A recently introduced approach to the classical gravitational dynamics of binary systems involves intricate integrals (linked to a combination of nonlocal-in-time interactions with iterated 1r-potential scattering) which have so far resisted attempts at their analytical evaluation.

In this paper we propose a new approach to detect clusters in undirected graphs with attributed vertices. The aim is to group vertices which are similar not only in terms of structural connectivity but also in terms of attribute values. We incorporate structural and attribute similarities between the vertices in an augmented graph by creating additional vertices and edges as proposed in [6, 38]. The augmented graph is then embedded in a Euclidean space associated to its Laplacian where a modified K-means algorithm is applied to identify clusters.

One of the most distinctive hallmarks of many-body systems far from equilibrium is the spontaneous emergence of order under conditions where disorder would be plausibly expected. Here, we report on the self-transition between ordered and disordered emulsions in divergent microfluidic channels, i.e., from monodisperse assemblies to heterogeneous polydisperse foamlike structures, and back again to ordered ones.

Motivated by the recent outbreak of coronavirus (COVID-19), we propose a stochastic model of epidemic temporal growth and mitigation based on a time-modulated Hawkes process. The model is sufficiently rich to incorporate specific characteristics of the novel coronavirus, to capture the impact of undetected, asymptomatic and super-diffusive individuals, and especially to take into account time-varying counter-measures and detection efforts. Yet, it is simple enough to allow scalable and efficient computation of the temporal evolution of the epidemic, and exploration of what-if scenarios.

Terrestrial and marine ecosystems provide essential goods and services to human societies. In the last decades, however, anthropogenic pressure has produced a loss of ecosystem services that can seriously affect human wellbeing and climate processes at local and regional scale.

This paper proposes a toy model where, in the Einstein equations, the right-hand side is modified by the addition of a term proportional to the symmetrized partial contraction of the Ricci tensor with the energy-momentum tensor, while the left-hand side remains equal to the Einstein tensor. Bearing in mind the existence of a natural length scale given by the Planck length, dimensional analysis shows that such a term yields a correction linear in ? to the classical term that is instead just proportional to the energy-momentum tensor.

The poles of the heart and branchiomeric muscles of the face and neck are formed from the cardiopharyngeal mesoderm within the pharyngeal apparatus. They are disrupted in patients with 22q11.2 deletion syndrome, due to haploinsufficiency of TBX1, encoding a T-box transcription factor. Here, using single cell RNA-sequencing, we now identify a multilineage primed population within the cardiopharyngeal mesoderm, marked by Tbx1, which has bipotent properties to form cardiac and branchiomeric muscle cells.

This work presents a microscale approach for simulating the dielectrophoresis assembly of polarizable particles under an external electric field. The model is shown to capture interesting dynamical and topological features, such as the formation of chains of particles and their incipient aggregation into hierarchical structures. A quantitative characterization in terms of the number and size of these structures is also discussed.

The need for more and more accurate gravitational-wave templates requires taking into account all possible contributions to the emission of gravitational radiation from a binary system. Therefore, working within a multipolar-post-Minkowskian framework to describe the gravitational-wave field in terms of the source multipole moments, the dominant instantaneous effects should be supplemented by hereditary contributions arising from nonlinear interactions between the multipoles.

Chandipura vesiculovirus (CHPV) is a rapidly emerging pathogen responsible for causing acute encephalitis. Due to its widespread occurrence in Asian and African countries, this has become a global threat, and there is an urgent need to design an effective and nonallergenic vaccine against this pathogen. The present study aimed to develop a multi-epitope vaccine using an immunoinformatics approach. The conventional method of vaccine design involves large proteins or whole organism which leads to unnecessary antigenic load with increased chances of allergenic reactions.