanisms generating periodic patterning in a realistic, noisy environment, and in particular, discusses the different considerations in achieving optimal design of the patterning network.

The Relationship among Family Interaction Patterns and Career Indecision and Career Decision-Making Self-Efficacy.

ERIC Educational Resources Information Center

Whiston, Susan C.

1996-01-01

Undergraduate women with higher levels of organization and control in their families experienced less career indecision but not higher career self-efficacy. Males and females whose families had intellectual/cultural orientation had higher self-efficacy in using occupational information. An inverse relationship appeared between this type of…

Lifelong learning of human actions with deep neural network self-organization.

PubMed

Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan

2017-12-01

Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences. The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns. We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields. Lifelong learning is achieved in terms of prediction-driven neural dynamics in which the growth and the adaptation of the recurrent networks are driven by their capability to reconstruct temporally ordered input sequences. Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions. Additional experiments show the ability of our model to adapt to non-stationary input avoiding catastrophic interference. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Exploring the behavior of Caenorhabditis Elegans by using a self-organizing map and hidden Markov model

NASA Astrophysics Data System (ADS)

Kang, Seung-Ho; Lee, Sang-Hee; Chon, Tae-Soo

2012-02-01

In recent decades, the behavior of Caenorhabditis elegans ( C. elegans) has been extensively studied to understand the respective roles of neural control and biomechanics. Thus far, however, only a few studies on the simulation modeling of C. elegans swimming behavior have been conducted because it is mathematically difficult to describe its complicated behavior. In this study, we built two hidden Markov models (HMMs), corresponding to the movements of C. elegans in a controlled environment with no chemical treatment and in a formaldehyde-treated environment (0.1 ppm), respectively. The movement was characterized by a series of shape patterns of the organism, taken every 0.25 s for 40 min. All shape patterns were quantified by branch length similarity (BLS) entropy and classified into seven patterns by using the self-organizing map (SOM) and the k-means clustering algorithm. The HMM coupled with the SOM was successful in accurately explaining the organism's behavior. In addition, we briefly discussed the possibility of using the HMM together with BLS entropy to develop bio-monitoring systems for real-time applications to determine water quality.

Chemotactic-based adaptive self-organization during colonial development

NASA Astrophysics Data System (ADS)

Cohen, Inon; Czirók, Andras; Ben-Jacob, Eshel

1996-02-01

Bacterial colonies have developed sophisticated modes of cooperative behavior which enable them to respond to adverse growth conditions. It has been shown that such behavior can be manifested in the development of complex colonial patterns. Certain bacterial species exhibit formation of branching patterns during colony development. Here we present a generic model to describe such patterning of swimming (tumbling) bacteria on agar surfaces. The model incorporates: (1) food diffusion, (2) reproduction and sporulation of the cells, (3) movement of the bacterial cells within a self-produced wetting fluid and (4) chemotactic signaling. As a plausible explanation for transitions between different branching morphologies, we propose an interplay between chemotaxis towards food, self-produced short range chemoattractant and long range chemorepellent.

Self-Organized Patterns in Gas-Discharge: Particle-Like Behaviour and Dissipative Solitons

NASA Astrophysics Data System (ADS)

Purwins, H.-G.

2008-03-01

The understanding of self-organise patterns in spatially extended nonlinear dissipative systems (SOPs) is one of the most challenging subjects in modern natural sciences. In the last 20 years it turned out that research in the field of low temperature gas-discharge can help to obtain insight into important aspect of SOPs. At the same time, due to the practical relevance of plasma systems one might expect interesting applications. In the present paper the focus is on self-organised filamentary patterns in planar dc and ac systems with high ohmic and dielectric barrier, respectively. - In the discharge plane of these systems filaments show up as spots which are also referred to as dissipative solitons (DSs). In many respect experimentally detected DSs exhibit particle-like behaviour. Among other things, isolated stationary or travelling DSs, stationary, travelling or rotating "molecules" and various kinds of many-body systems have been observed. Also scattering, generation and annihilation of DSs are frequent phenomena. - At least some of these patterns can be described quantitatively in terms of a drift diffusion model. It is also demonstrated that a simple reaction diffusion model allows for an intuitive understanding of many of the observed phenomena. At the same time this model is the basis for a theoretical foundation of the particle picture and the experimentally observed universal behaviour of SOPs. - Finally some hypothetical applications are discussed.

Self-Organized Information Processing in Neuronal Networks: Replacing Layers in Deep Networks by Dynamics

NASA Astrophysics Data System (ADS)

Kirst, Christoph

It is astonishing how the sub-parts of a brain co-act to produce coherent behavior. What are mechanism that coordinate information processing and communication and how can those be changed flexibly in order to cope with variable contexts? Here we show that when information is encoded in the deviations around a collective dynamical reference state of a recurrent network the propagation of these fluctuations is strongly dependent on precisely this underlying reference. Information here 'surfs' on top of the collective dynamics and switching between states enables fast and flexible rerouting of information. This in turn affects local processing and consequently changes in the global reference dynamics that re-regulate the distribution of information. This provides a generic mechanism for self-organized information processing as we demonstrate with an oscillatory Hopfield network that performs contextual pattern recognition. Deep neural networks have proven to be very successful recently. Here we show that generating information channels via collective reference dynamics can effectively compress a deep multi-layer architecture into a single layer making this mechanism a promising candidate for the organization of information processing in biological neuronal networks.

Topology assisted self-organization of colloidal nanoparticles: application to 2D large-scale nanomastering

PubMed Central

Kostcheev, Serguei; Turover, Daniel; Salas-Montiel, Rafael; Nomenyo, Komla; Gokarna, Anisha; Lerondel, Gilles

2014-01-01

Summary Our aim was to elaborate a novel method for fully controllable large-scale nanopatterning. We investigated the influence of the surface topology, i.e., a pre-pattern of hydrogen silsesquioxane (HSQ) posts, on the self-organization of polystyrene beads (PS) dispersed over a large surface. Depending on the post size and spacing, long-range ordering of self-organized polystyrene beads is observed wherein guide posts were used leading to single crystal structure. Topology assisted self-organization has proved to be one of the solutions to obtain large-scale ordering. Besides post size and spacing, the colloidal concentration and the nature of solvent were found to have a significant effect on the self-organization of the PS beads. Scanning electron microscope and associated Fourier transform analysis were used to characterize the morphology of the ordered surfaces. Finally, the production of silicon molds is demonstrated by using the beads as a template for dry etching. PMID:25161854

Plasma-driven self-organization of Ni nanodot arrays on Si(100)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levchenko, I.; Ostrikov, K.; Diwan, K.

The results of the combined experimental and numerical study suggest that nonequilibrium plasma-driven self-organization leads to better size and positional uniformity of nickel nanodot arrays on a Si(100) surface compared with neutral gas-based processes under similar conditions. This phenomenon is explained by introducing the absorption zone patterns, whose areas relative to the small nanodot sizes become larger when the surface is charged. Our results suggest that strongly nonequilibrium and higher-complexity plasma systems can be used to improve ordering and size uniformity in nanodot arrays of various materials, a common and seemingly irresolvable problem in self-organized systems of small nanoparticles.

Morphological self-organizing feature map neural network with applications to automatic target recognition

NASA Astrophysics Data System (ADS)

Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

2005-01-01

The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals.

PubMed

Marcon, Luciano; Diego, Xavier; Sharpe, James; Müller, Patrick

2016-04-08

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems.

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals

PubMed Central

Marcon, Luciano; Diego, Xavier; Sharpe, James; Müller, Patrick

2016-01-01

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems. DOI: http://dx.doi.org/10.7554/eLife.14022.001 PMID:27058171

Vegetation recovery patterns assessment at landslides caused by catastrophic earthquake: a case study in central Taiwan.

PubMed

Chou, Wen-Chieh; Lin, Wen-Tzu; Lin, Chao-Yuan

2009-05-01

The catastrophic earthquake, 7.3 on the Richter scale, occurred on September 21, 1999 in Central Taiwan. Much of standing vegetation on slopes was eliminated and massive, scattered landslides were induced at the Jou-Jou Mountain area of the Wu-Chi basin in Nantou County. We evaluated three methods for assessing landslide hazard and vegetation recovery conditions. (1) Self-organizing map (SOM) neural network coupled with fuzzy technique was used to quickly extract the landslide. (2) The NDVI-based vegetation recovery index derived from multi-temporal SPOT satellite images was used to evaluate vegetation recovery rate in the denudation sites. (3) The spatial distribution index (SDI) based on land-cover topographic location was employed to analyze vegetation recovery patterns, including the invading, surviving and mixed patterns at the Jou-Jou Mountain area. On September 27, 1999, there were 849.20 ha of landslide area extracted using the self-organizing map and fuzzy technique combined model. After six years of natural vegetation succession, the landslide has gradually restored, and vegetation recovery rate reached up to 86%. On-site observation shows that many native pioneer plants have invaded onto the denudation sites even if disturbed by several typhoons. Two native surviving plants, Arundo formosana Hack and Pinus taiwanensis Hayata, play a vital role in natural vegetation succession in this area, especially for the sites on ridgeline and steep slopes.

Soft liquid phase adsorption for fabrication of organic semiconductor films on wettability patterned surfaces.

PubMed

Watanabe, Satoshi; Akiyoshi, Yuri; Matsumoto, Mutsuyoshi

2014-01-01

We report a soft liquid-phase adsorption (SLPA) technique for the fabrication of organic semiconductor films on wettability-patterned substrates using toluene/water emulsions. Wettability-patterned substrates were obtained by the UV-ozone treatment of self-assembled monolayers of silane coupling agents on glass plates using a metal mask. Organic semiconductor polymer films were formed selectively on the hydrophobic part of the wettability-patterned substrates. The thickness of the films fabricated by the SLPA technique is significantly larger than that of the films fabricated by dip-coating and spin-coating techniques. The film thickness can be controlled by adjusting the volume ratio of toluene to water, immersion angle, immersion temperature, and immersion time. The SLPA technique allows for the direct production of organic semiconductor films on wettability-patterned substrates with minimized material consumption and reduced number of fabrication steps.

The performance evaluation of a new neural network based traffic management scheme for a satellite communication network

NASA Technical Reports Server (NTRS)

Ansari, Nirwan; Liu, Dequan

1991-01-01

A neural-network-based traffic management scheme for a satellite communication network is described. The scheme consists of two levels of management. The front end of the scheme is a derivation of Kohonen's self-organization model to configure maps for the satellite communication network dynamically. The model consists of three stages. The first stage is the pattern recognition task, in which an exemplar map that best meets the current network requirements is selected. The second stage is the analysis of the discrepancy between the chosen exemplar map and the state of the network, and the adaptive modification of the chosen exemplar map to conform closely to the network requirement (input data pattern) by means of Kohonen's self-organization. On the basis of certain performance criteria, whether a new map is generated to replace the original chosen map is decided in the third stage. A state-dependent routing algorithm, which arranges the incoming call to some proper path, is used to make the network more efficient and to lower the call block rate. Simulation results demonstrate that the scheme, which combines self-organization and the state-dependent routing mechanism, provides better performance in terms of call block rate than schemes that only have either the self-organization mechanism or the routing mechanism.

Prioritization of malaria endemic zones using self-organizing maps in the Manipur state of India.

PubMed

Murty, Upadhyayula Suryanarayana; Srinivasa Rao, Mutheneni; Misra, Sunil

2008-09-01

Due to the availability of a huge amount of epidemiological and public health data that require analysis and interpretation by using appropriate mathematical tools to support the existing method to control the mosquito and mosquito-borne diseases in a more effective way, data-mining tools are used to make sense from the chaos. Using data-mining tools, one can develop predictive models, patterns, association rules, and clusters of diseases, which can help the decision-makers in controlling the diseases. This paper mainly focuses on the applications of data-mining tools that have been used for the first time to prioritize the malaria endemic regions in Manipur state by using Self Organizing Maps (SOM). The SOM results (in two-dimensional images called Kohonen maps) clearly show the visual classification of malaria endemic zones into high, medium and low in the different districts of Manipur, and will be discussed in the paper.

From antinode clusters to node clusters: the concentration-dependent transition of floaters on a standing Faraday wave.

PubMed

Sanlı, Ceyda; Lohse, Detlef; van der Meer, Devaraj

2014-05-01

A hydrophilic floating sphere that is denser than water drifts to an amplitude maximum (antinode) of a surface standing wave. A few identical floaters therefore organize into antinode clusters. However, beyond a transitional value of the floater concentration ϕ, we observe that the same spheres spontaneously accumulate at the nodal lines, completely inverting the self-organized particle pattern on the wave. From a potential energy estimate we show (i) that at low ϕ antinode clusters are energetically favorable over nodal ones and (ii) how this situation reverses at high ϕ, in agreement with the experiment.

Self-organizing map (SOM) of space acceleration measurement system (SAMS) data.

PubMed

Sinha, A; Smith, A D

1999-01-01

In this paper, space acceleration measurement system (SAMS) data have been classified using self-organizing map (SOM) networks without any supervision; i.e., no a priori knowledge is assumed regarding input patterns belonging to a certain class. Input patterns are created on the basis of power spectral densities of SAMS data. Results for SAMS data from STS-50 and STS-57 missions are presented. Following issues are discussed in details: impact of number of neurons, global ordering of SOM weight vectors, effectiveness of a SOM in data classification, and effects of shifting time windows in the generation of input patterns. The concept of 'cascade of SOM networks' is also developed and tested. It has been found that a SOM network can successfully classify SAMS data obtained during STS-50 and STS-57 missions.

Self-organizing map (SOM) of space acceleration measurement system (SAMS) data

NASA Technical Reports Server (NTRS)

Sinha, A.; Smith, A. D.

1999-01-01

In this paper, space acceleration measurement system (SAMS) data have been classified using self-organizing map (SOM) networks without any supervision; i.e., no a priori knowledge is assumed regarding input patterns belonging to a certain class. Input patterns are created on the basis of power spectral densities of SAMS data. Results for SAMS data from STS-50 and STS-57 missions are presented. Following issues are discussed in details: impact of number of neurons, global ordering of SOM weight vectors, effectiveness of a SOM in data classification, and effects of shifting time windows in the generation of input patterns. The concept of 'cascade of SOM networks' is also developed and tested. It has been found that a SOM network can successfully classify SAMS data obtained during STS-50 and STS-57 missions.

Sorted bedform pattern evolution: Persistence, destruction and self-organized intermittency

NASA Astrophysics Data System (ADS)

Goldstein, Evan B.; Murray, A. Brad; Coco, Giovanni

2011-12-01

We investigate the long-term evolution of inner continental shelf sorted bedform patterns. Numerical modeling suggests that a range of behaviors are possible, from pattern persistence to spatial-temporal intermittency. Sorted bedform persistence results from a robust sorting feedback that operates when the seabed features a sufficient concentration of coarse material. In the absence of storm events, pattern maturation processes such as defect dynamics and pattern migration tend to cause the burial of coarse material and excavation of fine material, leading to the fining of the active layer. Vertical sorting occurs until a critical state of active layer coarseness is reached. This critical state results in the local cessation of the sorting feedback, leading to a self-organized spatially intermittent pattern, a hallmark of observed sorted bedforms. Bedforms in shallow conditions and those subject to high wave climates may be temporally intermittent features as a result of increased wave orbital velocity during storms. Erosion, or deposition of bimodal sediment, similarly leads to a spatially intermittent pattern, with individual coarse domains exhibiting temporal intermittence. Recurring storm events cause coarsening of the seabed (strengthening the sorting feedback) and the development of large wavelength patterns. Cessation of storm events leads to the superposition of storm (large wavelength) and inter-storm (small wavelength) patterns and spatial heterogeneity of pattern modes.

Shifts in growth strategies reflect tradeoffs in cellular economics

PubMed Central

Molenaar, Douwe; van Berlo, Rogier; de Ridder, Dick; Teusink, Bas

2009-01-01

The growth rate-dependent regulation of cell size, ribosomal content, and metabolic efficiency follows a common pattern in unicellular organisms: with increasing growth rates, cell size and ribosomal content increase and a shift to energetically inefficient metabolism takes place. The latter two phenomena are also observed in fast growing tumour cells and cell lines. These patterns suggest a fundamental principle of design. In biology such designs can often be understood as the result of the optimization of fitness. Here we show that in basic models of self-replicating systems these patterns are the consequence of maximizing the growth rate. Whereas most models of cellular growth consider a part of physiology, for instance only metabolism, the approach presented here integrates several subsystems to a complete self-replicating system. Such models can yield fundamentally different optimal strategies. In particular, it is shown how the shift in metabolic efficiency originates from a tradeoff between investments in enzyme synthesis and metabolic yields for alternative catabolic pathways. The models elucidate how the optimization of growth by natural selection shapes growth strategies. PMID:19888218

Adaptive Variability in Skilled Human Movements

NASA Astrophysics Data System (ADS)

Kudo, Kazutoshi; Ohtsuki, Tatsuyuki

Human movements are produced in variable external/internal environments. Because of this variability, the same motor command can result in quite different movement patterns. Therefore, to produce skilled movements humans must coordinate the variability, not try to exclude it. In addition, because human movements are produced in redundant and complex systems, a combination of variability should be observed in different anatomical/physiological levels. In this paper, we introduce our research about human movement variability that shows remarkable coordination among components, and between organism and environment. We also introduce nonlinear dynamical models that can describe a variety of movements as a self-organization of a dynamical system, because the dynamical systems approach is a major candidate to understand the principle underlying organization of varying systems with huge degrees-of-freedom.

Supramolecular liquid crystalline π-conjugates: the role of aromatic π-stacking and van der Waals forces on the molecular self-assembly of oligophenylenevinylenes.

PubMed

Goel, Mahima; Jayakannan, M

2010-10-07

Here, we report a unique design strategy to trace the role of aromatic π-stacking and van der Waals interactions on the molecular self-organization of π-conjugated building blocks in a single system. A new series of bulky oligophenylenevinylenes (OPVs) bearing a tricyclodecanemethylene (TCD) unit in the aromatic π-core with flexible long methylene chains (n = 0-12 and 16) in the longitudinal position were designed and synthesized. The OPVs were found to be liquid crystalline, and their enthalpies of phase transitions (also entropies) showed odd-even oscillation with respect to the number of carbon atoms in alkyl chains. OPVs with an even number of methylene units in the side chains showed higher enthalpies with respect to their highly packed solid structures compared to odd-numbered ones. Polarized light microscopic analysis confirmed the formation of cholesteric liquid crystalline (LC) phases of fan shaped textures with focal conics in OPVs with 5 ≤ n ≤ 9. OPVs with longer alkyl chains (OPV-10 to OPV-12) produced a birefringence pattern consisting of dark and bright ring-banded suprastructures. The melting temperature followed a sigmoidal trend, indicating the transformation of molecular self-organization in OPVs from solid to ring-banded suprastructures via cholesteric LC intermediates. At longer alkyl chain lengths, the van der Waals interactions among the alkyl chains became predominant and translated the mesogenic effect across the lamellae; as a consequence, the lamellae underwent twisted self-organization along the radial growth direction of the spherulites to produce bright and dark bands. Scanning electron microscope (SEM) analysis of cholesteric LC and ring-banded textures strongly supported the existence of twisted lamellae in the OPVs with ring-banded textures. Variable temperature X-ray diffraction analysis confirmed the reversibility of the molecular self-organization in the solid state and also showed the existence of the higher ordered lamellar structure in ring-banded OPVs. Photophysical characterizations such as excitation, emission, and time resolved fluorescence decay measurements were employed to trace molecular self-organization in their liquid crystalline phases. The emission spectra of the OPV samples showed odd-even oscillation in their emission wavelengths with respect to the length of alkyl chains. Highly packed even-OPVs showed more blue shift compared to that of less crystalline odd-OPVs. Time dependent fluorescence decay of OPVs followed a biexponential fit, and their lifetimes (τ(1) and τ(2) values) revealed that the decay is faster for odd-OPVs compared to even-OPVs. Among all the OPVs, the τ(2) values for OPV-8 and OPV-12 were found to be much higher, indicating their high luminescent characteristics. In a nut shell, bulky liquid crystalline OPV chromophores were cleverly utilized, for the first time, to probe the aromatic π-stacking versus van der Waals interactions on the molecular self-organization of π-conjugated system.

Self-organizing hierarchies in sensor and communication networks.

PubMed

Prokopenko, Mikhail; Wang, Peter; Valencia, Philip; Price, Don; Foreman, Mark; Farmer, Anthony

2005-01-01

We consider a hierarchical multicellular sensing and communication network, embedded in an ageless aerospace vehicle that is expected to detect and react to multiple impacts and damage over a wide range of impact energies. In particular, we investigate self-organization of impact boundaries enclosing critically damaged areas, and impact networks connecting remote cells that have detected noncritical impacts. Each level of the hierarchy is shown to have distinct higher-order emergent properties, desirable in self-monitoring and self-repairing vehicles. In addition, cells and communication messages are shown to need memory (hysteresis) in order to retain desirable emergent behavior within and between various hierarchical levels. Spatiotemporal robustness of self-organizing hierarchies is quantitatively measured with graph-theoretic and information-theoretic techniques, such as the Shannon entropy. This allows us to clearly identify phase transitions separating chaotic dynamics from ordered and robust patterns.

Misfit-guided self-organization of anticorrelated Ge quantum dot arrays on Si nanowires.

PubMed

Kwon, Soonshin; Chen, Zack C Y; Kim, Ji-Hun; Xiang, Jie

2012-09-12

Misfit-strain guided growth of periodic quantum dot (QD) arrays in planar thin film epitaxy has been a popular nanostructure fabrication method. Engineering misfit-guided QD growth on a nanoscale substrate such as the small curvature surface of a nanowire represents a new approach to self-organized nanostructure preparation. Perhaps more profoundly, the periodic stress underlying each QD and the resulting modulation of electro-optical properties inside the nanowire backbone promise to provide a new platform for novel mechano-electronic, thermoelectronic, and optoelectronic devices. Herein, we report a first experimental demonstration of self-organized and self-limited growth of coherent, periodic Ge QDs on a one-dimensional Si nanowire substrate. Systematic characterizations reveal several distinctively different modes of Ge QD ordering on the Si nanowire substrate depending on the core diameter. In particular, Ge QD arrays on Si nanowires of around 20 nm diameter predominantly exhibit an anticorrelated pattern whose wavelength agrees with theoretical predictions. The correlated pattern can be attributed to propagation and correlation of misfit strain across the diameter of the thin nanowire substrate. The QD array growth is self-limited as the wavelength of the QDs remains unchanged even after prolonged Ge deposition. Furthermore, we demonstrate a direct kinetic transformation from a uniform Ge shell layer to discrete QD arrays by a postgrowth annealing process.

A realistic chemical system presenting a self-organized critical behavior

NASA Astrophysics Data System (ADS)

Gaveau, Bernard; Latrémolière, Daniel; Moreau, Michel

2003-04-01

We consider a realistic example of chemical system which presents self-organized criticality. We can study the kinetic equations analytically, and show that the conditions for self-organized criticality are satisfied. We find power relaxation laws for certain variables near the critical state, confirming the self-organized critical behavior.

Correlation of resource plays and biodiversity patterns: accumulation of organic-rich shale tracks taxonomic turnover

USGS Publications Warehouse

Eoff, Jennifer D.

2012-01-01

Similar paleogeographic and paleotectonic settings characterize most self-sourced shale hydrocarbon plays. Their deposition occurred within similar orders of magnitude of eustatic events and during geologic periods characterized by “warm” (or transitional) climates and calcitic seas. In addition, the stratigraphic occurrence of shale plays parallels certain historical patterns of marine metazoan biodiversity. Such strong agreement among several correlation tools elucidates why these resources may be limited to discrete intervals of geological time. Correlation of self-sourced shale with biodiversity trends indicates that the factors controlling the deposition of marine organic matter may not be independent of those that induced taxonomic turnover. Paleoecological changes promoted accumulation and preservation of Type II kerogen. Deposition of self-sourced shale appears to correspond to reductions in absolute biodiversity and declining percentages of bioturbating taxa, with concomitant increases in proportions of pelagic taxa relative to infaunal and epifaunal organisms. Whereas upwelling and anoxia may have contributed to the deposition of kerogen in source rocks throughout much of the sedimentary record, diminished consumption of biomass by benthic metazoans likely augmented the preservation of organic carbon during deposition of this shale type. Rapid tectonic-plate reconfiguration induced coeval events, creating basins with sufficiently high rates of accommodation creation necessary to preserve additional organic material accumulating as the heterotrophic benthos suffered in response to rapidly changing environments. Combining sea-level curves, paleogeography, climate, and seawater chemistry provides a first-order approximation of the distribution of potential self-sourced shale in the geologic record. A model that predicts the stratigraphic distribution of self-sourced-shale deposition can aid in exploration of continuous hydrocarbon accumulations in self-sourced reservoirs globally.

Fluid flows created by swimming bacteria drive self-organization in confined suspensions

PubMed Central

Lushi, Enkeleida; Wioland, Hugo; Goldstein, Raymond E.

2014-01-01

Concentrated suspensions of swimming microorganisms and other forms of active matter are known to display complex, self-organized spatiotemporal patterns on scales that are large compared with those of the individual motile units. Despite intensive experimental and theoretical study, it has remained unclear the extent to which the hydrodynamic flows generated by swimming cells, rather than purely steric interactions between them, drive the self-organization. Here we use the recent discovery of a spiral-vortex state in confined suspensions of Bacillus subtilis to study this issue in detail. Those experiments showed that if the radius of confinement in a thin cylindrical chamber is below a critical value, the suspension will spontaneously form a steady single-vortex state encircled by a counter-rotating cell boundary layer, with spiral cell orientation within the vortex. Left unclear, however, was the flagellar orientation, and hence the cell swimming direction, within the spiral vortex. Here, using a fast simulation method that captures oriented cell–cell and cell–fluid interactions in a minimal model of discrete particle systems, we predict the striking, counterintuitive result that in the presence of collectively generated fluid motion, the cells within the spiral vortex actually swim upstream against those flows. This prediction is then confirmed by the experiments reported here, which include measurements of flagella bundle orientation and cell tracking in the self-organized state. These results highlight the complex interplay between cell orientation and hydrodynamic flows in concentrated suspensions of microorganisms. PMID:24958878

Morphological computation of multi-gaited robot locomotion based on free vibration.

PubMed

Reis, Murat; Yu, Xiaoxiang; Maheshwari, Nandan; Iida, Fumiya

2013-01-01

In recent years, there has been increasing interest in the study of gait patterns in both animals and robots, because it allows us to systematically investigate the underlying mechanisms of energetics, dexterity, and autonomy of adaptive systems. In particular, for morphological computation research, the control of dynamic legged robots and their gait transitions provides additional insights into the guiding principles from a synthetic viewpoint for the emergence of sensible self-organizing behaviors in more-degrees-of-freedom systems. This article presents a novel approach to the study of gait patterns, which makes use of the intrinsic mechanical dynamics of robotic systems. Each of the robots consists of a U-shaped elastic beam and exploits free vibration to generate different locomotion patterns. We developed a simplified physics model of these robots, and through experiments in simulation and real-world robotic platforms, we show three distinctive mechanisms for generating different gait patterns in these robots.

Effects of developmental variability on the dynamics and self-organization of cell populations

NASA Astrophysics Data System (ADS)

Prabhakara, Kaumudi H.; Gholami, Azam; Zykov, Vladimir S.; Bodenschatz, Eberhard

2017-11-01

We report experimental and theoretical results for spatiotemporal pattern formation in cell populations, where the parameters vary in space and time due to mechanisms intrinsic to the system, namely Dictyostelium discoideum (D.d.) in the starvation phase. We find that different patterns are formed when the populations are initialized at different developmental stages, or when populations at different initial developmental stages are mixed. The experimentally observed patterns can be understood with a modified Kessler-Levine model that takes into account the initial spatial heterogeneity of the cell populations and a developmental path introduced by us, i.e. the time dependence of the various biochemical parameters. The dynamics of the parameters agree with known biochemical studies. Most importantly, the modified model reproduces not only our results, but also the observations of an independent experiment published earlier. This shows that pattern formation can be used to understand and quantify the temporal evolution of the system parameters.

Bioengineering single crystal growth.

PubMed

Wu, Ching-Hsuan; Park, Alexander; Joester, Derk

2011-02-16

Biomineralization is a "bottom-up" synthesis process that results in the formation of inorganic/organic nanocomposites with unrivaled control over structure, superior mechanical properties, adaptive response, and the capability of self-repair. While de novo design of such highly optimized materials may still be out of reach, engineering of the biosynthetic machinery may offer an alternative route to design advanced materials. Herein, we present an approach using micro-contact-printed lectins for patterning sea urchin embryo primary mesenchyme cells (PMCs) in vitro. We demonstrate not only that PMCs cultured on these substrates show attachment to wheat germ agglutinin and concanavalin A patterns but, more importantly, that the deposition and elongation of calcite spicules occurs cooperatively by multiple cells and in alignment with the printed pattern. This allows us to control the placement and orientation of smooth, cylindrical calcite single crystals where the crystallographic c-direction is parallel to the cylinder axis and the underlying line pattern.

Self-aligning and compressed autosophy video databases

NASA Astrophysics Data System (ADS)

Holtz, Klaus E.

1993-04-01

Autosophy, an emerging new science, explains `self-assembling structures,' such as crystals or living trees, in mathematical terms. This research provides a new mathematical theory of `learning' and a new `information theory' which permits the growing of self-assembling data network in a computer memory similar to the growing of `data crystals' or `data trees' without data processing or programming. Autosophy databases are educated very much like a human child to organize their own internal data storage. Input patterns, such as written questions or images, are converted to points in a mathematical omni dimensional hyperspace. The input patterns are then associated with output patterns, such as written answers or images. Omni dimensional information storage will result in enormous data compression because each pattern fragment is only stored once. Pattern recognition in the text or image files is greatly simplified by the peculiar omni dimensional storage method. Video databases will absorb input images from a TV camera and associate them with textual information. The `black box' operations are totally self-aligning where the input data will determine their own hyperspace storage locations. Self-aligning autosophy databases may lead to a new generation of brain-like devices.

Understanding response patterns in dyadic conflict: An interactive approach combining self-construal and opponent's dominance-submissiveness.

PubMed

Au, Al K C; Lam, Shui-Fong

2017-04-01

Previous works on the effect of self-construal in interpersonal behaviours tend to adopt a main effect approach. The present research proposes an interactive approach in understanding two response patterns in dyadic conflict by combining self-construal and the stance of the opponent. Independent self-construal was hypothesised to be associated with a self-centred pattern of conflict response, which is characterised by taking contending responses regardless of whether the stance of the opponent is dominant or submissive. Relational self-construal was hypothesised to be associated with a tuning-in pattern of conflict response, which is characterised by showing contending responses when the opponent is submissive but yielding responses when the opponent is dominant. With trait self-construal measured and opponent's stance manipulated, Study 1 provided initial support for the hypotheses. Study 2 showed a three-way interaction effect between trait self-construal, manipulated self-construal and the opponent's stance on actual conflict responses during discussion of a scenario. The effect of self-construal manipulation was only observed among people who were low in trait independent self-construal and average in trait relational self-construal. The results pinpoint the importance of considering personal and opponent factors simultaneously in understanding the dynamics of dyadic conflict processes. © 2015 International Union of Psychological Science.

Adding dynamic rules to self-organizing fuzzy systems

NASA Technical Reports Server (NTRS)

Buhusi, Catalin V.

1992-01-01

This paper develops a Dynamic Self-Organizing Fuzzy System (DSOFS) capable of adding, removing, and/or adapting the fuzzy rules and the fuzzy reference sets. The DSOFS background consists of a self-organizing neural structure with neuron relocation features which will develop a map of the input-output behavior. The relocation algorithm extends the topological ordering concept. Fuzzy rules (neurons) are dynamically added or released while the neural structure learns the pattern. The DSOFS advantages are the automatic synthesis and the possibility of parallel implementation. A high adaptation speed and a reduced number of neurons is needed in order to keep errors under some limits. The computer simulation results are presented in a nonlinear systems modelling application.

Self-Organization of Light in Optical Media with Competing Nonlinearities.

PubMed

Maucher, F; Pohl, T; Skupin, S; Krolikowski, W

2016-04-22

We study the propagation of light beams through optical media with competing nonlocal nonlinearities. We demonstrate that the nonlocality of competing focusing and defocusing nonlinearities gives rise to self-organization and stationary states with stable hexagonal intensity patterns, akin to transverse crystals of light filaments. Signatures of this long-range ordering are shown to be observable in the propagation of light in optical waveguides and even in free space. We consider a specific form of the nonlinear response that arises in atomic vapor upon proper light coupling. Yet, the general phenomenon of self-organization is a generic consequence of competing nonlocal nonlinearities, and may, hence, also be observed in other settings.

The walking behaviour of pedestrian social groups and its impact on crowd dynamics.

PubMed

Moussaïd, Mehdi; Perozo, Niriaska; Garnier, Simon; Helbing, Dirk; Theraulaz, Guy

2010-04-07

Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behaviour consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium-scale aggregated structures and their impact on crowd dynamics is still largely unknown. In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its "non-aerodynamic" shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange. These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.

Reaction-diffusion pattern in shoot apical meristem of plants.

PubMed

Fujita, Hironori; Toyokura, Koichi; Okada, Kiyotaka; Kawaguchi, Masayoshi

2011-03-29

A fundamental question in developmental biology is how spatial patterns are self-organized from homogeneous structures. In 1952, Turing proposed the reaction-diffusion model in order to explain this issue. Experimental evidence of reaction-diffusion patterns in living organisms was first provided by the pigmentation pattern on the skin of fishes in 1995. However, whether or not this mechanism plays an essential role in developmental events of living organisms remains elusive. Here we show that a reaction-diffusion model can successfully explain the shoot apical meristem (SAM) development of plants. SAM of plants resides in the top of each shoot and consists of a central zone (CZ) and a surrounding peripheral zone (PZ). SAM contains stem cells and continuously produces new organs throughout the lifespan. Molecular genetic studies using Arabidopsis thaliana revealed that the formation and maintenance of the SAM are essentially regulated by the feedback interaction between WUSHCEL (WUS) and CLAVATA (CLV). We developed a mathematical model of the SAM based on a reaction-diffusion dynamics of the WUS-CLV interaction, incorporating cell division and the spatial restriction of the dynamics. Our model explains the various SAM patterns observed in plants, for example, homeostatic control of SAM size in the wild type, enlarged or fasciated SAM in clv mutants, and initiation of ectopic secondary meristems from an initial flattened SAM in wus mutant. In addition, the model is supported by comparing its prediction with the expression pattern of WUS in the wus mutant. Furthermore, the model can account for many experimental results including reorganization processes caused by the CZ ablation and by incision through the meristem center. We thus conclude that the reaction-diffusion dynamics is probably indispensable for the SAM development of plants.

Reaction-Diffusion Pattern in Shoot Apical Meristem of Plants

PubMed Central

Fujita, Hironori; Toyokura, Koichi; Okada, Kiyotaka; Kawaguchi, Masayoshi

2011-01-01

A fundamental question in developmental biology is how spatial patterns are self-organized from homogeneous structures. In 1952, Turing proposed the reaction-diffusion model in order to explain this issue. Experimental evidence of reaction-diffusion patterns in living organisms was first provided by the pigmentation pattern on the skin of fishes in 1995. However, whether or not this mechanism plays an essential role in developmental events of living organisms remains elusive. Here we show that a reaction-diffusion model can successfully explain the shoot apical meristem (SAM) development of plants. SAM of plants resides in the top of each shoot and consists of a central zone (CZ) and a surrounding peripheral zone (PZ). SAM contains stem cells and continuously produces new organs throughout the lifespan. Molecular genetic studies using Arabidopsis thaliana revealed that the formation and maintenance of the SAM are essentially regulated by the feedback interaction between WUSHCEL (WUS) and CLAVATA (CLV). We developed a mathematical model of the SAM based on a reaction-diffusion dynamics of the WUS-CLV interaction, incorporating cell division and the spatial restriction of the dynamics. Our model explains the various SAM patterns observed in plants, for example, homeostatic control of SAM size in the wild type, enlarged or fasciated SAM in clv mutants, and initiation of ectopic secondary meristems from an initial flattened SAM in wus mutant. In addition, the model is supported by comparing its prediction with the expression pattern of WUS in the wus mutant. Furthermore, the model can account for many experimental results including reorganization processes caused by the CZ ablation and by incision through the meristem center. We thus conclude that the reaction-diffusion dynamics is probably indispensable for the SAM development of plants. PMID:21479227

Gene Expression Profiling in the Injured Spinal Cord of Trachemys scripta elegans: An Amniote with Self-Repair Capabilities

PubMed Central

Valentin-Kahan, Adrián; García-Tejedor, Gabriela B.; Robello, Carlos; Trujillo-Cenóz, Omar; Russo, Raúl E.; Alvarez-Valin, Fernando

2017-01-01

Slider turtles are the only known amniotes with self-repair mechanisms of the spinal cord that lead to substantial functional recovery. Their strategic phylogenetic position makes them a relevant model to investigate the peculiar genetic programs that allow anatomical reconnection in some vertebrate groups but are absent in others. Here, we analyze the gene expression profile of the response to spinal cord injury (SCI) in the turtle Trachemys scripta elegans. We found that this response comprises more than 1000 genes affecting diverse functions: reaction to ischemic insult, extracellular matrix re-organization, cell proliferation and death, immune response, and inflammation. Genes related to synapses and cholesterol biosynthesis are down-regulated. The analysis of the evolutionary distribution of these genes shows that almost all are present in most vertebrates. Additionally, we failed to find genes that were exclusive of regenerating taxa. The comparison of expression patterns among species shows that the response to SCI in the turtle is more similar to that of mice and non-regenerative Xenopus than to Xenopus during its regenerative stage. This observation, along with the lack of conserved “regeneration genes” and the current accepted phylogenetic placement of turtles (sister group of crocodilians and birds), indicates that the ability of spinal cord self-repair of turtles does not represent the retention of an ancestral vertebrate character. Instead, our results suggest that turtles developed this capability from a non-regenerative ancestor (i.e., a lineage specific innovation) that was achieved by re-organizing gene expression patterns on an essentially non-regenerative genetic background. Among the genes activated by SCI exclusively in turtles, those related to anoxia tolerance, extracellular matrix remodeling, and axonal regrowth are good candidates to underlie functional recovery. PMID:28223917

Gene Expression Profiling in the Injured Spinal Cord of Trachemys scripta elegans: An Amniote with Self-Repair Capabilities.

PubMed

Valentin-Kahan, Adrián; García-Tejedor, Gabriela B; Robello, Carlos; Trujillo-Cenóz, Omar; Russo, Raúl E; Alvarez-Valin, Fernando

2017-01-01

Slider turtles are the only known amniotes with self-repair mechanisms of the spinal cord that lead to substantial functional recovery. Their strategic phylogenetic position makes them a relevant model to investigate the peculiar genetic programs that allow anatomical reconnection in some vertebrate groups but are absent in others. Here, we analyze the gene expression profile of the response to spinal cord injury (SCI) in the turtle Trachemys scripta elegans . We found that this response comprises more than 1000 genes affecting diverse functions: reaction to ischemic insult, extracellular matrix re-organization, cell proliferation and death, immune response, and inflammation. Genes related to synapses and cholesterol biosynthesis are down-regulated. The analysis of the evolutionary distribution of these genes shows that almost all are present in most vertebrates. Additionally, we failed to find genes that were exclusive of regenerating taxa. The comparison of expression patterns among species shows that the response to SCI in the turtle is more similar to that of mice and non-regenerative Xenopus than to Xenopus during its regenerative stage. This observation, along with the lack of conserved "regeneration genes" and the current accepted phylogenetic placement of turtles (sister group of crocodilians and birds), indicates that the ability of spinal cord self-repair of turtles does not represent the retention of an ancestral vertebrate character. Instead, our results suggest that turtles developed this capability from a non-regenerative ancestor (i.e., a lineage specific innovation) that was achieved by re-organizing gene expression patterns on an essentially non-regenerative genetic background. Among the genes activated by SCI exclusively in turtles, those related to anoxia tolerance, extracellular matrix remodeling, and axonal regrowth are good candidates to underlie functional recovery.

A New Theoretical Foundation for Relationship-centered Care

PubMed Central

Suchman, Anthony L

2006-01-01

Relationship-centered care (RCC) is a clinical philosophy that stresses partnership, careful attention to relational process, shared decision-making, and self-awareness. A new complexity-inspired theory of human interaction called complex responsive processes of relating (CRPR) offers strong theoretical confirmation for the principles and practices of RCC, and thus may be of interest to communications researchers and reflective practitioners. It points out the nonlinear nature of human interaction and accounts for the emergence of self-organizing patterns of meaning (e.g., themes or ideas) and patterns of relating (e.g., power relations). CRPR offers fresh new perspectives on the mind, self, communication, and organizations. For observers of interaction, it focuses attention on the nature of moment-to-moment relational process, the value of difference and diversity, and the importance of authentic and responsive participation, thus closely corresponding to and providing theoretical support for RCC. PMID:16405709

First-Principles Study of the Self-Assembled Pentacene Molecules on Metal Surfaces

NASA Astrophysics Data System (ADS)

Lee, Kyuho; Han, Myung-Joon; Yu, Jaejun

2003-03-01

Oriented thin films of organic semiconducting small molecules have received considerable attention as active semiconductors for device applications such as Schottky diodes and thin-film transistors (TFTs). Among these organic materials, pentacene has been found to have the highest mobilities for hole transport. Understanding the formation of self-organized ad-layers of pentacene would contribute to the fabrication of nanostructures and possibly highly oriented pentacene layers by epitaxy for use in electronic devices. To understand the ordering patterns of pentacene ad-layers on metal surfaces, we investigated the energetics between pentacene molecules with and without metal substrates and analyzed its electronic structure. We used a self-consistent first-principles calculation method based on the density functional theory (DFT) within local density approximation (LDA). The localized pseudo-atomic orbitals (PAO) are employed for a real-space numerical basis set, which was suggested by Sankey and Niklewski, and the Troullier-Martins-type pseudo-potential is used. As results, we found that the ordering patterns can be explained by the energetics between pentacene molecules, and the metal substrates appears not to influence too much on the interaction between pentacenes. To investigate the nature of the self-assembled structure, we calculated the total energies of various configurations for the molecule pattern, e.g., side-by-side and head-to-head ordering or on-top stacking. Depending on its direction, extremely different interaction character between two pentacenes is found and explained by its electronic structure analysis.

Competing Effects Between Screen Media Time and Physical Activity in Adolescent Girls: Clustering a Self-Organizing Maps Analysis.

PubMed

Valencia-Peris, Alexandra; Devís-Devís, José; García-Massó, Xavier; Lizandra, Jorge; Pérez-Gimeno, Esther; Peiró-Velert, Carmen

2016-06-01

Previous research shows contradictory findings on potential competing effects between sedentary screen media usage (SMU) and physical activity (PA). This study examined these effects on adolescent girls via self-organizing maps analysis focusing on 3 target profiles. A sample of 1,516 girls aged 12 to 18 years self-reported daily time engagement in PA (moderate and vigorous intensity) and in screen media activities (TV/video/DVD, computer, and videogames), separately and combined. Topological interrelationships from the 13 emerging maps indicated a moderate competing effect between physically active and sedentary SMU patterns. Higher SES and overweight status were linked to either active or inactive behaviors. Three target clusters were explored in more detail. Cluster 1, named temperate-media actives, showed capabilities of being active while engaging in a moderate level of SMU (TV/video/DVD mainly). In Cluster 2, named prudent-media inactives, and Cluster 3, compulsive-media inactives, a competing effect between SMU and PA emerged, being sedentary SMU behaviors responsible for a low involvement in active pursuits. SMU and PA emerge as both related and independent behaviors in girls, resulting in a moderate competing effect. Findings support the case for recommending the timing of PA and SMU for recreational purposes considering different profiles, sociodemographic factors and types of SMU.

Signals of impending change

USGS Publications Warehouse

Grace, James B.

2017-01-01

Society has an increasing awareness that there are finite limits to what we can expect the planet to absorb and still provide goods and services at current rates1. Both historical reconstructions and contemporary events continue to remind us that ecological regime changes are often abrupt rather than gradual. This reality motivates researchers who seek to discover leading indicators for impending ecosystem change. Berdugo et al.2 report an important advance in our ability to anticipate the conversion of arid lands from self-organized, self-maintaining and productive ecosystems, to a state characterized by disorganization and low functionality. Such conversions have important implications for our understanding of ‘desertification’ — which is a shift from arid to desert-like conditions.Theoretical studies have suggested that patterns in the patchiness of vegetation might indicate how close a system is to making an abrupt change to desert-like conditions3,4,5. Empirical studies, however, have tended to show instead that simply the total cover of vegetation, rather than its arrangement, often foretells the state of the system4,5,6,7,8,9. Berdugo et al.2 combine these competing ideas into one integrated perspective. They show how major environmental drivers, such as aridity, influence both vegetation cover and patchiness, as well as where self-organizing, stabilizing forces in the vegetation are likely to be found.

Personal sleep pattern visualization using sequence-based kernel self-organizing map on sound data.

PubMed

Wu, Hongle; Kato, Takafumi; Yamada, Tomomi; Numao, Masayuki; Fukui, Ken-Ichi

2017-07-01

We propose a method to discover sleep patterns via clustering of sound events recorded during sleep. The proposed method extends the conventional self-organizing map algorithm by kernelization and sequence-based technologies to obtain a fine-grained map that visualizes the distribution and changes of sleep-related events. We introduced features widely applied in sound processing and popular kernel functions to the proposed method to evaluate and compare performance. The proposed method provides a new aspect of sleep monitoring because the results demonstrate that sound events can be directly correlated to an individual's sleep patterns. In addition, by visualizing the transition of cluster dynamics, sleep-related sound events were found to relate to the various stages of sleep. Therefore, these results empirically warrant future study into the assessment of personal sleep quality using sound data. Copyright © 2017 Elsevier B.V. All rights reserved.

Self-Construal Priming Modulates Self-Evaluation under Social Threat

PubMed Central

Zhang, Tianyang; Xi, Sisi; Jin, Yan; Wu, Yanhong

2017-01-01

Previous studies have shown that Westerners evaluate themselves in an especially flattering way when faced with a social-evaluative threat. The current study first investigated whether East Asians also have a similar pattern by recruiting Chinese participants and using social-evaluative threat manipulations in which participants perform self-evaluation tasks while adopting different social-evaluative feedbacks (Experiment 1). Then further examined whether the different response patterns can be modulated by different types of self-construal by using social-evaluative threat manipulations in conjunction with a self-construal priming task (Experiment 2). The results showed that, as opposed to Westerners' pattern, Chinese participants rated themselves as having significantly greater above-average effect only when faced with the nonthreatening feedback but not the social-evaluative threat. More importantly, we found that self-construal modulated the self-evaluation under social-evaluative threat: following independent self-construal priming, participants tended to show a greater above-average effect when faced with a social-evaluative threat. However, this pattern in conjunction with a social threat disappeared after participants received interdependent self-construal priming or neutral priming. These findings suggest that the effects of social-evaluative threat on self-evaluation are not culturally universal and is strongly modulated by self-construal priming. PMID:29081755

Self-organizing systems in planetary physics: Harmonic resonances of planet and moon orbits

NASA Astrophysics Data System (ADS)

Aschwanden, Markus J.

2018-01-01

The geometric arrangement of planet and moon orbits into a regularly spaced pattern of distances is the result of a self-organizing system. The positive feedback mechanism that operates a self-organizing system is accomplished by harmonic orbit resonances, leading to long-term stable planet and moon orbits in solar or stellar systems. The distance pattern of planets was originally described by the empirical Titius-Bode law, and by a generalized version with a constant geometric progression factor (corresponding to logarithmic spacing). We find that the orbital periods Ti and planet distances Ri from the Sun are not consistent with logarithmic spacing, but rather follow the quantized scaling (Ri + 1 /Ri) =(Ti + 1 /Ti) 2 / 3 =(Hi + 1 /Hi) 2 / 3 , where the harmonic ratios are given by five dominant resonances, namely (Hi + 1 :Hi) =(3 : 2) ,(5 : 3) ,(2 : 1) ,(5 : 2) ,(3 : 1) . We find that the orbital period ratios tend to follow the quantized harmonic ratios in increasing order. We apply this harmonic orbit resonance model to the planets and moons in our solar system, and to the exo-planets of 55 Cnc and HD 10180 planetary systems. The model allows us a prediction of missing planets in each planetary system, based on the quasi-regular self-organizing pattern of harmonic orbit resonance zones. We predict 7 (and 4) missing exo-planets around the star 55 Cnc (and HD 10180). The accuracy of the predicted planet and moon distances amounts to a few percents. All analyzed systems are found to have ≈ 10 resonant zones that can be occupied with planets (or moons) in long-term stable orbits.

Patterning layer-by-layer self-assembled multilayer by lithography and its applications to thin film devices

NASA Astrophysics Data System (ADS)

Hua, Feng

Nanoparticles are exciting materials because they exhibit unique electronic, catalytic, and optical properties. As a novel and promising nanobuilding block, it attracts considerable research efforts in its integration into a wide variety of thin film devices. Nanoparticles were adsorbed onto the substrate with layer-by-layer self-assembly which becomes of great interest due to its suitability in colloid particle assembly. Without extremely high temperatures and sophisticated equipment, molecularly organized films in an exactly pre-designed order can grow on almost all the substrates in nature. Two approaches generating spatially separated patterns comprised of nanoparticles are demonstrated, as well as two approaches patterning more than one type of nonoparticle on a silicon wafer. The structure of the thin film patterned by these approaches are analyzed and considered suitable to the thin film device. Finally, the combination of lithography and layer-by-layer (lbl) self-assembly is utilized to realize the microelectronic device with functional nonoparticles. The lbl self-assembly is the way to coat the nonoparticles and the lighography to pattern them. Based on the coating and patterning technique, a MOS-capacitor, a MOS field-effect-transistor and magnetic thin film cantilever are fabricated.

Formation of self-organized domain structures with charged domain walls in lithium niobate with surface layer modified by proton exchange

NASA Astrophysics Data System (ADS)

Shur, V. Ya.; Akhmatkhanov, A. R.; Chuvakova, M. A.; Dolbilov, M. A.; Zelenovskiy, P. S.; Lobov, A. I.

2017-03-01

We have studied the self-organized dendrite domain structures appeared as a result of polarization reversal in the uniform field in lithium niobate single crystals with the artificial surface layer created by proton exchange. We have revealed the self-organized sub-micron scale dendrite domain patterns consisting of domain stripes oriented along the X crystallographic directions separated by arrays of dashed residual domains at the surface by scanning probe microscopy. Raman confocal microscopy allowed visualizing the quasi-regular dendrite domain structures with similar geometry in the vicinity of both polar surfaces. The depth of the structure was about 20 μm for Z+ polar surface and 70 μm for Z- one. According to the proposed mechanism, the dendrite structure formation at the surface was related to the ineffective screening of the residual depolarization field. The computer simulation of the structure formation based on the cellular automata model with probabilistic switching rule proved the eligibility of the proposed scheme, the simulated dendrite domain patterns at various depths being similar to the experimental ones.

Dynamics of spiral patterns in gas discharge detected by optical method

NASA Astrophysics Data System (ADS)

Yang, Fan; Wang, Mingyi; Liu, Shuhua

2016-09-01

The dynamics behavior of spiral patterns is investigated in gas discharge using optical method. Rich kinks of spiral patterns are obtained and the formation and evolution process is investigated. The process of pattern formation is breakdown -> hexagon -> bee comb-like -> strip -> spiral -> chaos. Spiral pattern always formed after the strip pattern. It is found that the temperature of the water electrodes plays an important role in the spiral patterns formation. When it exceeds 20°C no spiral has been obtained. The discharge current waveform and the emission spectrum of the discharge have been measured when the filaments self-organized in spiral pattern. Electron excited temperature of forming spiral pattern is calculated using intensity ratio method. It is found that the electron excited temperature of spiral pattern increase as the power supply frequency increased. Relation between wavelength and discharge parameter has been measured. It shows that the wavelength of spiral pattern increases as the discharge gap increases, and decreases as the air ratio mixed in argon increases. Accompanying measurements proved that the wavelength is approximately linear to the square root of the spiral rotating period .This work has useful reference value for studying pattern dynamics.

Rethinking pattern formation in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Halatek, J.; Frey, E.

2018-05-01

The present theoretical framework for the analysis of pattern formation in complex systems is mostly limited to the vicinity of fixed (global) equilibria. Here we present a new theoretical approach to characterize dynamical states arbitrarily far from (global) equilibrium. We show that reaction-diffusion systems that are driven by locally mass-conserving interactions can be understood in terms of local equilibria of diffusively coupled compartments. Diffusive coupling generically induces lateral redistribution of the globally conserved quantities, and the variable local amounts of these quantities determine the local equilibria in each compartment. We find that, even far from global equilibrium, the system is well characterized by its moving local equilibria. We apply this framework to in vitro Min protein pattern formation, a paradigmatic model for biological pattern formation. Within our framework we can predict and explain transitions between chemical turbulence and order arbitrarily far from global equilibrium. Our results reveal conceptually new principles of self-organized pattern formation that may well govern diverse dynamical systems.

Self-organized mechano-chemical dynamics in amoeboid locomotion of Physarum fragments

NASA Astrophysics Data System (ADS)

Zhang, Shun; Guy, Robert D.; Lasheras, Juan C.; del Álamo, Juan C.

2017-05-01

The aim of this work is to quantify the spatio-temporal dynamics of flow-driven amoeboid locomotion in small (∼100 μm) fragments of the true slime mold Physarum polycephalum. In this model organism, cellular contraction drives intracellular flows, and these flows transport the chemical signals that regulate contraction in the first place. As a consequence of these non-linear interactions, a diversity of migratory behaviors can be observed in migrating Physarum fragments. To study these dynamics, we measure the spatio-temporal distributions of the velocities of the endoplasm and ectoplasm of each migrating fragment, the traction stresses it generates on the substratum, and the concentration of free intracellular calcium. Using these unprecedented experimental data, we classify migrating Physarum fragments according to their dynamics, finding that they often exhibit spontaneously coordinated waves of flow, contractility and chemical signaling. We show that Physarum fragments exhibiting symmetric spatio-temporal patterns of endoplasmic flow migrate significantly slower than fragments with asymmetric patterns. In addition, our joint measurements of ectoplasm velocity and traction stress at the substratum suggest that forward motion of the ectoplasm is enabled by a succession of stick-slip transitions, which we conjecture are also organized in the form of waves. Combining our experiments with a simplified convection-diffusion model, we show that the convective transport of calcium ions may be key for establishing and maintaining the spatio-temporal patterns of calcium concentration that regulate the generation of contractile forces.

Making sense of sparse rating data in collaborative filtering via topographic organization of user preference patterns.

PubMed

Polcicová, Gabriela; Tino, Peter

2004-01-01

We introduce topographic versions of two latent class models (LCM) for collaborative filtering. Latent classes are topologically organized on a square grid. Topographic organization of latent classes makes orientation in rating/preference patterns captured by the latent classes easier and more systematic. The variation in film rating patterns is modelled by multinomial and binomial distributions with varying independence assumptions. In the first stage of topographic LCM construction, self-organizing maps with neural field organized according to the LCM topology are employed. We apply our system to a large collection of user ratings for films. The system can provide useful visualization plots unveiling user preference patterns buried in the data, without loosing potential to be a good recommender model. It appears that multinomial distribution is most adequate if the model is regularized by tight grid topologies. Since we deal with probabilistic models of the data, we can readily use tools from probability and information theories to interpret and visualize information extracted by our system.

Order out of Randomness: Self-Organization Processes in Astrophysics

NASA Astrophysics Data System (ADS)

Aschwanden, Markus J.; Scholkmann, Felix; Béthune, William; Schmutz, Werner; Abramenko, Valentina; Cheung, Mark C. M.; Müller, Daniel; Benz, Arnold; Chernov, Guennadi; Kritsuk, Alexei G.; Scargle, Jeffrey D.; Melatos, Andrew; Wagoner, Robert V.; Trimble, Virginia; Green, William H.

2018-03-01

Self-organization is a property of dissipative nonlinear processes that are governed by a global driving force and a local positive feedback mechanism, which creates regular geometric and/or temporal patterns, and decreases the entropy locally, in contrast to random processes. Here we investigate for the first time a comprehensive number of (17) self-organization processes that operate in planetary physics, solar physics, stellar physics, galactic physics, and cosmology. Self-organizing systems create spontaneous " order out of randomness", during the evolution from an initially disordered system to an ordered quasi-stationary system, mostly by quasi-periodic limit-cycle dynamics, but also by harmonic (mechanical or gyromagnetic) resonances. The global driving force can be due to gravity, electromagnetic forces, mechanical forces (e.g., rotation or differential rotation), thermal pressure, or acceleration of nonthermal particles, while the positive feedback mechanism is often an instability, such as the magneto-rotational (Balbus-Hawley) instability, the convective (Rayleigh-Bénard) instability, turbulence, vortex attraction, magnetic reconnection, plasma condensation, or a loss-cone instability. Physical models of astrophysical self-organization processes require hydrodynamic, magneto-hydrodynamic (MHD), plasma, or N-body simulations. Analytical formulations of self-organizing systems generally involve coupled differential equations with limit-cycle solutions of the Lotka-Volterra or Hopf-bifurcation type.

Misfit-guided self-organization of anti-correlated Ge quantum dot arrays on Si nanowires

PubMed Central

Kwon, Soonshin; Chen, Zack C.Y.; Kim, Ji-Hun; Xiang, Jie

2012-01-01

Misfit-strain guided growth of periodic quantum dot (QD) arrays in planar thin film epitaxy has been a popular nanostructure fabrication method. Engineering misfit-guided QD growth on a nanoscale substrate such as the small curvature surface of a nanowire represents a new approach to self-organized nanostructure preparation. Perhaps more profoundly, the periodic stress underlying each QD and the resulting modulation of electro-optical properties inside the nanowire backbone promise to provide a new platform for novel mechano-electronic, thermoelectronic, and optoelectronic devices. Herein, we report a first experimental demonstration of self-organized and self-limited growth of coherent, periodic Ge QDs on a one dimensional Si nanowire substrate. Systematic characterizations reveal several distinctively different modes of Ge QD ordering on the Si nanowire substrate depending on the core diameter. In particular, Ge QD arrays on Si nanowires of around 20 nm diameter predominantly exhibit an anti-correlated pattern whose wavelength agrees with theoretical predictions. The correlated pattern can be attributed to propagation and correlation of misfit strain across the diameter of the thin nanowire substrate. The QD array growth is self-limited as the wavelength of the QDs remains unchanged even after prolonged Ge deposition. Furthermore, we demonstrate a direct kinetic transformation from a uniform Ge shell layer to discrete QD arrays by a post-growth annealing process. PMID:22889063

Patterned self-assembled monolayers of alkanethiols on copper nanomembranes by submerged laser ablation

NASA Astrophysics Data System (ADS)

Rhinow, Daniel; Hampp, Norbert A.

2012-06-01

Self-assembled monolayers (SAMs) of alkanethiols are major building blocks for nanotechnology. SAMs provide a functional interface between electrodes and biomolecules, which makes them attractive for biochip fabrication. Although gold has emerged as a standard, copper has several advantages, such as compatibility with semiconductors. However, as copper is easily oxidized in air, patterning SAMs on copper is a challenging task. In this work we demonstrate that submerged laser ablation (SLAB) is well-suited for this purpose, as thiols are exchanged in-situ, avoiding air exposition. Using different types of ω-substituted alkanethiols we show that alkanethiol SAMs on copper surfaces can be patterned using SLAB. The resulting patterns were analyzed by atomic force microscopy (AFM) and scanning electron microscopy (SEM). Both methods indicate that the intense laser beam promotes the exchange of thiols at the copper surface. Furthermore, we present a procedure for the production of free-standing copper nanomembranes, oxidation-protected by alkanethiol SAMs. Incubation of copper-coated mica in alkanethiol solutions leads to SAM formation on both surfaces of the copper film due to intercalation of the organic molecules. Corrosion-protected copper nanomembranes were floated onto water, transferred to electron microscopy grids, and subsequently analyzed by electron energy loss spectroscopy (EELS).

A spiking neural network model of self-organized pattern recognition in the early mammalian olfactory system.

PubMed

Kaplan, Bernhard A; Lansner, Anders

2014-01-01

Olfactory sensory information passes through several processing stages before an odor percept emerges. The question how the olfactory system learns to create odor representations linking those different levels and how it learns to connect and discriminate between them is largely unresolved. We present a large-scale network model with single and multi-compartmental Hodgkin-Huxley type model neurons representing olfactory receptor neurons (ORNs) in the epithelium, periglomerular cells, mitral/tufted cells and granule cells in the olfactory bulb (OB), and three types of cortical cells in the piriform cortex (PC). Odor patterns are calculated based on affinities between ORNs and odor stimuli derived from physico-chemical descriptors of behaviorally relevant real-world odorants. The properties of ORNs were tuned to show saturated response curves with increasing concentration as seen in experiments. On the level of the OB we explored the possibility of using a fuzzy concentration interval code, which was implemented through dendro-dendritic inhibition leading to winner-take-all like dynamics between mitral/tufted cells belonging to the same glomerulus. The connectivity from mitral/tufted cells to PC neurons was self-organized from a mutual information measure and by using a competitive Hebbian-Bayesian learning algorithm based on the response patterns of mitral/tufted cells to different odors yielding a distributed feed-forward projection to the PC. The PC was implemented as a modular attractor network with a recurrent connectivity that was likewise organized through Hebbian-Bayesian learning. We demonstrate the functionality of the model in a one-sniff-learning and recognition task on a set of 50 odorants. Furthermore, we study its robustness against noise on the receptor level and its ability to perform concentration invariant odor recognition. Moreover, we investigate the pattern completion capabilities of the system and rivalry dynamics for odor mixtures.

A spiking neural network model of self-organized pattern recognition in the early mammalian olfactory system

PubMed Central

Kaplan, Bernhard A.; Lansner, Anders

2014-01-01

Olfactory sensory information passes through several processing stages before an odor percept emerges. The question how the olfactory system learns to create odor representations linking those different levels and how it learns to connect and discriminate between them is largely unresolved. We present a large-scale network model with single and multi-compartmental Hodgkin–Huxley type model neurons representing olfactory receptor neurons (ORNs) in the epithelium, periglomerular cells, mitral/tufted cells and granule cells in the olfactory bulb (OB), and three types of cortical cells in the piriform cortex (PC). Odor patterns are calculated based on affinities between ORNs and odor stimuli derived from physico-chemical descriptors of behaviorally relevant real-world odorants. The properties of ORNs were tuned to show saturated response curves with increasing concentration as seen in experiments. On the level of the OB we explored the possibility of using a fuzzy concentration interval code, which was implemented through dendro-dendritic inhibition leading to winner-take-all like dynamics between mitral/tufted cells belonging to the same glomerulus. The connectivity from mitral/tufted cells to PC neurons was self-organized from a mutual information measure and by using a competitive Hebbian–Bayesian learning algorithm based on the response patterns of mitral/tufted cells to different odors yielding a distributed feed-forward projection to the PC. The PC was implemented as a modular attractor network with a recurrent connectivity that was likewise organized through Hebbian–Bayesian learning. We demonstrate the functionality of the model in a one-sniff-learning and recognition task on a set of 50 odorants. Furthermore, we study its robustness against noise on the receptor level and its ability to perform concentration invariant odor recognition. Moreover, we investigate the pattern completion capabilities of the system and rivalry dynamics for odor mixtures. PMID:24570657

How Animals Understand the Meaning of Indefinite Information from Environments?

NASA Astrophysics Data System (ADS)

Shimizu, H.; Yamaguchi, Y.

Animals, including human beings, have ability to understand the meaning of indefinite information from environments. Thanks to this ability the animals have flexibility in their behaviors for the environmental changes. Staring from a hypothesis that understanding of the input (Shannonian) information is based on the self-organization of a neuronal representation, that is, a spatio-temporal pattern constituted of coherent activities of neurons encoding a ``figure'', being separated from the ``background'' encoded by incoherent activities, the conditions necessary for the understanding of indefinite information were discussed. The crucial conditions revealed are that the neuronal system is incomplete or indefinite in a sense that its rules for the self-organization of the neuronal activities are completed only after the input of the environmental information and that it has an additional system named "self-specific to relevantly self-organize dynamical ``constraints'' or ``boundary conditions'' for the self-organization of the representation. For the simultaneous self-organizations of the relevant constraints and the representation, a global circulation of activities must be self-organized between these two kinds of neuronal systems. Moreover, for the performance of these functions, a specific kind of synergetic elements, ``holon elements'', are also necessary. By means of a neuronal model, the visual perception of indefinite input signals is demonstrated. The results obtained are consistent with those recently observed in the visual cortex of cats.

Visualizing human communication in business process simulations

NASA Astrophysics Data System (ADS)

Groehn, Matti; Jalkanen, Janne; Haho, Paeivi; Nieminen, Marko; Smeds, Riitta

1999-03-01

In this paper a description of business process simulation is given. Crucial part in the simulation of business processes is the analysis of social contacts between the participants. We will introduce a tool to collect log data and how this log data can be effectively analyzed using two different kind of methods: discussion flow charts and self-organizing maps. Discussion flow charts revealed the communication patterns and self-organizing maps are a very effective way of clustering the participants into development groups.

Structure Formation of Ultrathin PEO Films at Solid Interfaces—Complex Pattern Formation by Dewetting and Crystallization

PubMed Central

Braun, Hans-Georg; Meyer, Evelyn

2013-01-01

The direct contact of ultrathin polymer films with a solid substrate may result in thin film rupture caused by dewetting. With crystallisable polymers such as polyethyleneoxide (PEO), molecular self-assembly into partial ordered lamella structures is studied as an additional source of pattern formation. Morphological features in ultrathin PEO films (thickness < 10 nm) result from an interplay between dewetting patterns and diffusion limited growth pattern of ordered lamella growing within the dewetting areas. Besides structure formation of hydrophilic PEO molecules, n-alkylterminated (hydrophobic) PEO oligomers are investigated with respect to self-organization in ultrathin films. Morphological features characteristic for pure PEO are not changed by the presence of the n-alkylgroups. PMID:23385233

Type A and B behavior patterns and self-reported health symptoms and stress: examining individual and organizational fit.

PubMed

Matteson, M T; Ivancevich, J M

1982-08-01

This article describes a preliminary investigation of the proposition that organizations, as well as people, can be classified along a Type A and B behavior pattern dimension and that the resulting match or lack thereof between individual and organizational behavior patterns is related to various health indices. A sample of 315 medical technologists were classified as either Type As or Bs and as working in either Type A or B environments. Results supported the hypotheses that (1) Type Bs in B organizations report the fewest negative health symptoms; (2) Type As in A organizations report the most; and (3) Type Bs in A organizations and Type As in B organizations report an intermediate level of symptoms. The results are treated within the framework of a person-environment fit model and the implications of the findings are discussed.

Eating behaviour patterns and BMI in Portuguese higher education students.

PubMed

Poínhos, Rui; Oliveira, Bruno M P M; Correia, Flora

2013-12-01

Our aim was to determine prototypical patterns of eating behaviour among Portuguese higher education students, and to relate these patterns with BMI. Data from 280 higher education students (63.2% females) aged between 18 and 27 years were analysed. Several eating behaviour dimensions (emotional and external eating, flexible and rigid restraint, binge eating, and eating self-efficacy) were assessed, and eating styles were derived through cluster analysis. BMI for current, desired and maximum self-reported weights and the differences between desired and current BMI and between maximum and current BMI were calculated. Women scored higher in emotional eating and restraint, whereas men showed higher eating self-efficacy. Men had higher current, desired and maximum BMI. Cluster analysis showed three eating styles in both male and female subsamples: "Overeating", "High self-efficacy" and "High restraint". High self-efficacy women showed lower BMI values than the others, and restrictive women had higher lost BMI. High self-efficacy men showed lower desired BMI than overeaters, and lower maximum and lost BMI than highly restrictive ones. Restrictive women and men differ on important eating behaviour features, which may be the cause of differences in the associations with BMI. Eating self-efficacy seems to be a central variable influencing the relationships between other eating behaviour dimensions and BMI. Copyright © 2013 Elsevier Ltd. All rights reserved.

Exploring the Role of Self-Esteem and Parenting Patterns on Alcohol Use and Abuse Among Adolescents

PubMed Central

Glozah, Franklin N.

2014-01-01

The type of parental child-rearing practices used by parents and guardians substantially influence children’s self-esteem and consequently their decision to engage in alcohol use, its abuse. The aim of this study was to explore the role of self-esteem and parenting patterns on alcohol use and abuse among adolescents. Three hundred and sixteen boys and girls in Senior High Schools completed self-report questionnaires assessing self-esteem, parenting patterns and alcohol use and abuse. The results showed that while girls reported lesser self-esteem than boys, boys reported higher levels of alcohol use and abuse than girls. Also, authoritative parenting pattern had a positive effect on self-esteem and a negative effect on alcohol use. On the other hand, authoritarian and permissive parenting patterns had negative effects on self-esteem and positive effects on alcohol use, with slight variations. These results provide valuable information regarding strategies aimed at fostering parent-child relationship and rapport with the ultimate aim of bolstering the self-esteem of adolescents to subsequently eschew insalubrious behaviour, particularly alcohol use and abuse. PMID:26973951

Exploring the Role of Self-Esteem and Parenting Patterns on Alcohol Use and Abuse Among Adolescents.

PubMed

Glozah, Franklin N

2014-11-06

The type of parental child-rearing practices used by parents and guardians substantially influence children's self-esteem and consequently their decision to engage in alcohol use, its abuse. The aim of this study was to explore the role of self-esteem and parenting patterns on alcohol use and abuse among adolescents. Three hundred and sixteen boys and girls in Senior High Schools completed self-report questionnaires assessing self-esteem, parenting patterns and alcohol use and abuse. The results showed that while girls reported lesser self-esteem than boys, boys reported higher levels of alcohol use and abuse than girls. Also, authoritative parenting pattern had a positive effect on self-esteem and a negative effect on alcohol use. On the other hand, authoritarian and permissive parenting patterns had negative effects on self-esteem and positive effects on alcohol use, with slight variations. These results provide valuable information regarding strategies aimed at fostering parent-child relationship and rapport with the ultimate aim of bolstering the self-esteem of adolescents to subsequently eschew insalubrious behaviour, particularly alcohol use and abuse.

Early Foreign Language Learning: The Biological Perspective.

ERIC Educational Resources Information Center

Peltzer-Karpf, Annemarie

A discussion of the biological and developmental issues in early second language learning first looks at psycholinguistic research on brain growth patterns and the relationship of first and second language learning. Focus is on three phenomena observed in the self-organization of living systems: selection of input data; organization of specialized…

Harm reduction as a complex adaptive system: A dynamic framework for analyzing Tanzanian policies concerning heroin use

PubMed Central

Ratliff, Eric A.; Kaduri, Pamela; Masao, Frank; Mbwambo, Jessie K.K.; McCurdy, Sheryl A.

2016-01-01

Contrary to popular belief, policies on drug use are not always based on scientific evidence or composed in a rational manner. Rather, decisions concerning drug policies reflect the negotiation of actors’ ambitions, values, and facts as they organize in different ways around the perceived problems associated with illicit drug use. Drug policy is thus best represented as a complex adaptive system (CAS) that is dynamic, self-organizing, and coevolving. In this analysis, we use a CAS framework to examine how harm reduction emerged around heroin trafficking and use in Tanzania over the past thirty years (1985-present). This account is an organizational ethnography based on of the observant participation of the authors as actors within this system. We review the dynamic history and self-organizing nature of harm reduction, noting how interactions among system actors and components have coevolved with patterns of heroin us, policing, and treatment activities over time. Using a CAS framework, we describe harm reduction as a complex process where ambitions, values, facts, and technologies interact in the Tanzanian socio-political environment. We review the dynamic history and self-organizing nature of heroin policies, noting how the interactions within and between competing prohibitionist and harm reduction policies have changed with patterns of heroin use, policing, and treatment activities over time. Actors learn from their experiences to organize with other actors, align their values and facts, and implement new policies. Using a CAS approach provides researchers and policy actors a better understanding of patterns and intricacies in drug policy. This knowledge of how the system works can help improve the policy process through adaptive action to introduce new actors, different ideas, and avenues for communication into the system. PMID:26790689

Harm reduction as a complex adaptive system: A dynamic framework for analyzing Tanzanian policies concerning heroin use.

PubMed

Ratliff, Eric A; Kaduri, Pamela; Masao, Frank; Mbwambo, Jessie K K; McCurdy, Sheryl A

2016-04-01

Contrary to popular belief, policies on drug use are not always based on scientific evidence or composed in a rational manner. Rather, decisions concerning drug policies reflect the negotiation of actors' ambitions, values, and facts as they organize in different ways around the perceived problems associated with illicit drug use. Drug policy is thus best represented as a complex adaptive system (CAS) that is dynamic, self-organizing, and coevolving. In this analysis, we use a CAS framework to examine how harm reduction emerged around heroin trafficking and use in Tanzania over the past thirty years (1985-present). This account is an organizational ethnography based on of the observant participation of the authors as actors within this system. We review the dynamic history and self-organizing nature of harm reduction, noting how interactions among system actors and components have coevolved with patterns of heroin us, policing, and treatment activities over time. Using a CAS framework, we describe harm reduction as a complex process where ambitions, values, facts, and technologies interact in the Tanzanian sociopolitical environment. We review the dynamic history and self-organizing nature of heroin policies, noting how the interactions within and between competing prohibitionist and harm reduction policies have changed with patterns of heroin use, policing, and treatment activities over time. Actors learn from their experiences to organize with other actors, align their values and facts, and implement new policies. Using a CAS approach provides researchers and policy actors a better understanding of patterns and intricacies in drug policy. This knowledge of how the system works can help improve the policy process through adaptive action to introduce new actors, different ideas, and avenues for communication into the system. Copyright © 2015 Elsevier B.V. All rights reserved.

77 FR 16883 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-22

... trading patterns. The analysis would examine trading in the proposed option product as well as trading in.... Additionally, the annual report would contain the following analysis of trading patterns in Expiration Friday... exercise. Further, the cash-settlement feature would allow investors to retain their existing underlying...

75 FR 5831 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Order Approving...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-04

... series.\\8\\ The annual report will also contain information and analysis of FLEX Options trading patterns... will also contain information and analysis of FLEX Options trading patterns, and index price volatility... To Establish a Pilot Program To Modify FLEX Option Exercise Settlement Values and Minimum Value Sizes...

Application of self-organizing maps for PCDD/F pattern recognition of environmental and biological samples to evaluate the impact of a hazardous waste incinerator.

PubMed

Mari, Montse; Nadal, Martí; Schuhmacher, Marta; Domingo, José L

2010-04-15

Kohonen's self-organizing maps (SOM) is one of the most popular artificial neural network models. In this study, SOM were used to assess the potential relationships between polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) congener profiles in environmental (soil, herbage, and ambient air) and biological (plasma, adipose tissue, and breast milk) samples, and the emissions of a hazardous waste incinerator (HWI) in Spain. The visual examination of PCDD/F congener profiles of most environmental and biological samples did not allow finding out any differences between monitors. However, the global SOM analysis of environmental and biological samples showed that the weight of the PCDD/F stack emissions of the HWI on the environmental burden and on the exposure of the individuals living in the surroundings was not significant in relation to the background levels. The results confirmed the small influence of the HWI emissions of PCDD/Fs on the environment and the population living in the neighborhood.

New Perspectives: Wave Mechanical Interpretations of Dark Matter, Baryon and Dark Energy

NASA Astrophysics Data System (ADS)

Russell, Esra

We model the cosmic components: dark matter, dark energy and baryon distributions in the Cosmic Web by means of highly nonlinear Schrodinger type and reaction diffusion type wave mechanical descriptions. The construction of these wave mechanical models of the structure formation is achieved by introducing the Fisher information measure and its comparison with highly nonlinear term which has dynamical analogy to infamous quantum potential in the wave equations. Strikingly, the comparison of this nonlinear term and the Fisher information measure provides a dynamical distinction between lack of self-organization and self-organization in the dynamical evolution of the cosmic components. Mathematically equivalent to the standard cosmic fluid equations, these approaches make it possible to follow the evolution of the matter distribution even into the highly nonlinear regime by circumventing singularities. Also, numerical realizations of the emerging web-like patterns are presented from the nonlinear dynamics of the baryon component while dark energy component shows Gaussian type dynamics corresponding to soliton-like solutions.

Interpretation of fingerprint image quality features extracted by self-organizing maps

NASA Astrophysics Data System (ADS)

Danov, Ivan; Olsen, Martin A.; Busch, Christoph

2014-05-01

Accurate prediction of fingerprint quality is of significant importance to any fingerprint-based biometric system. Ensuring high quality samples for both probe and reference can substantially improve the system's performance by lowering false non-matches, thus allowing finer adjustment of the decision threshold of the biometric system. Furthermore, the increasing usage of biometrics in mobile contexts demands development of lightweight methods for operational environment. A novel two-tier computationally efficient approach was recently proposed based on modelling block-wise fingerprint image data using Self-Organizing Map (SOM) to extract specific ridge pattern features, which are then used as an input to a Random Forests (RF) classifier trained to predict the quality score of a propagated sample. This paper conducts an investigative comparative analysis on a publicly available dataset for the improvement of the two-tier approach by proposing additionally three feature interpretation methods, based respectively on SOM, Generative Topographic Mapping and RF. The analysis shows that two of the proposed methods produce promising results on the given dataset.

Self-organization of punishment in structured populations

NASA Astrophysics Data System (ADS)

Perc, Matjaž; Szolnoki, Attila

2012-04-01

Cooperation is crucial for the remarkable evolutionary success of the human species. Not surprisingly, some individuals are willing to bear additional costs in order to punish defectors. Current models assume that, once set, the fine and cost of punishment do not change over time. Here we show that relaxing this assumption by allowing players to adapt their sanctioning efforts in dependence on the success of cooperation can explain both the spontaneous emergence of punishment and its ability to deter defectors and those unwilling to punish them with globally negligible investments. By means of phase diagrams and the analysis of emerging spatial patterns, we demonstrate that adaptive punishment promotes public cooperation through the invigoration of spatial reciprocity, the prevention of the emergence of cyclic dominance, or the provision of competitive advantages to those that sanction antisocial behavior. The results presented indicate that the process of self-organization significantly elevates the effectiveness of punishment, and they reveal new mechanisms by means of which this fascinating and widespread social behavior could have evolved.

Stem Cells, Patterning and Regeneration in Planarians: Self-Organization at the Organismal Scale.

PubMed

Rink, Jochen C

2018-01-01

The establishment of size and shape remains a fundamental challenge in biological research that planarian flatworms uniquely epitomize. Planarians can regenerate complete and perfectly proportioned animals from tiny and arbitrarily shaped tissue pieces; they continuously renew all organismal cell types from abundant pluripotent stem cells, yet maintain shape and anatomy in the face of constant turnover; they grow when feeding and literally degrow when starving, while scaling form and function over as much as a 40-fold range in body length or an 800-fold change in total cell numbers. This review provides a broad overview of the current understanding of the planarian stem cell system, the mechanisms that pattern the planarian body plan and how the interplay between patterning signals and cell fate choices orchestrates regeneration. What emerges is a conceptual framework for the maintenance and regeneration of the planarian body plan on basis of the interplay between pluripotent stem cells and self-organizing patterns and further, the general utility of planarians as model system for the mechanistic basis of size and shape.

Self-organized microstructures induced by MeV ion beam on silicon surface

NASA Astrophysics Data System (ADS)

Ahmad, Muthanna

2017-02-01

Micro patterning of self organized structure on silicon surface is induced by ion implantation of energetic (MeV) copper ions. This work reports for the first time the ability of using energetic ions for producing highly ordered ripples and dots of micro sizes. The experiments are realized at the Tandem ion beam accelerator (3 MV) at the IBA laboratory of the Atomic Energy Commission of Syria. Similarly to nano patterning formed by slow ions, the formation of micro patterned structures dots and ripples is observed to be depending on the angle of ion beam incidence, energy and ion fluence. The observation of such microstructures formation is limited to a range of ion energies (few MeV) at fluence higher than 1.75 × 1017 ion cm-2. The patterned surface layer is completely amorphousized by the ion implantation. Shadowing effect is observed in the formation of microripples and superstructures in the top of ripples. The superstructure develops new morphology that is not observed before. This morphology has butterfly shape with symmetry in its structure.

Data-driven cluster reinforcement and visualization in sparsely-matched self-organizing maps.

PubMed

Manukyan, Narine; Eppstein, Margaret J; Rizzo, Donna M

2012-05-01

A self-organizing map (SOM) is a self-organized projection of high-dimensional data onto a typically 2-dimensional (2-D) feature map, wherein vector similarity is implicitly translated into topological closeness in the 2-D projection. However, when there are more neurons than input patterns, it can be challenging to interpret the results, due to diffuse cluster boundaries and limitations of current methods for displaying interneuron distances. In this brief, we introduce a new cluster reinforcement (CR) phase for sparsely-matched SOMs. The CR phase amplifies within-cluster similarity in an unsupervised, data-driven manner. Discontinuities in the resulting map correspond to between-cluster distances and are stored in a boundary (B) matrix. We describe a new hierarchical visualization of cluster boundaries displayed directly on feature maps, which requires no further clustering beyond what was implicitly accomplished during self-organization in SOM training. We use a synthetic benchmark problem and previously published microbial community profile data to demonstrate the benefits of the proposed methods.

The concept of self-organizing systems. Why bother?

NASA Astrophysics Data System (ADS)

Elverfeldt, Kirsten v.; Embleton-Hamann, Christine; Slaymaker, Olav

2016-04-01

Complexity theory and the concept of self-organizing systems provide a rather challenging conceptual framework for explaining earth systems change. Self-organization - understood as the aggregate processes internal to an environmental system that lead to a distinctive spatial or temporal organization - reduces the possibility of implicating a specific process as being causal, and it poses some restrictions on the idea that external drivers cause a system to change. The concept of self-organizing systems suggests that many phenomena result from an orchestration of different mechanisms, so that no causal role can be assigned to an individual factor or process. The idea that system change can be due to system-internal processes of self-organization thus proves a huge challenge to earth system research, especially in the context of global environmental change. In order to understand the concept's implications for the Earth Sciences, we need to know the characteristics of self-organizing systems and how to discern self-organizing systems. Within the talk, we aim firstly at characterizing self-organizing systems, and secondly at highlighting the advantages and difficulties of the concept within earth system sciences. The presentation concludes that: - The concept of self-organizing systems proves especially fruitful for small-scale earth surface systems. Beach cusps and patterned ground are only two of several other prime examples of self-organizing earth surface systems. They display characteristics of self-organization like (i) system-wide order from local interactions, (ii) symmetry breaking, (iii) distributed control, (iv) robustness and resilience, (v) nonlinearity and feedbacks, (vi) organizational closure, (vii) adaptation, and (viii) variation and selection. - It is comparatively easy to discern self-organization in small-scale systems, but to adapt the concept to larger scale systems relevant to global environmental change research is more difficult: Self-organizing systems seem to form nested hierarchies, and on different hierarchical levels self-organizing and externally driven subsystems might occur simultaneously. - Traditional geomorphological concepts such as sensitivity to change, and intrinsic or extrinsic thresholds are compatible with the concept of self-organizing system, and these concepts are even enriched in their explanatory power when viewed in the larger framework of self-organization. The conceptual step to acknowledge self-organizing system change within earth system sciences thus can be regarded as relatively small. The concept of self-organization suggests a change of focus for earth system change research: a shift from input-output relations toward the inner organization of systems, since external controls rather limit the degrees of freedom of a system instead of triggering changes. Many systems might in fact be rather autonomous, and the specific and observable external trigger might be less important than the intrinsic system state. Hence, neither gradual nor catastrophic system changes necessarily need an external driver. The concept of self-organization provides important caveats to generally attributing environmental change to external drivers, and it encourages a frank admission of ignorance in the face of complexity.

Anisotropic optical transmission of femtosecond laser induced periodic surface nanostructures on indium-tin-oxide films.

PubMed

Wang, Chih; Wang, Hsuan-I; Luo, Chih-Wei; Leu, Jihperng

2012-09-03

Two types of periodic nanostructures, self-organized nanodots and nanolines, were fabricated on the surfaces of indium-tin-oxide (ITO) films using femtosecond laser pulse irradiation. Multiple periodicities (approximately 800 nm and 400 nm) were clearly observed on the ITO films with nanodot and nanoline structures and were identified using two-dimensional Fourier transformation patterns. Both nanostructures show the anisotropic transmission characteristics in the visible range, which are strongly correlated with the geometry and the metallic content of the laser-induced nanostructures.

Anisotropic optical transmission of femtosecond laser induced periodic surface nanostructures on indium-tin-oxide films

PubMed Central

Wang, Chih; Wang, Hsuan-I; Luo, Chih-Wei; Leu, Jihperng

2012-01-01

Two types of periodic nanostructures, self-organized nanodots and nanolines, were fabricated on the surfaces of indium-tin-oxide (ITO) films using femtosecond laser pulse irradiation. Multiple periodicities (approximately 800 nm and 400 nm) were clearly observed on the ITO films with nanodot and nanoline structures and were identified using two-dimensional Fourier transformation patterns. Both nanostructures show the anisotropic transmission characteristics in the visible range, which are strongly correlated with the geometry and the metallic content of the laser-induced nanostructures. PMID:23066167

Interconnect patterns for printed organic thermoelectric devices with large fill factors

NASA Astrophysics Data System (ADS)

Gordiz, Kiarash; Menon, Akanksha K.; Yee, Shannon K.

2017-09-01

Organic materials can be printed into thermoelectric (TE) devices for low temperature energy harvesting applications. The output voltage of printed devices is often limited by (i) small temperature differences across the active materials attributed to small leg lengths and (ii) the lower Seebeck coefficient of organic materials compared to their inorganic counterparts. To increase the voltage, a large number of p- and n-type leg pairs is required for organic TEs; this, however, results in an increased interconnect resistance, which then limits the device output power. In this work, we discuss practical concepts to address this problem by positioning TE legs in a hexagonal closed-packed layout. This helps achieve higher fill factors (˜91%) than conventional inorganic devices (˜25%), which ultimately results in higher voltages and power densities due to lower interconnect resistances. In addition, wiring the legs following a Hilbert spacing-filling pattern allows for facile load matching to each application. This is made possible by leveraging the fractal nature of the Hilbert interconnect pattern, which results in identical sub-modules. Using the Hilbert design, sub-modules can better accommodate non-uniform temperature distributions because they naturally self-localize. These device design concepts open new avenues for roll-to-roll printing and custom TE module shapes, thereby enabling organic TE modules for self-powered sensors and wearable electronic applications.

The fractal geometry of life.

PubMed

Losa, Gabriele A

2009-01-01

The extension of the concepts of Fractal Geometry (Mandelbrot [1983]) toward the life sciences has led to significant progress in understanding complex functional properties and architectural / morphological / structural features characterising cells and tissues during ontogenesis and both normal and pathological development processes. It has even been argued that fractal geometry could provide a coherent description of the design principles underlying living organisms (Weibel [1991]). Fractals fulfil a certain number of theoretical and methodological criteria including a high level of organization, shape irregularity, functional and morphological self-similarity, scale invariance, iterative pathways and a peculiar non-integer fractal dimension [FD]. Whereas mathematical objects are deterministic invariant or self-similar over an unlimited range of scales, biological components are statistically self-similar only within a fractal domain defined by upper and lower limits, called scaling window, in which the relationship between the scale of observation and the measured size or length of the object can be established (Losa and Nonnenmacher [1996]). Selected examples will contribute to depict complex biological shapes and structures as fractal entities, and also to show why the application of the fractal principle is valuable for measuring dimensional, geometrical and functional parameters of cells, tissues and organs occurring within the vegetal and animal realms. If the criteria for a strict description of natural fractals are met, then it follows that a Fractal Geometry of Life may be envisaged and all natural objects and biological systems exhibiting self-similar patterns and scaling properties may be considered as belonging to the new subdiscipline of "fractalomics".

Cinematic Operation of the Cerebral Cortex Interpreted via Critical Transitions in Self-Organized Dynamic Systems

PubMed Central

Kozma, Robert; Freeman, Walter J.

2017-01-01

Measurements of local field potentials over the cortical surface and the scalp of animals and human subjects reveal intermittent bursts of beta and gamma oscillations. During the bursts, narrow-band metastable amplitude modulation (AM) patters emerge for a fraction of a second and ultimately dissolve to the broad-band random background activity. The burst process depends on previously learnt conditioned stimuli (CS), thus different AM patterns may emerge in response to different CS. This observation leads to our cinematic theory of cognition when perception happens in discrete steps manifested in the sequence of AM patterns. Our article summarizes findings in the past decades on experimental evidence of cinematic theory of cognition and relevant mathematical models. We treat cortices as dissipative systems that self-organize themselves near a critical level of activity that is a non-equilibrium metastable state. Criticality is arguably a key aspect of brains in their rapid adaptation, reconfiguration, high storage capacity, and sensitive response to external stimuli. Self-organized criticality (SOC) became an important concept to describe neural systems. We argue that transitions from one AM pattern to the other require the concept of phase transitions, extending beyond the dynamics described by SOC. We employ random graph theory (RGT) and percolation dynamics as fundamental mathematical approaches to model fluctuations in the cortical tissue. Our results indicate that perceptions are formed through a phase transition from a disorganized (high entropy) to a well-organized (low entropy) state, which explains the swiftness of the emergence of the perceptual experience in response to learned stimuli. PMID:28352218

Study of the microbiological environment within long- and medium-range Canadian Forces aircraft.

PubMed

Clayton, A J; O'Connell, D C; Gaunt, R A; Clarke, R E

1976-05-01

Because of a possible requirement to carry patients with highly virulent communicable diseases, a study was undertaken to observe smoke patterns within Canadian Forces transport aircraft. This was followed by the quantitative evaluation of the spread on non-pathogenic organisms disseminated within a Boeing 707 and a C13OE (Hercules). Thirdly, an attempt to recover respiratory tract viruses during transatlantic flights was made. Smoke patterns showed that an infected patient should be placed at the rear of the aircraft. The spread of the nonpathogenic organisms in a 707 indicated that contamination was largely confined to the rear, except when the aircraft was in an unpressurized mode. In the C13OE, contamination was shown to occur throughout the whole aircraft. No respiratory tract viruses were recovered during the transatlantic flights. It is essential that a 707 should be utilized for aeromedical evacuations. If a C13OE is being considered, then a portable self-contained isolation care unit is mandatory.

Self-organization processes in field-invasion team sports : implications for leadership.

PubMed

Passos, Pedro; Araújo, Duarte; Davids, Keith

2013-01-01

In nature, the interactions between agents in a complex system (fish schools; colonies of ants) are governed by information that is locally created. Each agent self-organizes (adjusts) its behaviour, not through a central command centre, but based on variables that emerge from the interactions with other system agents in the neighbourhood. Self-organization has been proposed as a mechanism to explain the tendencies for individual performers to interact with each other in field-invasion sports teams, displaying functional co-adaptive behaviours, without the need for central control. The relevance of self-organization as a mechanism that explains pattern-forming dynamics within attacker-defender interactions in field-invasion sports has been sustained in the literature. Nonetheless, other levels of interpersonal coordination, such as intra-team interactions, still raise important questions, particularly with reference to the role of leadership or match strategies that have been prescribed in advance by a coach. The existence of key properties of complex systems, such as system degeneracy, nonlinearity or contextual dependency, suggests that self-organization is a functional mechanism to explain the emergence of interpersonal coordination tendencies within intra-team interactions. In this opinion article we propose how leadership may act as a key constraint on the emergent, self-organizational tendencies of performers in field-invasion sports.

Self-organized adaptation of a simple neural circuit enables complex robot behaviour

NASA Astrophysics Data System (ADS)

Steingrube, Silke; Timme, Marc; Wörgötter, Florentin; Manoonpong, Poramate

2010-03-01

Controlling sensori-motor systems in higher animals or complex robots is a challenging combinatorial problem, because many sensory signals need to be simultaneously coordinated into a broad behavioural spectrum. To rapidly interact with the environment, this control needs to be fast and adaptive. Present robotic solutions operate with limited autonomy and are mostly restricted to few behavioural patterns. Here we introduce chaos control as a new strategy to generate complex behaviour of an autonomous robot. In the presented system, 18 sensors drive 18 motors by means of a simple neural control circuit, thereby generating 11 basic behavioural patterns (for example, orienting, taxis, self-protection and various gaits) and their combinations. The control signal quickly and reversibly adapts to new situations and also enables learning and synaptic long-term storage of behaviourally useful motor responses. Thus, such neural control provides a powerful yet simple way to self-organize versatile behaviours in autonomous agents with many degrees of freedom.

Growth and characterization of organic layers deposited on porous-patterned Si surface

NASA Astrophysics Data System (ADS)

Gorbach, Tamara Ya.; Smertenko, Petro S.; Olkhovik, G. P.; Wisz, Grzegorz

2017-01-01

The organic layers with the thickness from a few nanometers up to few micrometers have been deposited from the chemical solution at room temperature on porous patterned Si surfaces using two medical solutions: thiamine diphosphide (pH=1÷2) and metamizole sodium (pH=6÷7). Based on evolution of morphology, structural and compositional features obtained by scanning electron microscopy, X-ray analysis, reflectance high energy electron diffraction the grown mechanisms in thin organic layers are discussed in the terms of terrace-step-kink model whereas self-organized assemblies evaluated more thick layers. Transport mechanism features and possible photovoltaic properties are discussed on the base of differential current-voltage characteristics.

Self-Organizing and Stochastic Behaviors During the Regeneration of Hair Stem Cells

PubMed Central

Plikus, Maksim V.; Baker, Ruth E.; Chen, Chih-Chiang; Fare, Clyde; de la Cruz, Damon; Andl, Thomas; Maini, Philip K.; Millar, Sarah E.; Widelitz, Randall; Chuong, Cheng-Ming

2012-01-01

Stem cells cycle through active and quiescent states. Large populations of stem cells in an organ may cycle randomly or in a coordinated manner. Although stem cell cycling within single hair follicles has been studied, less is known about regenerative behavior in a hair follicle population. By combining predictive mathematical modeling with in vivo studies in mice and rabbits, we show that a follicle progresses through cycling stages by continuous integration of inputs from intrinsic follicular and extrinsic environmental signals based on universal patterning principles. Signaling from the WNT/bone morphogenetic protein activator/inhibitor pair is coopted to mediate interactions among follicles in the population. This regenerative strategy is robust and versatile because relative activator/inhibitor strengths can be modulated easily, adapting the organism to different physiological and evolutionary needs. PMID:21527712

Self-assembly of hierarchically ordered structures in DNA nanotube systems

NASA Astrophysics Data System (ADS)

Glaser, Martin; Schnauß, Jörg; Tschirner, Teresa; Schmidt, B. U. Sebastian; Moebius-Winkler, Maximilian; Käs, Josef A.; Smith, David M.

2016-05-01

The self-assembly of molecular and macromolecular building blocks into organized patterns is a complex process found in diverse systems over a wide range of size and time scales. The formation of star- or aster-like configurations, for example, is a common characteristic in solutions of polymers or other molecules containing multi-scaled, hierarchical assembly processes. This is a recurring phenomenon in numerous pattern-forming systems ranging from cellular constructs to solutions of ferromagnetic colloids or synthetic plastics. To date, however, it has not been possible to systematically parameterize structural properties of the constituent components in order to study their influence on assembled states. Here, we circumvent this limitation by using DNA nanotubes with programmable mechanical properties as our basic building blocks. A small set of DNA oligonucleotides can be chosen to hybridize into micron-length DNA nanotubes with a well-defined circumference and stiffness. The self-assembly of these nanotubes to hierarchically ordered structures is driven by depletion forces caused by the presence of polyethylene glycol. This trait allowed us to investigate self-assembly effects while maintaining a complete decoupling of density, self-association or bundling strength, and stiffness of the nanotubes. Our findings show diverse ranges of emerging structures including heterogeneous networks, aster-like structures, and densely bundled needle-like structures, which compare to configurations found in many other systems. These show a strong dependence not only on concentration and bundling strength, but also on the underlying mechanical properties of the nanotubes. Similar network architectures to those caused by depletion forces in the low-density regime are obtained when an alternative hybridization-based bundling mechanism is employed to induce self-assembly in an isotropic network of pre-formed DNA nanotubes. This emphasizes the universal effect inevitable attractive forces in crowded environments have on systems of self-assembling soft matter, which should be considered for macromolecular structures applied in crowded systems such as cells.

Heredity and self-organization: partners in the generation and evolution of phenotypes.

PubMed

Malagon, Nicolas; Larsen, Ellen

2015-01-01

In this review we examine the role of self-organization in the context of the evolution of morphogenesis. We provide examples to show that self-organized behavior is ubiquitous, and suggest it is a mechanism that can permit high levels of biodiversity without the invention of ever-increasing numbers of genes. We also examine the implications of self-organization for understanding the "internal descriptions" of organisms and the concept of a genotype-phenotype map. Copyright © 2015 Elsevier Inc. All rights reserved.

Self-organization of neural patterns and structures in 3D culture of stem cells

NASA Astrophysics Data System (ADS)

Sasai, Yoshiki

2013-05-01

Over the last several years, much progress has been made for in vitro culture of mouse and human ES cells. Our laboratory focuses on the molecular and cellular mechanisms of neural differentiation from pluripotent cells. Pluripotent cells first become committed to the ectodermal fate and subsequently differentiate into uncommitted neuroectodermal cells. Both previous mammalian and amphibian studies on pluripotent cells have indicated that the neural fate is a sort of the basal direction of the differentiation of these cells while mesoendodermal differentiation requires extrinsic inductive signals. ES cells differentiate into neuroectodermal cells with a rostral-most character (telencephalon and hypothalamus) when they are cultured in the absence of strong patterning signals. In this talk, I first discuss this issue by referring to our recent data on the mechanism of spontaneous neural differentiation in serum-free culture of mouse ES cells. Then, I will talk about self-organization phenomena observed in 3D culture of ES cells, which lead to tissue-autonomous formation of regional structures such as layered cortical tissues. I also discuss our new attempt to monitor these in vitro morphogenetic processes by live imaging, in particular, self-organizing morphogenesis of the optic cup in three-dimensional cultures.

The sensitivity of Turing self-organization to biological feedback delays: 2D models of fish pigmentation.

PubMed

Gaffney, E A; Lee, S Seirin

2015-03-01

Turing morphogen models have been extensively explored in the context of large-scale self-organization in multicellular biological systems. However, reconciling the detailed biology of morphogen dynamics, while accounting for time delays associated with gene expression, reveals aberrant behaviours that are not consistent with early developmental self-organization, especially the requirement for exquisite temporal control. Attempts to reconcile the interpretation of Turing's ideas with an increasing understanding of the mechanisms driving zebrafish pigmentation suggests that one should reconsider Turing's model in terms of pigment cells rather than morphogens (Nakamasu et al., 2009, PNAS, 106: , 8429-8434; Yamaguchi et al., 2007, PNAS, 104: , 4790-4793). Here the dynamics of pigment cells is subject to response delays implicit in the cell cycle and apoptosis. Hence we explore simulations of fish skin patterning, focussing on the dynamical influence of gene expression delays in morphogen-based Turing models and response delays for cell-based Turing models. We find that reconciling the mechanisms driving the behaviour of Turing systems with observations of fish skin patterning remains a fundamental challenge. © The Authors 2013. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Implications of tristability in pattern-forming ecosystems

NASA Astrophysics Data System (ADS)

Zelnik, Yuval R.; Gandhi, Punit; Knobloch, Edgar; Meron, Ehud

2018-03-01

Many ecosystems show both self-organized spatial patterns and multistability of possible states. The combination of these two phenomena in different forms has a significant impact on the behavior of ecosystems in changing environments. One notable case is connected to tristability of two distinct uniform states together with patterned states, which has recently been found in model studies of dryland ecosystems. Using a simple model, we determine the extent of tristability in parameter space, explore its effects on the system dynamics, and consider its implications for state transitions or regime shifts. We analyze the bifurcation structure of model solutions that describe uniform states, periodic patterns, and hybrid states between the former two. We map out the parameter space where these states exist, and note how the different states interact with each other. We further focus on two special implications with ecological significance, breakdown of the snaking range and complex fronts. We find that the organization of the hybrid states within a homoclinic snaking structure breaks down as it meets a Maxwell point where simple fronts are stationary. We also discover a new series of complex fronts between the uniform states, each with its own velocity. We conclude with a brief discussion of the significance of these findings for the dynamics of regime shifts and their potential control.

Emergent pattern formation in an interstitial biofilm

NASA Astrophysics Data System (ADS)

Zachreson, Cameron; Wolff, Christian; Whitchurch, Cynthia B.; Toth, Milos

2017-01-01

Collective behavior of bacterial colonies plays critical roles in adaptability, survivability, biofilm expansion and infection. We employ an individual-based model of an interstitial biofilm to study emergent pattern formation based on the assumptions that rod-shaped bacteria furrow through a viscous environment and excrete extracellular polymeric substances which bias their rate of motion. Because the bacteria furrow through their environment, the substratum stiffness is a key control parameter behind the formation of distinct morphological patterns. By systematically varying this property (which we quantify with a stiffness coefficient γ ), we show that subtle changes in the substratum stiffness can give rise to a stable state characterized by a high degree of local order and long-range pattern formation. The ordered state exhibits characteristics typically associated with bacterial fitness advantages, even though it is induced by changes in environmental conditions rather than changes in biological parameters. Our findings are applicable to a broad range of biofilms and provide insights into the relationship between bacterial movement and their environment, and basic mechanisms behind self-organization of biophysical systems.

Self-organization of grafted polyelectrolyte layers via the coupling of chemical equilibrium and physical interactions.

PubMed

Tagliazucchi, Mario; de la Cruz, Mónica Olvera; Szleifer, Igal

2010-03-23

The competition between chemical equilibrium, for example protonation, and physical interactions determines the molecular organization and functionality of biological and synthetic systems. Charge regulation by displacement of acid-base equilibrium induced by changes in the local environment provides a feedback mechanism that controls the balance between electrostatic, van der Waals, steric interactions and molecular organization. Which strategies do responsive systems follow to globally optimize chemical equilibrium and physical interactions? We address this question by theoretically studying model layers of end-grafted polyacids. These layers spontaneously form self-assembled aggregates, presenting domains of controlled local pH and whose morphologies can be manipulated by the composition of the solution in contact with the film. Charge regulation stabilizes micellar domains over a wide range of pH by reducing the local charge in the aggregate at the cost of chemical free energy and gaining in hydrophobic interactions. This balance determines the boundaries between different aggregate morphologies. We show that a qualitatively new form of organization arises from the coupling between physical interactions and protonation equilibrium. This optimization strategy presents itself with polyelectrolytes coexisting in two different and well-defined protonation states. Our results underline the need of considering the coupling between chemical equilibrium and physical interactions due to their highly nonadditive behavior. The predictions provide guidelines for the creation of responsive polymer layers presenting self-organized patterns with functional properties and they give insights for the understanding of competing interactions in highly inhomogeneous and constrained environments such as those relevant in nanotechnology and those responsible for biological cells function.

Self-control of traffic lights and vehicle flows in urban road networks

NASA Astrophysics Data System (ADS)

Lämmer, Stefan; Helbing, Dirk

2008-04-01

Based on fluid-dynamic and many-particle (car-following) simulations of traffic flows in (urban) networks, we study the problem of coordinating incompatible traffic flows at intersections. Inspired by the observation of self-organized oscillations of pedestrian flows at bottlenecks, we propose a self-organization approach to traffic light control. The problem can be treated as a multi-agent problem with interactions between vehicles and traffic lights. Specifically, our approach assumes a priority-based control of traffic lights by the vehicle flows themselves, taking into account short-sighted anticipation of vehicle flows and platoons. The considered local interactions lead to emergent coordination patterns such as 'green waves' and achieve an efficient, decentralized traffic light control. While the proposed self-control adapts flexibly to local flow conditions and often leads to non-cyclical switching patterns with changing service sequences of different traffic flows, an almost periodic service may evolve under certain conditions and suggests the existence of a spontaneous synchronization of traffic lights despite the varying delays due to variable vehicle queues and travel times. The self-organized traffic light control is based on an optimization and a stabilization rule, each of which performs poorly at high utilizations of the road network, while their proper combination reaches a superior performance. The result is a considerable reduction not only in the average travel times, but also of their variation. Similar control approaches could be applied to the coordination of logistic and production processes.

Self-evaluation on Motion Adaptation for Service Robots

NASA Astrophysics Data System (ADS)

Funabora, Yuki; Yano, Yoshikazu; Doki, Shinji; Okuma, Shigeru

We suggest self motion evaluation method to adapt to environmental changes for service robots. Several motions such as walking, dancing, demonstration and so on are described with time series patterns. These motions are optimized with the architecture of the robot and under certain surrounding environment. Under unknown operating environment, robots cannot accomplish their tasks. We propose autonomous motion generation techniques based on heuristic search with histories of internal sensor values. New motion patterns are explored under unknown operating environment based on self-evaluation. Robot has some prepared motions which realize the tasks under the designed environment. Internal sensor values observed under the designed environment with prepared motions show the interaction results with the environment. Self-evaluation is composed of difference of internal sensor values between designed environment and unknown operating environment. Proposed method modifies the motions to synchronize the interaction results on both environment. New motion patterns are generated to maximize self-evaluation function without external information, such as run length, global position of robot, human observation and so on. Experimental results show that the possibility to adapt autonomously patterned motions to environmental changes.

Evaluating controls on fluvial sand-body clustering in the Ferris Formation (Cretaceous/Paleogene, Wyoming, USA)

NASA Astrophysics Data System (ADS)

Hajek, E. A.; Heller, P.

2009-12-01

A primary goal of sedimentary geologists is to interpret past tectonic, climatic, and eustatic conditions from the stratigraphic record. Stratigraphic changes in alluvial-basin fills are routinely interpreted as the result of past tectonic movements or changes in climate or sea level. Recent physical and numerical models have shown that sedimentary systems can exhibit self-organization on basin-filling time scales, suggesting that structured stratigraphic patterns can form spontaneously rather than as the result of changing boundary conditions. The Ferris Formation (Upper Cretaceous/Paleogene, Hanna Basin, Wyoming) exhibits stratigraphic organization where clusters of closely-spaced channel deposits are separated from other clusters by intervals dominated by overbank material. In order to evaluate the role of basinal controls on deposition and ascertain the potential for self-organization in this ancient deposit, the spatial patterns of key channel properties (including sand-body dimensions, paleoflow depth, maximum clast size, paleocurrent direction, and sediment provenance) are analyzed. Overall the study area lacks strong trends sand-body properties through the stratigraphic succession and in cluster groups. Consequently there is no indication that the stratigraphic pattern observed in the Ferris Formation was driven by systematic changes in climate or tectonics.

Pattern self-repetition of fingerprints, lip prints, and palatal rugae among three generations of family: A forensic approach to identify family hierarchy.

PubMed

Mala, Sankeerti; Rathod, Vanita; Pundir, Siddharth; Dixit, Sudhanshu

2017-01-01

The unique pattern and structural diversity of fingerprints, lip prints, palatal rugae, and their occurrence in different patterns among individuals make it questionable whether they are completely unique even in a family hierarchy? Do they have any repetition of the patterns among the generations? Or is this a mere chaos theory? The present study aims to assess the pattern self-repetition of fingerprints, lip prints, and palatal rugae among three generations of ten different families. The present study was conducted at Rungta College of Dental Science and Research, Bhilai, India. Participants birth by origin of Chhattisgarh were only included in the study. Thirty participants from three consecutive generations of ten different families were briefed about the purpose of the study, and their fingerprints, lip prints, and palatal rugae impression were recorded and analyzed for the pattern of self-repetition. Multiple comparisons among the generations and one-way analysis of variance test were performed using SPSS 20 trial version. Among the pattern of primary palatal rugae, 10% showed repetition in all the three generations. Thirty percent showed repetition of the pattern of thumb fingerprints in all the three generation. The pattern of lip prints in the middle 1/3 rd of lower lip, 20% showed repetition in alternative generations. The evaluations of fingerprints, lip prints, and palatal rugae showed fractal dimensions, occurring variations in dimensions according to the complexity of each structure. Even though a minute self-repetition in the patterns of lip, thumb, and palate among the three consequent generations in a family was observed considering the sample size, these results need to be confirmed in a larger sample, either to establish the role of chaos theory in forensic science or identifying a particular pattern of the individual in his family hierarchy.

A study of the relationship between parental bonding, self-concept and eating disturbances in Norwegian and American college populations.

PubMed

Perry, Judith A; Silvera, David H; Neilands, Torsten B; Rosenvinge, Jan H; Hanssen, Tina

2008-01-01

This study investigated the relationship between bonding patterns and self-concept, and the influence of these constructs on a measure of sub-clinical eating disturbances. Undergraduate students from the United States (N=166) and Norway (N=233) were given self-report questionnaires that included measures of parental bonding, locus of control, self-concept clarity, self-esteem, and disturbed cognitions associated with eating. A structural equation model showed the expected pattern, with bonding predicting self-concept and self-concept predicting eating disturbances. The model fit equally well for samples from both countries and for both genders. This model links the pattern of low care and overprotective parental bonding indicators mediated through a self-concept defined by a lack of self-understanding, low self-esteem, and external locus of control to increased risk of eating disturbances for college aged men and women.

Behavioral and Physiological Neural Network Analyses: A Common Pathway toward Pattern Recognition and Prediction

ERIC Educational Resources Information Center

Ninness, Chris; Lauter, Judy L.; Coffee, Michael; Clary, Logan; Kelly, Elizabeth; Rumph, Marilyn; Rumph, Robin; Kyle, Betty; Ninness, Sharon K.

2012-01-01

Using 3 diversified datasets, we explored the pattern-recognition ability of the Self-Organizing Map (SOM) artificial neural network as applied to diversified nonlinear data distributions in the areas of behavioral and physiological research. Experiment 1 employed a dataset obtained from the UCI Machine Learning Repository. Data for this study…

Vascular pattern formation in plants.

PubMed

Scarpella, Enrico; Helariutta, Ykä

2010-01-01

Reticulate tissue systems exist in most multicellular organisms, and the principles underlying the formation of cellular networks have fascinated philosophers, mathematicians, and biologists for centuries. In particular, the beautiful and varied arrangements of vascular tissues in plants have intrigued mankind since antiquity, yet the organizing signals have remained elusive. Plant vascular tissues form systems of interconnected cell files throughout the plant body. Vascular cells are aligned with one another along continuous lines, and vascular tissues differentiate at reproducible positions within organ environments. However, neither the precise path of vascular differentiation nor the exact geometry of vascular networks is fixed or immutable. Several recent advances converge to reconcile the seemingly conflicting predictability and plasticity of vascular tissue patterns. A control mechanism in which an apical-basal flow of signal establishes a basic coordinate system for body axis formation and vascular strand differentiation, and in which a superimposed level of radial organizing cues elaborates cell patterns, would generate a reproducible tissue configuration in the context of an underlying robust, self-organizing structure, and account for the simultaneous regularity and flexibility of vascular tissue patterns. Copyright 2010 Elsevier Inc. All rights reserved.

Physical Mechanisms Driving Cell Sorting in Hydra.

PubMed

Cochet-Escartin, Olivier; Locke, Tiffany T; Shi, Winnie H; Steele, Robert E; Collins, Eva-Maria S

2017-12-19

Cell sorting, whereby a heterogeneous cell mixture organizes into distinct tissues, is a fundamental patterning process in development. Hydra is a powerful model system for carrying out studies of cell sorting in three dimensions, because of its unique ability to regenerate after complete dissociation into individual cells. The physicists Alfred Gierer and Hans Meinhardt recognized Hydra's self-organizing properties more than 40 years ago. However, what drives cell sorting during regeneration of Hydra from cell aggregates is still debated. Differential motility and differential adhesion have been proposed as driving mechanisms, but the available experimental data are insufficient to distinguish between these two. Here, we answer this longstanding question by using transgenic Hydra expressing fluorescent proteins and a multiscale experimental and numerical approach. By quantifying the kinematics of single cell and whole aggregate behaviors, we show that no differences in cell motility exist among cell types and that sorting dynamics follow a power law with an exponent of ∼0.5. Additionally, we measure the physical properties of separated tissues and quantify their viscosities and surface tensions. Based on our experimental results and numerical simulations, we conclude that tissue interfacial tensions are sufficient to explain cell sorting in aggregates of Hydra cells. Furthermore, we demonstrate that the aggregate's geometry during sorting is key to understanding the sorting dynamics and explains the exponent of the power law behavior. Our results answer the long standing question of the physical mechanisms driving cell sorting in Hydra cell aggregates. In addition, they demonstrate how powerful this organism is for biophysical studies of self-organization and pattern formation. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Emergence of intercolonial variation in termite shelter tube patterns and prediction of its underlying mechanism

PubMed Central

2015-01-01

Building behaviours occur in various organisms from bacteria to humans. Social insects build various structures such as large nests and underground galleries, achieved by self-organization. Structures built by social insects have recently been demonstrated to vary widely in size and shape within a species, even under the same environmental conditions. However, little is known about how intraspecific variation in structures emerges from collective behaviours. Here we show that the colony variation of structures can be generated by simply changing two behavioural parameters of group members, even with the same building algorithm. Our laboratory experiment of termite shelter tube construction demonstrated clear intercolonial variation, and a two-dimensional lattice model showed that it can be attributed to the extent of positive feedback and the number of individuals engaged in building. This study contributes to explaining the great diversity of structures emerging from collective building in social insects. PMID:26715997

Rich complex behaviour of self-assembled nanoparticles far from equilibrium

PubMed Central

Ilday, Serim; Makey, Ghaith; Akguc, Gursoy B.; Yavuz, Özgün; Tokel, Onur; Pavlov, Ihor; Gülseren, Oguz; Ilday, F. Ömer

2017-01-01

A profoundly fundamental question at the interface between physics and biology remains open: what are the minimum requirements for emergence of complex behaviour from nonliving systems? Here, we address this question and report complex behaviour of tens to thousands of colloidal nanoparticles in a system designed to be as plain as possible: the system is driven far from equilibrium by ultrafast laser pulses that create spatiotemporal temperature gradients, inducing Marangoni flow that drags particles towards aggregation; strong Brownian motion, used as source of fluctuations, opposes aggregation. Nonlinear feedback mechanisms naturally arise between flow, aggregate and Brownian motion, allowing fast external control with minimal intervention. Consequently, complex behaviour, analogous to those seen in living organisms, emerges, whereby aggregates can self-sustain, self-regulate, self-replicate, self-heal and can be transferred from one location to another, all within seconds. Aggregates can comprise only one pattern or bifurcated patterns can coexist, compete, endure or perish. PMID:28443636

Rich complex behaviour of self-assembled nanoparticles far from equilibrium

NASA Astrophysics Data System (ADS)

Ilday, Serim; Makey, Ghaith; Akguc, Gursoy B.; Yavuz, Özgün; Tokel, Onur; Pavlov, Ihor; Gülseren, Oguz; Ilday, F. Ömer

2017-04-01

A profoundly fundamental question at the interface between physics and biology remains open: what are the minimum requirements for emergence of complex behaviour from nonliving systems? Here, we address this question and report complex behaviour of tens to thousands of colloidal nanoparticles in a system designed to be as plain as possible: the system is driven far from equilibrium by ultrafast laser pulses that create spatiotemporal temperature gradients, inducing Marangoni flow that drags particles towards aggregation; strong Brownian motion, used as source of fluctuations, opposes aggregation. Nonlinear feedback mechanisms naturally arise between flow, aggregate and Brownian motion, allowing fast external control with minimal intervention. Consequently, complex behaviour, analogous to those seen in living organisms, emerges, whereby aggregates can self-sustain, self-regulate, self-replicate, self-heal and can be transferred from one location to another, all within seconds. Aggregates can comprise only one pattern or bifurcated patterns can coexist, compete, endure or perish.

Effects of Short-Term Set-Aside Management Practices on Soil Microorganism and Enzyme Activity in China.

PubMed

Li, Guangyu; Wu, Cifang

2017-08-14

Set-aside farmland can effectively improve the self-rehabilitation of arable soil. Long-term set-asides however cannot satisfy provisionment, therefore the use of short-term set-asides to restore cultivated soil is a better option. Few studies have compared short-term set-aside patterns, and the effects of set-asides on soil microbial community and enzyme enzymes. We analyzed the bacterial structure, microbial biomass carbon/nitrogen and enzyme activity of farmland soil under different set-aside regimes in the Yellow River Delta of China. Bacterial alpha diversity was relatively lower under only irrigation, and farmyard manure applications showed clear advantages. Set-asides should consider their influence on soil organic carbon and nitrogen, which were correlated with microbial community structure. Nitrospira (0.47-1.67%), Acidobacteria Gp6 (8.26-15.91%) and unclassified Burkholderiales (1.50-2.81%) were significantly altered ( p < 0.01). Based on functions of these genera, some set-aside patterns led to a relative balance in nitrogen and carbon turnover. Partial treatments showed a deficiency in organic matter. In addition, farmyard manure may lead to the increased consumption of organic matter, with the exception of native plants set-asides. Conventional farming (control group) displayed a significant enzyme activity advantage. Set-aside management practices guided soil microbial communities to different states. Integrated soil microbiota and the content of carbon and nitrogen, native plants with farmyard manure showed an equilibrium state relatively, which would be helpful to improve land quality in the short-term.

Controlled evaporative self-assembly of confined microfluids: A route to complex ordered structures

NASA Astrophysics Data System (ADS)

Byun, Myunghwan

The evaporative self-assembly of nonvolatile solutes such as polymers, nanocrystals, and carbon nanotubes has been widely recognized as a non-lithographic means of producing a diverse range of intriguing complex structures. Due to the spatial variation of evaporative flux and possible convection, however, these non-equilibrium dissipative structures (e.g., fingering patterns and polygonal network structures) are often irregularly and stochastically organized. Yet for many applications in microelectronics, data storage devices, and biotechnology, it is highly desirable to achieve surface patterns having a well-controlled spatial arrangement. To date, only a few elegant studies have centered on precise control over the evaporation process to produce ordered structures. In a remarked comparison with conventional lithography techniques, surface patterning by controlled solvent evaporation is simple and cost-effective, offering a lithography- and external field-free means to organize nonvolatile materials into ordered microscopic structures over large surface areas. The ability to engineer an evaporative self-assembly process that yields a wide range of complex, self-organizing structures over large areas offers tremendous potential for applications in electronics, optoelectronics, and bio- or chemical sensors. We developed a facile, robust tool for evaporating polymer, nanoparticle, or DNA solutions in curve-on-flat geometries to create versatile, highly regular microstructures, including hierarchically structured polymer blend rings, conjugated polymer "snake-skins", block copolymer stripes, and punch-hole-like meshes, biomolecular microring arrays, etc. The mechanism of structure formation was elucidated both experimentally and theoretically. Our method further enhances current fabrication approaches to creating highly ordered structures in a simple and cost-effective manner, envisioning the potential to be tailored for use in photonics, optoelectronics, microfluidic devices, nanotechnology and biotechnology, etc.

Microbial Life in Soil - Linking Biophysical Models with Observations

NASA Astrophysics Data System (ADS)

Or, Dani; Tecon, Robin; Ebrahimi, Ali; Kleyer, Hannah; Ilie, Olga; Wang, Gang

2015-04-01

Microbial life in soil occurs within fragmented aquatic habitats formed in complex pore spaces where motility is restricted to short hydration windows (e.g., following rainfall). The limited range of self-dispersion and physical confinement promote spatial association among trophically interdepended microbial species. Competition and preferences for different nutrient resources and byproducts and their diffusion require high level of spatial organization to sustain the functioning of multispecies communities. We report mechanistic modeling studies of competing multispecies microbial communities grown on hydrated surfaces and within artificial soil aggregates (represented by 3-D pore network). Results show how trophic dependencies and cell-level interactions within patchy diffusion fields promote spatial self-organization of motile microbial cells. The spontaneously forming patterns of segregated, yet coexisting species were robust to spatial heterogeneities and to temporal perturbations (hydration dynamics), and respond primarily to the type of trophic dependencies. Such spatially self-organized consortia may reflect ecological templates that optimize substrate utilization and could form the basic architecture for more permanent surface-attached microbial colonies. Hydration dynamics affect structure and spatial arrangement of aerobic and anaerobic microbial communities and their biogeochemical functions. Experiments with well-characterized artificial soil microbial assemblies grown on porous surfaces provide access to community dynamics during wetting and drying cycles detected through genetic fingerprinting. Experiments for visual observations of spatial associations of tagged bacterial species with known trophic dependencies on model porous surfaces are underway. Biophysical modeling provide a means for predicting hydration-mediated critical separation distances for activation of spatial self-organization. The study provides new modeling and observational tools that enable new mechanistic insights into how differences in substrate affinities among microbial species and soil micro-hydrological conditions may give rise to a remarkable spatial and functional order in an extremely heterogeneous soil microbial world

Microbial Life in Soil - Linking Biophysical Models with Observations

NASA Astrophysics Data System (ADS)

Or, D.; Tecon, R.; Ebrahimi, A.; Kleyer, H.; Ilie, O.; Wang, G.

2014-12-01

Microbial life in soil occurs within fragmented aquatic habitats in complex pore spaces where motility is restricted to short hydration windows (e.g., following rainfall). The limited range of self-dispersion and physical confinement promote spatial association among trophically interdepended microbial species. Competition and preferences for different nutrient resources and byproducts and their diffusion require high level of spatial organization to sustain the functioning of multispecies communities. We report mechanistic modeling studies of competing multispecies microbial communities grown on hydrated surfaces and within artificial soil aggregates (represented by 3-D pore network). Results show how trophic dependencies and cell-level interactions within patchy diffusion fields promote spatial self-organization of motile microbial cells. The spontaneously forming patterns of segregated, yet coexisting species were robust to spatial heterogeneities and to temporal perturbations (hydration dynamics), and respond primarily to the type of trophic dependencies. Such spatially self-organized consortia may reflect ecological templates that optimize substrate utilization and could form the basic architecture for more permanent surface-attached microbial colonies. Hydration dynamics affect structure and spatial arrangement of aerobic and anaerobic microbial communities and their biogeochemical functions. Experiments with well-characterized artificial soil microbial assemblies grown on porous surfaces provide access to community dynamics during wetting and drying cycles detected through genetic fingerprinting. Experiments for visual observations of spatial associations of tagged bacterial species with known trophic dependencies on model porous surfaces are underway. Biophysical modeling provide a means for predicting hydration-mediated critical separation distances for activation of spatial self-organization. The study provides new modeling and observational tools that enable new mechanistic insights into how differences in substrate affinities among microbial species and soil micro-hydrological conditions may give rise to a remarkable spatial and functional order in an extremely heterogeneous soil microbial world.

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Identification of large-scale meteorological patterns associated with extreme precipitation in the US northeast

NASA Astrophysics Data System (ADS)

Agel, Laurie; Barlow, Mathew; Feldstein, Steven B.; Gutowski, William J.

2018-03-01

Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. The tropopause height provides a compact representation of the upper-tropospheric potential vorticity, which is closely related to the overall evolution and intensity of weather systems. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into the overall context of patterns for all days. Six tropopause patterns are identified through KMC for extreme day precipitation: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong moisture transport preceding, and upward motion during, extreme precipitation events.

Large-Scale Meteorological Patterns Associated with Extreme Precipitation in the US Northeast

NASA Astrophysics Data System (ADS)

Agel, L. A.; Barlow, M. A.

2016-12-01

Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. Tropopause height provides a compact representation of large-scale circulation patterns, as it is linked to mid-level circulation, low-level thermal contrasts and low-level diabatic heating. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into a larger context. Six tropopause patterns are identified on extreme days: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong upward motion during, and moisture transport preceding, extreme precipitation events.

It Comes With the Job: Work Organizational, Job Design, and Self-Regulatory Barriers to Improving the Health Status of Train Drivers.

PubMed

Naweed, Anjum; Chapman, Janine; Allan, Matthew; Trigg, Joshua

2017-03-01

This study aimed to examine the impacts of key barriers to improving the occupational health status of Australian train drivers. From May to June, 2015, five semi-structured qualitative focus groups were conducted with 29 train drivers from South Australian, Victorian, and New South Wales-based rail organizations in Australia. Occupational health was impeded by multiple barriers regarding sleep (patterns/fatigue), diet (planning/context), mental health (occupational stress), rostering (low autonomy), sedentary time, low fitness motivation, and family/social life conflicts. Work organizational barriers included communication issues, low organizational support, and existing social norms. Job design barriers included rostering, fatigue, stimulant reliance, and family/social life imbalances. Self-regulatory barriers included dietary and exercise patterns habits and patterns. Occupational health interventions for Australian train drivers must address work organizational, job design, and self-regulatory barriers to healthier lifestyle behaviors.

Precipitation-generated oscillations in open cellular cloud fields.

PubMed

Feingold, Graham; Koren, Ilan; Wang, Hailong; Xue, Huiwen; Brewer, Wm Alan

2010-08-12

Cloud fields adopt many different patterns that can have a profound effect on the amount of sunlight reflected back to space, with important implications for the Earth's climate. These cloud patterns can be observed in satellite images of the Earth and often exhibit distinct cell-like structures associated with organized convection at scales of tens of kilometres. Recent evidence has shown that atmospheric aerosol particles-through their influence on precipitation formation-help to determine whether cloud fields take on closed (more reflective) or open (less reflective) cellular patterns. The physical mechanisms controlling the formation and evolution of these cells, however, are still poorly understood, limiting our ability to simulate realistically the effects of clouds on global reflectance. Here we use satellite imagery and numerical models to show how precipitating clouds produce an open cellular cloud pattern that oscillates between different, weakly stable states. The oscillations are a result of precipitation causing downward motion and outflow from clouds that were previously positively buoyant. The evaporating precipitation drives air down to the Earth's surface, where it diverges and collides with the outflows of neighbouring precipitating cells. These colliding outflows form surface convergence zones and new cloud formation. In turn, the newly formed clouds produce precipitation and new colliding outflow patterns that are displaced from the previous ones. As successive cycles of this kind unfold, convergence zones alternate with divergence zones and new cloud patterns emerge to replace old ones. The result is an oscillating, self-organized system with a characteristic cell size and precipitation frequency.

Monolayer-Mediated Growth of Organic Semiconductor Films with Improved Device Performance.

PubMed

Huang, Lizhen; Hu, Xiaorong; Chi, Lifeng

2015-09-15

Increased interest in wearable and smart electronics is driving numerous research works on organic electronics. The control of film growth and patterning is of great importance when targeting high-performance organic semiconductor devices. In this Feature Article, we summarize our recent work focusing on the growth, crystallization, and device operation of organic semiconductors intermediated by ultrathin organic films (in most cases, only a monolayer). The site-selective growth, modified crystallization and morphology, and improved device performance of organic semiconductor films are demonstrated with the help of the inducing layers, including patterned and uniform Langmuir-Blodgett monolayers, crystalline ultrathin organic films, and self-assembled polymer brush films. The introduction of the inducing layers could dramatically change the diffusion of the organic semiconductors on the surface and the interactions between the active layer with the inducing layer, leading to improved aggregation/crystallization behavior and device performance.

Pattern-Directed Ordering of Spin-Dewetted Liquid Crystal Micro- or Nanodroplets as Pixelated Light Reflectors and Locomotives.

PubMed

Ravi, Bolleddu; Chakraborty, Snigdha; Bhattacharjee, Mitradip; Mitra, Shirsendu; Ghosh, Abir; Gooh Pattader, Partho Sarathi; Bandyopadhyay, Dipankar

2017-01-11

Chemical pattern directed spin-dewetting of a macroscopic droplet composed of a dilute organic solution of liquid crystal (LC) formed an ordered array of micro- and nanoscale LC droplets. Controlled evaporation of the spin-dewetted droplets through vacuum drying could further miniaturize the size to the level of ∼90 nm. The size, periodicity, and spacing of these mesoscale droplets could be tuned with the variations in the initial loading of LC in the organic solution, the strength of the centripetal force on the droplet, and the duration of the evaporation. A simple theoretical model was developed to predict the spacing between the spin-dewetted droplets. The patterned LC droplets showed a reversible phase transition from nematic to isotropic and vice versa with the periodic exposure of a solvent vapor and its removal. A similar phase transition behavior was also observed with the periodic increase or reduction of temperature, suggesting their usefulness as vapor or temperature sensors. Interestingly, when the spin-dewetted droplets were confined between a pair of electrodes and an external electric field was applied, the droplets situated at the hydrophobic patches showed light-reflecting properties under the polarization microscopy highlighting their importance in the development of micro- or nanoscale LC displays. The digitized LC droplets, which were stationary otherwise, showed dielectrophoretic locomotion under the guidance of the external electric field beyond a threshold intensity of the field. Remarkably, the motion of these droplets could be restricted to the hydrophilic zones, which were confined between the hydrophobic patches of the chemically patterned surface. The findings could significantly contribute in the development of futuristic vapor or temperature sensors, light reflectors, and self-propellers using the micro- or nanoscale digitized LC droplets.

Perspective of Islamic Self: Rethinking Ibn al-Qayyim's Three-Heart Model from the Scope of Dynamical Social Psychology.

PubMed

Briki, Walid; Amara, Mahfoud

2018-06-01

The present article proposes the perspective of Islamic self (PIS), which is guided by three core principles. First, the Islamic self is shaped by the God's predicament: The life test. Second, the structure of the self and its spiritual virtues represent means to succeed the life test. Third, the complex dynamics of the self can be mathematically formalized into a parsimonious framework. Specifically, the PIS considers the self as a dynamical system characterized by the emergence of self-organized stable and unstable patterns taking the form of positive ("illuminating heart") or negative ("darkened heart") dynamics.

Self-Organization of Stem Cell Colonies and of Early Mammalian Embryos: Recent Experiments Shed New Light on the Role of Autonomy vs. External Instructions in Basic Body Plan Development

PubMed Central

Denker, Hans-Werner

2016-01-01

“Organoids”, i.e., complex structures that can develop when pluripotent or multipotent stem cells are maintained in three-dimensional cultures, have become a new area of interest in stem cell research. Hopes have grown that when focussing experimentally on the mechanisms behind this type of in vitro morphogenesis, research aiming at tissue and organ replacements can be boosted. Processes leading to the formation of organoids in vitro are now often addressed as self-organization, a term referring to the formation of complex tissue architecture in groups of cells without depending on specific instruction provided by other cells or tissues. The present article focuses on recent reports using the term self-organization in the context of studies on embryogenesis, specifically addressing pattern formation processes in human blastocysts attaching in vitro, or in colonies of pluripotent stem cells (“gastruloids”). These morphogenetic processes are of particular interest because, during development in vivo, they lead to basic body plan formation and individuation. Since improved methodologies like those employed by the cited authors became available, early embryonic pattern formation/self-organization appears to evolve now as a research topic of its own. This review discusses concepts concerning the involved mechanisms, focussing on autonomy of basic body plan development vs. dependence on external signals, as possibly provided by implantation in the uterus, and it addresses biological differences between an early mammalian embryo, e.g., a morula, and a cluster of pluripotent stem cells. It is concluded that, apart from being of considerable biological interest, the described type of research needs to be contemplated carefully with regard to ethical implications when performed with human cells. PMID:27792143

Self-Organization of Stem Cell Colonies and of Early Mammalian Embryos: Recent Experiments Shed New Light on the Role of Autonomy vs. External Instructions in Basic Body Plan Development.

PubMed

Denker, Hans-Werner

2016-10-25

" Organoids ", i.e., complex structures that can develop when pluripotent or multipotent stem cells are maintained in three-dimensional cultures, have become a new area of interest in stem cell research. Hopes have grown that when focussing experimentally on the mechanisms behind this type of in vitro morphogenesis, research aiming at tissue and organ replacements can be boosted. Processes leading to the formation of organoids in vitro are now often addressed as self-organization , a term referring to the formation of complex tissue architecture in groups of cells without depending on specific instruction provided by other cells or tissues. The present article focuses on recent reports using the term self-organization in the context of studies on embryogenesis , specifically addressing pattern formation processes in human blastocysts attaching in vitro, or in colonies of pluripotent stem cells (" gastruloids "). These morphogenetic processes are of particular interest because, during development in vivo, they lead to basic body plan formation and individuation. Since improved methodologies like those employed by the cited authors became available, early embryonic pattern formation/self-organization appears to evolve now as a research topic of its own. This review discusses concepts concerning the involved mechanisms, focussing on autonomy of basic body plan development vs. dependence on external signals, as possibly provided by implantation in the uterus, and it addresses biological differences between an early mammalian embryo, e.g., a morula, and a cluster of pluripotent stem cells. It is concluded that, apart from being of considerable biological interest, the described type of research needs to be contemplated carefully with regard to ethical implications when performed with human cells.

Subtle Nonlinearity in Popular Album Charts

NASA Astrophysics Data System (ADS)

Bentley, R. Alexander; Maschner, Herbert D. G.

Large-scale patterns of culture change may be explained by models of self organized criticality, or alternatively, by multiplicative processes. We speculate that popular album activity may be similar to critical models of extinction in that interconnected agents compete to survive within a limited space. Here we investigate whether popular music albums as listed on popular album charts display evidence of self-organized criticality, including a self-affine time series of activity and power-law distributions of lifetimes and exit activity in the chart. We find it difficult to distinguish between multiplicative growth and critical model hypotheses for these data. However, aspects of criticality may be masked by the selective sampling that a "Top 200" listing necessarily implies.

Self-similar conductance patterns in graphene Cantor-like structures.

PubMed

García-Cervantes, H; Gaggero-Sager, L M; Díaz-Guerrero, D S; Sotolongo-Costa, O; Rodríguez-Vargas, I

2017-04-04

Graphene has proven to be an ideal system for exotic transport phenomena. In this work, we report another exotic characteristic of the electron transport in graphene. Namely, we show that the linear-regime conductance can present self-similar patterns with well-defined scaling rules, once the graphene sheet is subjected to Cantor-like nanostructuring. As far as we know the mentioned system is one of the few in which a self-similar structure produces self-similar patterns on a physical property. These patterns are analysed quantitatively, by obtaining the scaling rules that underlie them. It is worth noting that the transport properties are an average of the dispersion channels, which makes the existence of scale factors quite surprising. In addition, that self-similarity be manifested in the conductance opens an excellent opportunity to test this fundamental property experimentally.

Transition from diffuse to self-organized discharge in a high frequency dielectric barrier discharge

NASA Astrophysics Data System (ADS)

Belinger, Antoine; Naudé, Nicolas; Gherardi, Nicolas

2017-05-01

Depending on the operating conditions, different regimes can be obtained in a dielectric barrier discharge (DBD): filamentary, diffuse (also called homogeneous) or self-organized. For a plane-to-plane DBD operated at high frequency (160 kHz) and at atmospheric pressure in helium gas, we show that the addition of a small amount of nitrogen induces a transition from the diffuse regime to a self-organized regime characterized by the appearance of filaments at the exit of the discharge. In this paper, we detail mechanisms that could be responsible of the transition from diffuse mode to this self-organized mode. We point out the critical role of the power supply and the importance of the gas memory effect from one discharge to the following one on the transition to the self-organised mode. The self-organized mode is usually attributed to a surface memory effect. In this work, we show an additional involvement of the gas memory effect on the self-organized mode. Contribution to the topical issue "The 15th International Symposium on High Pressure Low Temperature Plasma Chemistry (HAKONE XV)", edited by Nicolas Gherardi and Tomáš Hoder

Pattern activation/recognition theory of mind

PubMed Central

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a “Pattern Recognition Theory of Mind” that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call “Pattern Activation/Recognition Theory of Mind.” While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

Pattern activation/recognition theory of mind.

PubMed

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

Mapping Patterns of Multiple Deprivation and Well-Being Using Self-Organizing Maps: An Application to Swiss Household Panel Data

ERIC Educational Resources Information Center

Lucchini, Mario; Assi, Jenny

2013-01-01

The aim of this paper is to propose multidimensional measures of deprivation and wellbeing in contemporary Switzerland, in order to overcome the limitations of standard approaches. More precisely, we have developed self organising maps (SOM) using data drawn from the 2009 Swiss Household Panel wave, in order to identify highly homogeneous clusters…

Self-concept in fairness and rule establishment during a competitive game: a computational approach

PubMed Central

Lee, Sang Ho; Kim, Sung-Phil; Cho, Yang Seok

2015-01-01

People consider fairness as well as their own interest when making decisions in economic games. The present study proposes a model that encompasses the self-concept determined by one's own kindness as a factor of fairness. To observe behavioral patterns that reflect self-concept and fairness, a chicken game experiment was conducted. Behavioral data demonstrates four distinct patterns; “switching,” “mutual rush,” “mutual avoidance,” and “unfair” patterns. Model estimation of chicken game data shows that a model with self-concept predicts those behaviors better than previous models of fairness, suggesting that self-concept indeed affects human behavior in competitive economic games. Moreover, a non-stationary parameter analysis revealed the process of reaching consensus between the players in a game. When the models were fitted to a continuous time window, the parameters of the players in a pair with “switching” and “mutual avoidance” patterns became similar as the game proceeded, suggesting that the players gradually formed a shared rule during the game. In contrast, the difference of parameters between the players in the “unfair” and “mutual rush” patterns did not become stable. The outcomes of the present study showed that people are likely to change their strategy until they reach a mutually beneficial status. PMID:26441707

Mechanical constraint from growing jaw facilitates mammalian dental diversity

PubMed Central

Renvoisé, Elodie; Kavanagh, Kathryn D.; Lazzari, Vincent; Häkkinen, Teemu J.; Rice, Ritva; Pantalacci, Sophie; Salazar-Ciudad, Isaac; Jernvall, Jukka

2017-01-01

Much of the basic information about individual organ development comes from studies using model species. Whereas conservation of gene regulatory networks across higher taxa supports generalizations made from a limited number of species, generality of mechanistic inferences remains to be tested in tissue culture systems. Here, using mammalian tooth explants cultured in isolation, we investigate self-regulation of patterning by comparing developing molars of the mouse, the model species of mammalian research, and the bank vole. A distinct patterning difference between the vole and the mouse molars is the alternate cusp offset present in the vole. Analyses of both species using 3D reconstructions of developing molars and jaws, computational modeling of cusp patterning, and tooth explants cultured with small braces show that correct cusp offset requires constraints on the lateral expansion of the developing tooth. Vole molars cultured without the braces lose their cusp offset, and mouse molars cultured with the braces develop a cusp offset. Our results suggest that cusp offset, which changes frequently in mammalian evolution, is more dependent on the 3D support of the developing jaw than other aspects of tooth shape. This jaw–tooth integration of a specific aspect of the tooth phenotype indicates that organs may outsource specific aspects of their morphology to be regulated by adjacent body parts or organs. Comparative studies of morphologically different species are needed to infer the principles of organogenesis. PMID:28808032

Modeling Multi-Agent Self-Organization through the Lens of Higher Order Attractor Dynamics.

PubMed

Butner, Jonathan E; Wiltshire, Travis J; Munion, A K

2017-01-01

Social interaction occurs across many time scales and varying numbers of agents; from one-on-one to large-scale coordination in organizations, crowds, cities, and colonies. These contexts, are characterized by emergent self-organization that implies higher order coordinated patterns occurring over time that are not due to the actions of any particular agents, but rather due to the collective ordering that occurs from the interactions of the agents. Extant research to understand these social coordination dynamics (SCD) has primarily examined dyadic contexts performing rhythmic tasks. To advance this area of study, we elaborate on attractor dynamics, our ability to depict them visually, and quantitatively model them. Primarily, we combine difference/differential equation modeling with mixture modeling as a way to infer the underlying topological features of the data, which can be described in terms of attractor dynamic patterns. The advantage of this approach is that we are able to quantify the self-organized dynamics that agents exhibit, link these dynamics back to activity from individual agents, and relate it to other variables central to understanding the coordinative functionality of a system's behavior. We present four examples that differ in the number of variables used to depict the attractor dynamics (1, 2, and 6) and range from simulated to non-simulated data sources. We demonstrate that this is a flexible method that advances scientific study of SCD in a variety of multi-agent systems.

Nanospace-Mediated Self-Organization of Nanoparticles in Flexible Porous Polymer Templates.

PubMed

Kuroda, Yoshiyuki; Muto, Itaru; Shimojima, Atsushi; Wada, Hiroaki; Kuroda, Kazuyuki

2017-09-12

Self-organization is a fundamental process for the construction of complex hierarchically ordered nanostructures, which are widespread in biological systems. However, precise control of size, shape, and surface properties is required for self-organization of nanoparticles. Here, we demonstrate a novel self-organization phenomenon mediated by flexible nanospaces in templates. Inorganic nanoparticles (e.g., silica, zirconia, and titania) are deposited in porous polymer thin films with randomly distributed pores on the surface, leaving a partially filled nanospace in each pore. Heating at temperatures beyond the glass transition temperature of the template leads to self-organization of the inorganic nanoparticles into one-dimensional chainlike networks. The self-organization is mediated by the deformation and fusion of the residual nanospaces, and it can be rationally controlled by sequential heat treatments. These results show that a nanospace, defined by the nonexistence of matter, interacts indirectly with matter and can be used as a component of self-organization systems.

A mechanism for the formation and sustainment of the self-organized global profile and E   ×   B staircase in tokamak plasmas

NASA Astrophysics Data System (ADS)

Wang, W.; Kishimoto, Y.; Imadera, K.; Li, J. Q.; Wang, Z. X.

2018-05-01

The mechanism for the formation and sustainment of a self-organized global profile and the ‘ E   ×   B staircase’ are investigated through simulations of a flux-driven ion temperature gradient (ITG) turbulence based on GKNET, a 5D global gyrokinetic code. The staircase is found to be initiated from the radially extended ITG mode structures with nearly up-down symmetry during the saturation phase, and is established as it evolves into a quasi-steady turbulence, leading to a self-organized global temperature profile and to meso-scale isomorphic profiles of the radial electric field and the temperature gradient. It is found that the quasi-regular E   ×   B shear flow pattern is primarily originated from an even-symmetrical zonal flow produced by the extended ITG mode, which flow pattern exhibits an in-phase relation with the mean flow variation induced by the temperature relaxation. Consequently, the staircase is initiated through the profiles of total electric field and temperature gradient with a self-organized manner. Since the sign of E   ×   B shear flow at the central part are opposite to that at both edges, it disintegrates the ITG mode into smaller scale eddies. Meanwhile, smaller scale eddies tend to be aligned radially by spontaneous phase matching, which can provide the growth of mode amplitude and the formation of radially extended mode structures, leading to the bursty heat transport. This process is repeated quasi-periodically, sustaining self-organized structures and the E   ×   B staircase. Moreover, the equilibrium mean field is found to be of specific importance in causing the structures and dynamics from meso- to macro scales in toroidal plasmas.

78 FR 50126 - Self-Regulatory Organizations; NASDAQ OMX BX, Inc.; Notice of Filing of a Proposed Rule Change To...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-16

.... However, as the Commission has made clear with respect to BX's affiliate, the NASDAQ Stock Exchange LLC...: Manipulation patterns that monitor solely BX activity, including patterns that monitor activity that might... the opposite side of the BX market at an improved price (often referred to as ``odd lot manipulation...

Membrane-bound MinDE complex acts as a toggle switch that drives Min oscillation coupled to cytoplasmic depletion of MinD.

PubMed

Vecchiarelli, Anthony G; Li, Min; Mizuuchi, Michiyo; Hwang, Ling Chin; Seol, Yeonee; Neuman, Keir C; Mizuuchi, Kiyoshi

2016-03-15

The Escherichia coli Min system self-organizes into a cell-pole to cell-pole oscillator on the membrane to prevent divisions at the cell poles. Reconstituting the Min system on a lipid bilayer has contributed to elucidating the oscillatory mechanism. However, previous in vitro patterns were attained with protein densities on the bilayer far in excess of those in vivo and failed to recapitulate the standing wave oscillations observed in vivo. Here we studied Min protein patterning at limiting MinD concentrations reflecting the in vivo conditions. We identified "burst" patterns--radially expanding and imploding binding zones of MinD, accompanied by a peripheral ring of MinE. Bursts share several features with the in vivo dynamics of the Min system including standing wave oscillations. Our data support a patterning mechanism whereby the MinD-to-MinE ratio on the membrane acts as a toggle switch: recruiting and stabilizing MinD on the membrane when the ratio is high and releasing MinD from the membrane when the ratio is low. Coupling this toggle switch behavior with MinD depletion from the cytoplasm drives a self-organized standing wave oscillator.

Dependency distance distribution - from the perspective of genre variation. Comment on "Dependency distance: a new perspective on syntactic patterns in natural languages" by Haitao Liu et al.

NASA Astrophysics Data System (ADS)

Wang, Yaqin

2017-07-01

Language can be regarded as a system where different components fit together, according to Saussure [1]. Likewise, the central axiom of synergetic linguistic is that language is a self-organized and self-adapting system. One of its main concerns is to view language as ;a psycho-social phenomenon and a biological-cognitive one at the same time; [2, 760]. Based on this assumption, Liu, Xu and Liang propose a novel approach, i.e., dependency distance, to study the general tendency hidden beneath diverse human languages [3]. As the authors describe in sections 1-3, variations within and between human languages all show the similar tendency towards dependency distance minimization (DDM). In sections 4-5, they introduce certain syntactic patterns related to both short and long dependency distances. However, the effect of genre seems to be given less sufficient attention by the authors. A study suggests that different distributions of closeness and degree centralities across genres can broaden the understanding of dependency distance distribution [4]. Another one shows that different genres have different parameters in terms of modeling dependency distance distribution [5]. Further research on the genre variation, therefore, can provide additional support for this issue.

Computing the variations in the self-similar properties of the various gait intervals in Parkinson disease patients.

PubMed

Manjeri Keloth, Sana; Arjunan, Sridhar P; Kumar, Dinesh

2017-07-01

This study has investigated the stride, swing, stance and double support intervals of gait for Parkinson's disease (PD) patients with different levels of severity. Self-similar properties of the gait signal were analyzed to investigate the changes in the gait pattern of the healthy and PD patients. To understand the self-similar property, detrended fluctuation analysis was performed. The analysis shows that the PD patients have less defined gait when compared to healthy. The study also shows that among the stance and swing phase of stride interval, the self-similarity is less for swing interval when compared to the stance interval of gait and decreases with the severity of gait. Also, PD patients show decreased self-similar patterns in double support interval of gait. This suggest that there are less rhythmic gait intervals and a sense of urgency to remain in support phase of gait by the PD patients.

Modeling self-organization of novel organic materials

NASA Astrophysics Data System (ADS)

Sayar, Mehmet

In this thesis, the structural organization of oligomeric multi-block molecules is analyzed by computational analysis of coarse-grained models. These molecules form nanostructures with different dimensionalities, and the nanostructured nature of these materials leads to novel structural properties at different length scales. Previously, a number of oligomeric triblock rodcoil molecules have been shown to self-organize into mushroom shaped noncentrosymmetric nanostructures. Interestingly, thin films of these molecules contain polar domains and a finite macroscopic polarization. However, the fully polarized state is not the equilibrium state. In the first chapter, by solving a model with dipolar and Ising-like short range interactions, we show that polar domains are stable in films composed of aggregates as opposed to isolated molecules. Unlike classical molecular systems, these nanoaggregates have large intralayer spacings (a ≈ 6 nm), leading to a reduction in the repulsive dipolar interactions that oppose polar order within layers. This enables the formation of a striped pattern with polar domains of alternating directions. The energies of the possible structures at zero temperature are computed exactly and results of Monte Carlo simulations are provided at non-zero temperatures. In the second chapter, the macroscopic polarization of such nanostructured films is analyzed in the presence of a short range surface interaction. The surface interaction leads to a periodic domain structure where the balance between the up and down domains is broken, and therefore films of finite thickness have a net macroscopic polarization. The polarization per unit volume is a function of film thickness and strength of the surface interaction. Finally, in chapter three, self-organization of organic molecules into a network of one dimensional objects is analyzed. Multi-block organic dendron rodcoil molecules were found to self-organize into supramolecular nanoribbons (threads) and form gels at very low concentrations. Here, the formation and structural properties of these networks are studied with Monte Carlo simulations. The model gelators can form intra and inter-thread bonds, and the threads have a finite stiffness. The results suggest that the high persistence length is a result of the interplay of thread stiffness and inter-thread interactions. Furthermore, this high persistence length enables the formation of networks at low concentrations.

Programmable assembly of pressure sensors using pattern-forming bacteria.

PubMed

Cao, Yangxiaolu; Feng, Yaying; Ryser, Marc D; Zhu, Kui; Herschlag, Gregory; Cao, Changyong; Marusak, Katherine; Zauscher, Stefan; You, Lingchong

2017-11-01

Biological systems can generate microstructured materials that combine organic and inorganic components and possess diverse physical and chemical properties. However, these natural processes in materials fabrication are not readily programmable. Here, we use a synthetic-biology approach to assemble patterned materials. We demonstrate programmable fabrication of three-dimensional (3D) materials by printing engineered self-patterning bacteria on permeable membranes that serve as a structural scaffold. Application of gold nanoparticles to the colonies creates hybrid organic-inorganic dome structures. The dynamics of the dome structures' response to pressure is determined by their geometry (colony size, dome height, and pattern), which is easily modified by varying the properties of the membrane (e.g., pore size and hydrophobicity). We generate resettable pressure sensors that process signals in response to varying pressure intensity and duration.

Delivering the lateral inhibition punchline: it's all about the timing.

PubMed

Axelrod, Jeffrey D

2010-10-26

Experimental and theoretical biologists have long been fascinated with the emergence of self-organizing patterns in developing organisms, and much attention has focused on Notch-mediated lateral inhibition. Within sheets of cells that may adopt either of two possible cell fates, lateral inhibition establishes patterns through the activity of a negative intercellular feedback loop involving the receptor, Notch, and its ligands Delta or Serrate. Despite a long history of intensive study in Drosophila, where the mechanism was first described, as well as in other organisms, new work continues to yield important insights. Mathematical modeling, combined with biological analyses, has now shed light on two features of the process: how antagonistic and activating ligand-receptor interactions work together to accelerate inhibition and ensure fidelity, and how filopodial dynamics contribute to the observed pattern refinement and spacing.

Servo-integrated patterned media by hybrid directed self-assembly.

PubMed

Xiao, Shuaigang; Yang, Xiaomin; Steiner, Philip; Hsu, Yautzong; Lee, Kim; Wago, Koichi; Kuo, David

2014-11-25

A hybrid directed self-assembly approach is developed to fabricate unprecedented servo-integrated bit-patterned media templates, by combining sphere-forming block copolymers with 5 teradot/in.(2) resolution capability, nanoimprint and optical lithography with overlay control. Nanoimprint generates prepatterns with different dimensions in the data field and servo field, respectively, and optical lithography controls the selective self-assembly process in either field. Two distinct directed self-assembly techniques, low-topography graphoepitaxy and high-topography graphoepitaxy, are elegantly integrated to create bit-patterned templates with flexible embedded servo information. Spinstand magnetic test at 1 teradot/in.(2) shows a low bit error rate of 10(-2.43), indicating fully functioning bit-patterned media and great potential of this approach for fabricating future ultra-high-density magnetic storage media.

Leadership development in a professional medical society using 360-degree survey feedback to assess emotional intelligence.

PubMed

Gregory, Paul J; Robbins, Benjamin; Schwaitzberg, Steven D; Harmon, Larry

2017-09-01

The current research evaluated the potential utility of a 360-degree survey feedback program for measuring leadership quality in potential committee leaders of a professional medical association (PMA). Emotional intelligence as measured by the extent to which self-other agreement existed in the 360-degree survey ratings was explored as a key predictor of leadership quality in the potential leaders. A non-experimental correlational survey design was implemented to assess the variation in leadership quality scores across the sample of potential leaders. A total of 63 of 86 (76%) of those invited to participate did so. All potential leaders received feedback from PMA Leadership, PMA Colleagues, and PMA Staff and were asked to complete self-ratings regarding their behavior. Analyses of variance revealed a consistent pattern of results as Under-Estimators and Accurate Estimators-Favorable were rated significantly higher than Over-Estimators in several leadership behaviors. Emotional intelligence as conceptualized in this study was positively related to overall performance ratings of potential leaders. The ever-increasing roles and potential responsibilities for PMAs suggest that these organizations should consider multisource performance reviews as these potential future PMA executives rise through their organizations to assume leadership positions with profound potential impact on healthcare. The current findings support the notion that potential leaders who demonstrated a humble pattern or an accurate pattern of self-rating scored significantly higher in their leadership, teamwork, and interpersonal/communication skills than those with an aggrandizing self-rating.

The Blue Bottle Experiment--Simple Demonstration of Self-Organization.

ERIC Educational Resources Information Center

Adamcikova, L'ubica; Sevcik, Peter

1998-01-01

Explains a way of observing pattern formation in the Blue Bottle chemistry demonstration by pouring a solution containing sodium hydroxide, glucose, and dye into a Petri dish and placing the dish on an overhead projector. (WRM)

Attractor Metabolic Networks

PubMed Central

De la Fuente, Ildefonso M.; Cortes, Jesus M.; Pelta, David A.; Veguillas, Juan

2013-01-01

Background The experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity. Methodology/Principal Findings In order to research the systemic mechanisms involved in the regulation of the cellular enzymatic activity we have studied different catalytic activities of a dissipative metabolic network under different external stimuli. The emergent biochemical data have been analysed using statistical mechanic tools, studying some macroscopic properties such as the global information and the energy of the system. We have also obtained an equivalent Hopfield network using a Boltzmann machine. Our main result shows that the dissipative metabolic network can behave as an attractor metabolic network. Conclusions/Significance We have found that the systemic enzymatic activities are governed by attractors with capacity to store functional metabolic patterns which can be correctly recovered from specific input stimuli. The network attractors regulate the catalytic patterns, modify the efficiency in the connection between the multienzymatic complexes, and stably retain these modifications. Here for the first time, we have introduced the general concept of attractor metabolic network, in which this dynamic behavior is observed. PMID:23554883

Self-Organizing Fluid Convection Patterns in an en Echelon Fault Array

NASA Astrophysics Data System (ADS)

Patterson, James W.; Driesner, Thomas; Matthai, Stephan K.

2018-05-01

We present three-dimensional numerical simulations of natural convection in buried, vertical en echelon faults in impermeable host rock. Despite the fractures being hydraulically disconnected, convection within each fracture alters the temperature field in the surrounding host rock, altering convection in neighboring fractures. This leads to self-organization of coherent patterns of upward/downward flow and heating/cooling of the host rock spanning the entire fault array. This "synchronization" effect occurs when fracture spacing is less than the width of convection cells within the fractures, which is controlled by fracture transmissivity (permeability times thickness) and heterogeneity. Narrow fracture spacing and synchronization enhance convective fluid flow within fractures and cause convection to initiate earlier, even lowering the critical transmissivity necessary for convection initiation. Heat flow through the en echelon region, however, is enhanced only in low-transmissivity fractures, while heat flow in high-permeability fractures is reduced due to thermal interference between fractures.

Module Based Complexity Formation: Periodic Patterning in Feathers and Hairs

PubMed Central

Chuong, Cheng-Ming; Yeh, Chao-Yuan; Jiang, Ting-Xin; Widelitz, Randall

2012-01-01

Patterns describe order which emerges from homogeneity. Complex patterns on the integument are striking because of their visibility throughout an organism's lifespan. Periodic patterning is an effective design because the ensemble of hair or feather follicles (modules) allows the generation of complexity, including regional variations and cyclic regeneration, giving the skin appendages a new lease on life. Spatial patterns include the arrangements of feathers and hairs in specified number, size, and spacing. We explore how a field of equivalent progenitor cells can generate periodically arranged modules based on genetic information, physical-chemical rules and developmental timing. Reconstitution experiments suggest a competitive equilibrium regulated by activators / inhibitors involving Turing reaction-diffusion. Temporal patterns result from oscillating stem cell activities within each module (micro-environment regulation), reflected as growth (anagen) and resting (telogen) phases during the cycling of feather and hair follicles. Stimulating modules with activators initiates the spread of regenerative hair waves, while global inhibitors outside each module (macro-environment) prevent this. Different wave patterns can be simulated by Cellular Automata principles. Hormonal status and seasonal changes can modulate appendage phenotypes, leading to “organ metamorphosis”, with multiple ectodermal organ phenotypes generated from the same precursors. We discuss potential evolutionary novel steps using this module based complexity in several amniote integument organs, exemplified by the spectacular peacock feather pattern. We thus explore the application of the acquired knowledge of patterning in tissue engineering. New hair follicles can be generated after wounding. Hairs and feathers can be reconstituted through self-organization of dissociated progenitor cells. PMID:23539312

The emergence of extracellular matrix mechanics and cell traction forces as important regulators of cellular self-organization.

PubMed

Checa, Sara; Rausch, Manuel K; Petersen, Ansgar; Kuhl, Ellen; Duda, Georg N

2015-01-01

Physical cues play a fundamental role in a wide range of biological processes, such as embryogenesis, wound healing, tumour invasion and connective tissue morphogenesis. Although it is well known that during these processes, cells continuously interact with the local extracellular matrix (ECM) through cell traction forces, the role of these mechanical interactions on large scale cellular and matrix organization remains largely unknown. In this study, we use a simple theoretical model to investigate cellular and matrix organization as a result of mechanical feedback signals between cells and the surrounding ECM. The model includes bi-directional coupling through cellular traction forces to deform the ECM and through matrix deformation to trigger cellular migration. In addition, we incorporate the mechanical contribution of matrix fibres and their reorganization by the cells. We show that a group of contractile cells will self-polarize at a large scale, even in homogeneous environments. In addition, our simulations mimic the experimentally observed alignment of cells in the direction of maximum stiffness and the building up of tension as a consequence of cell and fibre reorganization. Moreover, we demonstrate that cellular organization is tightly linked to the mechanical feedback loop between cells and matrix. Cells with a preference for stiff environments have a tendency to form chains, while cells with a tendency for soft environments tend to form clusters. The model presented here illustrates the potential of simple physical cues and their impact on cellular self-organization. It can be used in applications where cell-matrix interactions play a key role, such as in the design of tissue engineering scaffolds and to gain a basic understanding of pattern formation in organogenesis or tissue regeneration.

Scalable Directed Self-Assembly Using Ultrasound Waves

DTIC Science & Technology

2015-09-04

SECURITY CLASSIFICATION OF: We aim to understand how ultrasound waves can be used to create organized patterns of nanoparticles in a host medium such...as a polymer matrix material. The critical difference between the ultrasound technology studied in this project, and other directed self-assembly...of nanoparticles dispersed in a host medium are assembled by means of standing ultrasound waves. Additionally, we have obtained experimental

Comparing the Self-Report and Measured Smartphone Usage of College Students: A Pilot Study.

PubMed

Lee, Heyoung; Ahn, Heejune; Nguyen, Trung Giang; Choi, Sam-Wook; Kim, Dae Jin

2017-03-01

Nowadays smartphone overuse has become a social and medical concern. For the diagnosis and treatment, clinicians use the self-report information, but the report data often does not match actual usage pattern. The paper examines the similarity and variance in smartphone usage patterns between the measured data and self-reported data. Together with the self-reported data, the real usage log data is collected from 35 college students in a metropolitan region of Northeast Asia, using Android smartphone monitoring application developed by the authors. The unconscious users underestimate their usage time by 40%, in spite of 15% more use in the actual usage. Messengers are most-used application regardless of their self-report, and significant preference to SNS applications was observed in addict group. The actual hourly pattern is consistent with the reported one. College students use more in the afternoon, when they have more free time and cannot use PCs. No significant difference in hourly pattern is observed between the measured and self-report. The result shows there are significant cognitive bias in actual usage patterns exists in self report of smartphone addictions. Clinicians are recommended to utilize measurement tools in diagnosis and treatment of smartphone overusing subjects.

Self-organized broadband light trapping in thin film amorphous silicon solar cells.

PubMed

Martella, C; Chiappe, D; Delli Veneri, P; Mercaldo, L V; Usatii, I; Buatier de Mongeot, F

2013-06-07

Nanostructured glass substrates endowed with high aspect ratio one-dimensional corrugations are prepared by defocused ion beam erosion through a self-organized gold (Au) stencil mask. The shielding action of the stencil mask is amplified by co-deposition of gold atoms during ion bombardment. The resulting glass nanostructures enable broadband anti-reflection functionality and at the same time ensure a high efficiency for diffuse light scattering (Haze). It is demonstrated that the patterned glass substrates exhibit a better photon harvesting than the flat glass substrate in p-i-n type thin film a-Si:H solar cells.

Discerning Thermodynamic Basis of Self-Organization in Critical Zone Structure and Function

NASA Astrophysics Data System (ADS)

Richardson, M.; Kumar, P.

2017-12-01

Self-organization characterizes the spontaneous emergence of order. Self-organization in the Critical Zone, the region of Earth's skin from below the groundwater table to the top of the vegetation canopy, involves the interaction of biotic and abiotic processes occurring through a hierarchy of temporal and spatial scales. The self-organization is sustained through input of energy and material in an open system framework, and the resulting formations are called dissipative structures. Why do these local states of organization form and how are they thermodynamically favorable? We hypothesize that structure formation is linked to energy conversion and matter throughput rates across driving gradients. Furthermore, we predict that structures in the Critical Zone evolve based on local availability of nutrients, water, and energy. By considering ecosystems as open thermodynamic systems, we model and study the throughput signatures on short times scales to determine origins and characteristics of ecosystem structure. This diagnostic approach allows us to use fluxes of matter and energy to understand the thermodynamic drivers of the system. By classifying the fluxes and dynamics in a system, we can identify patterns to determine the thermodynamic drivers for organized states. Additionally, studying the partitioning of nutrients, water, and energy throughout ecosystems through dissipative structures will help identify reasons for structure shapes and how these shapes impact major Critical Zone functions.

Hydrograph Shape Controls Channel Morphology and Organization in a Sand-Gravel Flume

NASA Astrophysics Data System (ADS)

Hempel, L. A.; Grant, G.; Hassan, M. A.; Eaton, B. C.

2016-12-01

A fundamental research question in fluvial geomorphology is to understand what flows shape river channels. Historically, the prevailing view has been that channel dimensions adjust to a so-termed "dominant discharge", which is often approximated as the bankfull flow. But using a single flow to reference the geomorphic effectiveness of an entire flow regime discounts many observations showing that different flows control different channel processes. Some flows entrain fine sediment, some entrain the full size distribution of bed sediment; some destabilize or build bars, some erode the banks, and so forth. To explore the relation between the full flow regime and channel morphology, we conducted a series of flume experiments to examine how hydrographs with different shapes, durations, and magnitudes result in different degrees of channel organization, which we define in terms of the regularity, spacing and architecture of self-formed channel features, such as bed patches, geometry and spacing of bedforms, and channel planform. Our experiments were run in a 12m long adjustable-width flume that developed a self-formed meandering, pool-riffle pattern. We found that hydrograph shape does control channel organization. In particular, channels formed by hydrographs with slower rising limbs and broader peaks were more organized than those formed by flashier hydrographs. To become organized, hydrographs needed to exceed a minimum flow threshold, defined by the intensity of sediment transport; below which the channel lacked bedforms and a regular meander pattern. Above an upper flow threshold, bars became disorganized and the channel planform transitioned towards braiding. Field studies of channels with different flow regimes but located in a similar physiographic setting support our experimental findings. Taken together, this work points to the importance of the hydrograph as a fundamental control on channel morphology, and offers the prospect of better understanding how changing hydrologic regimes, either through climate, land use, or dams, translates into geomorphic changes.

Self-Theories: Their Role in Motivation, Personality, and Development. Essays in Social Psychology.

ERIC Educational Resources Information Center

Dweck, Carol S.

Based on extensive research with children and young adults, this book examines adaptive and maladaptive cognitive-motivational patterns and shows how these patterns originate in people's self theories; their consequences for one's achievement, social relationships, and emotional well-being; their consequences for society; and the experiences that…

Optical Pattern Formation in Cold Atoms: Explaining the Red-Blue Asymmetry

NASA Astrophysics Data System (ADS)

Schmittberger, Bonnie; Gauthier, Daniel

2013-05-01

The study of pattern formation in atomic systems has provided new insight into fundamental many-body physics and low-light-level nonlinear optics. Pattern formation in cold atoms in particular is of great interest in condensed matter physics and quantum information science because atoms undergo self-organization at ultralow input powers. We recently reported the first observation of pattern formation in cold atoms but found that our results were not accurately described by any existing theoretical model of pattern formation. Previous models describing pattern formation in cold atoms predict that pattern formation should occur using both red and blue-detuned pump beams, favoring a lower threshold for blue detunings. This disagrees with our recent work, in which we only observed pattern formation with red-detuned pump beams. Previous models also assume a two-level atom, which cannot account for the cooling processes that arise when beams counterpropagate through a cold atomic vapor. We describe a new model for pattern formation that accounts for Sisyphus cooling in multi-level atoms, which gives rise to a new nonlinearity via spatial organization of the atoms. This spatial organization causes a sharp red-blue detuning asymmetry, which agrees well with our experimental observations. We gratefully acknowledge the financial support of the NSF through Grant #PHY-1206040.

Self-Esteem, Need for Approval, and Reactions to Personal Evaluations

ERIC Educational Resources Information Center

Hewitt, Jay; Goldman, Morton

1974-01-01

The major premise of the current study is that subjects with high self-esteem scores plus high Marlowe-Crowne scores should show behavior patterns similar to those of low self-esteem subjects. (Author)

Rapid Prototyping of Patterned Multifunctional Nanostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

FAN,HONGYOU; LU,YUNFENG; LOPEZ,GABRIEL P.

2000-07-18

The ability to engineer ordered arrays of objects on multiple length scales has potential for applications such as microelectronics, sensors, wave guides, and photonic lattices with tunable band gaps. Since the invention of surfactant templated mesoporous sieves in 1992, great progress has been made in controlling different mesophases in the form of powders, particles, fibers, and films. To date, although there have been several reports of patterned mesostructures, materials prepared have been limited to metal oxides with no specific functionality. For many of the envisioned applications of hierarchical materials in micro-systems, sensors, waveguides, photonics, and electronics, it is necessary tomore » define both form and function on several length scales. In addition, the patterning strategies utilized so far require hours or even days for completion. Such slow processes are inherently difficult to implement in commercial environments. The authors present a series of new methods of producing patterns within seconds. Combining sol-gel chemistry, Evaporation-Induced Self-Assembly (EISA), and rapid prototyping techniques like pen lithography, ink-jet printing, and dip-coating on micro-contact printed substrates, they form hierarchically organized silica structures that exhibit order and function on multiple scales: on the molecular scale, functional organic moieties are positioned on pore surfaces, on the mesoscale, mono-sized pores are organized into 1-, 2-, or 3-dimensional networks, providing size-selective accessibility from the gas or liquid phase, and on the macroscale, 2-dimensional arrays and fluidic or photonic systems may be defined. These rapid patterning techniques establish for the first time a link between computer-aided design and rapid processing of self-assembled nanostructures.« less

What if Reading is Easy but Unimportant? How Students’ Patterns of Affirming and Undermining Motivation for Reading Information Texts Predict Different Reading Outcomes

PubMed Central

Rosenzweig, Emily Q.; Wigfield, Allan

2016-01-01

Many affirming and undermining motivational constructs affect students as they read information texts, but few researchers have explored how these motivations are patterned within students. In this study we used cluster analysis to classify middle school students (n = 1,134) based on their patterns of self-efficacy, perceived difficulty, value, and devalue for reading school information texts. We then compared how the patterns predicted students’ language arts grades, science information text comprehension, and dedication to reading school information texts. We found and validated a four-cluster solution. One cluster included a pattern of high affirming and low undermining motivations, and another included low affirming and high undermining motivations. Students with these patterns earned the highest and lowest scores, respectively, on all outcomes. A third pattern showed high self-efficacy/low difficulty with low value/high devalue, and a fourth showed moderate levels of all four motivational constructs. Students with the high efficacy and devalue pattern showed high information text comprehension but relatively low dedication. Students with the moderate pattern showed high dedication but low initial information text comprehension. Students with these two patterns earned similar grades. We discuss the implications of our findings for motivation theories and for school instruction that involves information text reading. PMID:28496289

What if Reading is Easy but Unimportant? How Students' Patterns of Affirming and Undermining Motivation for Reading Information Texts Predict Different Reading Outcomes.

PubMed

Rosenzweig, Emily Q; Wigfield, Allan

2017-01-01

Many affirming and undermining motivational constructs affect students as they read information texts, but few researchers have explored how these motivations are patterned within students. In this study we used cluster analysis to classify middle school students (n = 1,134) based on their patterns of self-efficacy, perceived difficulty, value, and devalue for reading school information texts. We then compared how the patterns predicted students' language arts grades, science information text comprehension, and dedication to reading school information texts. We found and validated a four-cluster solution. One cluster included a pattern of high affirming and low undermining motivations, and another included low affirming and high undermining motivations. Students with these patterns earned the highest and lowest scores, respectively, on all outcomes. A third pattern showed high self-efficacy/low difficulty with low value/high devalue, and a fourth showed moderate levels of all four motivational constructs. Students with the high efficacy and devalue pattern showed high information text comprehension but relatively low dedication. Students with the moderate pattern showed high dedication but low initial information text comprehension. Students with these two patterns earned similar grades. We discuss the implications of our findings for motivation theories and for school instruction that involves information text reading.

Preparation and characterization of injectable Mitoxantrone poly (lactic acid)/fullerene implants for in vivo chemo-photodynamic therapy.

PubMed

Li, Zhi; Zhang, Fei-long; Pan, Li-li; Zhu, Xia-li; Zhang, Zhen-zhong

2015-08-01

Fullerene (C60) L-phenylalanine derivative attached with poly (lactic acid) (C60-phe-PLA) was developed to prepare injectable Mitoxantrone (MTX) multifunctional implants. C60-phe-PLA was self-assembled to form microspheres consisting of a hydrophilic antitumor drug (MTX) and a hydrophobic block (C60) by dispersion-solvent diffusion method. The self-assembled microspheres showed sustained release pattern almost 15days in vitro release experiments. According to the tissue distribution of C57BL mice after intratumoral administration of the microspheres, the MTX mainly distributed in tumors, and rarely in heart, liver, spleen, lung, and kidney. Photodynamic antitumor efficacy of blank microsphere was realized. Microspheres afforded high antitumor efficacy without obvious toxic effects to normal organs, owing to its significantly increased MTX tumor retention time, low MTX levels in normal organs and strong photodynamic activity of PLA-phe-C60. These C60-phe-PLA microspheres may be promising for the efficacy with minimal side effects in future treatment of solid tumors. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatiotemporal classification of environmental monitoring data in the Yeongsan River basin, Korea, using self-organizing maps.

PubMed

Jin, Y-H; Kawamura, A; Park, S-C; Nakagawa, N; Amaguchi, H; Olsson, J

2011-10-01

Environmental monitoring data for planning, implementing and evaluating the Total Maximum Daily Loads (TMDL) management system have been measured at about 8-day intervals in a number of rivers in Korea since 2004. In the present study, water quality parameters such as Suspended Solids (SS), Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Total Nitrogen (TN), and Total Phosphorus (TP) and the corresponding runoff were collected from six stations in the Yeongsan River basin for six years and transformed into monthly mean values. With the primary objective to understand spatiotemporal characteristics of the data, a methodologically systematic application of a Self-Organizing Map (SOM) was made. The SOM application classified the environmental monitoring data into nine clusters showing exclusively distinguishable patterns. Data frequency at each station on a monthly basis identified the spatiotemporal distribution for the first time in the study area. Consequently, the SOM application provided useful information that the sub-basin containing a metropolitan city is associated with deteriorating water quality and should be monitored and managed carefully during spring and summer for water quality improvement in the river basin.

Self-organization in precipitation reactions far from the equilibrium

PubMed Central

Nakouzi, Elias; Steinbock, Oliver

2016-01-01

Far from the thermodynamic equilibrium, many precipitation reactions create complex product structures with fascinating features caused by their unusual origins. Unlike the dissipative patterns in other self-organizing reactions, these features can be permanent, suggesting potential applications in materials science and engineering. We review four distinct classes of precipitation reactions, describe similarities and differences, and discuss related challenges for theoretical studies. These classes are hollow micro- and macrotubes in chemical gardens, polycrystalline silica carbonate aggregates (biomorphs), Liesegang bands, and propagating precipitation-dissolution fronts. In many cases, these systems show intricate structural hierarchies that span from the nanometer scale into the macroscopic world. We summarize recent experimental progress that often involves growth under tightly regulated conditions by means of wet stamping, holographic heating, and controlled electric, magnetic, or pH perturbations. In this research field, progress requires mechanistic insights that cannot be derived from experiments alone. We discuss how mesoscopic aspects of the product structures can be modeled by reaction-transport equations and suggest important targets for future studies that should also include materials features at the nanoscale. PMID:27551688

Lava Lake Thermal Pattern Classification Using Self-Organizing Maps and Relationships to Eruption Processes at Kīlauea Volcano, Hawaii

NASA Astrophysics Data System (ADS)

Burzynski, A. M.; Anderson, S. W.; Morrison, K.; LeWinter, A. L.; Patrick, M. R.; Orr, T. R.; Finnegan, D. C.

2014-12-01

Nested within the Halema'uma'u Crater on the summit of Kīlauea Volcano, the active lava lake of Overlook Crater poses hazards to local residents and Hawaii Volcanoes National Park visitors. Since its formation in March 2008, the lava lake has enlarged to +28,500 m2 and has been closely monitored by researchers at the USGS Hawaiian Volcano Observatory (HVO). Time-lapse images, collected via visible and thermal infrared cameras, reveal thin crustal plates, separated by incandescent cracks, moving across the lake surface as lava circulates beneath. We hypothesize that changes in size, shape, velocity, and patterns of these crustal plates are related to other eruption processes at the volcano. Here we present a methodology to identify characteristic lava lake surface patterns from thermal infrared video footage using a self-organizing maps (SOM) algorithm. The SOM is an artificial neural network that performs unsupervised clustering and enables us to visualize the relationships between groups of input patterns on a 2-dimensional grid. In a preliminary trial, we input ~4 hours of thermal infrared time-lapse imagery collected on December 16-17, 2013 during a transient deflation-inflation deformation event at a rate of one frame every 10 seconds. During that same time period, we also acquired a series of one-second terrestrial laser scans (TLS) every 30 seconds to provide detailed topography of the lava lake surface. We identified clusters of characteristic thermal patterns using a self-organizing maps algorithm within the Matlab SOM Toolbox. Initial results from two SOMs, one large map (81 nodes) and one small map (9 nodes), indicate 4-6 distinct groups of thermal patterns. We compare these surface patterns with lava lake surface slope and crustal plate velocities derived from concurrent TLS surveys and with time series of other eruption variables, including outgassing rates and inflation-deflation events. This methodology may be applied to the continuous stream of thermal video footage at Kīlauea to expand the breadth of eruption information we are able to obtain from a remote thermal infrared camera and may potentially allow for the recognition of lava lake patterns as a proxy for other eruption parameters.

Stronger Intermolecular Forces or Closer Molecular Spacing? Key Impact Factor Research of Gelator Self-Assembly Mechanism.

PubMed

Chen, Si; An, Zhihang; Tong, Xiaoqian; Chen, Yining; Ma, Meng; Shi, Yanqin; Wang, Xu

2017-12-19

The benzene ring of low-molecular-weight gelators provides strong intermolecular forces but increases molecular spacing during self-assembly. To explore both of the above influences on the gel properties, we synthesize two gelators (Glu-CBZ and Glu-DPA) consisting of the same terminal long side chain but different aliphatic functional groups. The aliphatic functional groups are carbobenzoxy group and diphenyl phosphate group. The self-assembly driving forces, self-organization patterns, network morphologies, rheological properties, and the influences of solvents are researched through 1 H NMR spectra, Fourier transform infrared spectra, field-emission scanning electron microscopy images, rheological characterizations curves, tube-inversion experiment, and calculation of van't Hoff plots. The results show that the carbobenzoxy group of Glu-CBZ makes molecules pack more tightly such that it improves the gel properties during static equilibrium. Whereas the diphenyl phosphate group of Glu-DPA provides stronger intermolecular forces, performing outstandingly during dynamic equilibrium. It is advantageous to further investigate the competitive relationship in gel system between the increased number of functional groups and the consequent steric effect.

Self-organization in irregular landscapes: Detecting autogenic interactions from field data using descriptive statistics and dynamical systems theory

NASA Astrophysics Data System (ADS)

Larsen, L.; Watts, D.; Khurana, A.; Anderson, J. L.; Xu, C.; Merritts, D. J.

2015-12-01

The classic signal of self-organization in nature is pattern formation. However, the interactions and feedbacks that organize depositional landscapes do not always result in regular or fractal patterns. How might we detect their existence and effects in these "irregular" landscapes? Emergent landscapes such as newly forming deltaic marshes or some restoration sites provide opportunities to study the autogenic processes that organize landscapes and their physical signatures. Here we describe a quest to understand autogenic vs. allogenic controls on landscape evolution in Big Spring Run, PA, a landscape undergoing restoration from bare-soil conditions to a target wet meadow landscape. The contemporary motivation for asking questions about autogenic vs. allogenic controls is to evaluate how important initial conditions or environmental controls may be for the attainment of management objectives. However, these questions can also inform interpretation of the sedimentary record by enabling researchers to separate signals that may have arisen through self-organization processes from those resulting from environmental perturbations. Over three years at Big Spring Run, we mapped the dynamic evolution of floodplain vegetation communities and distributions of abiotic variables and topography. We used principal component analysis and transition probability analysis to detect associative interactions between vegetation and geomorphic variables and convergent cross-mapping on lidar data to detect causal interactions between biomass and topography. Exploratory statistics revealed that plant communities with distinct morphologies exerted control on landscape evolution through stress divergence (i.e., channel initiation) and promoting the accumulation of fine sediment in channels. Together, these communities participated in a negative feedback that maintains low energy and multiple channels. Because of the spatially explicit nature of this feedback, causal interactions could not be uncovered from convergent cross-mapping with this limited dataset, serving as a reminder that spatially explicit approaches for revealing causality are needed to reconstruct self-organizing mechanisms from data.

A bifractal nature of reticular patterns induced by oxygen plasma on polymer films

NASA Astrophysics Data System (ADS)

Bae, Junwan; Lee, I. J.

2015-05-01

Plasma etching was demonstrated to be a promising tool for generating self-organized nano-patterns on various commercial films. Unfortunately, dynamic scaling approach toward fundamental understanding of the formation and growth of the plasma-induced nano-structure has not always been straightforward. The temporal evolution of self-aligned nano-patterns may often evolve with an additional scale-invariance, which leads to breakdown of the well-established dynamic scaling law. The concept of a bifractal interface is successfully applied to reticular patterns induced by oxygen plasma on the surface of polymer films. The reticular pattern, composed of nano-size self-aligned protuberances and underlying structure, develops two types of anomalous dynamic scaling characterized by super-roughening and intrinsic anomalous scaling, respectively. The diffusion and aggregation of short-cleaved chains under the plasma environment are responsible for the regular distribution of the nano-size protuberances. Remarkably, it is uncovered that the dynamic roughening of the underlying structure is governed by a relaxation mechanism described by the Edwards-Wilkinson universality class with a conservative noise. The evidence for the basic phase, characterized by the negative roughness and growth exponents, has been elusive since its first theoretical consideration more than two decades ago.

Cytoskeletal self-organization in neuromorphogenesis.

PubMed

Dehmelt, Leif

2014-01-01

Self-organization of dynamic microtubules via interactions with associated motors plays a critical role in spindle formation. The microtubule-based mechanisms underlying other aspects of cellular morphogenesis, such as the formation and development of protrusions from neuronal cells is less well understood. In a recent study, we investigated the molecular mechanism that underlies the massive reorganization of microtubules induced in non-neuronal cells by expression of the neuronal microtubule stabilizer MAP2c. In that study we directly observed cortical dynein complexes and how they affect the dynamic behavior of motile microtubules in living cells. We found that stationary dynein complexes transiently associate with motile microtubules near the cell cortex and that their rapid turnover facilitates efficient microtubule transport. Here, we discuss our findings in the larger context of cellular morphogenesis with specific focus on self-organizing principles from which cellular shape patterns such as the thin protrusions of neurons can emerge.

Cytoskeletal self-organization in neuromorphogenesis

PubMed Central

Dehmelt, Leif

2014-01-01

Self-organization of dynamic microtubules via interactions with associated motors plays a critical role in spindle formation. The microtubule-based mechanisms underlying other aspects of cellular morphogenesis, such as the formation and development of protrusions from neuronal cells is less well understood. In a recent study, we investigated the molecular mechanism that underlies the massive reorganization of microtubules induced in non-neuronal cells by expression of the neuronal microtubule stabilizer MAP2c. In that study we directly observed cortical dynein complexes and how they affect the dynamic behavior of motile microtubules in living cells. We found that stationary dynein complexes transiently associate with motile microtubules near the cell cortex and that their rapid turnover facilitates efficient microtubule transport. Here, we discuss our findings in the larger context of cellular morphogenesis with specific focus on self-organizing principles from which cellular shape patterns such as the thin protrusions of neurons can emerge. PMID:24847718

Self-Organized Lattices of Nonlinear Optochemical Waves in Photopolymerizable Fluids: The Spontaneous Emergence of 3-D Order in a Weakly Correlated System.

PubMed

Ponte, Matthew R; Hudson, Alexander D; Saravanamuttu, Kalaichelvi

2018-03-01

Many of the extraordinary three-dimensional architectures that pattern our physical world emerge from complex nonlinear systems or dynamic populations whose individual constituents are only weakly correlated to each other. Shoals of fish, murmuration behaviors in birds, congestion patterns in traffic, and even networks of social conventions are examples of spontaneous pattern formation, which cannot be predicted from the properties of individual elements alone. Pattern formation at a different scale has been observed or predicted in weakly correlated systems including superconductors, atomic gases near Bose Einstein condensation, and incoherent optical fields. Understanding pattern formation in nonlinear weakly correlated systems, which are often unified through mathematical expression, could pave intelligent self-organizing pathways to functional materials, architectures, and computing technologies. However, it is experimentally difficult to directly visualize the nonlinear dynamics of pattern formation in most populations-especially in three dimensions. Here, we describe the collective behavior of large populations of nonlinear optochemical waves, which are poorly correlated in both space and time. The optochemical waves-microscopic filaments of white light entrapped within polymer channels-originate from the modulation instability of incandescent light traveling in photopolymerizable fluids. By tracing the three-dimensional distribution of optical intensity in the nascent polymerizing system, we find that populations of randomly distributed, optochemical waves synergistically and collectively shift in space to form highly ordered lattices of specific symmetries. These, to our knowledge, are the first three-dimensionally periodic structures to emerge from a system of weakly correlated waves. Their spontaneous formation in an incoherent and effectively chaotic field is counterintuitive, but the apparent contradiction of known behaviors of light including the laws of optical interference can be explained through the soliton-like interactions of optochemical waves with nearest neighbors. Critically, this work casts fundamentally new insight into the collective behaviors of poorly correlated nonlinear waves in higher dimensions and provides a rare, accessible platform for further experimental studies of these previously unexplored behaviors. Furthermore, it defines a self-organization paradigm that, unlike conventional counterparts, could generate polymer microstructures with symmetries spanning all the Bravais lattices.

Wafer-scale Thermodynamically Stable GaN Nanorods via Two-Step Self-Limiting Epitaxy for Optoelectronic Applications

NASA Astrophysics Data System (ADS)

Kum, Hyun; Seong, Han-Kyu; Lim, Wantae; Chun, Daemyung; Kim, Young-Il; Park, Youngsoo; Yoo, Geonwook

2017-01-01

We present a method of epitaxially growing thermodynamically stable gallium nitride (GaN) nanorods via metal-organic chemical vapor deposition (MOCVD) by invoking a two-step self-limited growth (TSSLG) mechanism. This allows for growth of nanorods with excellent geometrical uniformity with no visible extended defects over a 100 mm sapphire (Al2O3) wafer. An ex-situ study of the growth morphology as a function of growth time for the two self-limiting steps elucidate the growth dynamics, which show that formation of an Ehrlich-Schwoebel barrier and preferential growth in the c-plane direction governs the growth process. This process allows monolithic formation of dimensionally uniform nanowires on templates with varying filling matrix patterns for a variety of novel electronic and optoelectronic applications. A color tunable phosphor-free white light LED with a coaxial architecture is fabricated as a demonstration of the applicability of these nanorods grown by TSSLG.

Self-assembly of a triangle-shaped, hexaplatinum-incorporated, supramolecular amphiphile in solution and at interfaces.

PubMed

Maran, Umamageswaran; Britt, David; Fox, Christopher B; Harris, Joel M; Orendt, Anita M; Conley, Hiram; Davis, Robert; Hlady, Vladamir; Stang, Peter J

2009-08-24

The self-assembly and characterization of a novel supramolecular amphiphile built from a new 60 degree amphiphilic precursor that incorporates hydrophilic platinum(II) metals and hydrophobic dioctadecyloxy chains is reported. The amphiphilic macrocycle and its precursor compound have been characterized by multinuclear NMR spectroscopy, ESI-MS, and other standard techniques. The coacervate morphology of the amphiphile at the liquid-liquid interface has been studied by using confocal optical microscopy and in situ Raman spectroscopy. The self-assembly of the amphiphilic macrocycle at the air-water interface has been investigated through Langmuir-trough techniques. The study indicates the possible formation of surface micelle-like aggregates. The disparity between the experimental molecular areas and those derived from molecular models support the idea of aggregation. AFM images of the surface aggregates show the formation of a flat topology with arbitrary ridgelike patterns. Reasonable molecular-packing arrangements are proposed to explain the molecular organization within the observed structures.

Confinement of surface state electrons in self-organized Co islands on Au(111)

NASA Astrophysics Data System (ADS)

Schouteden, Koen; Lijnen, Erwin; Janssens, Ewald; Ceulemans, Arnout; Chibotaru, Liviu F.; Lievens, Peter; Van Haesendonck, Chris

2008-04-01

We report on detailed low temperature scanning tunneling spectroscopy measurements performed on nanoscale Co islands on Au(111) films. At low coverages, Co islands self-organize in arrays of mono- and bilayer nanoscale structures that often have an hexagonal shape. The process of self-organization is induced by the Au(111) 'herringbone' reconstruction. By means of mapping of the local density of states with lock-in detection, electron standing wave patterns are resolved on top of the atomically flat Co islands. The surface state electrons are observed to be strongly confined laterally inside the Co nanosized islands, with their wavefunctions reflecting the symmetry of the islands. To complement the experimental work, particle-in-a-box calculations were performed. The calculations are based on a newly developed variational method that can be applied to '2D boxes' of arbitrary polygonal shape. The experimental patterns are found to fit nicely to the calculated wavefunctions for a box having a symmetry corresponding to the experimental island symmetry. The small size of the Co islands under study (down to 7.7 nm2) is observed to induce a strong discretization of the energy levels, with very large energy separations between the eigenstates up to several 100 meV. The observed standing wave patterns are identified either as individual eigenstates or as a 'mixture' of two or more energetically close-lying eigenstates of the cobalt island. Additionally, the Co surface state appears not to be limited to mono- and bilayer islands, but this state remains observable for multilayered islands up to five monolayers of Co.

Critical Point in Self-Organized Tissue Growth

NASA Astrophysics Data System (ADS)

Aguilar-Hidalgo, Daniel; Werner, Steffen; Wartlick, Ortrud; González-Gaitán, Marcos; Friedrich, Benjamin M.; Jülicher, Frank

2018-05-01

We present a theory of pattern formation in growing domains inspired by biological examples of tissue development. Gradients of signaling molecules regulate growth, while growth changes these graded chemical patterns by dilution and advection. We identify a critical point of this feedback dynamics, which is characterized by spatially homogeneous growth and proportional scaling of patterns with tissue length. We apply this theory to the biological model system of the developing wing of the fruit fly Drosophila melanogaster and quantitatively identify signatures of the critical point.

A connectionist model of category learning by individuals with high-functioning autism spectrum disorder.

PubMed

Dovgopoly, Alexander; Mercado, Eduardo

2013-06-01

Individuals with autism spectrum disorder (ASD) show atypical patterns of learning and generalization. We explored the possible impacts of autism-related neural abnormalities on perceptual category learning using a neural network model of visual cortical processing. When applied to experiments in which children or adults were trained to classify complex two-dimensional images, the model can account for atypical patterns of perceptual generalization. This is only possible, however, when individual differences in learning are taken into account. In particular, analyses performed with a self-organizing map suggested that individuals with high-functioning ASD show two distinct generalization patterns: one that is comparable to typical patterns, and a second in which there is almost no generalization. The model leads to novel predictions about how individuals will generalize when trained with simplified input sets and can explain why some researchers have failed to detect learning or generalization deficits in prior studies of category learning by individuals with autism. On the basis of these simulations, we propose that deficits in basic neural plasticity mechanisms may be sufficient to account for the atypical patterns of perceptual category learning and generalization associated with autism, but they do not account for why only a subset of individuals with autism would show such deficits. If variations in performance across subgroups reflect heterogeneous neural abnormalities, then future behavioral and neuroimaging studies of individuals with ASD will need to account for such disparities.

Hierarchical self-assembly of a bow-shaped molecule bearing self-complementary hydrogen bonding sites into extended supramolecular assemblies.

PubMed

Ikeda, Masato; Nobori, Tadahito; Schmutz, Marc; Lehn, Jean-Marie

2005-01-07

The bow-shaped molecule 1 bearing a self-complementary DAAD-ADDA (D=donor A=acceptor) hydrogen-bonding array generates, in hydrocarbon solvents, highly ordered supramolecular sheet aggregates that subsequently give rise to gels by formation of an entangled network. The process of hierarchical self-assembly of compound 1 was investigated by the concentration and temperature dependence of UV-visible and (1)H NMR spectra, fluorescence spectra, and electron microscopy data. The temperature dependence of the UV-visible spectra indicates a highly cooperative process for the self-assembly of compound 1 in decaline. The electron micrograph of the decaline solution of compound 1 (1.0 mM) revealed supramolecular sheet aggregates forming an entangled network. The selected area electronic diffraction patterns of the supramolecular sheet aggregates were typical for single crystals, indicative of a highly ordered assembly. The results exemplify the generation, by hierarchical self-assembly, of highly organized supramolecular materials presenting novel collective properties at each level of organization.

Annealing a magnetic cactus into phyllotaxis

NASA Astrophysics Data System (ADS)

Nisoli, Cristiano; Gabor, Nathaniel M.; Lammert, Paul E.; Maynard, J. D.; Crespi, Vincent H.

2010-04-01

The appearance of mathematical regularities in the disposition of leaves on a stem, scales on a pine-cone, and spines on a cactus has puzzled scholars for millennia; similar so-called phyllotactic patterns are seen in self-organized growth, polypeptides, convection, magnetic flux lattices and ion beams. Levitov showed that a cylindrical lattice of repulsive particles can reproduce phyllotaxis under the (unproved) assumption that minimum of energy would be achieved by two-dimensional Bravais lattices. Here we provide experimental and numerical evidence that the Phyllotactic lattice is actually a ground state. When mechanically annealed, our experimental “magnetic cactus” precisely reproduces botanical phyllotaxis, along with domain boundaries (called transitions in Botany) between different phyllotactic patterns. We employ a structural genetic algorithm to explore the more general axially unconstrained case, which reveals multijugate (multiple spirals) as well as monojugate (single-spiral) phyllotaxis.

Self-organized multi-species vegetation patterns: the role of connectivity of environmental niches in natural water harvesting ecosystems

NASA Astrophysics Data System (ADS)

Callegaro, Chiara; Ursino, Nadia

2016-04-01

Self-organizing vegetation patterns are natural water harvesting systems in arid and semi-arid regions of the world and should be imitated when designing man-managed water-harvesting systems for rain-fed crop. Disconnected vegetated and bare zones, functioning as a source-sink system of resources, sustain vegetation growth and reduce water and soil losses. Mechanisms such as soil crusting over bare areas and soil loosening in vegetated areas feed back to the local net facilitation effect and contribute to maintain the patterned landscape structure. Dis-connectivity of run-off production and run-on infiltration sites reduces runoff production at the landscape scale, and increases water retention in the vegetated patches. What is the effect of species adaptation to different resource niches on the landscape structure? A minimal model for two coexisting species and soil moisture balance was formulated, to improve our understanding of the effects of species differentiation on the dynamics of plants and water at single-pattern and landscape scale within a tiger bush type ecosystem. A basic assumption of our model was that soil moisture availability is a proxy for the environmental niche of plant species. Connectivity and dis-connectivity of specific niches of adaptation of two differing plant species was an input parameter of our model, in order to test the effect of coexistence on the ecosystem structure. The ecosystem structure is the model outcome, including: patterns persistence of coexisting species; patterns persistence of one species with exclusion of the other; patterns decline with just one species surviving in a non organized structure; bare landscape with loss of both species. Results suggest that pattern-forming-species communities arise as a result of complementary niche adaptation (niche dis-connecivity), whereas niche superposition (niche connectivity) may lead to impoverishment of environmental resources and loss of vegetation cover and diversity.

Self-Perception in Late Adolescence: An Interactive Perspective.

ERIC Educational Resources Information Center

Klein, Helen Altman

1995-01-01

Examined self-perception during late adolescence as a correlate of individual temperament. Found that positive self-perception correlated with approaching, flexible, and positive mood patterns, and with high task orientation. Different aspects of self-perception showed distinct relationships with specific temperament dimensions. Noted men's and…

Effects of Short-Term Set-Aside Management Practices on Soil Microorganism and Enzyme Activity in China

PubMed Central

Wu, Cifang

2017-01-01

Set-aside farmland can effectively improve the self-rehabilitation of arable soil. Long-term set-asides however cannot satisfy provisionment, therefore the use of short-term set-asides to restore cultivated soil is a better option. Few studies have compared short-term set-aside patterns, and the effects of set-asides on soil microbial community and enzyme enzymes. We analyzed the bacterial structure, microbial biomass carbon/nitrogen and enzyme activity of farmland soil under different set-aside regimes in the Yellow River Delta of China. Bacterial alpha diversity was relatively lower under only irrigation, and farmyard manure applications showed clear advantages. Set-asides should consider their influence on soil organic carbon and nitrogen, which were correlated with microbial community structure. Nitrospira (0.47–1.67%), Acidobacteria Gp6 (8.26–15.91%) and unclassified Burkholderiales (1.50–2.81%) were significantly altered (p < 0.01). Based on functions of these genera, some set-aside patterns led to a relative balance in nitrogen and carbon turnover. Partial treatments showed a deficiency in organic matter. In addition, farmyard manure may lead to the increased consumption of organic matter, with the exception of native plants set-asides. Conventional farming (control group) displayed a significant enzyme activity advantage. Set-aside management practices guided soil microbial communities to different states. Integrated soil microbiota and the content of carbon and nitrogen, native plants with farmyard manure showed an equilibrium state relatively, which would be helpful to improve land quality in the short-term. PMID:28805737

Fractal growth mechanism of sp3-bonded 5H-BN microcones by plasma-assisted pulsed-laser chemical vapor deposition

NASA Astrophysics Data System (ADS)

Komatsu, Shojiro; Kazami, Daisuke; Tanaka, Hironori; Moriyoshi, Yusuke; Shiratani, Masaharu; Okada, Katsuyuki

2006-08-01

Here we propose a repetitive photochemical reaction and diffusion model for the fractal pattern formation of sp3-bonded 5H-BN microcones in laser-assisted plasma chemical vapor deposition, which was observed experimentally and reported previously. This model describing the behavior of the surface density of precursor species gave explanations to (1) the "line-drawing" nature of the patterns, (2) the origin of the scale-invariant self-similarity (fractality) of the pattern, and (3) the temperature-dependent uniform to fractal transition. The results have implications for controlling the self-organized arrangements of electron-emitter cones at the micro-and nanoscale by adjusting macroscopically the boundary condition (LX,LY) for the deposition, which will be very effective in improving the electron field emission properties.

Integument pattern formation involves genetic and epigenetic controls: feather arrays simulated by digital hormone models

PubMed Central

Jiang, Ting-Xin; Widelitz, Randall B.; Shen, Wei-Min; Will, Peter; Wu, Da-Yu; Lin, Chih-Min; Jung, Han-Sung; Chuong, Cheng-Ming

2015-01-01

Pattern formation is a fundamental morphogenetic process. Models based on genetic and epigenetic control have been proposed but remain controversial. Here we use feather morphogenesis for further evaluation. Adhesion molecules and/or signaling molecules were first expressed homogenously in feather tracts (restrictive mode, appear earlier) or directly in bud or inter-bud regions (de novo mode, appear later). They either activate or inhibit bud formation, but paradoxically co-localize in the bud. Using feather bud reconstitution, we showed that completely dissociated cells can reform periodic patterns without reference to previous positional codes. The patterning process has the characteristics of being self-organizing, dynamic and plastic. The final pattern is an equilibrium state reached by competition, and the number and size of buds can be altered based on cell number and activator/inhibitor ratio, respectively. We developed a Digital Hormone Model which consists of (1) competent cells without identity that move randomly in a space, (2) extracellular signaling hormones which diffuse by a reaction-diffusion mechanism and activate or inhibit cell adhesion, and (3) cells which respond with topological stochastic actions manifested as changes in cell adhesion. Based on probability, the results are cell clusters arranged in dots or stripes. Thus genetic control provides combinational molecular information which defines the properties of the cells but not the final pattern. Epigenetic control governs interactions among cells and their environment based on physical-chemical rules (such as those described in the Digital Hormone Model). Complex integument patterning is the sum of these two components of control and that is why integument patterns are usually similar but non-identical. These principles may be shared by other pattern formation processes such as barb ridge formation, fingerprints, pigmentation patterning, etc. The Digital Hormone Model can also be applied to swarming robot navigation, reaching intelligent automata and representing a self-re-configurable type of control rather than a follow-the-instruction type of control. PMID:15272377

Emergence of Life-Like Properties from Dissipative Self-Assembly of Nanoparticles

NASA Astrophysics Data System (ADS)

Ilday, Serim; Makey, Ghaith; Akguc, Gursoy B.; Yavuz, Ozgun; Tokel, Onur; Pavlov, Ihor; Gulseren, Oguz; Ilday, F. Omer

A profoundly fundamental question at the interface between physics and biology remains open: What are the minimum requirements for emergence of life-like properties from non-living systems? Here, we address this question and report emergent complex behavior of tens to thousands of colloidal nanoparticles in a system designed to be as plain as possible: The system is driven far from equilibrium by ultrafast laser pulses, which create spatiotemporal temperature gradients, inducing Marangoni-type flow that drags the particles towards aggregation; strong Brownian motion, used as source of fluctuations, opposes aggregation. Nonlinear feedback mechanisms naturally arise between the flow, the aggregate, and Brownian motion, allowing fast external control with minimal intervention. Consequently, complex behavior, analogous to those commonly seen in living organisms, emerges, whereby the aggregates can self-sustain, self-regulate, self-replicate, self-heal and can be transferred from one location to another, all within seconds. Aggregates can comprise of only one pattern or bifurcated patterns can co-exist, compete, survive or die.

The pattern of self-harm in Fars Province in South Iran: A population-based study.

PubMed

Gholamzadeh, Saeid; Zahmatkeshan, Mozhghan; Zarenezhad, Mohammad; Ghaffari, Elaheh; Hoseni, Sanaz

2017-10-01

Non-suicidal self-harm includes cutting, scratching, burning and minor overdosing. There have been few studies that have examined the rate and pattern of self-harm among different individuals of the society. We performed a population-based study to determine different aspects of non-suicidal self-harm in cases referred to legal medicine organization of Fars Province and south Iran. In a population-based longitudinal survey, we applied data from cases referred to legal medicine organization of Fars province. The survey included questions about the history, method, frequency, age of onset and help-seeking for non-suicidal self-harm. The data about non-suicidal self-harm were collected since 2007 to 2011 and analyzed using students' T-test for continuous data and χ 2 for binary or categorical data using SPSS ver. 21.0. Totally 2166 individuals were diagnosed who had ever harmed themselves. Self-injuries such as cutting, scratching and self-hitting were the most common forms of non-suicidal self-harm (83.2%). The mean age of onset was 25.7 ± 2.6 years. Self-injury was more frequent in males and individuals with lower education levels mostly unemployed. The most frequent injury site was posterior side of the body for example shoulders (157; 9.8%) and the most type of the injury was bruise in 398(55.26%) cases. Hard objects (1197; 55.26%) were the most used devices for self-injury followed by cutting and sharp devices. Among those who reported non-suicidal self-harm, 56% had sought help while self-injury. We found a high prevalence of non-suicidal self-harm in different individuals of the society in Fars province since 2007 to 2011. Many mental-health symptoms as well as legal and financial gains should be evaluated for any association with this behavior. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Enhancement of field effect mobility of poly(3-hexylthiophene) thin film transistors by soft-lithographical nanopatterning on the gate-dielectric surface

NASA Astrophysics Data System (ADS)

Park, Jeong-Ho; Kang, Seok-Ju; Park, Jeong-Woo; Lim, Bogyu; Kim, Dong-Yu

2007-11-01

The submicroscaled octadecyltrichlorosilane (OTS) line patterns on gate-dielectric surfaces were introduced into the fabrication of organic field effect transistors (OFETs). These spin-cast regioregular poly(3-hexylthiophene) films on soft-lithographically patterned SiO2 surfaces yielded a higher hole mobility (˜0.072cm2/Vs ) than those of unpatterned (˜0.015cm2/Vs) and untreated (˜5×10-3cm2/Vs) OFETs. The effect of mobility enhancement as a function of the patterned line pitch was investigated in structural and geometric characteristics. The resulting improved mobility is likely attributed to the formation of efficient π-π stacking as a result of guide-assisted, local self-organization-involved molecular interactions between the poly(3-hexylthiophene) polymer and the geometrical OTS patterns.

Programmable assembly of pressure sensors using pattern-forming bacteria

PubMed Central

Cao, Yangxiaolu; Feng, Yaying; Ryser, Marc D.; Zhu, Kui; Herschlag, Gregory; Cao, Changyong; Marusak, Katherine; Zauscher, Stefan; You, Lingchong

2017-01-01

Biological systems can generate microstructured materials that combine organic and inorganic components and possess diverse physical and chemical properties. However, these natural processes in materials fabrication are not readily programmable. Here, we use a synthetic-biology approach to mimic such natural processes to assemble patterned materials.. We demonstrate programmable fabrication of three-dimensional (3D) materials by printing engineered self-patterning bacteria on permeable membranes that serve as a structural scaffold. Application of gold nanoparticles to the colonies creates hybrid organic-inorganic dome structures. The dynamics of the dome structures' response to pressure is determined by their geometry (colony size, dome height and pattern), which is easily modified by varying the properties of the membrane (e.g., pore size and hydrophobicity). We generate resettable pressure sensors that process signals in response to varying pressure intensity and duration. PMID:28991268

Tuning the Growth Pattern in 2D Confinement Regime of Sm2O3 and the Emerging Room Temperature Unusual Superparamagnetism

PubMed Central

Guria, Amit K.; Dey, Koushik; Sarkar, Suresh; Patra, Biplab K.; Giri, Saurav; Pradhan, Narayan

2014-01-01

Programming the reaction chemistry for superseding the formation of Sm2O3 in a competitive process of formation and dissolution, the crystal growth patterns are varied and two different nanostructures of Sm2O3 in 2D confinement regime are designed. Among these, the regular and self-assembled square platelets nanostructures exhibit paramagnetic behavior analogous to the bulk Sm2O3. But, the other one, 2D flower like shaped nanostructure, formed by irregular crystal growth, shows superparamagnetism at room temperature which is unusual for bulk paramagnet. It has been noted that the variation in the crystal growth pattern is due to the difference in the binding ability of two organic ligands, oleylamine and oleic acid, used for the synthesis and the magnetic behavior of the nanostructures is related to the defects incorporated during the crystal growth. Herein, we inspect the formation chemistry and plausible origin of contrasting magnetism of these nanostructures of Sm2O3. PMID:25269458

Molecular and genetic characterization of the S locus in Hordeum bulbosum L., a wild self-incompatible species related to cultivated barley.

PubMed

Kakeda, Katsuyuki; Ibuki, Toshiro; Suzuki, Junko; Tadano, Hidetaka; Kurita, Yuko; Hanai, Yosuke; Kowyama, Yasuo

2008-12-01

Gametophytic self-incompatibility (GSI) in the grasses is controlled by a distinct two-locus genetic system governed by the multiallelic loci S and Z. We have employed diploid Hordeum bulbosum as a model species for identifying the self-incompatibility (SI) genes and for elucidating the molecular mechanisms of the two-locus SI system in the grasses. In this study, we attempted to identify S haplotype-specific cDNAs expressed in pistils and anthers at the flowering stage in H. bulbosum, using the AFLP-based mRNA fingerprinting (AMF, also called cDNA-AFLP) technique. We used the AMF-derived DNA clones as markers for fine mapping of the S locus, and found that the locus resided in a chromosomal region displaying remarkable suppression of recombination, encompassing a large physical region. Furthermore, we identified three AMF-derived markers displaying complete linkage to the S locus, although they showed no significant homology with genes of known functions. Two of these markers showed expression patterns that were specific to the reproductive organs (pistil or anther), suggesting that they could be potential candidates for the S gene.

Pulmonary effects of synthetic marijuana: chest radiography and CT findings.

PubMed

Berkowitz, Eugene A; Henry, Travis S; Veeraraghavan, Srihari; Staton, Gerald W; Gal, Anthony A

2015-04-01

The purpose of this article is to present the first chest radiographic and CT descriptions of organizing pneumonia in response to smoking synthetic marijuana. Chest radiographs showed a diffuse miliary-micronodular pattern. Chest CT images showed diffuse centrilobular nodules and tree-in-bud pattern and a histopathologic pattern of organizing pneumonia with or without patchy acute alveolar damage. This distinct imaging pattern should alert radiologists to include synthetic marijuana abuse in the differential diagnosis.

Visual Field Asymmetries in Attention Vary with Self-Reported Attention Deficits

ERIC Educational Resources Information Center

Poynter, William; Ingram, Paul; Minor, Scott

2010-01-01

The purpose of this study was to determine whether an index of self-reported attention deficits predicts the pattern of visual field asymmetries observed in behavioral measures of attention. Studies of "normal" subjects do not present a consistent pattern of asymmetry in attention functions, with some studies showing better left visual field (LVF)…

Bio-Organic Nanotechnology: Using Proteins and Synthetic Polymers for Nanoscale Devices

NASA Technical Reports Server (NTRS)

Molnar, Linda K.; Xu, Ting; Trent, Jonathan D.; Russell, Thomas P.

2003-01-01

While the ability of proteins to self-assemble makes them powerful tools in nanotechnology, in biological systems protein-based structures ultimately depend on the context in which they form. We combine the self-assembling properties of synthetic diblock copolymers and proteins to construct intricately ordered, three-dimensional polymer protein structures with the ultimate goal of forming nano-scale devices. This hybrid approach takes advantage of the capabilities of organic polymer chemistry to build ordered structures and the capabilities of genetic engineering to create proteins that are selective for inorganic or organic substrates. Here, microphase-separated block copolymers coupled with genetically engineered heat shock proteins are used to produce nano-scale patterning that maximizes the potential for both increased structural complexity and integrity.

Asymmetric Branching in Biological Resource Distribution Networks

NASA Astrophysics Data System (ADS)

Brummer, Alexander Byers

There is a remarkable relationship between an organism's metabolic rate (resting power consumption) and the organism's mass. It may be a universal law of nature that an organism's resting metabolic rate is proportional to its mass to the power of 3/4. This relationship, known as Kleiber's Law, appears to be valid for both plants and animals. This law is important because it implies that larger organisms are more efficient than smaller organisms, and knowledge regarding metabolic rates are essential to a multitude of other fields in ecology and biology. This includes modeling the interactions of many species across multiple trophic levels, distributions of species abundances across large spatial landscapes, and even medical diagnostics for respiratory and cardiovascular pathologies. Previous models of vascular networks that seek to identify the origin of metabolic scaling have all been based on the unrealistic assumption of perfectly symmetric branching. In this dissertation I will present a theory of asymmetric branching in self-similar vascular networks (published by Brummer et al. in [9]). The theory shows that there can exist a suite of vascular forms that result in the often observed 3/4 metabolic scaling exponent of Kleiber's Law. Furthermore, the theory makes predictions regarding major morphological features related to vascular branching patterns and their relationships to metabolic scaling. These predictions are suggestive of evolutionary convergence in vascular branching. To test these predictions, I will present an analysis of real mammalian and plant vascular data that shows: (i) broad patterns in vascular networks across entire animal kingdoms and (ii) within these patterns, plant and mammalian vascular networks can be uniquely distinguished from one another (publication in preparation by Brummer et al.). I will also present results from a computational study in support of point (i). Namely, that asymmetric branching may be the optimal strategy to balance the simultaneous demands of maximizing the number of nutrient exchange sites (capillaries or leaves) versus hydraulic resistance to resource transport (publication in preparation by Brummer et al.). Finally, I report on improved methods of estimating whole organism metabolism based solely on measurements of vasculature.

Self-organization and solution of shortest-path optimization problems with memristive networks

NASA Astrophysics Data System (ADS)

Pershin, Yuriy V.; Di Ventra, Massimiliano

2013-07-01

We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path. Finally, we provide an algorithm to solve the traveling salesman problem. Similar considerations apply to networks of memcapacitors and meminductors, and networks with memory in various dimensions.

Bio-soliton model that predicts non-thermal electromagnetic frequency bands, that either stabilize or destabilize living cells.

PubMed

Geesink, J H; Meijer, D K F

2017-01-01

Solitons, as self-reinforcing solitary waves, interact with complex biological phenomena such as cellular self-organization. A soliton model is able to describe a spectrum of electromagnetism modalities that can be applied to understand the physical principles of biological effects in living cells, as caused by endogenous and exogenous electromagnetic fields and is compatible with quantum coherence. A bio-soliton model is proposed, that enables to predict which eigen-frequencies of non-thermal electromagnetic waves are life-sustaining and which are, in contrast, detrimental for living cells. The particular effects are exerted by a range of electromagnetic wave eigen-frequencies of one-tenth of a Hertz till Peta Hertz that show a pattern of 12 bands, and can be positioned on an acoustic reference frequency scale. The model was substantiated by a meta-analysis of 240 published articles of biological electromagnetic experiments, in which a spectrum of non-thermal electromagnetic waves were exposed to living cells and intact organisms. These data support the concept of coherent quantized electromagnetic states in living organisms and the theories of Fröhlich, Davydov and Pang. It is envisioned that a rational control of shape by soliton-waves and related to a morphogenetic field and parametric resonance provides positional information and cues to regulate organism-wide systems properties like anatomy, control of reproduction and repair.

Variants of guided self-organization for robot control.

PubMed

Martius, Georg; Herrmann, J Michael

2012-09-01

Autonomous robots can generate exploratory behavior by self-organization of the sensorimotor loop. We show that the behavioral manifold that is covered in this way can be modified in a goal-dependent way without reducing the self-induced activity of the robot. We present three strategies for guided self-organization, namely by using external rewards, a problem-specific error function, or assumptions about the symmetries of the desired behavior. The strategies are analyzed for two different robots in a physically realistic simulation.

Planarian yorkie/YAP functions to integrate adult stem cell proliferation, organ homeostasis and maintenance of axial patterning.

PubMed

Lin, Alexander Y T; Pearson, Bret J

2014-03-01

During adult homeostasis and regeneration, the freshwater planarian must accomplish a constant balance between cell proliferation and cell death, while also maintaining proper tissue and organ size and patterning. How these ordered processes are precisely modulated remains relatively unknown. Here we show that planarians use the downstream effector of the Hippo signaling cascade, yorkie (yki; YAP in vertebrates) to control a diverse set of pleiotropic processes in organ homeostasis, stem cell regulation, regeneration and axial patterning. We show that yki functions to maintain the homeostasis of the planarian excretory (protonephridial) system and to limit stem cell proliferation, but does not affect the differentiation process or cell death. Finally, we show that Yki acts synergistically with WNT/β-catenin signaling to repress head determination by limiting the expression domains of posterior WNT genes and that of the WNT-inhibitor notum. Together, our data show that yki is a key gene in planarians that integrates stem cell proliferation control, organ homeostasis, and the spatial patterning of tissues.

Multivariate pattern classification reveals autonomic and experiential representations of discrete emotions.

PubMed

Kragel, Philip A; Labar, Kevin S

2013-08-01

Defining the structural organization of emotions is a central unresolved question in affective science. In particular, the extent to which autonomic nervous system activity signifies distinct affective states remains controversial. Most prior research on this topic has used univariate statistical approaches in attempts to classify emotions from psychophysiological data. In the present study, electrodermal, cardiac, respiratory, and gastric activity, as well as self-report measures were taken from healthy subjects during the experience of fear, anger, sadness, surprise, contentment, and amusement in response to film and music clips. Information pertaining to affective states present in these response patterns was analyzed using multivariate pattern classification techniques. Overall accuracy for classifying distinct affective states was 58.0% for autonomic measures and 88.2% for self-report measures, both of which were significantly above chance. Further, examining the error distribution of classifiers revealed that the dimensions of valence and arousal selectively contributed to decoding emotional states from self-report, whereas a categorical configuration of affective space was evident in both self-report and autonomic measures. Taken together, these findings extend recent multivariate approaches to study emotion and indicate that pattern classification tools may improve upon univariate approaches to reveal the underlying structure of emotional experience and physiological expression. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Multivariate Pattern Classification Reveals Autonomic and Experiential Representations of Discrete Emotions

PubMed Central

Kragel, Philip A.; LaBar, Kevin S.

2013-01-01

Defining the structural organization of emotions is a central unresolved question in affective science. In particular, the extent to which autonomic nervous system activity signifies distinct affective states remains controversial. Most prior research on this topic has used univariate statistical approaches in attempts to classify emotions from psychophysiological data. In the present study, electrodermal, cardiac, respiratory, and gastric activity, as well as self-report measures were taken from healthy subjects during the experience of fear, anger, sadness, surprise, contentment, and amusement in response to film and music clips. Information pertaining to affective states present in these response patterns was analyzed using multivariate pattern classification techniques. Overall accuracy for classifying distinct affective states was 58.0% for autonomic measures and 88.2% for self-report measures, both of which were significantly above chance. Further, examining the error distribution of classifiers revealed that the dimensions of valence and arousal selectively contributed to decoding emotional states from self-report, whereas a categorical configuration of affective space was evident in both self-report and autonomic measures. Taken together, these findings extend recent multivariate approaches to study emotion and indicate that pattern classification tools may improve upon univariate approaches to reveal the underlying structure of emotional experience and physiological expression. PMID:23527508

Study of flowability effect on self-planarization performance at SOC materials

NASA Astrophysics Data System (ADS)

Yun, Huichan; Kim, Jinhyung; Park, Youjung; Kim, Yoona; Jeong, Seulgi; Baek, Jaeyeol; Yoon, Byeri; Lim, Sanghak

2017-03-01

For multilayer process, importance of carbon-based spin-on hardmask material that replaces amorphous carbon layer (ACL) is ever increasing. Carbon-based spin-on hardmask is an organic polymer with high carbon content formulated in organic solvents for spin-coating application that is cured through baking. In comparison to CVD process for ACL, carbon-based spin-on hardmask material can offer several benefits: lower cost of ownership (CoO) and improved process time, as well as better gap-fill and planarization performances. Thus carbon-based spin-on hardmask material of high etch resistance, good gap-fill properties and global planarization performances over various pattern topographies are desired to achieve the fine patterning and high aspect ratio (A/R). In particular, good level of global planarization of spin coated layer over the underlying pattern topographies is important for self-aligned double patterning (SADP) process as it dictates the photolithographic margin. Herein, we report a copolymer carbon-based spin-on hardmask resin formulation that exhibits favorable film shrinkage profile and good etch resistance properties. By combining the favorable characteristics of each resin - one resin with good shrinkage property and the other with excellent etch resistance into the copolymer, it was possible to achieve a carbonbased spin-on hardmask formulation with desirable level of etch resistance and the planarization performances across various underlying substrate pattern topographies.

On the Interplay between Order Parameter Dynamics and System Parameter Dynamics in Human Perceptual-Cognitive-Behavioral Systems.

PubMed

Frank, T D

2015-04-01

Previous research has demonstrated that perceiving, thinking, and acting are human activities that correspond to self-organized patterns. The emergence of such patterns can be completely described in terms of the dynamics of the pattern amplitudes, which are referred to as order parameters. The patterns emerge at bifurcations points when certain system parameters internal and external to a human agent exceed critical values. At issue is how one might study the order parameter dynamics for sequences of consecutive, emergent perceptual, cognitive, or behavioral activities. In particular, these activities may in turn impact the system parameters that have led to the emergence of the activities in the first place. This interplay between order parameter dynamics and system parameter dynamics is discussed in general and formulated in mathematical terms. Previous work that has made use of this two-tiered framework of order parameter and system parameter dynamics are briefly addressed. As an application, a model for perception under functional fixedness is presented. Finally, it is argued that the phenomena that emerge in this framework and can be observed when human agents perceive, think, and act are just as likely to occur in pattern formation systems of the inanimate world. Consequently, these phenomena do not necessarily have a neurophysiological basis but should instead be understood from the perspective of the theory of self-organization.

Temperature Oscillation Modulated Self-Assembly of Periodic Concentric Layered Magnesium Carbonate Microparticles

PubMed Central

Li, Shihong; Wang, Zheng Jim; Chang, Ting-Tung

2014-01-01

Intriguing patterns of periodic, concentric, layered, mineral microstructure are present in nature and organisms, yet they have elusive geneses. We hypothesize temperature oscillation can be an independent factor that causes the self-assembly of such patterns in mineral phases synthesized in solution. Static experiments verify that rhythmic concentric multi-layered magnesium carbonate microhemispheres can be synthesized from bicarbonate solution by temperature oscillation, without use of a chemical template, additive or gel-diffusion system. Appropriate reactant concentration and initial pH value can restrain the competitive growth of other mineral generations. Polarized light microscopy images indicate the microhemispheres are crystalline and the crystallinity increases with incubation time. The thickness of a single mineral layer of microhemisphere in microscale is precisely controlled by the waveform parameters of the temperature oscillation, while the layer number, which can reach tens to about one hundred, is constrained by the temperature oscillation period number. FT-IR spectra show that these microhemispheres synthesized under different conditions can be identified as the basic form of magnesium carbonate, hydromagnesite (Mg5(CO3)4(OH)2⋅4H2O). SEM images exhibit the characteristic microscopic texture of the alternating dark and light rings of these microhemispheres. TEM images and ED patterns suggest the nanoflakes of microhemispheres are present in polycrystalline form with some degree of oriented assembly. The temperature oscillation modulated self-assembly may offer a new mechanism to understand the formation of layered microstructure of minerals in solution, and provide a non-invasive and programmable means to synthesize hierarchically ordered materials. PMID:24520410

Processes and content of narrative identity development in adolescence: gender and well-being.

PubMed

McLean, Kate C; Breen, Andrea V

2009-05-01

The present study examined narrative identity in adolescence (14-18 years) in terms of narrative content and processes of identity development. Age- and gender-related differences in narrative patterns in turning point memories and gender differences in the content and functions for sharing those memories were examined, as was the relationship between narrative patterns and self-esteem. The narrative patterns focused on were meaning-making (learning from past events) and emotionality of the narratives, specified as overall positive emotional tone and redemptive sequencing. Results showed an age-related increase in meaning-making but no gender differences in the degree of meaning-making. Results further showed that gender predicted self-esteem and that boys evidenced higher self-esteem. Emotionality also predicted self-esteem; this was especially true for redemption and for boys. In terms of telling functions, girls endorsed more relational reasons for telling memories than did boys. Results are discussed in terms of potential gendered and nongendered pathways for identity development in adolescence. Copyright 2009 APA, all rights reserved

The spatiotemporal organization of cilia activity drives multiscale circular flows of mucus in reconstituted human bronchial epithelium

NASA Astrophysics Data System (ADS)

Loiseau, Etienne; Gras, Delphine; Chanez, Pascal; Viallat, Annie

2017-11-01

Chronic respiratory diseases affect hundreds of millions of people worldwide. The bronchial epithelium is the first barrier to protect the respiratory tract via an innate mechanism called mucociliary clearance. It consists in the active transport of a sticky fluid, the mucus, via a myriad of cilia at the epithelial surface of the airways. The mucus traps inhaled pathogens and the protective role of the mucociliary clearance relies on the ability of the cilia to self-organize and coordinate their beating to transport the mucus over the full bronchial tree till its elimination through swallowing or expectoration. Despite a rich corpus of clinical studies, chronic respiratory diseases remain poorly understood and quantitative biophysical studies are still missing. Here we will present the physical mechanisms underlying the mucociliary transport. We will show how the cilia self-organize during the ciliogenesis and how the coordination of their beating direction leads to the formation of fluid flow patterns at the macroscopic scale. Finally, we will discuss the role of long range hydrodynamics interactions in this intricate coupled system. ANR MUCOCIL project, Grant ANR-13-BSV5-0015 and European Union's Seventh Framework Programme (FP7/2007-2013) under REA Grant agreement n. PCOFUND-GA-2013-609102.

Self-organizing neural network models for visual pattern recognition.

PubMed

Fukushima, K

1987-01-01

Two neural network models for visual pattern recognition are discussed. The first model, called a "neocognitron", is a hierarchical multilayered network which has only afferent synaptic connections. It can acquire the ability to recognize patterns by "learning-without-a-teacher": the repeated presentation of a set of training patterns is sufficient, and no information about the categories of the patterns is necessary. The cells of the highest stage eventually become "gnostic cells", whose response shows the final result of the pattern-recognition of the network. Pattern recognition is performed on the basis of similarity in shape between patterns, and is not affected by deformation, nor by changes in size, nor by shifts in the position of the stimulus pattern. The second model has not only afferent but also efferent synaptic connections, and is endowed with the function of selective attention. The afferent and the efferent signals interact with each other in the hierarchical network: the efferent signals, that is, the signals for selective attention, have a facilitating effect on the afferent signals, and at the same time, the afferent signals gate efferent signal flow. When a complex figure, consisting of two patterns or more, is presented to the model, it is segmented into individual patterns, and each pattern is recognized separately. Even if one of the patterns to which the models is paying selective attention is affected by noise or defects, the model can "recall" the complete pattern from which the noise has been eliminated and the defects corrected.

Self Organizing Maps for use in Deep Inelastic Scattering

NASA Astrophysics Data System (ADS)

Askanazi, Evan

2015-04-01

Self Organizing Maps are a type of artificial neural network that has been proven to be particularly useful in solving complex problems in neural biology, engineering, robotics and physics. We are attempting to use the Self Organizing Map to solve problems and probe phenomenological patterns in subatomic physics, specifically in Deep Inelastic Scattering (DIS). In DIS there is a cross section in electron hadron scattering that is dependent on the momentum fraction x of the partons in the hadron and the momentum transfer of the virtual photon exchanged. There is a soft cross part of this cross section that currently can only be found through experimentation; this soft part is comprised of Structure Functions which in turn are comprised of the Parton Distribution Functions (PDFs). We aim to use the Self Organizing Process, or SOP, to take theoretical models of these PDFs and fit it to the previous, known data. The SOP will also be used to probe the behavior of the PDFs in particular at large x values, in order to observe how they congregate. The ability of the SOPto take multidimensional data and convert it into two dimensional output is anticipated to be particularly useful in achieving this aim.

Self-organization of intertidal snails facilitates evolution of aggregation behavior.

PubMed

Stafford, Richard; Davies, Mark S; Williams, Gray A

2008-01-01

Many intertidal snails form aggregations during emersion to minimize desiccation stress. Here we investigate possible mechanisms for the evolution of such behavior. Two behavioral traits (following of mucus trails, and crevice occupation), which both provide selective advantages to individuals that possess the traits over individuals that do not, result in self-organization of aggregations in crevices in the rock surface. We suggest that the existence of self-organizing aggregations provides a mechanism by which aggregation behavior can evolve. The inclusion of an explicitly coded third behavior, aggregation, in a simulated population produces patterns statistically similar to those found on real rocky shores. Allowing these three behaviors to evolve using an evolutionary algorithm, however, results in aggregation behavior being selected against on shores with high crevice density. The inclusion of broadcast spawning dispersal mechanisms in the simulation, however, results in aggregation behavior evolving as predicted on shores with both high crevice density and low crevice density (evolving in crevices first, and then both in crevices and on flat rock), indicating the importance of environmental interactions in understanding evolutionary processes. We propose that self-organization can be an important factor in the evolution of group behaviors.

A Dynamical View of High School Attendance: An Assessment of Short-term and Long-term Dependencies in Five Urban Schools.

PubMed

Koopmans, Matthijs

2015-01-01

While school attendance is a critical mediator to academic achievement, its time dependent characteristics are rarely investigated. To remedy situation, this paper reports on the analysis of daily attendance rates in five urban high schools over a seven-year period. Traditional time series analyses were conducted to estimate short-range and cyclical dependencies in the data. An Autoregressive Fractional Integrated Moving Average (ARFIMA) approach was used to address long-range correlational patterns, and detect signs of self-organized criticality. The analysis reveals a strong cyclical pattern (weekly) in all five schools, and evidence for self-organized criticality in one of the five. These findings illustrate the insufficiency of traditional statistical summary measures to characterize the distribution of daily attendance, and they suggest that daily attendance is not necessarily the stable and predictable feature of school effectiveness it is conventionally assumed to be. While educational practitioners can probably attest to the many of the irregularities in attendance patterns as well as some of their sources, a systematic description of these temporal aspects needs to be included in our assessment of daily attendance behavior to inform policy decisions, if only to better align formal research in this area with existing local knowledge about those patterns.

Between giant oscillations and uniform distribution of droplets: The role of varying lumen of channels in microfluidic networks.

PubMed

Cybulski, Olgierd; Jakiela, Slawomir; Garstecki, Piotr

2015-12-01

The simplest microfluidic network (a loop) comprises two parallel channels with a common inlet and a common outlet. Recent studies that assumed a constant cross section of the channels along their length have shown that the sequence of droplets entering the left (L) or right (R) arm of the loop can present either a uniform distribution of choices (e.g., RLRLRL...) or long sequences of repeated choices (RRR...LLL), with all the intermediate permutations being dynamically equivalent and virtually equally probable to be observed. We use experiments and computer simulations to show that even small variation of the cross section along channels completely shifts the dynamics either into the strong preference for highly grouped patterns (RRR...LLL) that generate system-size oscillations in flow or just the opposite-to patterns that distribute the droplets homogeneously between the arms of the loop. We also show the importance of noise in the process of self-organization of the spatiotemporal patterns of droplets. Our results provide guidelines for rational design of systems that reproducibly produce either grouped or homogeneous sequences of droplets flowing in microfluidic networks.

Comparing the Self-Report and Measured Smartphone Usage of College Students: A Pilot Study

PubMed Central

Lee, Heyoung; Nguyen, Trung Giang; Choi, Sam-Wook; Kim, Dae Jin

2017-01-01

Objective Nowadays smartphone overuse has become a social and medical concern. For the diagnosis and treatment, clinicians use the self-report information, but the report data often does not match actual usage pattern. The paper examines the similarity and variance in smartphone usage patterns between the measured data and self-reported data. Methods Together with the self-reported data, the real usage log data is collected from 35 college students in a metropolitan region of Northeast Asia, using Android smartphone monitoring application developed by the authors. Results The unconscious users underestimate their usage time by 40%, in spite of 15% more use in the actual usage. Messengers are most-used application regardless of their self-report, and significant preference to SNS applications was observed in addict group. The actual hourly pattern is consistent with the reported one. College students use more in the afternoon, when they have more free time and cannot use PCs. No significant difference in hourly pattern is observed between the measured and self-report. Conclusion The result shows there are significant cognitive bias in actual usage patterns exists in self report of smartphone addictions. Clinicians are recommended to utilize measurement tools in diagnosis and treatment of smartphone overusing subjects. PMID:28326119

Love flows downstream: mothers’ and children’s neural representation similarity in perceiving distress of self and family

PubMed Central

Qu, Yang

2017-01-01

Abstract The current study aimed to capture empathy processing in an interpersonal context. Mother–adolescent dyads (N = 22) each completed an empathy task during fMRI, in which they imagined the target person in distressing scenes as either themselves or their family (i.e. child for the mother, mother for the child). Using multi-voxel pattern approach, we compared neural pattern similarity for the self and family conditions and found that mothers showed greater perceptual similarity between self and child in the fusiform face area (FFA), representing high self–child overlap, whereas adolescents showed significantly less self–mother overlap. Adolescents’ pattern similarity was dependent upon family relationship quality, such that they showed greater self–mother overlap with higher relationship quality, whereas mothers’ pattern similarity was independent of relationship quality. Furthermore, adolescents’ perceptual similarity in the FFA was associated with increased social brain activation (e.g. temporal parietal junction). Mediation analyses indicated that high relationship quality was associated with greater social brain activation, which was mediated by greater self–mother overlap in the FFA. Our findings suggest that adolescents show more distinct neural patterns in perceiving their own vs their mother’s distress, and such distinction is sensitive to mother–child relationship quality. In contrast, mothers’ perception for their own and child’s distress is highly similar and unconditional. PMID:29069521

Self-organized surface ripple pattern formation by ion implantation

NASA Astrophysics Data System (ADS)

Hofsäss, Hans; Zhang, Kun; Bobes, Omar

2016-10-01

Ion induced ripple pattern formation on solid surfaces has been extensively studied in the past and the theories describing curvature dependent ion erosion as well as redistribution of recoil atoms have been very successful in explaining many features of the pattern formation. Since most experimental studies use noble gas ion irradiation, the incorporation of the ions into the films is usually neglected. In this work we show that the incorporation or implantation of non-volatile ions also leads to a curvature dependent term in the equation of motion of a surface height profile. The implantation of ions can be interpreted as a negative sputter yield; and therefore, the effect of ion implantation is opposite to the one of ion erosion. For angles up to about 50°, implantation of ions stabilizes the surface, whereas above 50°, ion implantation contributes to the destabilization of the surface. We present simulations of the curvature coefficients using the crater function formalism and we compare the simulation results to the experimental data on the ion induced pattern formation using non-volatile ions. We present several model cases, where the incorporation of ions is a crucial requirement for the pattern formation.

Global adaptation in networks of selfish components: emergent associative memory at the system scale.

PubMed

Watson, Richard A; Mills, Rob; Buckley, C L

2011-01-01

In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organize into structures that enhance global adaptation, efficiency, or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology, and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalization, and optimization are well understood. Such global functions within a single agent or organism are not wholly surprising, since the mechanisms (e.g., Hebbian learning) that create these neural organizations may be selected for this purpose; but agents in a multi-agent system have no obvious reason to adhere to such a structuring protocol or produce such global behaviors when acting from individual self-interest. However, Hebbian learning is actually a very simple and fully distributed habituation or positive feedback principle. Here we show that when self-interested agents can modify how they are affected by other agents (e.g., when they can influence which other agents they interact with), then, in adapting these inter-agent relationships to maximize their own utility, they will necessarily alter them in a manner homologous with Hebbian learning. Multi-agent systems with adaptable relationships will thereby exhibit the same system-level behaviors as neural networks under Hebbian learning. For example, improved global efficiency in multi-agent systems can be explained by the inherent ability of associative memory to generalize by idealizing stored patterns and/or creating new combinations of subpatterns. Thus distributed multi-agent systems can spontaneously exhibit adaptive global behaviors in the same sense, and by the same mechanism, as with the organizational principles familiar in connectionist models of organismic learning.

Morphodynamics of growing bacterial colony

NASA Astrophysics Data System (ADS)

Ghosh, Pushpita; Perlekar, Prasad; Rana, Navdeep

Self-organization into multicellular communities is a natural trend of most of the bacteria. Mutual interactions and competition among the bacterial cells in such multicellular organization play essential role in governing the spatiotemporal dynamics. We here present the spatiotemporal dynamics of growing bacterial colony using theory and a particle-based or individual-based simulation model of nonmotile cells growing utilizing a diffusing nutrient/food on a semi-solid surface by their growth and division forces and by pushing each-other through sliding motility. We show how the resource competition over a fixed amount of food, the diffusion coefficient of the nutrient and the random genetic noise govern the morphodynamics of a single species and a well-mixed two-species bacterial colonies. Our results show that for a very low initial food concentrations, colony develops fingering pattern at the front, while for intermediate values of initial food sources, the colony undergoes transitions to branched structures at the periphery and for very high values of food colony develops smoother fronts.

Preserved Self-Other Distinction during Empathy in Autism Is Linked to Network Integrity of Right Supramarginal Gyrus

ERIC Educational Resources Information Center

Hoffmann, Ferdinand; Koehne, Svenja; Steinbeis, Nikolaus; Dziobek, Isabel; Singer, Tania

2016-01-01

Autism spectrum disorder (ASD) shows deficits in self-other distinction during theory of mind (ToM). Here we investigated whether ASD patients also show difficulties in self-other distinction during empathy and if potential deficits are linked to dysfunctional resting-state connectivity patterns. In a first study, ASD patients and controls…

Happiness as a belief system: individual differences and priming in emotion judgments.

PubMed

Robinson, Michael D; Kirkeby, Ben S

2005-08-01

Three studies involving 104 undergraduates sought to examine how an individual's level of life satisfaction organizes their knowledge concerning the self's emotions. Participants judged the self's positive and negative emotions within a computerized task. Key results sought to determine whether judging two positive emotions in a consecutive sequence speeds the second judgment--a pattern of priming that would suggest a tighter, more interconnected structure in semantic memory related to one's positive emotions. As expected, individual differences in life satisfaction predicted the magnitude of this priming effect (Studies 1 & 2), which appeared to be unique to judgments of the self's emotions (Study 3). The results indicate that happy, relative to less happy, individuals organize information concerning their positive emotions in a qualitatively different and tighter semantic manner.

Growth-mediated autochemotactic pattern formation in self-propelling bacteria

NASA Astrophysics Data System (ADS)

Mukherjee, Mrinmoy; Ghosh, Pushpita

2018-01-01

Bacteria, while developing a multicellular colony or biofilm, can undergo pattern formation by diverse intricate mechanisms. One such route is directional movement or chemotaxis toward or away from self-secreted or externally employed chemicals. In some bacteria, the self-produced signaling chemicals or autoinducers themselves act as chemoattractants or chemorepellents and thereby regulate the directional movements of the cells in the colony. In addition, bacteria follow a certain growth kinetics which is integrated in the process of colony development. Here, we study the interplay of bacterial growth dynamics, cell motility, and autochemotactic motion with respect to the self-secreted diffusive signaling chemicals in spatial pattern formation. Using a continuum model of motile bacteria, we show growth can act as a crucial tuning parameter in determining the spatiotemporal dynamics of a colony. In action of growth dynamics, while chemoattraction toward autoinducers creates arrested phase separation, pattern transitions and suppression can occur for a fixed chemorepulsive strength.

Hybrid nanostructures of well-organized arrays of colloidal quantum dots and a self-assembled monolayer of gold nanoparticles for enhanced fluorescence

NASA Astrophysics Data System (ADS)

Liu, Xiaoying; McBride, Sean P.; Jaeger, Heinrich M.; Nealey, Paul F.

2016-07-01

Hybrid nanomaterials comprised of well-organized arrays of colloidal semiconductor quantum dots (QDs) in close proximity to metal nanoparticles (NPs) represent an appealing system for high-performance, spectrum-tunable photon sources with controlled photoluminescence. Experimental realization of such materials requires well-defined QD arrays and precisely controlled QD-metal interspacing. This long-standing challenge is tackled through a strategy that synergistically combines lateral confinement and vertical stacking. Lithographically generated nanoscale patterns with tailored surface chemistry confine the QDs into well-organized arrays with high selectivity through chemical pattern directed assembly, while subsequent coating with a monolayer of close-packed Au NPs introduces the plasmonic component for fluorescence enhancement. The results show uniform fluorescence emission in large-area ordered arrays for the fabricated QD structures and demonstrate five-fold fluorescence amplification for red, yellow, and green QDs in the presence of the Au NP monolayer. Encapsulation of QDs with a silica shell is shown to extend the design space for reliable QD/metal coupling with stronger enhancement of 11 times through the tuning of QD-metal spatial separation. This approach provides new opportunities for designing hybrid nanomaterials with tailored array structures and multiple functionalities for applications such as multiplexed optical coding, color display, and quantum transduction.

Uterus segmentation in dynamic MRI using LBP texture descriptors

NASA Astrophysics Data System (ADS)

Namias, R.; Bellemare, M.-E.; Rahim, M.; Pirró, N.

2014-03-01

Pelvic floor disorders cover pathologies of which physiopathology is not well understood. However cases get prevalent with an ageing population. Within the context of a project aiming at modelization of the dynamics of pelvic organs, we have developed an efficient segmentation process. It aims at alleviating the radiologist with a tedious one by one image analysis. From a first contour delineating the uterus-vagina set, the organ border is tracked along a dynamic mri sequence. The process combines movement prediction, local intensity and texture analysis and active contour geometry control. Movement prediction allows a contour intitialization for next image in the sequence. Intensity analysis provides image-based local contour detection enhanced by local binary pattern (lbp) texture descriptors. Geometry control prohibits self intersections and smoothes the contour. Results show the efficiency of the method with images produced in clinical routine.

Hardwiring stem cell communication through tissue structure

PubMed Central

Xin, Tianchi; Greco, Valentina; Myung, Peggy

2016-01-01

Adult stem cells across diverse organs self-renew and differentiate to maintain tissue homeostasis. How stem cells receive input to preserve tissue structure and function largely relies on their communication with surrounding cellular and non-cellular elements. As such, how tissues are organized and patterned not only reflects organ function but also inherently hardwires networks of communication between stem cells and their environment to direct tissue homeostasis and injury repair. This review highlights how different methods of stem cell communication reflect the unique organization and function of diverse tissues. PMID:26967287

Multistability of the Brain Network for Self-other Processing

PubMed Central

Chen, Yi-An; Huang, Tsung-Ren

2017-01-01

Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate “self-specific” and “other-specific” regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns. Combining an automated synthesis of fMRI data with a presumption-free diffusion spectrum image (DSI) fibre-tracking algorithm, we isolated a network putatively composed of brain areas and white matter tracts involved in self-other processing. We sampled synchronisation patterns from the dynamical systems of this network using various combinations of physiological parameters. Our results showed that the self-other processing network, with simulated gamma-band activity, tended to stabilise at a number of distinct synchronisation patterns. This phenomenon, termed “multistability,” could serve as an alternative model in theorising the mechanism of processing self-other information. PMID:28256520

Fatigue Level Estimation of Bill Based on Acoustic Signal Feature by Supervised SOM

NASA Astrophysics Data System (ADS)

Teranishi, Masaru; Omatu, Sigeru; Kosaka, Toshihisa

Fatigued bills have harmful influence on daily operation of Automated Teller Machine(ATM). To make the fatigued bills classification more efficient, development of an automatic fatigued bill classification method is desired. We propose a new method to estimate bending rigidity of bill from acoustic signal feature of banking machines. The estimated bending rigidities are used as continuous fatigue level for classification of fatigued bill. By using the supervised Self-Organizing Map(supervised SOM), we estimate the bending rigidity from only the acoustic energy pattern effectively. The experimental result with real bill samples shows the effectiveness of the proposed method.

Non-equilibrium magnetic colloidal dispersions at liquid-air interfaces: dynamic patterns, magnetic order and self-assembled swimmers.

PubMed

Snezhko, Alexey

2011-04-20

Colloidal dispersions of interacting particles subjected to an external periodic forcing often develop nontrivial self-assembled patterns and complex collective behavior. A fundamental issue is how collective ordering in such non-equilibrium systems arises from the dynamics of discrete interacting components. In addition, from a practical viewpoint, by working in regimes far from equilibrium new self-organized structures which are generally not available through equilibrium thermodynamics can be created. In this review spontaneous self-assembly phenomena in magnetic colloidal dispersions suspended at liquid-air interfaces and driven out of equilibrium by an alternating magnetic field are presented. Experiments reveal a new type of nontrivially ordered self-assembled structures emerging in such systems in a certain range of excitation parameters. These dynamic structures emerge as a result of the competition between magnetic and hydrodynamic forces and have complex unconventional magnetic ordering. Nontrivial self-induced hydrodynamic fields accompany each out-of-equilibrium pattern. Spontaneous symmetry breaking of the self-induced surface flows leading to a formation of self-propelled microstructures has been discovered. Some features of the self-localized structures can be understood in the framework of the amplitude equation (Ginzburg-Landau type equation) for parametric waves coupled to the conservation law equation describing the evolution of the magnetic particle density and the Navier-Stokes equation for hydrodynamic flows. To understand the fundamental microscopic mechanisms governing self-assembly processes in magnetic colloidal dispersions at liquid-air interfaces a first-principle model for a non-equilibrium self-assembly is presented. The latter model allows us to capture in detail the entire process of out-of-equilibrium self-assembly in the system and reproduces most of the observed phenomenology.

Electron transfer with self-assembled copper ions at Au-deposited biomimetic films: mechanistic ‘anomalies’ disclosed by temperature- and pressure-assisted fast-scan voltammetry

NASA Astrophysics Data System (ADS)

Khoshtariya, Dimitri E.; Dolidze, Tinatin D.; Tretyakova, Tatyana; van Eldik, Rudi

2015-06-01

It has been suggested that electron transfer (ET) processes occurring in complex environments capable of glass transitions, specifically in biomolecules, under certain conditions may experience the medium’s nonlinear response and nonergodic kinetic patterns. The interiors of self-assembled organic films (SAMs) deposited on solid conducting platforms (electrodes) are known to undergo glassy dynamics as well, hence they may also exhibit the abovementioned ‘irregularities’. We took advantage of Cu2+ ions as redox-active probes trapped in the Au-deposited  -COOH-terminated SAMs, either L-cysteine, or 3-mercaptopropionic acid diluted by the inert 2-mercaptoethanol, to systematically study the impact of glassy dynamics on ET using the fast-scan voltammetry technique and its temperature and high-pressure extensions. We found that respective kinetic data can be rationalized within the extended Marcus theory, taking into account the frictionally controlled (adiabatic) mechanism for short-range ET, and complications due to the medium’s nonlinear response and broken ergodicity. This combination shows up in essential deviations from the conventional energy gap (overpotential) dependence and in essentially nonlinear temperature (Arrhenius) and high-pressure patterns, respectively. Biomimetic aspects for these systems are also discussed in the context of recently published results for interfacial ET involving self-assembled blue copper protein (azurin) placed in contact with a glassy environment.

Revisiting play elements and self-handicapping in play: a comparative ethogram of five Old World monkey species.

PubMed

Petrů, Milada; Spinka, Marek; Charvátová, Veronika; Lhota, Stanislav

2009-08-01

Play behavior has been viewed as a mixture of elements drawn from "serious" behavior, interspersed by ritualized play signals. Two other types of play behaviors have been overlooked: patterns that are dissimilar from any serious behavior and patterns with self-handicapping character, that is, those that put the animal into unnecessary disadvantageous positions or situations. Here the authors show that these 2 types of patterns can constitute a major part of play repertoire. From our own videorecordings and observations, we constructed play ethograms of 5 monkey species (Semnopithecus entellus, Erythrocebus patas, Chlorocebus pygerythrus, Cercopithecus neglectus, and Cercopithecus diana). The authors evaluated the self-handicapping character of each pattern and in Hanuman langurs also the (dis)similarity to serious behavior. Of the 74 patterns in the 5 species, 33 (45%) were judged to have a self-handicapping character. Of 48 patterns observed in langurs, 16 (33%) were totally dissimilar to any serious langur behavior known to us. The authors discuss the possibility that the different types of play elements may have different functions in play. Copyright 2009 APA, all rights reserved.

Self-Induced Switchings between Multiple Space-Time Patterns on Complex Networks of Excitable Units

NASA Astrophysics Data System (ADS)

Ansmann, Gerrit; Lehnertz, Klaus; Feudel, Ulrike

2016-01-01

We report on self-induced switchings between multiple distinct space-time patterns in the dynamics of a spatially extended excitable system. These switchings between low-amplitude oscillations, nonlinear waves, and extreme events strongly resemble a random process, although the system is deterministic. We show that a chaotic saddle—which contains all the patterns as well as channel-like structures that mediate the transitions between them—is the backbone of such a pattern-switching dynamics. Our analyses indicate that essential ingredients for the observed phenomena are that the system behaves like an inhomogeneous oscillatory medium that is capable of self-generating spatially localized excitations and that is dominated by short-range connections but also features long-range connections. With our findings, we present an alternative to the well-known ways to obtain self-induced pattern switching, namely, noise-induced attractor hopping, heteroclinic orbits, and adaptation to an external signal. This alternative way can be expected to improve our understanding of pattern switchings in spatially extended natural dynamical systems like the brain and the heart.

USING SELF-ORGANIZING MAPS TO EXPLORE PATTERNS IN SPECIES RICHNESS AND PROTECTION

EPA Science Inventory

The combination of species distributions with abiotic and landscape variables using Geographic Information Systems can be used to help prioritize areas for biodiversity protection, although the number of variables and complexity of the relationships between them can prove difficu...

On the nature and shape of tubulin trails: implications on microtubule self-organization.

PubMed

Glade, Nicolas

2012-06-01

Microtubules, major elements of the cell skeleton are, most of the time, well organized in vivo, but they can also show self-organizing behaviors in time and/or space in purified solutions in vitro. Theoretical studies and models based on the concepts of collective dynamics in complex systems, reaction-diffusion processes and emergent phenomena were proposed to explain some of these behaviors. In the particular case of microtubule spatial self-organization, it has been advanced that microtubules could behave like ants, self-organizing by 'talking to each other' by way of hypothetic (because never observed) concentrated chemical trails of tubulin that are expected to be released by their disassembling ends. Deterministic models based on this idea yielded indeed like-looking spatio-temporal self-organizing behaviors. Nevertheless the question remains of whether microscopic tubulin trails produced by individual or bundles of several microtubules are intense enough to allow microtubule self-organization at a macroscopic level. In the present work, by simulating the diffusion of tubulin in microtubule solutions at the microscopic scale, we measure the shape and intensity of tubulin trails and discuss about the assumption of microtubule self-organization due to the production of chemical trails by disassembling microtubules. We show that the tubulin trails produced by individual microtubules or small microtubule arrays are very weak and not elongated even at very high reactive rates. Although the variations of concentration due to such trails are not significant compared to natural fluctuations of the concentration of tubuline in the chemical environment, the study shows that heterogeneities of biochemical composition can form due to microtubule disassembly. They could become significant when produced by numerous microtubule ends located in the same place. Their possible formation could play a role in certain conditions of reaction. In particular, it gives a mesoscopic basis to explain the collective dynamics observed in excitable microtubule solutions showing the propagation of concentration waves of microtubules at the millimeter scale, although we doubt that individual microtubules or bundles can behave like molecular ants.

Transfer Printing Method to Obtain Polarized Light Emission in Organic Light-Emitting Device

NASA Astrophysics Data System (ADS)

Noh, Hee Yeon; Park, Chang-sub; Park, Ji-Sub; Kang, Shin-Won; Kim, Hak-Rin

2012-06-01

We demonstrate a transfer printing method to obtain polarized light emission in organic light-emitting devices (OLEDs). On a rubbed self-assembled monolayer (SAM), a spin-coated liquid crystalline light-emissive polymer is aligned along the rubbing direction because of the anisotropic interfacial intermolecular interaction. Owing to the low surface energy of the SAM surface, the light-emissive layer was easily transferred to a patterned poly(dimethylsiloxane) (PDMS) stamp surface without degrading the ordering. Finally, a polarized light-emissive OLED device was prepared by transferring the patterned light-emissive layer to the charge transport layer of the OLED structure.

Module-based complexity formation: periodic patterning in feathers and hairs.

PubMed

Chuong, Cheng-Ming; Yeh, Chao-Yuan; Jiang, Ting-Xin; Widelitz, Randall

2013-01-01

Patterns describe order which emerges from homogeneity. Complex patterns on the integument are striking because of their visibility throughout an organism’s lifespan. Periodic patterning is an effective design because the ensemble of hair or feather follicles (modules) allows the generation of complexity, including regional variations and cyclic regeneration, giving the skin appendages a new lease on life. Spatial patterns include the arrangements of feathers and hairs in specific number, size, and spacing.We explorehowa field of equivalent progenitor cells can generate periodically arranged modules based on genetic information, physical–chemical rules and developmental timing. Reconstitution experiments suggest a competitive equilibrium regulated by activators/inhibitors involving Turing reaction-diffusion. Temporal patterns result from oscillating stem cell activities within each module (microenvironment regulation), reflected as growth (anagen) and resting (telogen) phases during the cycling of feather and hair follicles. Stimulating modules with activators initiates the spread of regenerative hair waves, while global inhibitors outside each module (macroenvironment) prevent this. Different wave patterns can be simulated by cellular automata principles. Hormonal status and seasonal changes can modulate appendage phenotypes, leading to ‘organ metamorphosis’, with multiple ectodermal organ phenotypes generated from the same precursors. We discuss potential novel evolutionary steps using this module-based complexity in several amniote integument organs, exemplified by the spectacular peacock feather pattern. We thus explore the application of the acquired knowledge of patterning in tissue engineering. New hair follicles can be generated after wounding. Hairs and feathers can be reconstituted through self-organization of dissociated progenitor cells. © 2012 Wiley Periodicals, Inc.

Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2017-12-01

Multiagent systems (MAS) provide a useful tool for exploring the complex dynamics and behavior of financial markets and now MAS approach has been widely implemented and documented in the empirical literature. This paper introduces the implementation of an innovative multi-scale mathematical model for a computational agent-based financial market. The paper develops a method to quantify the degree of self-organization which emerges in the system and shows that the capacity of self-organization is maximized when the agent behaviors are heterogeneous. Numerical results are presented and analyzed, showing how the global market behavior emerges from specific individual behavior interactions.

Real-time imaging of self-organization and mechanical competition in carbon nanotube forest growth [Real-time environmental TEM investigation of self-organization and mechanical competition in carbon nanotube forest growth

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balakrishnan, Viswanath; Bedewy, Mostafa; Meshot, Eric R.

Here, the properties of carbon nanotube (CNT) networks and analogous materials comprising filamentary nanostructures are governed by the intrinsic filament properties and their hierarchical organization and interconnection. As a result, direct knowledge of the collective dynamics of CNT synthesis and self-organization is essential to engineering improved CNT materials for applications such as membranes and thermal interfaces. Here, we use real-time environmental transmission electron microscopy (E-TEM) to observe nucleation and self-organization of CNTs into vertically aligned forests. Upon introduction of the carbon source, we observe a large scatter in the onset of nucleation of individual CNTs and the ensuing growth rates.more » Experiments performed at different temperatures and catalyst particle densities show the critical role of CNT density on the dynamics of self-organization; low-density CNT nucleation results in the CNTs becoming pinned to the substrate and forming random networks, whereas higher density CNT nucleation results in self-organization of the CNTs into bundles that are oriented perpendicular to the substrate. We also find that mechanical coupling between growing CNTs alters their growth trajectory and shape, causing significant deformations, buckling, and defects in the CNT walls. Therefore, it appears that CNT–CNT coupling not only is critical for self-organization but also directly influences CNT quality and likely the resulting properties of the forest. As a result, our findings show that control of the time-distributed kinetics of CNT nucleation and bundle formation are critical to manufacturing well-organized CNT assemblies and that E-TEM can be a powerful tool to investigate the mesoscale dynamics of CNT networks.« less

Real-time imaging of self-organization and mechanical competition in carbon nanotube forest growth [Real-time environmental TEM investigation of self-organization and mechanical competition in carbon nanotube forest growth

DOE PAGES

Balakrishnan, Viswanath; Bedewy, Mostafa; Meshot, Eric R.; ...

2016-11-23

Here, the properties of carbon nanotube (CNT) networks and analogous materials comprising filamentary nanostructures are governed by the intrinsic filament properties and their hierarchical organization and interconnection. As a result, direct knowledge of the collective dynamics of CNT synthesis and self-organization is essential to engineering improved CNT materials for applications such as membranes and thermal interfaces. Here, we use real-time environmental transmission electron microscopy (E-TEM) to observe nucleation and self-organization of CNTs into vertically aligned forests. Upon introduction of the carbon source, we observe a large scatter in the onset of nucleation of individual CNTs and the ensuing growth rates.more » Experiments performed at different temperatures and catalyst particle densities show the critical role of CNT density on the dynamics of self-organization; low-density CNT nucleation results in the CNTs becoming pinned to the substrate and forming random networks, whereas higher density CNT nucleation results in self-organization of the CNTs into bundles that are oriented perpendicular to the substrate. We also find that mechanical coupling between growing CNTs alters their growth trajectory and shape, causing significant deformations, buckling, and defects in the CNT walls. Therefore, it appears that CNT–CNT coupling not only is critical for self-organization but also directly influences CNT quality and likely the resulting properties of the forest. As a result, our findings show that control of the time-distributed kinetics of CNT nucleation and bundle formation are critical to manufacturing well-organized CNT assemblies and that E-TEM can be a powerful tool to investigate the mesoscale dynamics of CNT networks.« less

How does the 'rest-self overlap' mediate the qualitative and automatic features of self-reference?

PubMed

Northoff, Georg

2016-01-01

The target article points out the qualitative and automatic features of self-reference while leaving open the underlying neural mechanisms. Based on empirical evidence about rest-self overlap and rest-stimulus interaction being special for self-related stimuli, I postulate that the resting state shows self-specific organization. The resting state's self-specific organization may be encoded by activity balances between different networks which in turn predispose the qualitative features of subsequent self-related stimulus-induced activity in, for instance, SAN as well as the automatic features of self-reference effects.

Alignment of Ge nanoislands on Si(111) by Ga-induced substrate self-patterning.

PubMed

Schmidt, Th; Flege, J I; Gangopadhyay, S; Clausen, T; Locatelli, A; Heun, S; Falta, J

2007-02-09

A novel mechanism is described which enables the selective formation of three-dimensional Ge islands. Submonolayer adsorption of Ga on Si(111) at high temperature leads to a self-organized two-dimensional pattern formation by separation of the 7 x 7 substrate and Ga/Si(111)-(square root[3] x square root[3])-R30 degrees domains. The latter evolve at step edges and domain boundaries of the initial substrate reconstruction. Subsequent Ge deposition results in the growth of 3D islands which are aligned at the boundaries between bare and Ga-covered domains. This result is explained in terms of preferential nucleation conditions due to a modulation of the surface chemical potential.

Unraveling the physics of vertical organic field effect transistors through nanoscale engineering of a self-assembled transparent electrode.

PubMed

Ben-Sasson, Ariel J; Tessler, Nir

2012-09-12

While organic transistors' performances are continually pushed to achieve lower power consumption, higher working frequencies, and higher current densities, a new type of organic transistors characterized by a vertical architecture offers a radically different design approach to outperform its traditional counterparts. Naturally, the distinct vertical architecture gives way to different governing physical ground rules and structural key features such as the need for an embedded transparent electrode. In this paper, we make use of a zero-frequency electric field-transparent patterned electrode produced through block-copolymer self-assembly based lithography to control the performances of the vertical organic field effect transistor (VOFET) and to study its governing physical mechanisms. Unlike other VOFET structures, this design, involving well-defined electrode architecture, is fully tractable, allowing for detailed modeling, analysis, and optimization. We provide for the first time a complete account of the physics underpinning the VOFET operation, considering two complementary mechanisms: the virtual contact formation (Schottky barrier lowering) and the induced potential barrier (solid-state triode-like shielding). We demonstrate how each mechanism, separately, accounts for the link between controllable nanoscale structural modifications in the patterned electrode and the VOFET performances. For example, the ON/OFF current ratio increases by up to 2 orders of magnitude when the perforations aspect ratio (height/width) decreases from ∼0.2 to ∼0.1. The patterned electrode is demonstrated to be not only penetrable to zero-frequency electric fields but also transparent in the visible spectrum, featuring uniformity, spike-free structure, material diversity, amenability with flexible surfaces, low sheet resistance (20-2000 Ω sq(-1)) and high transparency (60-90%). The excellent layer transparency of the patterned electrode and the VOFET's exceptional electrical performances make them both promising elements for future transparent and/or efficient organic electronics.

Principal component analysis vs. self-organizing maps combined with hierarchical clustering for pattern recognition in volcano seismic spectra

NASA Astrophysics Data System (ADS)

Unglert, K.; Radić, V.; Jellinek, A. M.

2016-06-01

Variations in the spectral content of volcano seismicity related to changes in volcanic activity are commonly identified manually in spectrograms. However, long time series of monitoring data at volcano observatories require tools to facilitate automated and rapid processing. Techniques such as self-organizing maps (SOM) and principal component analysis (PCA) can help to quickly and automatically identify important patterns related to impending eruptions. For the first time, we evaluate the performance of SOM and PCA on synthetic volcano seismic spectra constructed from observations during two well-studied eruptions at Klauea Volcano, Hawai'i, that include features observed in many volcanic settings. In particular, our objective is to test which of the techniques can best retrieve a set of three spectral patterns that we used to compose a synthetic spectrogram. We find that, without a priori knowledge of the given set of patterns, neither SOM nor PCA can directly recover the spectra. We thus test hierarchical clustering, a commonly used method, to investigate whether clustering in the space of the principal components and on the SOM, respectively, can retrieve the known patterns. Our clustering method applied to the SOM fails to detect the correct number and shape of the known input spectra. In contrast, clustering of the data reconstructed by the first three PCA modes reproduces these patterns and their occurrence in time more consistently. This result suggests that PCA in combination with hierarchical clustering is a powerful practical tool for automated identification of characteristic patterns in volcano seismic spectra. Our results indicate that, in contrast to PCA, common clustering algorithms may not be ideal to group patterns on the SOM and that it is crucial to evaluate the performance of these tools on a control dataset prior to their application to real data.

SOM neural network fault diagnosis method of polymerization kettle equipment optimized by improved PSO algorithm.

PubMed

Wang, Jie-sheng; Li, Shu-xia; Gao, Jie

2014-01-01

For meeting the real-time fault diagnosis and the optimization monitoring requirements of the polymerization kettle in the polyvinyl chloride resin (PVC) production process, a fault diagnosis strategy based on the self-organizing map (SOM) neural network is proposed. Firstly, a mapping between the polymerization process data and the fault pattern is established by analyzing the production technology of polymerization kettle equipment. The particle swarm optimization (PSO) algorithm with a new dynamical adjustment method of inertial weights is adopted to optimize the structural parameters of SOM neural network. The fault pattern classification of the polymerization kettle equipment is to realize the nonlinear mapping from symptom set to fault set according to the given symptom set. Finally, the simulation experiments of fault diagnosis are conducted by combining with the industrial on-site historical data of the polymerization kettle and the simulation results show that the proposed PSO-SOM fault diagnosis strategy is effective.

Unfolding large-scale online collaborative human dynamics

PubMed Central

Zha, Yilong; Zhou, Tao; Zhou, Changsong

2016-01-01

Large-scale interacting human activities underlie all social and economic phenomena, but quantitative understanding of regular patterns and mechanism is very challenging and still rare. Self-organized online collaborative activities with a precise record of event timing provide unprecedented opportunity. Our empirical analysis of the history of millions of updates in Wikipedia shows a universal double–power-law distribution of time intervals between consecutive updates of an article. We then propose a generic model to unfold collaborative human activities into three modules: (i) individual behavior characterized by Poissonian initiation of an action, (ii) human interaction captured by a cascading response to previous actions with a power-law waiting time, and (iii) population growth due to the increasing number of interacting individuals. This unfolding allows us to obtain an analytical formula that is fully supported by the universal patterns in empirical data. Our modeling approaches reveal “simplicity” beyond complex interacting human activities. PMID:27911766

Membrane-bound MinDE complex acts as a toggle switch that drives Min oscillation coupled to cytoplasmic depletion of MinD

PubMed Central

Vecchiarelli, Anthony G.; Li, Min; Mizuuchi, Michiyo; Hwang, Ling Chin; Seol, Yeonee; Neuman, Keir C.; Mizuuchi, Kiyoshi

2016-01-01

The Escherichia coli Min system self-organizes into a cell-pole to cell-pole oscillator on the membrane to prevent divisions at the cell poles. Reconstituting the Min system on a lipid bilayer has contributed to elucidating the oscillatory mechanism. However, previous in vitro patterns were attained with protein densities on the bilayer far in excess of those in vivo and failed to recapitulate the standing wave oscillations observed in vivo. Here we studied Min protein patterning at limiting MinD concentrations reflecting the in vivo conditions. We identified “burst” patterns—radially expanding and imploding binding zones of MinD, accompanied by a peripheral ring of MinE. Bursts share several features with the in vivo dynamics of the Min system including standing wave oscillations. Our data support a patterning mechanism whereby the MinD-to-MinE ratio on the membrane acts as a toggle switch: recruiting and stabilizing MinD on the membrane when the ratio is high and releasing MinD from the membrane when the ratio is low. Coupling this toggle switch behavior with MinD depletion from the cytoplasm drives a self-organized standing wave oscillator. PMID:26884160

Adaptive Classification of Landscape Process and Function: An Integration of Geoinformatics and Self-Organizing Maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Andre M.

2009-07-17

The advanced geospatial information extraction and analysis capabilities of a Geographic Information System (GISs) and Artificial Neural Networks (ANNs), particularly Self-Organizing Maps (SOMs), provide a topology-preserving means for reducing and understanding complex data relationships in the landscape. The Adaptive Landscape Classification Procedure (ALCP) is presented as an adaptive and evolutionary capability where varying types of data can be assimilated to address different management needs such as hydrologic response, erosion potential, habitat structure, instrumentation placement, and various forecast or what-if scenarios. This paper defines how the evaluation and analysis of spatial and/or temporal patterns in the landscape can provide insight intomore » complex ecological, hydrological, climatic, and other natural and anthropogenic-influenced processes. Establishing relationships among high-dimensional datasets through neurocomputing based pattern recognition methods can help 1) resolve large volumes of data into a structured and meaningful form; 2) provide an approach for inferring landscape processes in areas that have limited data available but exhibit similar landscape characteristics; and 3) discover the value of individual variables or groups of variables that contribute to specific processes in the landscape. Classification of hydrologic patterns in the landscape is demonstrated.« less

Self-Organizing Map With Time-Varying Structure to Plan and Control Artificial Locomotion.

PubMed

Araujo, Aluizio F R; Santana, Orivaldo V

2015-08-01

This paper presents an algorithm, self-organizing map-state trajectory generator (SOM-STG), to plan and control legged robot locomotion. The SOM-STG is based on an SOM with a time-varying structure characterized by constructing autonomously close-state trajectories from an arbitrary number of robot postures. Each trajectory represents a cyclical movement of the limbs of an animal. The SOM-STG was designed to possess important features of a central pattern generator, such as rhythmic pattern generation, synchronization between limbs, and swapping between gaits following a single command. The acquisition of data for SOM-STG is based on learning by demonstration in which the data are obtained from different demonstrator agents. The SOM-STG can construct one or more gaits for a simulated robot with six legs, can control the robot with any of the gaits learned, and can smoothly swap gaits. In addition, SOM-STG can learn to construct a state trajectory form observing an animal in locomotion. In this paper, a dog is the demonstrator agent.

Self-organization in the limb: a Turing mechanism for digit development.

PubMed

Cooper, Kimberly L

2015-06-01

The statistician George E. P. Box stated, 'Essentially all models are wrong, but some are useful.' (Box GEP, Draper NR: Empirical Model-Building and Response Surfaces. Wiley; 1987). Modeling biological processes is challenging for many of the reasons classically trained developmental biologists often resist the idea that black and white equations can explain the grayscale subtleties of living things. Although a simplified mathematical model of development will undoubtedly fall short of precision, a good model is exceedingly useful if it raises at least as many testable questions as it answers. Self-organizing Turing models that simulate the pattern of digits in the hand replicate events that have not yet been explained by classical approaches. The union of theory and experimentation has recently identified and validated the minimal components of a Turing network for digit pattern and triggered a cascade of questions that will undoubtedly be well-served by the continued merging of disciplines. Copyright © 2015 Elsevier Ltd. All rights reserved.

Self-assembly of Archimedean tilings with enthalpically and entropically patchy polygons.

PubMed

Millan, Jaime A; Ortiz, Daniel; van Anders, Greg; Glotzer, Sharon C

2014-03-25

Considerable progress in the synthesis of anisotropic patchy nanoplates (nanoplatelets) promises a rich variety of highly ordered two-dimensional superlattices. Recent experiments of superlattices assembled from nanoplates confirm the accessibility of exotic phases and motivate the need for a better understanding of the underlying self-assembly mechanisms. Here, we present experimentally accessible, rational design rules for the self-assembly of the Archimedean tilings from polygonal nanoplates. The Archimedean tilings represent a model set of target patterns that (i) contain both simple and complex patterns, (ii) are comprised of simple regular shapes, and (iii) contain patterns with potentially interesting materials properties. Via Monte Carlo simulations, we propose a set of design rules with general applicability to one- and two-component systems of polygons. These design rules, specified by increasing levels of patchiness, correspond to a reduced set of anisotropy dimensions for robust self-assembly of the Archimedean tilings. We show for which tilings entropic patches alone are sufficient for assembly and when short-range enthalpic interactions are required. For the latter, we show how patchy these interactions should be for optimal yield. This study provides a minimal set of guidelines for the design of anisostropic patchy particles that can self-assemble all 11 Archimedean tilings.

A Model of Self-Organizing Head-Centered Visual Responses in Primate Parietal Areas

PubMed Central

Mender, Bedeho M. W.; Stringer, Simon M.

2013-01-01

We present a hypothesis for how head-centered visual representations in primate parietal areas could self-organize through visually-guided learning, and test this hypothesis using a neural network model. The model consists of a competitive output layer of neurons that receives afferent synaptic connections from a population of input neurons with eye position gain modulated retinal receptive fields. The synaptic connections in the model are trained with an associative trace learning rule which has the effect of encouraging output neurons to learn to respond to subsets of input patterns that tend to occur close together in time. This network architecture and synaptic learning rule is hypothesized to promote the development of head-centered output neurons during periods of time when the head remains fixed while the eyes move. This hypothesis is demonstrated to be feasible, and each of the core model components described is tested and found to be individually necessary for successful self-organization. PMID:24349064

Neuronal avalanches of a self-organized neural network with active-neuron-dominant structure.

PubMed

Li, Xiumin; Small, Michael

2012-06-01

Neuronal avalanche is a spontaneous neuronal activity which obeys a power-law distribution of population event sizes with an exponent of -3/2. It has been observed in the superficial layers of cortex both in vivo and in vitro. In this paper, we analyze the information transmission of a novel self-organized neural network with active-neuron-dominant structure. Neuronal avalanches can be observed in this network with appropriate input intensity. We find that the process of network learning via spike-timing dependent plasticity dramatically increases the complexity of network structure, which is finally self-organized to be active-neuron-dominant connectivity. Both the entropy of activity patterns and the complexity of their resulting post-synaptic inputs are maximized when the network dynamics are propagated as neuronal avalanches. This emergent topology is beneficial for information transmission with high efficiency and also could be responsible for the large information capacity of this network compared with alternative archetypal networks with different neural connectivity.

Organ regeneration based on developmental biology: past and future.

PubMed

Takeo, Makoto; Tsuji, Takashi

2018-06-05

In this decade, great progress has been made in the field of organ regeneration by incorporating emerging concepts from the fields of stem cell biology and developmental biology, and this progress has pioneered a new frontier in regenerative medicine. The generation of bioengineered organ germ-utilizing, fate-determined, organ-inductive epithelial and mesenchymal cells has provided evidence for the concept of functional organ regeneration in vivo. Organoid studies have verified that nearly all organs can be generated in the form of a mini-organ by recapitulating embryonic body patterning and establishing an organ-forming field among self-organizing pluripotent stem cells by utilizing cytokines that mimic the patterning and positional signals of organogenesis. More recently, the regeneration of an integumentary organ system composed of multiple organs, including hair follicles, has been achieved, demonstrating that regenerative medicine is forthcoming. In this review, we will introduce current research trends aimed at regenerating a functional three-dimensional (3D) organ, and we will discuss the potential use of these recent achievements and future directions needed to realize the next-generation of regenerative therapy for organ replacement. Copyright © 2018 Elsevier Ltd. All rights reserved.

Social behavior of bacteria: from physics to complex organization

NASA Astrophysics Data System (ADS)

Ben-Jacob, E.

2008-10-01

I describe how bacteria develop complex colonial patterns by utilizing intricate communication capabilities, such as quorum sensing, chemotactic signaling and exchange of genetic information (plasmids) Bacteria do not store genetically all the information required for generating the patterns for all possible environments. Instead, additional information is cooperatively generated as required for the colonial organization to proceed. Each bacterium is, by itself, a biotic autonomous system with its own internal cellular informatics capabilities (storage, processing and assessments of information). These afford the cell certain plasticity to select its response to biochemical messages it receives, including self-alteration and broadcasting messages to initiate alterations in other bacteria. Hence, new features can collectively emerge during self-organization from the intra-cellular level to the whole colony. Collectively bacteria store information, perform decision make decisions (e.g. to sporulate) and even learn from past experience (e.g. exposure to antibiotics)-features we begin to associate with bacterial social behavior and even rudimentary intelligence. I also take Schrdinger’s’ “feeding on negative entropy” criteria further and propose that, in addition organisms have to extract latent information embedded in the environment. By latent information we refer to the non-arbitrary spatio-temporal patterns of regularities and variations that characterize the environmental dynamics. In other words, bacteria must be able to sense the environment and perform internal information processing for thriving on latent information embedded in the complexity of their environment. I then propose that by acting together, bacteria can perform this most elementary cognitive function more efficiently as can be illustrated by their cooperative behavior.

Associative memory for online learning in noisy environments using self-organizing incremental neural network.

PubMed

Sudo, Akihito; Sato, Akihiro; Hasegawa, Osamu

2009-06-01

Associative memory operating in a real environment must perform well in online incremental learning and be robust to noisy data because noisy associative patterns are presented sequentially in a real environment. We propose a novel associative memory that satisfies these requirements. Using the proposed method, new associative pairs that are presented sequentially can be learned accurately without forgetting previously learned patterns. The memory size of the proposed method increases adaptively with learning patterns. Therefore, it suffers neither redundancy nor insufficiency of memory size, even in an environment in which the maximum number of associative pairs to be presented is unknown before learning. Noisy inputs in real environments are classifiable into two types: noise-added original patterns and faultily presented random patterns. The proposed method deals with two types of noise. To our knowledge, no conventional associative memory addresses noise of both types. The proposed associative memory performs as a bidirectional one-to-many or many-to-one associative memory and deals not only with bipolar data, but also with real-valued data. Results demonstrate that the proposed method's features are important for application to an intelligent robot operating in a real environment. The originality of our work consists of two points: employing a growing self-organizing network for an associative memory, and discussing what features are necessary for an associative memory for an intelligent robot and proposing an associative memory that satisfies those requirements.

Channel Patterns as the Result of Self-Organization Within the Flow-Sediment-Vegetation System

NASA Astrophysics Data System (ADS)

Tal, M.; Paola, C.

2003-12-01

The familiar patterns of braided and meandering rivers can be thought of as the result of self-organization within a "three-phase" system comprising fluid, sediment, and vegetation. Interactions between these three components are also largely responsible for the organization of river systems into separate and distinguishable channels and floodplains. Key elements of the self organization include the space and time characteristics of seed dispersal and plant growth as well as the statistics of occupation, abandonment, and reworking of the bed by the flow. Seeds are transported and dispersed readily by wind and water and opportunistically colonize areas of the channel that are abandoned or exposed at low flows. Vegetation increases bank stability through root reinforcement of the sediment and increases the threshold shear stress needed for erosion. In addition, vegetation offers resistance to the flow by increasing the drag and reducing the velocity, thus decreasing the stream power available for erosion and transport. Vegetation that is not removed while young will become stronger and increasingly resistant to erosion and removal by the flow. Thus a key organizing parameter in the flow-sediment-vegetation system is the time scale for establishment of the vegetation relative to a characteristic channel or bed mobility time. Experiments at the St. Anthony Falls Laboratory demonstrate how repeated cycling of vegetation seeding and water discharge changes an unvegetated braided channel morphology: the flow is gradually corralled into a single sinuous channel that largely tracks the thread of maximum velocity in the original braided network. The experiments are carried out in a large unconsolidated sand bed flume in which alfalfa sprouts are used to simulate riparian vegetation and offer the only form of cohesion in the system. An initial braided pattern is allowed to evolve freely in conjunction with alternating high and low discharges and repeated seedings. As the vegetation density and age increase with time, smaller and weaker channels are choked off leaving a single relatively narrow channel with a sinuous thalweg. This channel develops its own internal bar forms with smaller length scales than the original braid bars.

Analysis of algal bloom risk with uncertainties in lakes by integrating self-organizing map and fuzzy information theory.

PubMed

Chen, Qiuwen; Rui, Han; Li, Weifeng; Zhang, Yanhui

2014-06-01

Algal blooms are a serious problem in waters, which damage aquatic ecosystems and threaten drinking water safety. However, the outbreak mechanism of algal blooms is very complex with great uncertainty, especially for large water bodies where environmental conditions have obvious variation in both space and time. This study developed an innovative method which integrated a self-organizing map (SOM) and fuzzy information diffusion theory to comprehensively analyze algal bloom risks with uncertainties. The Lake Taihu was taken as study case and the long-term (2004-2010) on-site monitoring data were used. The results showed that algal blooms in Taihu Lake were classified into four categories and exhibited obvious spatial-temporal patterns. The lake was mainly characterized by moderate bloom but had high uncertainty, whereas severe blooms with low uncertainty were observed in the northwest part of the lake. The study gives insight on the spatial-temporal dynamics of algal blooms, and should help government and decision-makers outline policies and practices on bloom monitoring and prevention. The developed method provides a promising approach to estimate algal bloom risks under uncertainties. Copyright © 2014 Elsevier B.V. All rights reserved.

Subordinate Imitation of Supervisor Behavior: The Role of Supervisor Power and Subordinate Self-Esteem.

ERIC Educational Resources Information Center

Adler, Seymour

1983-01-01

Examined similarity in the behavior tendencies of subordinates and their supervisors. Respondents were 66 department heads and branch managers in an Israeli banking organization. The overall pattern of results largely supported the applicability of Social Learning Theory to organizational modeling. (JAC)

Real-Time Imaging of Self-Organization and Mechanical Competition in Carbon Nanotube Forest Growth.

PubMed

Balakrishnan, Viswanath; Bedewy, Mostafa; Meshot, Eric R; Pattinson, Sebastian W; Polsen, Erik S; Laye, Fabrice; Zakharov, Dmitri N; Stach, Eric A; Hart, A John

2016-12-27

The properties of carbon nanotube (CNT) networks and analogous materials comprising filamentary nanostructures are governed by the intrinsic filament properties and their hierarchical organization and interconnection. As a result, direct knowledge of the collective dynamics of CNT synthesis and self-organization is essential to engineering improved CNT materials for applications such as membranes and thermal interfaces. Here, we use real-time environmental transmission electron microscopy (E-TEM) to observe nucleation and self-organization of CNTs into vertically aligned forests. Upon introduction of the carbon source, we observe a large scatter in the onset of nucleation of individual CNTs and the ensuing growth rates. Experiments performed at different temperatures and catalyst particle densities show the critical role of CNT density on the dynamics of self-organization; low-density CNT nucleation results in the CNTs becoming pinned to the substrate and forming random networks, whereas higher density CNT nucleation results in self-organization of the CNTs into bundles that are oriented perpendicular to the substrate. We also find that mechanical coupling between growing CNTs alters their growth trajectory and shape, causing significant deformations, buckling, and defects in the CNT walls. Therefore, it appears that CNT-CNT coupling not only is critical for self-organization but also directly influences CNT quality and likely the resulting properties of the forest. Our findings show that control of the time-distributed kinetics of CNT nucleation and bundle formation are critical to manufacturing well-organized CNT assemblies and that E-TEM can be a powerful tool to investigate the mesoscale dynamics of CNT networks.

Self-assemblies of luminescent rare earth compounds in capsules and multilayers.

PubMed

Zhang, Renjie; Shang, Juanjuan; Xin, Jing; Xie, Beibei; Li, Ya; Möhwald, Helmuth

2014-05-01

This review addresses luminescent rare earth compounds assembled in microcapsules as well as in planar films fabricated by the layer-by-layer (LbL) technique, the Langmuir-Blodgett (LB) method and in self-assembled monolayers. Chemical precipitation, electrostatic, van der Waals interactions and covalent bonds are involved in the assembly of these compounds. Self-organized ring patterns of rare earth complexes in Langmuir monolayers and on planar surfaces with stripe patterns, as well as fluorescence enhancement due to donor-acceptor pairs, microcavities, enrichment of rare earth compounds, and shell protection against water are described. Recent information on the tuning of luminescence intensity and multicolors by the excitation wavelength and the ratio of rare earth ions, respectively, are also reviewed. Potential applications of luminescent rare earth complex assemblies serving as biological probes, temperature and gas sensors are pointed out. Copyright © 2014 Elsevier B.V. All rights reserved.

Explaining the relationship between religiousness and substance use: self-control matters.

PubMed

DeWall, C Nathan; Pond, Richard S; Carter, Evan C; McCullough, Michael E; Lambert, Nathaniel M; Fincham, Frank D; Nezlek, John B

2014-08-01

Religiousness is reliably associated with lower substance use, but little research has examined whether self-control helps explain why religiousness predicts lower substance use. Building on prior theoretical work, our studies suggest that self-control mediates the relationship between religiousness and a variety of substance-use behaviors. Study 1 showed that daily prayer predicted lower alcohol use on subsequent days. In Study 2, religiousness related to lower alcohol use, which was mediated by self-control. Study 3 replicated this mediational pattern using a behavioral measure of self-control. Using a longitudinal design, Study 4 revealed that self-control mediated the relationship between religiousness and lower alcohol use 6 weeks later. Study 5 replicated this mediational pattern again and showed that it remained significant after controlling for trait mindfulness. Studies 6 and 7 replicated and extended these effects to both alcohol and various forms of drug use among community and cross-cultural adult samples. These findings offer novel evidence regarding the role of self-control in explaining why religiousness is associated with lower substance use.

Reversal of the sleep-wake cycle by heroin self-administration in rats.

PubMed

Coffey, Alissa A; Guan, Zhiwei; Grigson, Patricia S; Fang, Jidong

2016-05-01

The goal of this study was to examine how heroin self-administration, abstinence, and extinction/reinstatement affect circadian sleep-wake cycles and the associated sleep architecture. We used electroencephalography (EEG) and electromyography (EMG) to measure sleep patterns in male Sprague-Dawley rats over 16 trials of heroin self-administration (acquisition), 14 days of abstinence, and a single day of extinction and drug-induced reinstatement. Rats self-administering heroin showed evidence of reversed (diurnal) patterns of wakefulness, non-rapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep throughout acquisition. During abstinence, their wake and NREM sleep patterns were immediately restored to the normal nocturnal distribution. REM patterns remained inverted for the first 3-6 days of abstinence in heroin self-administering rats. The single extinction/reinstatement test was without effect. These data suggest that heroin may have the ability to affect circadian distribution of sleep and wakefulness, either indirectly, where animals shift their sleep-wake cycle to allow for drug taking, or directly, through wake-promoting actions or actions at circadian oscillators in the brain. Copyright © 2015 Elsevier Inc. All rights reserved.

The relationship between core self-evaluations, views of god, and intrinsic/extrinsic religious motivation.

PubMed

Smither, James W; Walker, Alan G

2015-04-01

Core self-evaluations refer to a higher-order construct that subsumes four well-established traits in the personality literature: self-esteem, generalized self-efficacy, (low) neuroticism, and (internal) locus of control. Studies that have examined the relationship between various measures of religiosity and individual components of core self-evaluations show no clear pattern of relationships. The absence of a clear pattern may be due to the failure of most previous studies in this area to use theory to guide research. Therefore, theories related to core self-evaluations, religious motivation, and views of God were used to develop and test four hypotheses. 220 adults completed measures of four religious attitudes (intrinsic religious motivation, extrinsic religious motivation, viewing God as loving, and viewing God as punitive), general religiosity, and core self-evaluations, separated by 6 weeks (with the order of measures counterbalanced). Multivariate multiple regression, controlling for general religiosity, showed that core self-evaluations were positively related to viewing God as loving, negatively related to viewing God as punitive, and negatively related to extrinsic religious motivation. The hypothesis that core self-evaluations would be positively related to intrinsic religious motivation was not supported.

Reorganization of the human central nervous system.

PubMed

Schalow, G; Zäch, G A

2000-10-01

The key strategies on which the discovery of the functional organization of the central nervous system (CNS) under physiologic and pathophysiologic conditions have been based included (1) our measurements of phase and frequency coordination between the firings of alpha- and gamma-motoneurons and secondary muscle spindle afferents in the human spinal cord, (2) knowledge on CNS reorganization derived upon the improvement of the functions of the lesioned CNS in our patients in the short-term memory and the long-term memory (reorganization), and (3) the dynamic pattern approach for re-learning rhythmic coordinated behavior. The theory of self-organization and pattern formation in nonequilibrium systems is explicitly related to our measurements of the natural firing patterns of sets of identified single neurons in the human spinal premotor network and re-learned coordinated movements following spinal cord and brain lesions. Therapy induced cell proliferation, and maybe, neurogenesis seem to contribute to the host of structural changes during the process of re-learning of the lesioned CNS. So far, coordinated functions like movements could substantially be improved in every of the more than 100 patients with a CNS lesion by applying coordination dynamic therapy. As suggested by the data of our patients on re-learning, the human CNS seems to have a second integrative strategy for learning, re-learning, storing and recalling, which makes an essential contribution of the functional plasticity following a CNS lesion. A method has been developed by us for the simultaneous recording with wire electrodes of extracellular action potentials from single human afferent and efferent nerve fibres of undamaged sacral nerve roots. A classification scheme of the nerve fibres in the human peripheral nervous system (PNS) could be set up in which the individual classes of nerve fibres are characterized by group conduction velocities and group nerve fibre diameters. Natural impulse patterns of several identified single afferent and efferent nerve fibres (motoneuron axons) were extracted from multi-unit impulse patterns, and human CNS functions could be analyzed under physiologic and pathophysiologic conditions. With our discovery of premotor spinal oscillators it became possible to judge upon CNS neuronal network organization based on the firing patterns of these spinal oscillators and their driving afferents. Since motoneurons fire occasionally for low activation and oscillatory for high activation, the coherent organization of subnetworks to generate macroscopic function is very complex and for the time being, may be best described by the theory of coordination dynamics. Since oscillatory firing has also been observed by us in single motor unit firing patterns measured electromyographically, it seems possible to follow up therapeutic intervention in patients with spinal cord and brain lesions not only based on the activity levels and phases of motor programs during locomotion but also based on the physiologic and pathophysiologic firing patterns and recruitment of spinal oscillators. The improvement of the coordination dynamics of the CNS can be partly measured directly by rhythmicity upon the patient performing rhythmic movements coordinated up to milliseconds. Since rhythmic dynamic, coordinated, stereotyped movements are mainly located in the spinal cord and only little supraspinal drive is necessary to initiate, maintain, and terminate them, rhythmic, dynamic, coordinated movements were used in therapy to enforce reorganization of the lesioned CNS by improving the self-organization and relative coordination of spinal oscillators (and their interactions with occasionally firing motoneurons) which became pathologic in their firing following CNS lesion. Paraparetic, tetraparetic spinal cord and brain-lesioned patients re-learned running and other movements by an oscillator formation and coordination dynamic therapy. Our development in neurorehabilitation is in accordance with those of theoretical and computational neurosciences which deal with the self-organization of neuronal networks. In particular, jumping on a springboard 'in-phase' and in 'anti-phase' to re-learn phase relations of oscillator coupling can be understood in the framework of the Haken-Kelso-Bunz coordination dynamic model. By introducing broken symmetry, intention, learning and spasticity in the landscape of the potential function of the integrated CNS activity, the change in self-organization becomes understandable. Movement patterns re-learned by oscillator formation and coordination dynamic therapy evolve from reorganization and regeneration of the lesioned CNS by cooperative and competitive interplay between intrinsic coordination dynamics, extrinsic therapy related inputs with physiologic re-afferent input, including intention, motivation, supervised learning, interpersonal coordination, and genetic constraints including neurogenesis. (ABSTRACT TRUNCATED)

Wnt/Yes-Associated Protein Interactions During Neural Tissue Patterning of Human Induced Pluripotent Stem Cells.

PubMed

Bejoy, Julie; Song, Liqing; Zhou, Yi; Li, Yan

2018-04-01

Human induced pluripotent stem cells (hiPSCs) have special ability to self-assemble into neural spheroids or mini-brain-like structures. During the self-assembly process, Wnt signaling plays an important role in regional patterning and establishing positional identity of hiPSC-derived neural progenitors. Recently, the role of Wnt signaling in regulating Yes-associated protein (YAP) expression (nuclear or cytoplasmic), the pivotal regulator during organ growth and tissue generation, has attracted increasing interests. However, the interactions between Wnt and YAP expression for neural lineage commitment of hiPSCs remain poorly explored. The objective of this study is to investigate the effects of Wnt signaling and YAP expression on the cellular population in three-dimensional (3D) neural spheroids derived from hiPSCs. In this study, Wnt signaling was activated using CHIR99021 for 3D neural spheroids derived from human iPSK3 cells through embryoid body formation. Our results indicate that Wnt activation induces nuclear localization of YAP and upregulates the expression of HOXB4, the marker for hindbrain/spinal cord. By contrast, the cells exhibit more rostral forebrain neural identity (expression of TBR1) without Wnt activation. Cytochalasin D was then used to induce cytoplasmic YAP and the results showed the decreased HOXB4 expression. In addition, the incorporation of microparticles in the neural spheroids was investigated for the perturbation of neural patterning. This study may indicate the bidirectional interactions of Wnt signaling and YAP expression during neural tissue patterning, which have the significance in neurological disease modeling, drug screening, and neural tissue regeneration.

Self-Organization of Microscale Condensate for Delayed Flooding of Nanostructured Superhydrophobic Surfaces.

PubMed

Ölçeroğlu, Emre; McCarthy, Matthew

2016-03-02

Superhydrophobic surfaces enhance condensation by inhibiting the formation of an insulating liquid layer. While this produces efficient heat transfer at low supersaturations, superhydrophobicity has been shown to break down at increased supersaturations. As heat transfer increases, the random distribution and high density of nucleation sites produces pinned droplets, which lead to uncontrollable flooding. In this work, engineered variations in wettability are used to promote the self-organization of microscale droplets, which is shown to effectively delay flooding. Virus-templated superhydrophobic surfaces are patterned with an array of superhydrophilic islands designed to minimize surface adhesion while promoting spatial order. By use of optical and electron microscopy, the surfaces are optimized and characterized during condensation. Mixed wettability imparts spatial order not only through preferential nucleation but more importantly through the self-organization of coalescing droplets at high supersaturations. The self-organization of microscale droplets (diameters of <25 μm) is shown to effectively delay flooding and govern the global wetting behavior of larger droplets (diameters of >1 mm) on the surface. As heat transfer increases, the surfaces transition from jumping-mode to shedding-mode removal with no flooding. This demonstrates the ability to engineer surfaces to resist flooding and can act as the basis for developing robust superhydrophobic surfaces for condensation applications.

Differentiating the Spatiotemporal Distribution of Natural and Anthropogenic Processes on River Water-Quality Variation Using a Self-Organizing Map With Factor Analysis.

PubMed

Wang, Yeuh-Bin; Liu, Chen-Wuing; Lee, Jin-Jing

2015-08-01

To elucidate the historical improvement and advanced measure of river water quality in the Taipei metropolitan area, this study applied the self-organizing map (SOM) technique with factor analysis (FA) to differentiate the spatiotemporal distribution of natural and anthropogenic processes on river water-quality variation spanning two decades. The SOM clustered river water quality into five groups: very low pollution, low pollution, moderate pollution, high pollution, and very high pollution. FA was then used to extract four latent factors that dominated water quality from 1991 to 2011 including three anthropogenic process factors (organic, industrial, and copper pollution) and one natural process factor [suspended solids (SS) pollution]. The SOM revealed that the water quality improved substantially over time. However, the downstream river water quality was still classified as high pollution because of an increase in anthropogenic activity. FA showed the spatiotemporal pattern of each factor score decreasing over time, but the organic pollution factor downstream of the Tamsui River, as well as the SS factor scores in the upstream major tributary (the Dahan Stream), remained within the high pollution level. Therefore, we suggest that public sewage-treatment plants should be upgraded from their current secondary biological processing to advanced treatment processing. The conservation of water and soil must also be reinforced to decrease the SS loading of the Dahan Stream from natural erosion processes in the future.

Statistical-mechanical analysis of self-organization and pattern formation during the development of visual maps

NASA Astrophysics Data System (ADS)

Obermayer, K.; Blasdel, G. G.; Schulten, K.

1992-05-01

We report a detailed analytical and numerical model study of pattern formation during the development of visual maps, namely, the formation of topographic maps and orientation and ocular dominance columns in the striate cortex. Pattern formation is described by a stimulus-driven Markovian process, the self-organizing feature map. This algorithm generates topologically correct maps between a space of (visual) input signals and an array of formal ``neurons,'' which in our model represents the cortex. We define order parameters that are a function of the set of visual stimuli an animal perceives, and we demonstrate that the formation of orientation and ocular dominance columns is the result of a global instability of the retinoptic projection above a critical value of these order parameters. We characterize the spatial structure of the emerging patterns by power spectra, correlation functions, and Gabor transforms, and we compare model predictions with experimental data obtained from the striate cortex of the macaque monkey with optical imaging. Above the critical value of the order parameters the model predicts a lateral segregation of the striate cortex into (i) binocular regions with linear changes in orientation preference, where iso-orientation slabs run perpendicular to the ocular dominance bands, and (ii) monocular regions with low orientation specificity, which contain the singularities of the orientation map. Some of these predictions have already been verified by experiments.

Message framing and defensive processing: a cultural examination.

PubMed

Ko, Deborah M; Kim, Heejung S

2010-01-01

Past research has shown that health messages on safer sexual practices that focus on relational consequences are more persuasive than messages that focus on personal consequences. However, we theorize that it is defensiveness against personal risk framing that threatens the self among people from more individualistic cultures. Two studies tested this idea. Study 1 showed that European Americans were less persuaded by personal framing than by relational framing but that this pattern was not found for Asian Americans, who are more collectivistic. Study 2 showed that these defensive patterns were eliminated among European American participants when a person's self-image was affirmed. These results suggest defensive processes as the mechanism behind the differences in message framing effectiveness and motivate a closer look at cultural patterns.

SURFING BIOLOGICAL SURFACES: EXPLOITING THE NUCLEOID FOR PARTITION AND TRANSPORT IN BACTERIA

PubMed Central

Vecchiarelli, Anthony G.; Mizuuchi, Kiyoshi; Funnell, Barbara E.

2012-01-01

The ParA family of ATPases are responsible for transporting bacterial chromosomes, plasmids, and large protein machineries. ParAs pattern the nucleoid in vivo, but how patterning functions or is exploited in transport is of considerable debate. Here we discuss the process of self-organization into patterns on the bacterial nucleoid and explore how it relates to the molecular mechanism of ParA action. We review ParA-mediated DNA partition as a general mechanism of how ATP-driven protein gradients on biological surfaces can result in spatial organization on a mesoscale. We also discuss how the nucleoid acts as a formidable diffusion barrier for large bodies in the cell, and make the case that the ParA family evolved to overcome the barrier by exploiting the nucleoid as a matrix for movement. PMID:22934804

Labor-force participation patterns of older self-employed workers.

PubMed

Quinn, J F

1980-04-01

Self-employed persons work in a less constrained environment than do most wage-and-salary employees. Generally they are not subject to compulsory retirement nor are they affected by institutional rules concerning labor supply. Data from the 1969 and 1971 interviews of the Retirement History Study show that the labor supply and retirement patterns of the self-employed are distinct from those of other workers. The self-employed (espeically "career" self-employed) nearing retirement age are less likely to be out of the labor force, and those who continue in the labor force have a wider variation in the number of hours worked per year. Downward flexibility in hours (the option for gradual retirement) may be an extremely valuable aspect of self-employed status, and one wonders whether other older workers would also choose this pattern if more flexible opportunities were available. Despite these differences, labor-supply decisions of the self-employed are found to be influenced by many of the same factors that affect the rest of the workforce--health, eligibility for social security and pension benefits, the wage rate, and the flow of asset.

Photo-Induced Self-Condensation, A Technique For Fabricating Organic Lightguide Structures

NASA Astrophysics Data System (ADS)

Franke, H.; Heuer, W.

1986-11-01

Planar lightguides have been fabricated from mixtures of the polymer PMMA with benzoin type photoinitiators. Using conventional UV-photolithography 2 dimensional refractive index patterns were recorded in the polymer films. Thickness and refractive index of the organic lightguides were determined by m-line spectroscopy. The achieved refractive index changes increased with increasing photoinitiator concentrations. For high concentrations (< 70 %) the film refractive index could be increased via UV exposure by Δn = 0.03. Thermal treatment at below 100°C caused the out diffusion of the unexposed photoinitiator and completion of the photochemically induced reaction in the exposed parts of the film. Thus refractive index patterns (Δn < 0.05) could be developed and fixed.

Cohort and duration patterns among Asian immigrants: Comparing trends in obesity and self-rated health

PubMed Central

Ro, Annie; Geronimus, Arline; Bound, John; Griffith, Derek; Gee, Gilbert

2015-01-01

Many studies, but not all, suggest that immigrant health worsens with duration of residence in the U.S. Cohort effects may explain the inconsistent findings; not only are cohort effects confounded with duration, but the timing of entry into the US may also create qualitatively different migration experiences. The present study tests for duration and cohort patterns among Asian immigrants to the United States across six year-of-entry cohorts (pre-1980, 1981-1985, 1986-1990, 1991-1995, 1996-2000, 2001-2005). Data come from the Asian American sample (n=44,002) from the 1994-2009 waves of the National Health Interview Survey. The data show cohort differences for self-rated health, such that more recent cohorts showed improved baseline health compared to older cohorts. After accounting for cohorts, there was no significant change in self-rated health by duration. Older cohorts actually showed improving self-rated health with longer duration. Obesity showed the opposite pattern; there were no differences across cohorts, but duration in the United States correlated with higher obesity. These results imply that immigrant health is not simply an issue of duration and adaptation, but underscore the utility of considering cohorts as broader contexts of migration. Collectively, the results encourage future research that more carefully examines the etiological mechanisms that drive immigrant health. PMID:25879262

Kinetic Monte Carlo simulation of self-organized pattern formation induced by ion beam sputtering using crater functions

NASA Astrophysics Data System (ADS)

Yang, Zhangcan; Lively, Michael A.; Allain, Jean Paul

2015-02-01

The production of self-organized nanostructures by ion beam sputtering has been of keen interest to researchers for many decades. Despite numerous experimental and theoretical efforts to understand ion-induced nanostructures, there are still many basic questions open to discussion, such as the role of erosion or curvature-dependent sputtering. In this work, a hybrid MD/kMC (molecular dynamics/kinetic Monte Carlo) multiscale atomistic model is developed to investigate these knowledge gaps, and its predictive ability is validated across the experimental parameter space. This model uses crater functions, which were obtained from MD simulations, to model the prompt mass redistribution due to single-ion impacts. Defect migration, which is missing from previous models that use crater functions, is treated by a kMC Arrhenius method. Using this model, a systematic study was performed for silicon bombarded by Ar+ ions of various energies (100 eV, 250 eV, 500 eV, 700 eV, and 1000 eV) at incidence angles of 0∘ to 80∘. The simulation results were compared with experimental findings, showing good agreement in many aspects of surface evolution, such as the phase diagram. The underestimation of the ripple wavelength by the simulations suggests that surface diffusion is not the main smoothening mechanism for ion-induced pattern formation. Furthermore, the simulated results were compared with moment-description continuum theory and found to give better results, as the simulation did not suffer from the same mathematical inconsistencies as the continuum model. The key finding was that redistributive effects are dominant in the formation of flat surfaces and parallel-mode ripples, but erosive effects are dominant at high angles when perpendicular-mode ripples are formed. Ion irradiation with simultaneous sample rotation was also simulated, resulting in arrays of square-ordered dots. The patterns obtained from sample rotation were strongly correlated to the rotation speed and to the pattern types formed without sample rotation, and a critical value of about 5 rpm was found between disordered ripples and square-ordered dots. Finally, simulations of dual-beam sputtering were performed, with the resulting patterns determined by the flux ratio of the two beams and the pattern types resulting from single-beam sputtering under the same conditions.

Self-assembled monolayers of shape-persistent macrocycles on graphite: interior design and conformational polymorphism.

PubMed

Vollmeyer, Joscha; Eberhagen, Friederike; Höger, Sigurd; Jester, Stefan-S

2014-01-01

Three shape-persistent naphthylene-phenylene-acetylene macrocycles of identical backbone structures and extraannular substitution patterns but different (empty, apolar, polar) nanopore fillings are self-assembled at the solid/liquid interface of highly oriented pyrolytic graphite and 1,2,4-trichlorobenzene. Submolecularly resolved images of the resulting two-dimensional (2D) crystalline monolayer patterns are obtained by in situ scanning tunneling microscopy. A concentration-dependent conformational polymorphism is found, and open and more dense packing motifs are observed. For all three compounds alike lattice parameters are found, therefore the intermolecular macrocycle distances are mainly determined by their size and symmetry. This is an excellent example that the graphite acts as a template for the macrocycle organization independent from their specific interior.

A new hypothesis and exploratory model for the formation of large-scale inner-shelf sediment sorting and ``rippled scour depressions''

NASA Astrophysics Data System (ADS)

Murray, A. Brad; Thieler, E. Robert

2004-02-01

Recent observations of inner continental shelves in many regions show numerous collections of relatively coarse sediment, which extend kilometers in the cross-shore direction and are on the order of 100 m wide. These "rippled scour depressions" have been interpreted to indicate concentrated cross-shelf currents. However, recent observations strongly suggest that they are associated with sediment transport along-shore rather than cross-shore. A new hypothesis for the origin of these features involves the large wave-generated ripples that form in the coarse material. Wave motions interacting with these large roughness elements generate near-bed turbulence that is greatly enhanced relative to that in other areas. This enhances entrainment and inhibits settling of fine material in an area dominated by coarse sediment. The fine sediment is then carried by mean currents past the coarse accumulations, and deposited where the bed is finer. We hypothesize that these interactions constitute a feedback tending to produce accumulations of fine material separated by self-perpetuating patches of coarse sediments. As with many types of self-organized bedforms, small features would interact as they migrate, leading to a better-organized, larger-scale pattern. As an initial test of this hypothesis, we use a numerical model treating the transport of coarse and fine sediment fractions, treated as functions of the local bed composition—a proxy for the presence of large roughness elements in coarse areas. Large-scale sorted patterns exhibiting the main characteristics of the natural features result robustly in the model, indicating that this new hypothesis offers a plausible explanation for the phenomena.

Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model.

PubMed

Gürsoy, Gamze; Xu, Yun; Liang, Jie

2017-07-01

Nuclear landmarks and biochemical factors play important roles in the organization of the yeast genome. The interaction pattern of budding yeast as measured from genome-wide 3C studies are largely recapitulated by model polymer genomes subject to landmark constraints. However, the origin of inter-chromosomal interactions, specific roles of individual landmarks, and the roles of biochemical factors in yeast genome organization remain unclear. Here we describe a multi-chromosome constrained self-avoiding chromatin model (mC-SAC) to gain understanding of the budding yeast genome organization. With significantly improved sampling of genome structures, both intra- and inter-chromosomal interaction patterns from genome-wide 3C studies are accurately captured in our model at higher resolution than previous studies. We show that nuclear confinement is a key determinant of the intra-chromosomal interactions, and centromere tethering is responsible for the inter-chromosomal interactions. In addition, important genomic elements such as fragile sites and tRNA genes are found to be clustered spatially, largely due to centromere tethering. We uncovered previously unknown interactions that were not captured by genome-wide 3C studies, which are found to be enriched with tRNA genes, RNAPIII and TFIIS binding. Moreover, we identified specific high-frequency genome-wide 3C interactions that are unaccounted for by polymer effects under landmark constraints. These interactions are enriched with important genes and likely play biological roles.

Pattern-formation mechanisms in motility mutants of Myxococcus xanthus

PubMed Central

Starruß, Jörn; Peruani, Fernando; Jakovljevic, Vladimir; Søgaard-Andersen, Lotte; Deutsch, Andreas; Bär, Markus

2012-01-01

Formation of spatial patterns of cells is a recurring theme in biology and often depends on regulated cell motility. Motility of the rod-shaped cells of the bacterium Myxococcus xanthus depends on two motility machineries, type IV pili (giving rise to S-motility) and the gliding motility apparatus (giving rise to A-motility). Cell motility is regulated by occasional reversals. Moving M. xanthus cells can organize into spreading colonies or spore-filled fruiting bodies, depending on their nutritional status. To ultimately understand these two pattern-formation processes and the contributions by the two motility machineries, as well as the cell reversal machinery, we analyse spatial self-organization in three M. xanthus strains: (i) a mutant that moves unidirectionally without reversing by the A-motility system only, (ii) a unidirectional mutant that is also equipped with the S-motility system, and (iii) the wild-type that, in addition to the two motility systems, occasionally reverses its direction of movement. The mutant moving by means of the A-engine illustrates that collective motion in the form of large moving clusters can arise in gliding bacteria owing to steric interactions of the rod-shaped cells, without the need of invoking any biochemical signal regulation. The two-engine strain mutant reveals that the same phenomenon emerges when both motility systems are present, and as long as cells exhibit unidirectional motion only. From the study of these two strains, we conclude that unidirectional cell motion induces the formation of large moving clusters at low and intermediate densities, while it results in vortex formation at very high densities. These findings are consistent with what is known from self-propelled rod models, which strongly suggests that the combined effect of self-propulsion and volume exclusion interactions is the pattern-formation mechanism leading to the observed phenomena. On the other hand, we learn that when cells occasionally reverse their moving direction, as observed in the wild-type, cells form small but strongly elongated clusters and self-organize into a mesh-like structure at high enough densities. These results have been obtained from a careful analysis of the cluster statistics of ensembles of cells, and analysed in the light of a coagulation Smoluchowski equation with fragmentation. PMID:24312730

Self-organized iron-oxide cementation geometry as an indicator of paleo-flows

DOE PAGES

Wang, Yifeng; Chan, Marjorie A.; Merino, Enrique

2015-06-30

Widespread iron oxide precipitation from groundwater in fine-grained red beds displays various patterns, including nodulation, banding and scallops and fingers. Hematite nodules have been reported also from the Meridiani Planum site on Mars and interpreted as evidence for the ancient presence of water on the red planet. Here we show that such patterns can autonomously emerge from a previously unrecognized Ostwald ripening mechanism and they capture rich information regarding ancient chemical and hydrologic environments. A linear instability analysis of the reaction-transport equations suggests that a pattern transition from nodules to bands may result from a symmetry breaking of mineral dissolutionmore » and precipitation triggered by groundwater advection. Round nodules tend to develop under nearly stagnant hydrologic conditions, while repetitive bands form in the presence of persistent water flows. Since water circulation is a prerequisite for a sustainable subsurface life, a Martian site with iron oxide precipitation bands, if one were found, may offer a better chance for detecting extraterrestrial biosignatures on Mars than would sites with nodules.« less

Mathematics and biology: a Kantian view on the history of pattern formation theory.

PubMed

Roth, Siegfried

2011-12-01

Driesch's statement, made around 1900, that the physics and chemistry of his day were unable to explain self-regulation during embryogenesis was correct and could be extended until the year 1972. The emergence of theories of self-organisation required progress in several areas including chemistry, physics, computing and cybernetics. Two parallel lines of development can be distinguished which both culminated in the early 1970s. Firstly, physicochemical theories of self-organisation arose from theoretical (Lotka 1910-1920) and experimental work (Bray 1920; Belousov 1951) on chemical oscillations. However, this research area gained broader acceptance only after thermodynamics was extended to systems far from equilibrium (1922-1967) and the mechanism of the prime example for a chemical oscillator, the Belousov-Zhabotinski reaction, was deciphered in the early 1970s. Secondly, biological theories of self-organisation were rooted in the intellectual environment of artificial intelligence and cybernetics. Turing wrote his The chemical basis of morphogenesis (1952) after working on the construction of one of the first electronic computers. Likewise, Gierer and Meinhardt's theory of local activation and lateral inhibition (1972) was influenced by ideas from cybernetics. The Gierer-Meinhardt theory provided an explanation for the first time of both spontaneous formation of spatial order and of self-regulation that proved to be extremely successful in elucidating a wide range of patterning processes. With the advent of developmental genetics in the 1980s, detailed molecular and functional data became available for complex developmental processes, allowing a new generation of data-driven theoretical approaches. Three examples of such approaches will be discussed. The successes and limitations of mathematical pattern formation theory throughout its history suggest a picture of the organism, which has structural similarity to views of the organic world held by the philosopher Immanuel Kant at the end of the eighteenth century. © The Author(s) 2011. This article is published with open access at Springerlink.com

Observing the restriction of another person: vicarious reactance and the role of self-construal and culture.

PubMed

Sittenthaler, Sandra; Traut-Mattausch, Eva; Jonas, Eva

2015-01-01

Psychological reactance occurs in response to threats posed to perceived behavioral freedoms. Research has shown that people can also experience vicarious reactance. They feel restricted in their own freedom even though they are not personally involved in the restriction but only witness the situation. The phenomenon of vicarious reactance is especially interesting when considered in a cross-cultural context because the cultural specific self-construal plays a crucial role in understanding people's response to self- and vicariously experienced restrictions. Previous studies and our pilot study (N = 197) could show that people with a collectivistic cultural background show higher vicarious reactance compared to people with an individualistic cultural background. But does it matter whether people experience the vicarious restriction for an in-group or an out-group member? Differentiating vicarious-in-group and vicarious-out-group restrictions, Study 1 (N = 159) suggests that people with a more interdependent self-construal show stronger vicarious reactance only with regard to in-group restrictions but not with regard to out-group restrictions. In contrast, participants with a more independent self-construal experience stronger reactance when being self-restricted compared to vicariously-restricted. Study 2 (N = 180) replicates this pattern conceptually with regard to individualistic and collectivistic cultural background groups. Additionally, participants' behavioral intentions show the same pattern of results. Moreover a mediation analysis demonstrates that cultural differences in behavioral intentions could be explained through people's self-construal differences. Thus, the present studies provide new insights and show consistent evidence for vicarious reactance depending on participants' culturally determined self-construal.

Observing the restriction of another person: vicarious reactance and the role of self-construal and culture

PubMed Central

Sittenthaler, Sandra; Traut-Mattausch, Eva; Jonas, Eva

2015-01-01

Psychological reactance occurs in response to threats posed to perceived behavioral freedoms. Research has shown that people can also experience vicarious reactance. They feel restricted in their own freedom even though they are not personally involved in the restriction but only witness the situation. The phenomenon of vicarious reactance is especially interesting when considered in a cross-cultural context because the cultural specific self-construal plays a crucial role in understanding people’s response to self- and vicariously experienced restrictions. Previous studies and our pilot study (N = 197) could show that people with a collectivistic cultural background show higher vicarious reactance compared to people with an individualistic cultural background. But does it matter whether people experience the vicarious restriction for an in-group or an out-group member? Differentiating vicarious-in-group and vicarious-out-group restrictions, Study 1 (N = 159) suggests that people with a more interdependent self-construal show stronger vicarious reactance only with regard to in-group restrictions but not with regard to out-group restrictions. In contrast, participants with a more independent self-construal experience stronger reactance when being self-restricted compared to vicariously-restricted. Study 2 (N = 180) replicates this pattern conceptually with regard to individualistic and collectivistic cultural background groups. Additionally, participants’ behavioral intentions show the same pattern of results. Moreover a mediation analysis demonstrates that cultural differences in behavioral intentions could be explained through people’s self-construal differences. Thus, the present studies provide new insights and show consistent evidence for vicarious reactance depending on participants’ culturally determined self-construal. PMID:26300795

Reversible Self-Assembly of 3D Architectures Actuated by Responsive Polymers.

PubMed

Zhang, Cheng; Su, Jheng-Wun; Deng, Heng; Xie, Yunchao; Yan, Zheng; Lin, Jian

2017-11-29

An assembly of three-dimensional (3D) architectures with defined configurations has important applications in broad areas. Among various approaches of constructing 3D structures, a stress-driven assembly provides the capabilities of creating 3D architectures in a broad range of functional materials with unique merits. However, 3D architectures built via previous methods are simple, irreversible, or not free-standing. Furthermore, the substrates employed for the assembly remain flat, thus not involved as parts of the final 3D architectures. Herein, we report a reversible self-assembly of various free-standing 3D architectures actuated by the self-folding of smart polymer substrates with programmed geometries. The strategically designed polymer substrates can respond to external stimuli, such as organic solvents, to initiate the 3D assembly process and subsequently become the parts of the final 3D architectures. The self-assembly process is highly controllable via origami and kirigami designs patterned by direct laser writing. Self-assembled geometries include 3D architectures such as "flower", "rainbow", "sunglasses", "box", "pyramid", "grating", and "armchair". The reported self-assembly also shows wide applicability to various materials including epoxy, polyimide, laser-induced graphene, and metal films. The device examples include 3D architectures integrated with a micro light-emitting diode and a flex sensor, indicting the potential applications in soft robotics, bioelectronics, microelectromechanical systems, and others.

Neural network modelling and dynamical system theory: are they relevant to study the governing dynamics of association football players?

PubMed

Dutt-Mazumder, Aviroop; Button, Chris; Robins, Anthony; Bartlett, Roger

2011-12-01

Recent studies have explored the organization of player movements in team sports using a range of statistical tools. However, the factors that best explain the performance of association football teams remain elusive. Arguably, this is due to the high-dimensional behavioural outputs that illustrate the complex, evolving configurations typical of team games. According to dynamical system analysts, movement patterns in team sports exhibit nonlinear self-organizing features. Nonlinear processing tools (i.e. Artificial Neural Networks; ANNs) are becoming increasingly popular to investigate the coordination of participants in sports competitions. ANNs are well suited to describing high-dimensional data sets with nonlinear attributes, however, limited information concerning the processes required to apply ANNs exists. This review investigates the relative value of various ANN learning approaches used in sports performance analysis of team sports focusing on potential applications for association football. Sixty-two research sources were summarized and reviewed from electronic literature search engines such as SPORTDiscus, Google Scholar, IEEE Xplore, Scirus, ScienceDirect and Elsevier. Typical ANN learning algorithms can be adapted to perform pattern recognition and pattern classification. Particularly, dimensionality reduction by a Kohonen feature map (KFM) can compress chaotic high-dimensional datasets into low-dimensional relevant information. Such information would be useful for developing effective training drills that should enhance self-organizing coordination among players. We conclude that ANN-based qualitative analysis is a promising approach to understand the dynamical attributes of association football players.

North Atlantic SST Patterns and NAO Flavors

NASA Astrophysics Data System (ADS)

Rousi, E.; Rahmstorf, S.; Coumou, D.

2017-12-01

North Atlantic SST variability results from the interaction of atmospheric and oceanic processes. The North Atlantic Oscillation (NAO) drives changes in SST patterns but is also driven by them on certain time-scales. These interactions are not very well understood and might be affected by anthropogenic climate change. Paleo reconstructions indicate a slowdown of the Atlantic Meridional Overturning Circulation (AMOC) in recent decades leading to a pronounced cold anomaly ("cold blob") in the North Atlantic (Rahmstorf et al., 2015). The latter may favor NAO to be in its negative mode. In this work, sea surface temperature (SST) patterns are studied in relation to NAO variations, with the aim of discovering preferred states and understanding their interactions. SST patterns are analyzed with Self-Organizing Maps (SOM), a clustering technique that helps identify different spatial patterns and their temporal evolution. NAO flavors refer to different longitudinal positions and tilts of the NAO action centers, also defined with SOMs. This way the limitations of the basic, index-based, NAO-definition are overcome, and the method handles different spatially shapes associated with NAO. Preliminary results show the existence of preferred combinations of SSTs and NAO flavors, which in turn affect weather and climate of Europe and North America. The possible influence of the cold blob on European weather is discussed.

From molecular to macroscopic engineering: shaping hydrogen-bonded organic nanomaterials.

PubMed

Yoosaf, K; Llanes-Pallas, Anna; Marangoni, Tomas; Belbakra, Abdelhalim; Marega, Riccardo; Botek, Edith; Champagne, Benoît; Bonifazi, Davide; Armaroli, Nicola

2011-03-07

The self-assembly and self-organization behavior of chromophoric acetylenic scaffolds bearing 2,6-bis(acetylamino)pyridine (1, 2) or uracyl-type (3-9) terminal groups has been investigated by photophysical and microscopic methods. Systematic absorption and luminescence studies show that 1 and 2, thanks to a combination of solvophilic/solvophobic forces and π-π stacking interactions, undergo self-organization in apolar solvents (i.e., cyclohexane) and form spherical nanoparticles, as evidenced by wide-field optical microscopy, TEM, and AFM analysis. For the longer molecular module, 2, a more uniform size distribution is found (80-200 nm) compared to 1 (20-1000 nm). Temperature scans in the range 283-353 K show that the self-organized nanoparticles are reversibly formed and destroyed, being stable at lower temperatures. Molecular modules 1 and 2 were then thoroughly mixed with the complementary triply hydrogen-bonding units 3-9. Depending on the specific geometrical structure of 3-9, different nanostructures are evidenced by microscopic investigations. Combination of modules 1 or 2 with 3, which bears only one terminal uracyl unit, leads to the formation of vesicular structures; instead, when 1 is combined with bis-uracyl derivative 4 or 5, a structural evolution from nanoparticles to nanowires is observed. The length of the wires obtained by mixing 1 and 4 or 1 and 5 can be controlled by addition of 3, which prompts transformation of the wires into shorter rods. The replacement of linear system 5 with the related angular modules 6 and 7 enables formation of helical nanostructures, unambiguously evidenced by AFM. Finally, thermally induced self-assembly was studied in parallel with modules 8 and 9, in which the uracyl recognition sites are protected with tert-butyloxycarbonyl (BOC) groups. This strategy allows further control of the self-assembly/self-organization process by temperature, since the BOC group is completely removed on heating. Microscopy studies show that the BOC-protected ditopic modules 8 self-assemble and self-organize with 1 into ordered linear nanostructures, whereas BOC-protected tritopic system 9 gives rise to extended domains of circular nano-objects in combination with 1. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The effect of self-disclosure skill training on communication patterns of referred couples to counseling clinics.

PubMed

Zarei, Eghbal; Sanaeimanesh, Mehri

2014-01-01

This study aimed to examine the effect of self-disclosure skill training on communication patterns of referred couples to counseling clinics in Bandar Abbas. The applied research design was an experimental study using pre-test and post-test, which was performed on a population of all referred couples to counseling clinics in Bandar Abbas who were interested to participate in a self-disclosure training workshop in response to the announcement. This study was performed on 26 couples who were selected by simple, convenient sampling method; however, they were randomly assigned to the control and experiment groups. A pre-test was administrated before self-disclosure training. The applied instrument includes Christensen and Salavy's scale of communication patterns. Participants in the experiment group had six sessions of training workshop, each lasted for 90 min. After the intervention, both groups answered the questionnaire again. The collected data were analyzed with paired t-test and covariance statistics. The results showed that the intervention led to significant (p < 0.05) increase in mutual constructive communication pattern and a reduction in mutual avoidance, demand/withdraw, demanding man/withdrawing woman communication patterns. It was also found that the training was not effective on the communication pattern of demanding woman/withdrawing man. The training of simple, but important skills of self-disclosure can help couples to improve their communication and consequently improve their marital satisfaction.