Thermoregulatory morphodynamics of honeybee swarm clusters

During reproductive swarming, honeybees clusters of more than 10,000 individuals that hang from structures in the environment (e.g., tree branches) are exposed to diurnal variations in ambient temperature for up to a week. Swarm clusters collectively modulate their morphology in response to these variations (i.e., expanding/contracting in response to heating/cooling) to maintain their internal temperature within a tolerable range and to avoid exhausting their honey stores prematurely. To understand the spatiotemporal aspects of thermoregulatory morphing, we measured the change in size, shape and internal temperature profiles of swarm clusters in response to dynamic temperature ramp perturbations. We see that swarm clusters show a two-fold variation in their volume/density when heated from 15°C to 30°C. However, they do not reach an equilibrium size or shape when held at 30°C for 5 hours, long after the core temperature of the cluster has stabilized. Furthermore, the changes in cluster shape and size are hysteretic, contracting in response to cooling faster than expanding in response to heating. Although the base contact diameter of the cluster increased continuously when the swarm is heated, the change in length of the swarm (base totip) over time is non-monotonic. Consequently, the aspect ratio of the swarm fluctuated continuously even when held at a constant temperature. Taken together, our results quantify the hysteretic and anisotropic morphological responses of swarm clusters to ambient temperature variations while suggesting that both mechanical constraints and heat transfer govern their thermoregulatory morphodynamics.

Topological Analysis of γH2AX and MRE11 Clusters Detected by Localization Microscopy during X-ray-Induced DNA Double-Strand Break Repair

DNA double-strand breaks (DSBs), known as the most severe damage in chromatin, were induced in breast cancer cells and normal skin fibroblasts by 2 Gy ionizing photon radiation. In response to DSB induction, phosphorylation of the histone variant H2AX to γH2AX was observed in the form of foci visualized by specific antibodies. By means of super-resolution single-molecule localization microscopy (SMLM), it has been recently shown in a first article about these data that these foci can be separated into clusters of about the same size (diameter ~400 nm). The number of clusters increased with the dose applied and decreased with the repair time. It has also been shown that during the repair period, antibody-labeled MRE11 clusters of about half of the γH2AX cluster diameter were formed inside several γH2AX clusters. MRE11 is part of the MRE11–RAD50–NBS1 (MRN) complex, which is known as a DNA strand resection and broken-end bridging component in homologous recombination repair (HRR) and alternative non-homologous end joining (a-NHEJ). This article is a follow-up of the former ones applying novel procedures of mathematics (topology) and similarity measurements on the data set: to obtain a measure for cluster shape and shape similarities, topological quantifications employing persistent homology were calculated and compared. In addition, based on our findings that γH2AX clusters associated with heterochromatin show a high degree of similarity independently of dose and repair time, these earlier published topological analyses and similarity calculations comparing repair foci within individual cells were extended by topological data averaging (2nd-generation heatmaps) over all cells analyzed at a given repair time point; thereby, the two dimensions (0 and 1) expressed by components and holes were studied separately. Finally, these mean value heatmaps were averaged, in addition. For γH2AX clusters, in both normal fibroblast and MCF-7 cancer cell lines, an increased similarity was found at early time points (up to 60 min) after irradiation for both components and holes of clusters. In contrast, for MRE11, the peak in similarity was found at later time points (2 h up to 48 h) after irradiation. In general, the normal fibroblasts showed quicker phosphorylation of H2AX and recruitment of MRE11 to γH2AX clusters compared to breast cancer cells and a shorter time interval of increased similarity for γH2AX clusters. γH2AX foci and randomly distributed MRE11 molecules naturally occurring in non-irradiated control cells did not show any significant topological similarity.

Dynamic Effects in Nucleation of Receptor Clusters

Nucleation theory has been widely applied for the interpretation of critical phenomena in nonequilibrium systems. Ligand-induced receptor clustering is a critical step of cellular activation. Receptor clusters on the cell surface are treated from the nucleation theory point of view. The authors propose that the redistribution of energy over the degrees of freedom is crucial for forming each new bond in the growing cluster. The expression for a kinetic barrier for new bond formation in a cluster was obtained. The shape of critical receptor clusters seems to be very important for the clustering on the cell surface. The von Neumann entropy of the graph of bonds is used to determine the influence of the cluster shape on the kinetic barrier. Numerical studies were carried out to assess the dependence of the barrier on the size of the cluster. The asymptotic expression, reflecting the conditions necessary for the formation of receptor clusters, was obtained. Several dynamic effects were found. A slight increase of the ligand mass has been shown to significantly accelerate the nucleation of receptor clusters. The possible meaning of the obtained results for medical applications is discussed.

Thermoregulatory morphodynamics of honeybee clusters

During reproductive swarming, honeybees form clusters of more than 10,000 bees that hang from structures in the environment (e.g., tree branches) and are exposed to diurnal variations in ambient temperature for up to one week during the search for a new nesting site. Swarm clusters collectively modulate their morphology in response to these variations (i.e., expanding/contracting in response to heating/cooling) to maintain their internal temperature within a tolerable range and to avoid exhausting their honey stores prematurely. To understand the spatiotemporal aspects of thermoregulatory morphing, we measured the change in size and shape of swarm clusters over time and the internal temperature profiles in response to dynamic temperature ramp perturbations. We found that swarm clusters can achieve a twofold increase/decrease their volume/density when heated from 15°C to 30°C, but they do not reach an equilibrium size or shape when held at 30°C for 5 hours, long after the core temperature of the cluster has stabilized. Furthermore, the changes in cluster shape and size are hysteretic, contracting in response to cooling faster than expanding in response to heating. Although the contact diameter of the cluster increased continuously when the swarm is heated, the change in length of the swarm (base to tip) over time is non-monotonic. Consequently, the aspect ratio of the swarm fluctuated continuously even when held at a constant temperature. Taken together, our results quantify the hysteretic and anisotropic morphological responses of swarm clusters to ambient temperature variations while suggesting that both mechanical constraints and heat transfer govern the thermoregulatory morphing dynamics of swarm clusters.

Halo cluster shapes: insights from simulated galaxies and ICL with prospects for weak lensing applications

ABSTRACT We present a detailed study of the shapes and alignments of different galaxy cluster components using hydrodynamical simulations. We compute shape parameters from the dark matter (DM) distribution, the galaxy members and the intracluster light (ICL). We assess how well the DM cluster shape can be constrained by means of the identified galaxy member positions and the ICL. Further, we address the dilution factor introduced when estimating the cluster elongation using weak-lensing stacking techniques, which arises due to the misalignment between the total surface mass distribution and the distribution of luminous tracers. The dilution is computed considering the alignment between the DM and the brightest cluster galaxy, the galaxy members and the ICL. Our study shows that distributions of galaxy members and ICL are less spherical than the DM component, although both are well aligned with the semimajor axis of the latter. We find that the distribution of galaxy members hosted in more concentrated subhaloes is more elongated than the distribution of the DM. Moreover, these galaxies are better aligned with the DM component compared to the distribution of galaxies hosted in less concentrated subhaloes. We conclude that the positions of galaxy members can be used as suitable tracers to estimate the cluster surface density orientation, even when a low number of members is considered. Our results provide useful information for interpreting the constraints on the shapes of galaxy clusters in observational studies.

Clusters formed by dumbbell-like one-patch particles confined in thin systems

Performing isothermal-isochoric Monte Carlo simulations, I examine the types of clusters that dumbbell-like one–patch particles form in thin space between two parallel walls, assuming that each particle is synthesized through the merging of two particles, one non-attracting and the other attracting for which, for example, the inter-particle interaction is approximated by the DLVO model . The shape of these dumbbell-like particles is controlled by the ratio of the diameters q of the two spherical particles and by the dimensionless distance l between these centers. Using a modified Kern–Frenkel potential, I examine the dependence of the cluster shape on l and q. Large island-like clusters are created when $$q<1$$ q < 1 . With increasing q, the clusters become chain-like . When q increases further, elongated clusters and regular polygonal clusters are created. In the simulations, the cluster shape becomes three-dimensional with increasing l because the thickness of the thin system increases proportionally to l.

Clusters Formed by Dumbbell-like One-Patch Particles Confined in Thin Systems

Performing isothermal-isochoric Monte Carlo simulations, I examine the types of clusters that dumbbell-like one–patch particles form in thin space between two parallel walls, assuming that each particle is synthesized through the merging of two particles, one non-attracting and the other attracting for which, for example, the inter-particle interaction is approximated by the DLVO model. The shape of these dumbbell-like particles is controlled by the ratio of the diameters q of the two spherical particles and by the dimensionless distance l between them. Using a modified Kern–Frenkel potential, I examine the dependence of the cluster shape on l and q. Large island-like clusters are created when q < 1. With increasing q, the clusters become chain-like. When q increases further, elongated clusters and regular polygonal clusters are created. In hte simulations, the cluster shape becomes three-dimensional with increasing l because the thickness of the thin system increases proportionally to l.

Performance evaluation results of evolutionary clustering algorithm star for clustering heterogeneous datasets

This article presents the data used to evaluate the performance of evolutionary clustering algorithm star (ECA*) compared to five traditional and modern clustering algorithms. Two experimental methods are employed to examine the performance of ECA* against genetic algorithm for clustering++ (GENCLUST++), learning vector quantisation (LVQ), expectation maximisation (EM), K-means++ (KM++) and K-means (KM). These algorithms are applied to 32 heterogenous and multi-featured datasets to determine which one performs well on the three tests. For one, ther paper examines the efficiency of ECA* in contradiction of its corresponding algorithms using clustering evaluation measures. These validation criteria are objective function and cluster quality measures. For another, it suggests a performance rating framework to measurethe the performance sensitivity of these algorithms on varos dataset features (cluster dimensionality, number of clusters, cluster overlap, cluster shape and cluster structure). The contributions of these experiments are two-folds: (i) ECA* exceeds its counterpart aloriths in ability to find out the right cluster number; (ii) ECA* is less sensitive towards dataset features compared to its competitive techniques. Nonetheless, the results of the experiments performed demonstrate some limitations in the ECA*: (i) ECA* is not fully applied based on the premise that no prior knowledge exists; (ii) Adapting and utilising ECA* on several real applications has not been achieved yet.

Corporate Social Responsibility and the Local Community Effect

The objective of the chapter is to take a multilevel perspective to better understand how CSR practices are developed inside a cluster. The authors aim to describe how CSR practices are developed comparing both firm's characteristics (e.g., innovative capacity, marketing innovation, international activities) and local interactions inside the cluster. In particular, they evaluate how internal dynamics of the cluster, defined by the networks of relationships that are developed with supporting organizations, along with leading firms in the cluster, shape a new institutional framework that locally legitimates CSR practices.