Crossing-Symmetric Dispersion Relations without Spurious Singularities.

Recently, there has been renewed interest in a crossing-symmetric dispersion relation from the 1970s due to its implications for both regular quantum field theory and conformal field theory. However, this dispersion relation introduces nonlocal spurious singularities and requires additional locality constraints for their removal, a process that presents considerable technical challenges. In this Letter, we address this issue by deriving a new crossing-symmetric dispersion relation free of spurious singularities. Our formulation offers a compact and nonperturbative representation of the local block expansion, effectively resumming both Witten (in conformal field theory) and Feynman (in quantum field theory) diagrams. Consequently, we explicitly derive all contact terms in relation to the corresponding perturbative expansion. Our results establish a solid foundation for the Polyakov-Mellin bootstrap in conformal field theories and the crossing-symmetry S-matrix bootstrap in quantum field theories.

Emergence of Polarization in Coevolving Networks.

Polarization is a ubiquitous phenomenon in social systems. Empirical studies document substantial evidence for opinion polarization across social media, showing a typical bipolarized pattern devising individuals into two groups with opposite opinions. While coevolving network models have been proposed to understand polarization, existing works cannot generate a stable bipolarized structure. Moreover, a quantitative and comprehensive theoretical framework capturing generic mechanisms governing polarization remains unaddressed. In this Letter, we discover a universal scaling law for opinion distributions, characterized by a set of scaling exponents. These exponents classify social systems into bipolarized and depolarized phases. We find two generic mechanisms governing the polarization dynamics and propose a coevolving framework that counts for opinion dynamics and network evolution simultaneously. Under a few generic assumptions on social interactions, we find a stable bipolarized community structure emerges naturally from the coevolving dynamics. Our theory analytically predicts two-phase transitions across three different polarization phases in line with the empirical observations for the Facebook and blogosphere data sets. Our theory not only accounts for the empirically observed scaling laws but also allows us to predict scaling exponents quantitatively.

Objective quantification of homophily in children with and without disabilities in naturalistic contexts.

Homophily, the tendency for individuals to preferentially interact with others similar to themselves is typically documented via self-report and, for children, adult report. Few studies have investigated homophily directly using objective measures of social movement. We quantified homophily in children with developmental disabilities (DD) and typical development (TD) using objective measures of position/orientation in preschool inclusion classrooms, designed to promote interaction between these groups of children. Objective measurements were collected using ultra-wideband radio-frequency tracking to determine social approach and social contact, measures of social movement and interaction. Observations of 77 preschoolers (47 with DD, and 30 TD) were conducted in eight inclusion classrooms on a total of 26 days. We compared DD and TD groups with respect to how children approached and shared time in social contact with peers using mixed-effects models. Children in concordant dyads (DD-DD and TD-TD) both moved toward each other at higher velocities and spent greater time in social contact than discordant dyads (DD-TD), evidencing homophily. DD-DD dyads spent less time in social contact than TD-TD dyads but were comparable to TD-TD dyads in their social approach velocities. Children's preference for similar peers appears to be a pervasive feature of their naturalistic interactions.

Reciprocal Patterns of Peer Speech in Preschoolers with and without Hearing Loss.

Children with hearing loss often attend inclusive preschool classrooms aimed at improving their spoken language skills. Although preschool classrooms are fertile environments for vocal interaction with peers, little is known about the dyadic processes that influence children's speech to one another and foster their language abilities and how these processes may vary in children with hearing loss. We used new objective measurement approaches to identify and quantify children's vocalizations during social contact, as determined by children's proximity and mutual orientation. The contributions of peer vocalizations to children's future vocalizations and language abilities were examined in oral language inclusion classrooms containing children with hearing loss who use hearing aids or cochlear implants and their typically hearing peers. Across over 600 hours of recorded vocal interactions of twenty-nine 2.5-3.5 year olds (16 girls) in three cohorts of children in a classroom, we found that vocalizations from each peer on a given observation predicted a child's vocalizations to that same peer on the subsequent observation. Children who produced more vocalizations to their peers had higher receptive and expressive language abilities, as measured by a standardized end-of-year language assessment. In fact, vocalizations from peers had an indirect association with end-of-year language abilities as mediated by children's vocalizations to peers. These findings did not vary as a function of hearing status. Overall, then, the results demonstrate the importance of dyadic peer vocal interactions for children's language use and abilities.

Simulating COVID19 transmission from observed movement.

Current models of COVID-19 transmission predict infection from reported or assumed interactions. Here we leverage high-resolution observations of interaction to simulate infectious processes. Ultra-Wide Radio Frequency Identification (RFID) systems were employed to track the real-time physical movements and directional orientation of children and their teachers in 4 preschool classes over a total of 34 observations. An agent-based transmission model combined observed interaction patterns (individual distance and orientation) with CDC-published risk guidelines to estimate the transmission impact of an infected patient zero attending class on the proportion of overall infections, the average transmission rate, and the time lag to the appearance of symptomatic individuals. These metrics highlighted the prophylactic role of decreased classroom density and teacher vaccinations. Reduction of classroom density to half capacity was associated with an 18.2% drop in overall infection proportion while teacher vaccination receipt was associated with a 25.3% drop. Simulation results of classroom transmission dynamics may inform public policy in the face of COVID-19 and similar infectious threats.

A granular perspective on inclusion: Objectively measured interactions of preschoolers with and without autism.

Children's preschool experiences have consequences for development. However, it is not clear how children's real-time interactions with peers affect their language development; nor is it clear whether these processes differ between children with autism spectrum disorder (ASD) and two other groups of children, those with general developmental delays (DD) and typically developing (TD) children. We used objective measures of movement and vocalizations to quantify children's real-time dyadic vocal interactions and quantify classroom social networks. Participants included 56 preschoolers (22 female; M = 50.14 months) in five inclusive classrooms for children with ASD or DD and their TD peers. Each class was observed monthly on two to five occasions. Overall, children vocalized more to peers who had vocalized more to them in the previous observation. These dyadic vocalization patterns were associated with group differences in social network analyses. Modularity, the cohesiveness of group ties, was lower among children with ASD than it was among TD children or children with DD. Individually, children with ASD exhibited lower total levels of vocalizations with peers (lower degree centrality) than TD children and children with DD. In an exploratory analysis with a subset of the participants, children's degree centrality was strongly associated with their end-of-year assessed language abilities, even when accounting for mean differences between groups. Findings highlight the impact peers and social networks play in real-time language use and in the developing language abilities of children with ASD in inclusion classrooms. LAY SUMMARY: This study objectively measured associations between children's peer vocal interactions and assessed language abilities in inclusion classrooms for children with autism spectrum disorder (ASD) and their peers. All children benefited from peers talking to them, but children with ASD were less central to classroom speech networks than were typically developing children. Children's centrality to social speech networks, regardless of ASD status, was associated with assessed language abilities.

Emergence of urban growth patterns from human mobility behavior.

Cities grow in a bottom-up manner, leading to fractal-like urban morphologies characterized by scaling laws. The correlated percolation model has succeeded in modeling urban geometries by imposing strong spatial correlations; however, the origin of the underlying mechanisms behind spatially correlated urban growth remains largely unknown. Our understanding of human movements has recently been revolutionized thanks to the increasing availability of large-scale human mobility data. This paper introduces a computational urban growth model that captures spatially correlated urban growth with a micro-foundation in human mobility behavior. We compare the proposed model with three empirical datasets, discovering that strong social interactions and long-term memory effects in human movements are two fundamental principles responsible for fractal-like urban morphology, along with the three important laws of urban growth. Our model connects the empirical findings in urban growth patterns and human mobility behavior.

Effects of microsurgical repair treatment on the clinical efficacy, complications, and flap follow-up scores of patients with exposed steel plates after surgery for foot and ankle fractures.

BACKGROUND: Treatment of exposed steel plates after surgery for foot and ankle fractures is complicated. This study aims to analyze the effects of microsurgical repair treatment on the clinical efficacy, complications, and flap follow-up scores of patients with exposed steel plates following foot and ankle fracture surgery. METHODS: Eighty-two patients with exposure of steel plates after surgical treatment for foot and ankle fractures in our hospital from March 2017 to March 2018 were included in this study. The patients were divided into a study group (43 patients who received microsurgical repair) and a control group (39 patients who received conventional repair surgery). We compared the clinical efficacy, complication rate, flap followup score, recovery of ankle-hindfoot function and ankle function before treatment and at 3 and 6 months after treatment, and patient satisfaction between the two groups. RESULTS: The clinical effectiveness rate in the study group was 95.35%, which was higher than the control group (76.92%) (P<0.05). The flap appearance, texture, and elasticity scores in the study group were higher than those in the control group (P<0.05). After treatment, the American Orthopedic Foot and Ankle Society (AOFAS) score and Baird ankle score increased significantly in both groups, and reached a peak at 6 months after treatment. The peak scores of the study group were considerably higher than those of the control group at each period after treatment (P<0.05). The incidence of complications in the study group (6.98%) was lower than the control group (25.64%) (P<0.05). Patient satisfaction was higher in the study group (97.67%) than the control group (79.49%) (P<0.05). CONCLUSIONS: Microsurgical repair of exposed steel plates after surgery for foot and ankle fractures has a significant clinical effect. It can improve the flap follow-up scores, accelerate healing of the ankle, improve aesthetics, and reduce the incidence of complications. It is therefore worthy of widespread use in clinics.

Emergence of scaling in complex substitutive systems.

Diffusion processes are central to human interactions. One common prediction of the current modelling frameworks is that initial spreading dynamics follow exponential growth. Here we find that, for subjects ranging from mobile handsets to automobiles and from smartphone apps to scientific fields, early growth patterns follow a power law with non-integer exponents. We test the hypothesis that mechanisms specific to substitution dynamics may play a role, by analysing unique data tracing 3.6 million individuals substituting different mobile handsets. We uncover three generic ingredients governing substitutions, allowing us to develop a minimal substitution model, which not only explains the power-law growth, but also collapses diverse growth trajectories of individual constituents into a single curve. These results offer a mechanistic understanding of power-law early growth patterns emerging from various domains and demonstrate that substitution dynamics are governed by robust self-organizing principles that go beyond the particulars of individual systems.

Continuous measurement of dynamic classroom social interactions.

Human observations can only capture a portion of ongoing classroom social activity, and are not ideal for understanding how children's interactions are spatially structured. Here we demonstrate how social interaction can be investigated by modeling automated continuous measurements of children's location and movement using a commercial system based on radio frequency identification. Continuous location data were obtained from 16 five-year-olds observed during three 1-h classroom free play observations. Illustrative coordinate mapping indicated that boys and girls tended to cluster in different physical locations in the classroom, but there was no suggestion of gender differences in children's velocity (i.e., speed of movement). To detect social interaction, we present the radial distribution function, an index of when children were in social contact at greater than chance levels. Rank-order plots indicated that children were in social contact tens to hundreds of times more with some peers than others. We illustrate the use of social ties (higher than average levels of social contact) to visualize the classroom network. Analysis of the network suggests that transitivity is a potential lens through which to examine male, female, and mixed-sex cliques. The illustrative findings suggest the validity of the new measurement approach by re-examining well-established gender segregation findings from a new perspective.

Hot streaks in artistic, cultural, and scientific careers.

The hot streak-loosely defined as 'winning begets more winnings'-highlights a specific period during which an individual's performance is substantially better than his or her typical performance. Although hot streaks have been widely debated in sports1,2, gambling3-5 and financial markets6,7 over the past several decades, little is known about whether they apply to individual careers. Here, building on rich literature on the lifecycle of creativity8-22, we collected large-scale career histories of individual artists, film directors and scientists, tracing the artworks, films and scientific publications they produced. We find that, across all three domains, hit works within a career show a high degree of temporal regularity, with each career being characterized by bursts of high-impact works occurring in sequence. We demonstrate that these observations can be explained by a simple hot-streak model, allowing us to probe quantitatively the hot streak phenomenon governing individual careers. We find this phenomemon to be remarkably universal across diverse domains: hot streaks are ubiquitous yet usually unique across different careers. The hot streak emerges randomly within an individual's sequence of works, is temporally localized, and is not associated with any detectable change in productivity. We show that, because works produced during hot streaks garner substantially more impact, the uncovered hot streaks fundamentally drive the collective impact of an individual, and ignoring this leads us to systematically overestimate or underestimate the future impact of a career. These results not only deepen our quantitative understanding of patterns that govern individual ingenuity and success, but also may have implications for identifying and nurturing individuals whose work will have lasting impact.

Quantifying the evolution of individual scientific impact.

Despite the frequent use of numerous quantitative indicators to gauge the professional impact of a scientist, little is known about how scientific impact emerges and evolves in time. Here, we quantify the changes in impact and productivity throughout a career in science, finding that impact, as measured by influential publications, is distributed randomly within a scientist's sequence of publications. This random-impact rule allows us to formulate a stochastic model that uncouples the effects of productivity, individual ability, and luck and unveils the existence of universal patterns governing the emergence of scientific success. The model assigns a unique individual parameter Q to each scientist, which is stable during a career, and it accurately predicts the evolution of a scientist's impact, from the h-index to cumulative citations, and independent recognitions, such as prizes.

Women's connectivity in extreme networks.

A popular stereotype is that women will play more minor roles than men as environments become more dangerous and aggressive. Our analysis of new longitudinal data sets from offline and online operational networks [for example, ISIS (Islamic State)] shows that although men dominate numerically, women emerge with superior network connectivity that can benefit the underlying system's robustness and survival. Our observations suggest new female-centric approaches that could be used to affect such networks. They also raise questions about how individual contributions in high-pressure systems are evaluated.

Scaling identity connects human mobility and social interactions.

Massive datasets that capture human movements and social interactions have catalyzed rapid advances in our quantitative understanding of human behavior during the past years. One important aspect affecting both areas is the critical role space plays. Indeed, growing evidence suggests both our movements and communication patterns are associated with spatial costs that follow reproducible scaling laws, each characterized by its specific critical exponents. Although human mobility and social networks develop concomitantly as two prolific yet largely separated fields, we lack any known relationships between the critical exponents explored by them, despite the fact that they often study the same datasets. Here, by exploiting three different mobile phone datasets that capture simultaneously these two aspects, we discovered a new scaling relationship, mediated by a universal flux distribution, which links the critical exponents characterizing the spatial dependencies in human mobility and social networks. Therefore, the widely studied scaling laws uncovered in these two areas are not independent but connected through a deeper underlying reality.

A Multiscale Survival Process for Modeling Human Activity Patterns.

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

Cavity method for force transmission in jammed disordered packings of hard particles.

The force distribution of jammed disordered packings has always been considered a central object in the physics of granular materials. However, many of its features are poorly understood. In particular, analytic relations to other key macroscopic properties of jammed matter, such as the contact network and its coordination number, are still lacking. Here we develop a mean-field theory for this problem, based on the consideration of the contact network as a random graph where the force transmission becomes a constraint satisfaction problem. We can thus use the cavity method developed in the past few decades within the statistical physics of spin glasses and hard computer science problems. This method allows us to compute the force distribution P(f) for random packings of hard particles of any shape, with or without friction. We find a new signature of jamming in the small force behavior P(f) ∼ f(θ), whose exponent has attracted recent active interest: we find a finite value for P(f = 0), along with θ = 0. Furthermore, we relate the force distribution to a lower bound of the average coordination number z[combining macron](µ) of jammed packings of frictional spheres with coefficient µ. This bridges the gap between the two known isostatic limits z[combining macron]c (µ = 0) = 2D (in dimension D) and z[combining macron]c(µ → ∞) = D + 1 by extending the naive Maxwell's counting argument to frictional spheres. The theoretical framework describes different types of systems, such as non-spherical objects in arbitrary dimensions, providing a common mean-field scenario to investigate force transmission, contact networks and coordination numbers of jammed disordered packings.

Quantitative social science. A network framework of cultural history.

The emergent processes driving cultural history are a product of complex interactions among large numbers of individuals, determined by difficult-to-quantify historical conditions. To characterize these processes, we have reconstructed aggregate intellectual mobility over two millennia through the birth and death locations of more than 150,000 notable individuals. The tools of network and complexity theory were then used to identify characteristic statistical patterns and determine the cultural and historical relevance of deviations. The resulting network of locations provides a macroscopic perspective of cultural history, which helps us to retrace cultural narratives of Europe and North America using large-scale visualization and quantitative dynamical tools and to derive historical trends of cultural centers beyond the scope of specific events or narrow time intervals.

Science communication. Response to Comment on "Quantifying long-term scientific impact".

Wang, Mei, and Hicks claim that they observed large mean prediction errors when using our model. We find that their claims are a simple consequence of overfitting, which can be avoided by standard regularization methods. Here, we show that our model provides an effective means to identify papers that may be subject to overfitting, and the model, with or without prior treatment, outperforms the proposed naïve approach.

Epigenetic state network approach for describing cell phenotypic transitions.

Recent breakthroughs of cell phenotype reprogramming impose theoretical challenges on unravelling the complexity of large circuits maintaining cell phenotypes coupled at many different epigenetic and gene regulation levels, and quantitatively describing the phenotypic transition dynamics. A popular picture proposed by Waddington views cell differentiation as a ball sliding down a landscape with valleys corresponding to different cell types separated by ridges. Based on theories of dynamical systems, we establish a novel 'epigenetic state network' framework that captures the global architecture of cell phenotypes, which allows us to translate the metaphorical low-dimensional Waddington epigenetic landscape concept into a simple-yet-predictive rigorous mathematical framework of cell phenotypic transitions. Specifically, we simplify a high-dimensional epigenetic landscape into a collection of discrete states corresponding to stable cell phenotypes connected by optimal transition pathways among them. We then apply the approach to the phenotypic transition processes among fibroblasts (FBs), pluripotent stem cells (PSCs) and cardiomyocytes (CMs). The epigenetic state network for this case predicts three major transition pathways connecting FBs and CMs. One goes by way of PSCs. The other two pathways involve transdifferentiation either indirectly through cardiac progenitor cells or directly from FB to CM. The predicted pathways and multiple intermediate states are supported by existing microarray data and other experiments. Our approach provides a theoretical framework for studying cell phenotypic transitions. Future studies at single-cell levels can directly test the model predictions.

Career on the move: geography, stratification, and scientific impact.

Changing institutions is an integral part of an academic life. Yet little is known about the mobility patterns of scientists at an institutional level and how these career choices affect scientific outcomes. Here, we examine over 420,000 papers, to track the affiliation information of individual scientists, allowing us to reconstruct their career trajectories over decades. We find that career movements are not only temporally and spatially localized, but also characterized by a high degree of stratification in institutional ranking. When cross-group movement occurs, we find that while going from elite to lower-rank institutions on average associates with modest decrease in scientific performance, transitioning into elite institutions does not result in subsequent performance gain. These results offer empirical evidence on institutional level career choices and movements and have potential implications for science policy.