Sorting of Chiral Microswimmers

Microscopic swimmers, e.g., chemotactic bacteria and cells, are capable of directed motion by exerting a force on their environment. For asymmetric microswimmers, e.g., bacteria, spermatozoa and many artificial active colloidal particles, a torque is also present leading in two dimensions to circular motion and in three dimensions to helicoidal motion with a well-defined chirality. Here, we demonstrate with numerical simulations in two dimensions how the chirality of circular motion couples to chiral features present in the microswimmer environment. Levogyre and dextrogyre microswimmers as small as $50\,\mathrm{nm}$ can be separated and selectively trapped in \emph{chiral flowers} of ellipses. Patterned microchannels can be used as \emph{funnels} to rectify the microswimmer motion, as \emph{sorters} to separate microswimmers based on their linear and angular velocities, and as \emph{sieves} to trap microswimmers with specific parameters. We also demonstrate that these results can be extended to helicoidal motion in three dimensions.Comment: 9 pages, 7 figure

Sorting of chiral microswmmers

Ankara : The Department of Physics and the Graduate School of Engineering and Science of Bilkent University, 2014.Thesis (Master's) -- Bilkent University, 2014.Includes bibliographical references leaves 40-42.Microscopic swimmers, for example chemotactic bacteria and cells, are capable of directed motion by exerting a force on their environment. In some cases, including bacteria and spermatozoa swimming near boundaries, or many asymmetrical artificial microswimmers, the driving force and propulsion direction are misaligned. In those situations a torque acting on the microswimmers arises, resulting in motion with a well-defined chirality which is circular in two dimensions and helicoidal in three dimensions. In this thesis, I demonstrate with numerical simulations in two dimensions, how the chirality of the circular motion can couple to chiral features present in the microswimmer environment. I show that by employing static chiral pattern of elliptical obstacles in their environment, microswimmers can be separated on the basis of their motion parameters. In particular, levogyre and dextrogyre microswimmers as small as 50nm can be separated and selectively trapped in chiral flowers of ellipses. Patterned microchannels can be used as funnels to rectify the microswimmer motion, as sorters to separate microswimmers based on their linear and angular velocities, and as sieves to trap microswimmers with specific parameters. I also demonstrate that these results can be extended to helicoidal motion in three dimensions.Mijalkov, MiteM.S

Engineering sensorial delay to control phototaxis and emergent collective behaviors

Collective motions emerging from the interaction of autonomous mobile individuals play a key role in many phenomena, from the growth of bacterial colonies to the coordination of robotic swarms. For these collective behaviours to take hold, the individuals must be able to emit, sense and react to signals. When dealing with simple organisms and robots, these signals are necessarily very elementary, e.g. a cell might signal its presence by releasing chemicals and a robot by shining light. An additional challenge arises because the motion of the individuals is often noisy, e.g. the orientation of cells can be altered by Brownian motion and that of robots by an uneven terrain. Therefore, the emphasis is on achieving complex and tunable behaviors from simple autonomous agents communicating with each other in robust ways. Here, we show that the delay between sensing and reacting to a signal can determine the individual and collective long-term behavior of autonomous agents whose motion is intrinsically noisy. We experimentally demonstrate that the collective behaviour of a group of phototactic robots capable of emitting a radially decaying light field can be tuned from segregation to aggregation and clustering by controlling the delay with which they change their propulsion speed in response to the light intensity they measure. We track this transition to the underlying dynamics of this system, in particular, to the ratio between the robots' sensorial delay time and the characteristic time of the robots' random reorientation. Supported by numerics, we discuss how the same mechanism can be applied to control active agents, e.g. airborne drones, moving in a three-dimensional space.Comment: 8 pages, 5 figure

Sex differences in multilayer functional network topology over the course of aging in 37543 UK Biobank participants

AbstractAging is a major risk factor for cardiovascular and neurodegenerative disorders, with considerable societal and economic implications. Healthy aging is accompanied by changes in functional connectivity between and within resting-state functional networks, which have been associated with cognitive decline. However, there is no consensus on the impact of sex on these age-related functional trajectories. Here, we show that multilayer measures provide crucial information on the interaction between sex and age on network topology, allowing for better assessment of cognitive, structural, and cardiovascular risk factors that have been shown to differ between men and women, as well as providing additional insights into the genetic influences on changes in functional connectivity that occur during aging. In a large cross-sectional sample of 37,543 individuals from the UK Biobank cohort, we demonstrate that such multilayer measures that capture the relationship between positive and negative connections are more sensitive to sex-related changes in the whole-brain connectivity patterns and their topological architecture throughout aging, when compared to standard connectivity and topological measures. Our findings indicate that multilayer measures contain previously unknown information on the relationship between sex and age, which opens up new avenues for research into functional brain connectivity in aging

Beyindeki kompleks ağları analiz etmek için graf teorisi

Cataloged from PDF version of article.Thesis (Ph.D.): Bilkent University, Department of Materials Science and Nanotechnology, İhsan Doğramacı Bilkent University, 2018.Includes bibliographical references (leaves 191-216).The brain is a large-scale, intricate web of neurons, known as the connectome. By representing the brain as a network i.e. a set of nodes connected by edges, one can study its organization by using concepts from graph theory to evaluate various measures. We have developed BRAPH - BRain Analysis using graPH theory, a MatLab, object-oriented freeware that facilitates the connectivity analysis of brain networks. BRAPH provides user-friendly interfaces that guide the user through the various steps of the connectivity analysis, such as, calculating adjacency matrices, evaluating global and local measures, performing group comparisons by non-parametric permutations and assessing the communities in a network. To demonstrate its capabilities, we performed connectivity analyses of structural and functional data in two separate studies. Furthermore, using graph theory, we showed that structural magnetic resonance imaging (MRI) undirected networks of stable mild cognitive impairment (sMCI) subjects, late MCI converters (lMCIc), early MCI converters (eMCIc), and Alzheimer’s Disease (AD) patients show abnormal organization. This is indicated, at global level, by decreases in clustering and transitivity accompanied by increases in path length and modularity and, at nodal level, by changes in nodal clustering and closeness centrality in patient groups when compared to controls. In samples that do not exhibit differences in the undirected analysis, we propose the usage of directed networks to assess any topological changes due to a neurodegenerative disease. We demonstrate that such changes can be identified in Alzheimer’s and Parkinson’s patients by using directed networks built by delayed correlation coefficients. Finally, we put forward a method that improves the reconstruction of the brain connectome by utilizing the delays in the dynamic behavior of the neurons. We show that this delayed correlation method correctly identifies 70% to 80% of the real connections in simulated networks and performs well in the identification of their global and nodal properties.by Mite Mijalkov.Ph.D

Delayed correlations improve the reconstruction of the brain connectome.

The brain works as a large-scale complex network, known as the connectome. The strength of the connections between two brain regions in the connectome is commonly estimated by calculating the correlations between their patterns of activation. This approach relies on the assumption that the activation of connected regions occurs together and at the same time. However, there are delays between the activation of connected regions due to excitatory and inhibitory connections. Here, we propose a method to harvest this additional information and reconstruct the structural brain connectome using delayed correlations. This delayed-correlation method correctly identifies 70% to 80% of connections of simulated brain networks, compared to only 5% to 25% of connections detected by the standard methods; this result is robust against changes in the network parameters (small-worldness, excitatory vs. inhibitory connection ratio, weight distribution) and network activation dynamics. The delayed-correlation method predicts more accurately both the global network properties (characteristic path length, global efficiency, clustering coefficient, transitivity) and the nodal network properties (nodal degree, nodal clustering, nodal global efficiency), particularly at lower network densities. We obtain similar results in networks derived from animal and human data. These results suggest that the use of delayed correlations improves the reconstruction of the structural brain connectome and open new possibilities for the analysis of the brain connectome, as well as for other types of networks

Directed Functional Brain Connectivity is Altered in Sub-threshold Amyloid-β Accumulation in Cognitively Normal Individuals

Several studies have shown that amyloid-β (Aβ) deposition below the clinically relevant cut-off levels is associated with subtle changes in cognitive function and increases the risk of developing future Alzheimer’s disease (AD). Although functional MRI is sensitive to early alterations occurring during AD, sub-threshold changes in Aβ levels have not been linked to functional connectivity measures. This study aimed to apply directed functional connectivity to identify early changes in network function in cognitively unimpaired participants who, at baseline, exhibit Aβ accumulation below the clinically relevant threshold. To this end, we analyzed baseline functional MRI data from 113 cognitively unimpaired participants of the Alzheimer’s Disease Neuroimaging Initiative cohort who underwent at least one 18 F-florbetapir-PET after the baseline scan. Using the longitudinal PET data, we classified these participants as Aβ negative (Aβ−) non-accumulators (n = 46) and Aβ− accumulators (n = 31). We also included 36 individuals who were amyloid-positive (Aβ+) at baseline and continued to accumulate Aβ (Aβ+ accumulators). For each participant, we calculated whole-brain directed functional connectivity networks using our own anti-symmetric correlation method and evaluated their global and nodal properties using measures of network segregation (clustering coefficient) and integration (global efficiency). When compared to Aβ− non-accumulators, the Aβ− accumulators showed lower global clustering coefficient. Moreover, the Aβ+ accumulator group exhibited reduced global efficiency and clustering coefficient, which at the nodal level mainly affected the superior frontal gyrus, anterior cingulate cortex, and caudate nucleus. In Aβ− accumulators, global measures were associated with lower baseline regional PET uptake values, as well as higher scores on the Modified Preclinical Alzheimer Cognitive Composite. Our findings indicate that directed connectivity network properties are sensitive to subtle changes occurring in individuals who have not yet reached the threshold for Aβ positivity, which makes them a potentially viable marker to detect negative downstream effects of very early Aβ pathology

Il diluvio azteco, l’evangelizzazione e la persistenza dei modelli narrativi nelle società indigene messicane

L’articolo propone una riflessione su un tema mitologico rinvenuto dai primi evangelizzatori dei popoli amerindiani nella tradizione religiosa nahua preispanica, nel quale i primi uomini sopravvissuti a un diluvio per certi versi simile a quello biblico offendono gli dèi e vengono da questi trasformati in cani, da cui poi discenderebbero alcune delle popolazioni della Mesoamerica. Un motivo narrativo che, mescolatosi con la versione vetero-testamentaria dell’arca, persiste nella narrativa orale di molti gruppi indigeni del Messico contemporaneo. Attraverso il raffronto e una sommaria analisi delle prime versioni del racconto azteco del diluvio e di quelle raccolte recentemente in una comunità indigena di Oaxaca, l’articolo propone alcune considerazioni circa le ragioni della persistenza di certi elementi narrativi e i criteri che hanno ispirato la loro rielaborazione e adattamento nell’attuale versione del racconto del diluvio huave.The article proposes a reflection on a mythological theme found by the early evangelizers of the American people in the pre-Hispanic Nahua tradition, in which the first survivors of a flood in some respects similar to that of the Bible, offend the gods and are transformed into dogs, which in turn give origin to some of the peoples of Mesoamerica. A narrative motif that, blended with the arch-testamentary version of the ark, persists in the oral narrative of many indigenous groups in contemporary Mexico. By comparing and analyzing the early versions of the Aztec tale of the flood and those recently collected in an indigenous community in Oaxaca, the article offers some considerations about the reasons for the persistence of some narrative elements and the criteria that have inspired their re-elaboration and adaptation into the current version of the Huave flood story

Media 9: Computational toolbox for optical tweezers in geometrical optics

Originally published in JOSA B on 01 May 2015 (josab-32-5-B11