Mean Cluster Size Research Articles

A mathematical model for the assembly of ion channel clusters in cardiac and smooth muscle cells

Various membrane ion channels have been shown to cluster in excitable cells. However, the mechanism of spatiotemporal organization of cluster complexes is unknown. We used super resolution microscopy to study the time course of membrane expression of CaV1.2 and TRPV4 channels in transfected tsA‐201 cells. Channel clusters vary in size but can be fit exponentially at all time points. Similarly, mean cluster size and cluster density increase rapidly, but eventually reach a plateau around 24 hours post transfection. Using our findings, we devised a model for stochastic cluster assembly based on probabilities of three factors: cluster nucleation, growth and removal. This model reproduced distributions from previous studies of various channels in different tissues and suggests that a feedback process is responsible for determining a setpoint of cluster density and size.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Development of a Gas Cluster Ion Source and Its Application for Surface Treatment

A custom-built gas cluster ion source with an energy up to 20 keV is constructed. Ar, CO2, N2, and O2 are used as the working gases. The clusters are formed by metal conical nozzles with critical diameters of 65−135 um and a cone angle of 14°. To facilitate evacuation of the chambers we use the pulse mode of nozzle feeding. This allows an increase in the gas pressure in the stagnation zone (inlet pressure) up to 15 bar. The current of the clusters with an energy of 20 keV is 20 µA; the maximal current density is 3 µA/cm2. The mass spectra of the argon clusters formed at different pressures and electron ionization energy are studied by time-of-flight spectroscopy. The inlet pressure dependence of the mean cluster size is considered as a function of the condensation parameter Г*. An argon cluster beam is used to smooth the surface of the titanium coating and pressed silicon nanopowder. The roughness of the Ti coating surface decreases from 3.7 to 0.8 nm; the removal of microparticles from the surface is also observed. In the case of the surface of Si, besides the smoothing effect the formation of 100 nm craters is observed.

Totally asymmetric exclusion process with site-wise dynamic disorder

We propose an extension of the totally asymmetric simple exclusion process (TASEP) in which particles hopping along a lattice can be blocked by obstacles that dynamically attach/detach from lattice sites. The model can be thought as TASEP with site-wise dynamic disorder. We consider two versions of defect dynamics: (i) defects can bind to any site, irrespective of particle occupation, (ii) defects only bind to sites which are not occupied by particles (particle-obstacle exclusion). In case (i) there is a symmetric, parabolic-like relationship between the current and particle density, as in the standard TASEP. Case (ii) leads to a skewed relationship for slow defect dynamics. We also show that the presence of defects induces particle clustering, despite the translation invariance of the system. For open boundaries the same three phases as for the standard TASEP are observed, albeit the position of phase boundaries is affected by the presence of obstacles. We develop a simple mean-field theory that captures the model’s quantitative behaviour for periodic and open boundary conditions and yields good estimates for the current-density relationship, mean cluster sizes and phase boundaries. Lastly, we discuss an application of the model to the biological process of gene transcription.

ДОСЛІДЖЕННЯ МЕТОДОМ КЛАСТЕРНОЇ ДИНАМІКИ ВПЛИВУ ЗМІНИ ТЕМПЕРАТУРИ НА НЕЙТРОННУ КРИХКІСТЬ АЛЬФА -ЗАЛІЗА

The actual issue of using data of neutron embrittlement of reactor materials received under the study of witness-samples, installed at selected points of the atomic reactor, to the assessment of the actual neutron embrittlement of the reactor is considered. Significant difference in the mechanical properties, including neutron embrittlement, of the predicted values based on the results of examination of witness-samples and the results of examinations of the reactor pressure vessel of the nuclear power plant Graiswald (Germany) after its closure in 1990, was found experimentally in 2010-2013 years. Here, the mechanical properties have been measured and the small-angle neutron scattering method has been used to determine the size and density of nano-defects with a size of up to 3 nm, namely clusters of point defects (vacancy clusters and clusters of interstitial atoms), copper precipitates, and clusters composed of point defects and alloying elements of the reactor pressure vessel steel. In the proposed study, one of the possible causes of the mentioned discrepancy is considered, namely, the difference in the surveillance temperature of the reactor (300 °C) and the temperature of the witness-sample (123 °C), which is irradiated for about one year in the reactor, and then extracted from it during routine shutdowns, for example, when replacing nuclear fuel. In order to simplify, we study the effect of temperature change not on reactor steel, but on commercial pure α -iron (carbon content is less than 30 ppm). The distribution functions of vacancy clusters and clusters of self-interstitial atoms respect to the number of monomers have been calculated by means of cluster dynamics calibrated by experimental data of small-angle neutron scattering, transmission electron microscopy and positron annihilation spectroscopy of commercially pure α - iron neutron irradiated in the research reactor BR-2 (Belgium, Mol). The mean cluster size and the number density of clusters are used to estimate the increase of the yield strength of Δ σ of α - iron due a neutron irradiation. This value is usually interpreted as a quantitative characteristic of neutron embrittlement. It is shown that the contribution of vacancy clusters to the value of Δ σ of the studied α -iron can be neglected while the contribution from clusters of self-interstitial atoms decreases with increasing time during which the temperature of the reactor was reduced.

Predominant Factor Determining Thermal Conductivity Behavior of Nanofluid: Effect of Cluster Structures with Various Nanoparticles

Despite several research efforts, the detailed mechanism that dominates the thermal conductivity of nanofluids has not been explained. We investigated the effect of the chemical surface design of NPs (hydrophobic–hydrophilic balance of the NPs containing Janus surface) and verified the influence of their self–assembled structures on the thermal conductivity of a nanofluid using molecular simulation. When hydrophobic (HO) NPs are added to a nanofluid, they only form one large cluster because they do not prefer to be in contact with water molecules. Hence, an increment in the thermal conductivity of the nanofluid added with HO NPs was observed. On the contrary, the mean cluster size of Janus NPs was limited because of their limited HO superficial areas (attractive domains). Hence, an increment in the enhancement ratio of thermal conductivity was not observed even when the volume fraction of the NPs (ϕNP) was increased. Thus, our results demonstrate that the mean cluster size of NPs is the key factor for thermal conductivity enhancement. In addition, this study reveals that it is possible to control the thermal conductivity of nanofluids (or the mean cluster size of Janus NPs) using Janus NPs with surfaces designed using anisotropic chemical interactions.

Modeling of the Evolution of Cluster-Size Distribution Functions in Polar Fullerene C60 Solutions

We propose a method for calculating the evolution of the cluster-size distribution functions of fullerene C60 aggregates in polar solutions within the previously developed limited growth model. This method allows calculation of the distribution function f(r,t) at arbitrary moments of time for the given parameters of the system. As an example, we calculate the evolution of the mean cluster size, concentrations of monomers, and f(r,t) for a model polar solution of fullerenes. Small-angle neutron scattering curves at different times from the onset of C60 aggregation in the solution are obtained.

Suppression effect on the Berezinskii-Kosterlitz-Thouless transition in growing networks

Since the discovery a half century ago that 1/r^2-type long-range interactions in the one-dimensional Ising model change the phase transition type, long-range interactions in diverse systems have received considerable attention. Recently, this interest extended to global suppression dynamics in the percolation transition, which changes a second-order transition to first order. Here, we investigate how the Berezinskii-Kosterlitz-Thouless (BKT) transition is changed by the global suppression effect. In fact, this effect often arises in real-world complex systems, yet it is not appropriately accounted for in models. We find that the BKT transition breaks down, but the features of infinite-, second-, and first-order transitions all emerge as the link occupation probability is controlled. Moreover, we find that such growing networks exhibit maximum diversity, causing the mean cluster size to diverge without formation of a giant cluster. We elucidate the underlying mechanisms and show that such anomalous transitions are universal.

Efficacy and mode of action of blossom thinners on ‘Fuji More’ apple trees

The objective of this study was to investigate the mechanism of action of the treatments: Ammonium thiosulfate (ATS), benzyladenine (BA), GA4+7+BA, foliar fertilizer, lime sulphur (LS), LS + mineral oil, mineral oil, NAA, urea, and vegetal oil in the interaction of these treatments with: 1) pollen grain germination, 2) stigma/style pollen tube (PT) development, and 3) the effectiveness of the treatments in field conditions on decreasing crop load and enhancing fruit quality of ‘Fuji More’ apple trees. In experiment 1 it was evaluated the effect of the treatments in inhibiting the in vitro pollen germination of ‘Maxi Gala’ apples. In Experiment 2 it was evaluated in vivo ‘Maxi Gala’ pollen germination in ‘Fuji’ pistils to assess the effect of the treatments applied 24 h before and after the pollination, in three portions of the styles. In experiment 3 it was evaluated the effect of the treatments sprayed at 90% full bloom in a commercial ‘Fuji More’ apple orchard on the variables: fruit set, crop load, yield efficiency, mean fruit weight, cluster size, fruit height and diameter, total soluble solids, flesh firmne, mean seed number, skin russet and red color. ATS reduced in vitro pollen germination and caused the greatest damage to the stigmas/styles, while in the field, it was effective to reduce crop load. Treatments containing LS were the most effective to reduce in vitro pollen germination, but the in vivo essay, mode of action seemed to be related to arresting pollen tube growth, and in the field these treatments caused severe russeting. Mineral and vegetal oil do not have direct effect on pollen germination, but arrest pollen tube growth, and in field conditions mineral oil and ATS reduced crop load. All growth regulators (BA, GA4+7 + BA, and NAA decreased greatly crop load and increased fruit weight and quality.

Precise sputtering of silicon dioxide by argon cluster ion beams

In this work, the sputtering yields of SiO2 by the argon cluster ion beam with incident angles 0° and 45° have been studied experimentally. The kinetic energy of the primary cluster ions was in the range of E = 5–23.5 keV, and the mean cluster size was Nmean = 100–1000 atom/cluster. It is found that, when the energy per cluster atom quantity E/N is comparable to the binding energy of the solid (of the order of several eV), the yields of atoms sputtered per primary atom Y/N, at the incident angle 45°, is 4 times greater than at normal incidence. Conversely, when energy E/N is significantly above the binding energy of the solid (~ 100 eV), the sputtering yields for the incident angles 0° and 45° have the same values.

Diagnostics of argon cluster ion beam for materials treatment

The important parameters for materials surface processing by a gas cluster ions are the mass composition, total energy and energy per atom in the cluster, which depends on the ion beam charge state. The purpose of this work is an experimental characterization of argon cluster ion beam, based on an original time-of-flight technique. The mean sizes of the cluster ions obtained from the measured mass spectra are compared with the mean sizes of the primary neutral clusters. By analyzing the mass spectra at different electron ionization current, the average charge state of cluster ion beam is evaluated.

Surface processing of amorphous optical materials by argon cluster ion beam

The production of a high-quality surface of fused silica is an important task for advanced optical technologies. In this work, the surface of fused silica has been processed by argon cluster ion beam having mean cluster size Nmean ranged from 180 to 1000 atoms/cluster and energy E ranged from 5 to 23.5 keV. The analysis of surface morphology using atomic force microscopy and the spectral power density (PSD) function shows a noticeable smoothing of roughness in different spatial frequency ranges, depending on the cluster ion parameters. To evaluate the processing efficiency, the dependence of the etching rate of SiO2 on the parameters of cluster ions has been investigated. It is shown that the etching rate vetch is determined by the energy per atom in the cluster E/Nmean and it varies from 0.2 to 20 nm/min with an energy change from 5 to 130 eV/atom.

Automated Indices of Clustering and Switching of Semantic Verbal Fluency in Parkinson's Disease.

Deficits in semantic verbal fluency (SVF) can stem from dysfunction of an executive control system and/or of semantic knowledge. Previous analyses of SVF responses were devised to characterize these two components including switching and mean cluster size (MCS) indices, but these rely on subjective experimenter-based assessment of the words' relatedness. To address this limitation, computational data-driven SVF indices have been developed. Our aim is to assess the validity and usefulness of these automated indices in the context of cognitive decline in Parkinson's disease (PD). This is a retrospective study including 50 advanced PD patients with (n=28) or without (n=22) mild cognitive impairment (PD-MCI). We analyzed animal SVF outputs using an automated computational approach yielding switching, MCS, and cumulative relatedness (CuRel) indices. We compared these indices to the classic experimenter-based switching and MCS indices to assess concurrent validity, and against neuropsychological measures of executive functioning and semantic knowledge to assess construct validity. We also examined whether these indices were impaired and predicted PD-MCI. Automated switching indices, but not MCS or CuRel, showed evidence of concurrent and construct validity, and characterized individual difference in advanced PD. Automated switching indices also outperformed the experimenter-dependent index in predicting the presence of PD-MCI. Computational methods hold promise as fine-grained, unbiased indices reflecting the executive component of SVF, but none of the methods provided valid measures of semantic knowledge in PD. Our data also confirm that SVF are not adequate tests of semantic memory in patients with executive dysfunction such as PD. (JINS, 2018, 24, 1047-1056).

Mechanisms behind overshoots in mean cluster size profiles in aggregation-breakup processes

Aggregation and breakup of small particles in stirred suspensions often shows an overshoot in the time evolution of the mean cluster size: Starting from a suspension of primary particles the mean cluster size first increases before going through a maximum beyond which a slow relaxation sets in. Such behavior was observed in various systems, including polymeric latices, inorganic colloids, asphaltenes, proteins, and, as shown by independent experiments in this work, in the flocculation of microalgae. This work aims at investigating possible mechanism to explain this phenomenon using detailed population balance modeling that incorporates refined rate models for aggregation and breakup of small particles in turbulence. Four mechanisms are considered: (1) restructuring, (2) decay of aggregate strength, (3) deposition of large clusters, and (4) primary particle aggregation where only aggregation events between clusters and primary particles are permitted. We show that all four mechanisms can lead to an overshoot in the mean size profile, while in contrast, aggregation and breakup alone lead to a monotonic, “S”-shaped size evolution profile. In order to distinguish between the different mechanisms simple protocols based on variations of the shear rate during the aggregation-breakup process are proposed.

Micron-size hydrogen cluster target for laser-driven proton acceleration

As a new laser-driven ion acceleration technique, we proposed a way to produce impurity-free, highly reproducible, and robust proton beams exceeding 100 MeV using a Coulomb explosion of micron-size hydrogen clusters. In this study, micron-size hydrogen clusters were generated by expanding the cooled high-pressure hydrogen gas into a vacuum via a conical nozzle connected to a solenoid valve cooled by a mechanical cryostat. The size distributions of the hydrogen clusters were evaluated by measuring the angular distribution of laser light scattered from the clusters. The data were analyzed mathematically based on the Mie scattering theory combined with the Tikhonov regularization method. The maximum size of the hydrogen cluster at 25 K and 6 MPa in the stagnation state was recognized to be 2.15 ± 0.10 μm. The mean cluster size decreased with increasing temperature, and was found to be much larger than that given by Hagena’s formula. This discrepancy suggests that the micron-size hydrogen clusters were formed by the atomization (spallation) of the liquid or supercritical fluid phase of hydrogen. In addition, the density profiles of the gas phase were evaluated for 25 to 80 K at 6 MPa using a Nomarski interferometer. Based on the measurement results and the equation of state for hydrogen, the cluster mass fraction was obtained. 3D particles-in-cell (PIC) simulations concerning the interaction processes of micron-size hydrogen clusters with high power laser pulses predicted the generation of protons exceeding 100 MeV and accelerating in a laser propagation direction via an anisotropic Coulomb explosion mechanism, thus demonstrating a future candidate in laser-driven proton sources for upcoming multi-petawatt lasers.

Nature of bonding and cooperativity in linear DMSO clusters: A DFT, AIM and NCI analysis

This study aims to cast light on the nature of interactions and cooperativity that exists in linear dimethyl sulfoxide (DMSO) clusters using dispersion corrected density functional theory. In the linear DMSO, DMSO molecules in the middle of the clusters are bound strongly than at the terminal. The plot of the total binding energy of the clusters vs the cluster size and mean polarizabilities vs cluster size shows an excellent linearity demonstrating the presence of cooperativity effect. The computed incremental binding energy of the clusters remains nearly constant, implying that DMSO addition at the terminal site can happen to form an infinite chain. In the linear clusters, two σ-hole at the terminal DMSO molecules were found and the value on it was found to increase with the increase in cluster size. The quantum theory of atoms in molecules topography shows the existence of hydrogen and SO⋯S type in linear tetramer and larger clusters. In the dimer and trimer SO⋯OS type of interaction exists. In 2D non-covalent interactions plot, additional peaks in the regions which contribute to the stabilization of the clusters were observed and it splits in the trimer and intensifies in the larger clusters. In the trimer and larger clusters in addition to the blue patches due to hydrogen bonds, additional, light blue patches were seen between the hydrogen atom of the methyl groups and the sulphur atom of the nearby DMSO molecule. Thus, in addition to the strong H-bonds, strong electrostatic interactions between the sulphur atom and methyl hydrogens exists in the linear clusters.

Dynamics of Surfactant Clustering at Interfaces and Its Influence on the Interfacial Tension: Atomistic Simulation of a Sodium Hexadecane-Benzene Sulfonate-Tetradecane-Water System.

The process of equilibration of the tetradecane-water interface in the presence of sodium hexadecane-benzene sulfonate is studied using intensive atomistic molecular dynamics simulations. Starting as an initial point with all of the surfactants at the interface, it is obtained that the equilibration timeof the interface (several microseconds) is orders of magnitude higher than previously reported simulated times. There is strong evidence that this slow equilibration process is due to the aggregation of surfactants molecules on the interface. To determine this fact, temporal evolution of interfacial tension and interfacial formation energy are studied and their temporal variations are correlated with cluster formation. To study cluster evolution, the mean cluster size and the probability that a molecule of surfactant chosen at random is free are obtained as a function of time. Cluster size distribution is estimated, and it is observed that some of the molecules remain free, whereas the rest agglomerate. Additionally, the temporal evolution of the interfacial thickness and the structure of the surfactant molecules on the interface are studied. It is observed how this structure depends on whether the molecules agglomerate or not.

Influence of age and education on the processing of clustering and switching in verbal fluency tasks.

ABSTRACTVerbal fluency (VF) is a widely used tool in neuropsychological assessment.Objective:We aimed to investigate the influence of age and educational level on clustering and switching in three VF modalities: phonemic (PVF), semantic (SVF) and unconstrained (UVF). We evaluated type of cluster, mean cluster size, and quantity of clusters, intersections, and returns. A total of 260 healthy subjects were assessed.Methods:Participants were divided into three age groups: young adults (18 to 39 years), middle-aged adults (40 to 59 years) and older adults (60 to 80 years) and into two groups of educational level: 1-8 years (low), 9 years or more (high). A two-way ANOVA analysis was conducted to analyze the effect of age and educational level and its interactions. A repeated measures ANOVA was performed to verify the performance during the task.Results:A main effect of age was detected on the UVF and SVF scores for total switches, taxonomic clusters, and for the total semantic clusters on the SVF. There was a greater effect of educational level on total switches (UVF, PFV and SVF), taxonomic clusters (UVF and SVF), thematic clusters and total semantic cluster (UVF), phonemic and mixed clusters (PVF), mean cluster size (UVF and SVF) and intersections (SVF). Educational level had a greater effect on all three VF tasks.

Диагностика потоков газовых кластеров с помощью поперечных профилей интенсивности молекулярного пучка

An experimental method for diagnostics of clusters in molecular beams formed from supersonic gas jets is described. The method is based on measuring the cross-section profile of the mass intensity of the beam at a given distance behind the skimmer and it allows one to determine the main parameters: the mean cluster size, the ratio of clusters to monomers and the cluster flow density. The described method can be used to diagnose cluster beams of any pure gases, without creating special models or determining empirical constants. Since the cluster beam has a high intensity, highly sensitive and complex equipment is not required for measurements. With this method, the average sizes of Ar clusters in the range from 50 to 2,000 molecules per cluster were determined. The reliability of the obtained values of the mean cluster sizes is confirmed by a comparison of the results with the data of other authors obtained by the various experimental methods using the similarity parameter of flows with condensation (the Hagena parameter) Г*. The physical limitations of the described method were analyzed.

A Tribute to Marian Smoluchowski's Legacy on Soft Grains Assembly and Hydrogel Formation

The paper compares the statistical description of physical-metallurgical processes and ceramic-polycrystalline evolutions, termed the normal grain growth (NGG), as adopted to soft- and chemically-reactive grains, with a Smoluchowski's population-constant kernel cluster-cluster aggregation (CCA) model, concerning irreversible chemical reaction kinetics. The former aiming at comprehending, in a semi-quantitative way, the volume-conservative (pressure-drifted) grain-growth process which we propose to adopt for hydrogel systems at quite low temperature (near a gel point). It has been noticed, that by identifying the mean cluster size $<k>$ from the Smoluchowski CCA description with the mean cluster radius' size $R_D$, from the NGG approach of proximate grains, one is able to embark on equivalence of both frameworks, but only under certain conditions. For great enough, close-packed clusters, the equivalence can be obtained by rearranging the time domain with rescaled time variable, where the scaling function originates from the dispersive (long-tail, or fractal) kinetics, with a single exponent equal to $d+1$ (in $d$-dimensional (Euclidean) space). This can be of interest for experimenters, working in the field of thermoresponsive gels formation, where crystalline structural predispositions overwhelm.

PBE Modeling of Flocculation of Microalgae: Investigating the Overshoot in Mean Size Profiles

Microalgae is considered as a viable feedstock to biomass gasification. After synthesis in water medium, microalgae are separated and dried to a suitable degree to be fed to the gasification process. In order to achieve an efficient separation, a flocculation process is employed, in which microalgae primary particles aggregate and form larger clusters. Although flocculation is a well-established process, there are still some unknown issues related to it, that are worth further research. Experiments show that the mean size of clusters during flocculation goes through a maximum and then decreases with time. We refer to this pattern in the mean size profile as the overshoot. Studying this phenomenon is crucial since the size of clusters has a significant effect on the overall efficiency of the separation of microalgae from water. In this work, we aim at investigating the mechanisms behind the overshoot.The flocculation process is modeled as an aggregation-breakup system by using population balance equations (PBEs). The primary results show that the aggregation and breakup alone cannot lead to the overshoot in the mean size profile. Thus, we suggested three mechanisms that can lead to the overshoot: deposition of large clusters (DLC), restructuring of clusters (RC), and primary particle aggregation (PPA). These mechanisms were examined with numerical simulations and it was revealed that all three lead to the overshoot.