Dynamics Of Cluster Formation Research Articles

In silico and physico-chemical characterization of cluster formation dynamics in peptide solutions

Although antimicrobial peptides are considered one of the most promising alternatives to conventional antibiotics given the alarming increase in bacterial multidrug resistance, many aspects of their mechanism of action remain unclear, in particular the emergence and role of collective phenomena such as the spontaneous formation of nano-sized unstructured objects (clusters) and their effects on the biodynamics. We study this process using two novel peptides from the mucus of the garden snail Cornu aspersum as an example to reveal its dynamics and bioactivity implications through coordinated in silico and in vitro techniques — molecular dynamics simulations, UV–Vis and fluorescence spectroscopy, and antibacterial activity tests against two representative bacterial strains — one gram-negative (Escherichia coli 3458) and one gram-positive (Bacillus subtilis). The results obtained confirm the impact of the aggregation processes of the peptides on their biological activity and provide insight into possible synergies in their action.

Role of Charge Ordering in the Dynamics of Cluster Formation in Associated Liquids.

Liquids are archetypes of disordered systems, yet liquids of polar molecules are locally more ordered than nonpolar molecules, due to the Coulomb interaction based charge ordering phenomenon. Hydrogen bonded liquids, such as water or alcohols, for example, represent a special type of polar liquids, in that they form labile clustered local structures. For water, in particular, hydrogen bonding and the related local tetrahedrality, play an important role in the various attempts to understand this liquid. However, labile structures imply dynamics, and it is not clear how it affects the understanding of this type of liquids from purely static point of view. Herein, we propose to reconsider hydrogen bonding as a charge ordering process. This concept allows us to demonstrate the insufficiency of the analysis of the microscopic structure based solely on static pair correlation functions, and the need for dynamical correlation functions, both in real and reciprocal space. The subsequent analysis allows to recover several aspects of our understanding of hydrogen bonded liquids, but from the charge order perspective. For water, it confirms the jump rotation picture found recently, and it allows to rationalize the contradicting pictures that arise when following the interpretations based on hydrogen bonding. For alcohols, it allows to understand the dynamical origin of the scattering prepeak, which does not exist for water, despite the fact that both these liquids have very similar hydroxyl group chain clusters. The concept of charge ordering complemented by the analysis of dynamical correlation functions appear as a promising way to understand microheterogeneity in complex liquids and mixtures from kinetics point of view.

The role of hydration in atmospheric salt particle formation.

New-particle formation from condensable acid and base molecules is a ubiquitous phenomenon in the atmosphere. The role of water in salt particle formation is not fully understood as it can stabilize or destabilize cluster structures, which leads to non-linear effects on cluster formation dynamics. In the studied systems, increased relative humidity can enhance the particle formation for up to four orders of magnitude in the case of nitric acid, but it can also slightly reduce the particle formation in the cases of sulfuric acid and methanesulfonic acid. As the effect of relative humidity in salt particle formation varies many orders of magnitude depending on the acid and base molecules, neglecting hydration or using the same value for different systems may introduce remarkable inaccuracies in large-scale models.

Formation of heterogeneous clusters in superfluid helium nanodroplets: phthalocyanine and water.

Clusters consisting of a single phthalocyanine molecule and a single water molecule are investigated by means of electronic spectroscopy in superfluid helium droplets. A recent spectroscopic study of those clusters [J. Fischer, F. Schlaghaufer, E.-M. Lottner, A. Slenczka, L. Christiansen, H. Stapelfeldt, M. Karra, B. Friedrich, T. Mullan, M. Schütz and D. Usvyat, J. Phys. Chem. A, 2019, 123, 10057-10064] which all exhibit a water induced electronic shift to the red is now complemented by the corresponding clusters exhibiting a water induced shift to the blue. These clusters will be analyzed by means of fluorescence excitation spectra, dispersed emission spectra, and additional experimental observations made feasible by helium droplets as cryogenic reactor. Together with the blue shifted clusters a total number of at least 6 isomeric variants could be identified in helium droplets. This contrasts to a number of only three isomeric variants obtained from quantum chemical calculations [J. Fischer, F. Schlaghaufer, E.-M. Lottner, A. Slenczka, L. Christiansen, H. Stapelfeldt, M. Karra, B. Friedrich, T. Mullan, M. Schütz and D. Usvyat, J. Phys. Chem. A, 2019, 123, 10057-10064] disregarding the helium environment and to a single isomer identified in a molecular beam experiment [J. Menapace and E. Bernstein, J. Chem. Phys., 1987, 87, 6877-6889]. The discrepancy in the number of isomers provides evidence of a profound involvement of helium in clustering. Moreover, the discrepancies between the gas phase experiment and quantum chemical calculations similarly reveal the influence of the dynamics of cluster formation on the population of global and local minima that are accessible as isomeric variants.

Enzyme Synergy in Transient Clusters of Endo- and Exocellulase Enables a Multilayer Mode of Processive Depolymerization of Cellulose.

Biological degradation of cellulosic materials relies on the molecular-mechanistic principle that internally chain-cleaving endocellulases work synergistically with chain end-cleaving exocellulases in polysaccharide chain depolymerization. How endo–exo synergy becomes effective in the deconstruction of a solid substrate that presents cellulose chains assembled into crystalline material is an open question of the mechanism, with immediate implications on the bioconversion efficiency of cellulases. Here, based on single-molecule evidence from real-time atomic force microscopy, we discover that endo- and exocellulases engage in the formation of transient clusters of typically three to four enzymes at the cellulose surface. The clusters form specifically at regular domains of crystalline cellulose microfibrils that feature molecular defects in the polysaccharide chain organization. The dynamics of cluster formation correlates with substrate degradation through a multilayer-processive mode of chain depolymerization, overall leading to the directed ablation of single microfibrils from the cellulose surface. Each multilayer-processive step involves the spatiotemporally coordinated and mechanistically concerted activity of the endo- and exocellulases in close proximity. Mechanistically, the cooperativity with the endocellulase enables the exocellulase to pass through its processive cycles ∼100-fold faster than when acting alone. Our results suggest an advanced paradigm of efficient multienzymatic degradation of structurally organized polymer materials by endo–exo synergetic chain depolymerization.

Nuclear α-particle Condensation and Dynamics of Cluster Formation

Nuclear α-particle Condensation and Dynamics of Cluster Formation

Alpha condensate and dynamics of cluster formation

The picture of alpha condensation is extended to a general concept of nonlocalized clustering, which is the so-called container picture and is applicable to promisingly all the cluster structures. The extended version of the so-called THSR wave function demonstrates the competition between the localized and nonlocalized cluster motions and then leads to the concept of the container, which plays a role in trapping the constituent clusters in a flexible way. It is also shown that the path of cluster evolution, which is indicated by the Ikeda diagram, can be described by the evolution of the container.

CLUSTER CREATING CONDITIONS

The dynamics of cluster formation in the context of the federal districts and Russia as a whole has been considered, trends in the development of cluster initiatives, as well as the basic principles for creating clusters have been analysed. It is shown that, since 2015, there has been a significant decrease in growth, and the Central Federal and Volga Federal districts are leading among the Federal subjects. It has been identified that in the process of creating a cluster the conducting approach dominates, which is manifested in the initiative of the state. It has been noted that among the principles of cluster formation, traditional rules prevail that are typical for world practice. An algorithmic scheme for creating a cluster based on the results of the formation of a cluster strategy with the subsequent development and implementation of a project to create such a cluster has been constructed.

Assessment of innovative development potential of a macroregion within the multilevel clustering model

The object of this research is the potential of innovative development of Volga Region. The subject of this research is assessment of the processes of innovative transformation of economic systems of Volga Region. Special attention is given to the analysis of peculiarities of spatial distribution of the potential for the development of innovative economy in the context of cluster policy. The author examines the dynamics of cluster formation in the Russian Federation and Volga Federal District, as well as the level of institutional development of the clusters formed in the Volga Region. Based on the previous research, the geographical zones of Volga Region are classified by the author into macroregions, districts, and interregional clusters; on each level of the proposed multilevel model can be determined the leading region and lagging regions. For assessing the innovative transformation of economic systems of Volga Region, the author developed the methodology for comprehensive analysis of innovative development potential of the regions. The outcome Index of innovative development potential of the region (IRIDP) is formed on the basis of four subindexes: index of economic potential of innovative development (IEP-1); index of human resource potential of innovative development (IHRP-2); index of financial potential of innovative development (IFP-3); index of scientific and technological potential of innovative development (ISTP-4). In the course of analysis of the processes of clusterization of the economy of Volga Region, the author determined a significant differentiation of economic space from the perspective of institutionalization of clusters. Nonuniformity of distribution of the clusters by regions, as well as differences in the level of their development, are substantiated by the objective economic-geographical prerequisites and by the performance regional authorities within the framework of federal cluster development projects. The formulated conclusions can serve as the foundation for the formation of spatial contours and vectors of a new stage of clusterization of the economy of Volga Region; its implementation of should consider the complementary nature of innovative and cluster activity of the regions.

Cavitation Clusters in Lipid Systems: The Generation of a Bifurcated Streamer and the Dual Collapse of a Bubble Cluster

AbstractSeveral studies have reported the use of high‐intensity ultrasound (HIU) to induce the crystallization of lipids. The effect that HIU has on lipid crystallization is usually attributed to the generation of cavities but acoustic cavitation has never been fully explored in lipids. The dynamics of a particular cavitation cluster next to a piston like emitter (PLE) in an oil was investigated in this study. The lipid systems, which are important in food processing, are studied with high‐speed camera imaging, laser scattering, and acoustic pressure measurements. A sequence of stable clusters was noted. In addition, a bifurcated streamer was detected, which exists within a sequence of clusters. This is shown to originate from two clusters on the PLE tip oscillating with a 180° phase shift in time with respect to one another. Finally, the collapse phase of the cluster is shown to involve a rapid (~10 μs) two‐stage process. These results show that the dynamics of cluster formation and collapse is driven by HIU power levels and might have implications in lipid sonocrystallization.

Effect of Financial Crisis in Efficiency and Strategic Homogeneity of Indian Commercial Banks: An Empirical Investigation

The financial crisis has send shock waves cutting across boundaries and economies. Major economies are still struggling to recover. The cause of the crisis was primarily the inefficiency of the banking system to manage their sub -prime asset class. It reflected the importance of efficiency of the banking system irrespective of the credit rating which signifies its quality of asset class. In the contemporary world economy no economic system can remain isolated. Indian banking system also felt the shock but managed it efficiently. This motivates for a comprehensive analysis to discover whether the so called resilience was due to some policy stimulus or the Indian banking industry is intrinsically efficient. Also, the pattern of grouping of the banks plays an important role in providing stability in the inter-connected system. Thus technical analysis of the banks along with the dynamics of cluster formation after factoring the pre and post financial crisis time periods was studied , so that it can provide valuable inputs in designing strategic outlook regarding the Indian banking industry. Key words: Technical Efficiency, DEA, Indian Commercial Banks, Cluster Analysis

USE OF LENGTH-BASED SIMILARITY MEASURE IN CLUSTERING PROBLEMS

Context. The study is devoted to the development of a flexible mathematical apparatus, which should have a sufficiently wide range of means for grouping objects into different types of similarity measures. This makes it possible, within the framework of the developed approach, to efficiently solve sufficiently broad classes of applied problems from different subject areas and to partition objects with clusters of different geometric forms. Objective. The aim of the study is improvement of the efficiency of solving cluster problems by applying a similar measure of the vector characteristics of objects. Method. A fuzzy binary relation and its membership function describing the similarity of objects according to the level of similarity of their vector attributes are described. The method of single-level clustering, based on fuzzy binary relations for the use of a similarity measure, is modified. In this case, certain values are set – the thresholds of clusterization that characterize the similarity degree of objects within the cluster. By changing the thresholds of clusterization, one can analyze the dynamics of cluster formation, investigate their structure and interrelationships between objects, determine the ultimate objects, and make a thorough analysis of the obtained results. The proposed approach does not require a preliminary determination of the number of clusters and allows clustering of data in concentric spheres in the absence of additional a priori information, so it can be used at the stage of preliminary data analysis. Results. The developed approach is implemented in the form of a software system on the basis of which the actual applied problem of investigating the intensity of population migration by regions of Ukraine is solved. Conclusions. The conducted experimental researches show the convenience and efficiency of using the similarity measure for solving applied problems requiring clustering in the form of concentric spheres. The presented approach provides an opportunity to conduct new meaningful studies of input data. Prospects for further research are development of a decision support system, to solve the problems of grouping objects into clusters by concentric spheres, cones, ellipses and their intersections; implementation of parallel multi-level clustering carried out simultaneously by several criteria of similarity of objects and their application; study of the partitioning of objects by different geometric forms of clusters for a single sample of input data and carrying out a meaningful interpretation of the obtained results

Container evolution and dynamics of cluster formation

We introduce the so-called Tohsaki-Horiuchi-Schuck-Röpke (THSR) wave function to describe various nuclear cluster states. Its importance, applicability, and usefulness are extensively discussed in this report. It is demonstrated that the THSR wave function provides a “container” picture for cluster structures and even an evolution of the container, for a couple of typical examples, such as 20Ne, 12C, and 16O nuclei.

Study of the cluster formation dynamics and its affect on generation of THz and X-Ray radiation in the expanding gas jet

Study of the cluster formation dynamics and its affect on generation of THz and X-Ray radiation in the expanding gas jet

Temperature-dependent BN cluster formation dynamics from a boron cluster: Density-functional tight-binding molecular dynamics simulations

The time-evolution dynamics of a boron nitride (BN) cluster from an amorphous B cluster is simulated by quantum chemical molecular dynamics based on the density-functional tight-binding method. In the simulations, N atoms are sequentially supplied around the B cluster in conjunction with the arc-melting BN fullerene synthesis from B-rich compounds. The simulations are performed at 1000, 1500, 2000, 2500, and 3000K, and we run 30 trajectories for 200ps at each temperature. At low temperature (1000K), the BN clusters tend to form stuffed cage structures, characterized by internal BN branched units. As the temperature increases, the proportion of stuffed cage structures decreases, whereas that of cage-like structure increases. At intermediate temperatures (2000 and 2500K), most of the BN clusters develop into hollow structures, exhibiting a strong cage forming preference. At 3000K, the BN clusters tend to form sparse branched chain structures, without forming cage-like structures. Mobility analysis of the cluster atoms at all the temperatures reveals that the transition from a liquid-like state to a solid-like state occurs at 2000 and 2500K, whereas the cluster remains in a solid-like state at 1000K and a liquid-like state at 3000K. The N2 dissociation reactions from the BN cluster proceed through various N2 unit formation processes in the BN cluster. We describe details of the representative N2 unit formation processes classified by the bonding of the cluster N atoms.

Mechanisms for impulsive energy dissipation and small-scale effects in microgranular media.

We study impulse response in one-dimensional homogeneous microgranular chains on a linear elastic substrate. Microgranular interactions are analytically described by the Schwarz contact model which includes nonlinear compressive as well as snap-to and from-contact adhesive effects forming a hysteretic loop in the force deformation relationship. We observe complex transient dynamics, including disintegration of solitary pulses, local clustering, and low-to-high-frequency energy transfers resulting in enhanced energy dissipation. We study in detail the underlying dynamics of cluster formation in the impulsively loaded medium and relate enhanced energy dissipation to the rate of cluster formation. These unusual and interesting dynamical phenomena are shown to be robust over a range of physically feasible conditions and are solely scale effects since they are attributed to surface forces, which have no effect at the macroscale. We establish a universal relation between the reclustering rate and the effective damping in these systems. Our findings demonstrate that scale effects generating new nonlinear features can drastically affect the dynamics and acoustics of microgranular materials.

Scaling of clusters near discontinuous percolation transitions in hyperbolic networks.

We investigate the onset of the discontinuous percolation transition in small-world hyperbolic networks by studying the systems-size scaling of the typical largest cluster approaching the transition, p ↗ p(c). To this end, we determine the average size of the largest cluster 〈s(max)〉 ∼ N(Ψ(p)) in the thermodynamic limit using real-space renormalization of cluster-generating functions for bond and site percolation in several models of hyperbolic networks that provide exact results. We determine that all our models conform to the recently predicted behavior regarding the growth of the largest cluster, which found diverging, albeit subextensive, clusters spanning the system with finite probability well below p(c) and at most quadratic corrections to unity in Ψ(p) for p ↗ p(c). Our study suggests a large universality in the cluster formation on small-world hyperbolic networks and the potential for an alternative mechanism in the cluster formation dynamics at the onset of discontinuous percolation transitions.

Dynamics of cluster formation in driven magnetic colloids dispersed on a monolayer

We report computer simulation results on the cluster formation of dipolar colloidal particles driven by a rotating external field in a quasi-two-dimensional setup. We focus on the interplay between permanent dipolar and hydrodynamic interactions and its influence on the dynamic behavior of the particles. This includes their individual as well as their collective motion. To investigate these characteristics, we employ Brownian dynamics simulations of a finite system with and without hydrodynamic interactions. Our results indicate that hydrodynamic interactions have a profound impact on the dynamic behavior of the clusters and the dynamics of the clustering process.

Study of Swarm Behavior in Modeling and Simulation of Cluster Formation in Nanofluids

Modeling the multiagents cooperative systems inspired from biological self-organized systems in the context of swarm model has been under great considerations especially in the field of the cooperation of multi robots. These models are trying to optimize the behavior of artificial multiagent systems by introducing a consensus, which is a mathematical model between the agents as an intelligence property for each member of the swarm set. The application of this novel approach in the modeling of nonintelligent multi agents systems in the field of cohesion and cluster formation of nanoparticles in nanofluids has been investigated in this study. This goal can be obtained by applying the basic swarm model for agents that are more mechanistic by considering their physical properties such as their mass, diameter, as well as the physical properties of the flow. Clustering in nanofluids is one of the major issues in the study of its effects on heat transfer. Study of the cluster formation dynamics in nanofluids using the swarm model can be useful in controlling the size and formation time of the clusters as well as designing appropriate microchannels, which the nanoparticles are plunged into.

SIMULTANEOUSLY SEGMENTING MULTIPLE GENE EXPRESSION TIME COURSES BY ANALYZING CLUSTER DYNAMICS

We present a new approach to segmenting multiple time series by analyzing the dynamics of cluster formation and rearrangement around putative segment boundaries. This approach finds application in distilling large numbers of gene expression profiles into temporal relationships underlying biological processes. By directly minimizing information-theoretic measures of segmentation quality derived from Kullback-Leibler (KL) divergences, our formulation reveals clusters of genes along with a segmentation such that clusters show concerted behavior within segments but exhibit significant regrouping across segmentation boundaries. The results of the segmentation algorithm can be summarized as Gantt charts revealing temporal dependencies in the ordering of key biological processes. Applications to the yeast metabolic cycle and the yeast cell cycle are described.