Social and Spatial Clustering of People at Humanity's Largest Gathering

The hybrid bio-robotic swarm as a powerful tool for collective motion research: a perspective

Swarming or collective motion is ubiquitous in natural systems, and instrumental in many technological applications. Accordingly, research interest in this phenomenon is crossing discipline boundaries. A common major question is that of the intricate interactions between the individual, the group, and the environment. There are, however, major gaps in our understanding of swarming systems, very often due to the theoretical difficulty of relating embodied properties to the physical agents-individual animals or robots. Recently, there has been much progress in exploiting the complementary nature of the two disciplines: biology and robotics. This, unfortunately, is still uncommon in swarm research. Specifically, there are very few examples of joint research programs that investigate multiple biological and synthetic agents concomitantly. Here we present a novel research tool, enabling a unique, tightly integrated, bio-inspired, and robot-assisted study of major questions in swarm collective motion. Utilizing a quintessential model of collective behavior-locust nymphs and our recently developed Nymbots (locust-inspired robots)-we focus on fundamental questions and gaps in the scientific understanding of swarms, providing novel interdisciplinary insights and sharing ideas disciplines. The Nymbot-Locust bio-hybrid swarm enables the investigation of biology hypotheses that would be otherwise difficult, or even impossible to test, and to discover technological insights that might otherwise remain hidden from view.

An Aspect of Kumbh Mela Massive Gathering and COVID-19

Purpose of Review

Kumbh Mela, a religious gathering of Hindus held in India, is the largest massive gathering event in the world. The COVID-19 pandemic is an unprecedented healthcare crisis in recent times with effects reverberating in all spheres of human lives. India has registered the second highest number of COVID-19 cases. This paper aims to dwell in the religious and social background of Kumbh Mela massive gathering, as well as the ritualistic practices that could potentially entail public health risks in the current situation. It also aims to identify possible preparatory and interventional measures to evade such risks.

Recent Findings

In recent years, the increase in the number of people attending the Kumbh Mela has been phenomenal. Congregants are put up at the holy sites for several days. The sheer number of people assembling at the religious venues poses a great challenge to manage the crowds, to cater to the requirements of basic amenities, and to meet their healthcare needs. Some of the ritualistic practices could heighten the risk for transmission of respiratory pathogens. The COVID-19 pandemic has escalated over the past few months in India. The pandemic is expected to sustain its tempo in India throughout the foreseeable future. Organization of the forthcoming Kumbh Mela needs meticulous planning.

Summary

Kumbh Mela is a Hindu religious gathering at the banks of India’s rivers, held periodically. It witnesses assembly of huge numbers of people and has the potential to amplify the COVID-19 pandemic in India; this could overwhelm the healthcare system.

Nonquenched rotators ease flocking and memorize it

We introduce a minimal model for a two-dimensional polar flock with nonquenched rotators and show that the rotators make the usual macroscopic long-range order of the flock more robust than the clean system. The rotators memorize the flock-information which helps in establishing the robustness. Moreover, the memory of the rotators assists in probing the moving flock. We also formulate a hydrodynamic framework for the microscopic model that makes our study comprehensive. Using linearized hydrodynamics, it is shown that the presence of such nonquenched heterogeneities increases the sound speeds of the flock. The enhanced sound speeds lead to faster convection of information and consequently the robust ordering in the system. We argue that similar nonquenched heterogeneities may be useful in monitoring and controlling large crowds.

Sparse Game Changers Restore Collective Motion in Panicked Human Crowds

Using a dynamic variant of the Vicsek model, we show that the emergence of disorder from an orderly moving human crowd is a nonequilibrium first-order phase transition. We also show that this transition can be reversed by modifying the dynamics of a few agents, deemed as game changers. Surprisingly, the optimal placement of these game changers is found to be in regions of maximum local crowd speed. The presence of such game changers is effective owing to the discontinuous nature of the underlying phase transition. Thus our generic approach provides strategies to (i) delay crowd crush and (ii) design safe evacuation procedures, two aspects that are of paramount importance in maintaining safety of mass gatherings of people.

Guiding interoperable electronic health records through patient-sharing networks

Effective sharing of clinical information between care providers is a critical component of a safe, efficient health system. National data-sharing systems may be costly, politically contentious and do not reflect local patterns of care delivery. This study examines hospital attendances in England from 2013 to 2015 to identify instances of patient sharing between hospitals. Of 19.6 million patients receiving care from 155 hospital care providers, 130 million presentations were identified. On 14.7 million occasions (12%), patients attended a different hospital to the one they attended on their previous interaction. A network of hospitals was constructed based on the frequency of patient sharing between hospitals which was partitioned using the Louvain algorithm into ten distinct data-sharing communities, improving the continuity of data sharing in such instances from 0 to 65-95%. Locally implemented data-sharing communities of hospitals may achieve effective accessibility of clinical information without a large-scale national interoperable information system.

Formation of homophily in academic performance: Students change their friends rather than performance

Homophily, the tendency of individuals to associate with others who share similar traits, has been identified as a major driving force in the formation and evolution of social ties. In many cases, it is not clear if homophily is the result of a socialization process, where individuals change their traits according to the dominance of that trait in their local social networks, or if it results from a selection process, in which individuals reshape their social networks so that their traits match those in the new environment. Here we demonstrate the detailed temporal formation of strong homophily in academic achievements of high school and university students. We analyze a unique dataset that contains information about the detailed time evolution of a friendship network of 6,000 students across 42 months. Combining the evolving social network data with the time series of the academic performance (GPA) of individual students, we show that academic homophily is a result of selection: students prefer to gradually reorganize their social networks according to their performance levels, rather than adapting their performance to the level of their local group. We find no signs for a pull effect, where a social environment of good performers motivates bad students to improve their performance. We are able to understand the underlying dynamics of grades and networks with a simple model. The lack of a social pull effect in classical educational settings could have important implications for the understanding of the observed persistence of segregation, inequality and social immobility in societies.