ASU Scholarship Showcase

Contemporary human populations conform to ecogeographic predictions that animals will become more compact in cooler climates and less compact in warmer ones. However, it remains unclear to what extent this pattern reflects plastic responses to current environments or genetic differences among populations. Analyzing anthropometric surveys of 232,684 children and adults from across 80 ethnolinguistic groups in sub-Saharan Africa, Asia and the Americas, we confirm that body surface-to-volume correlates with contemporary temperature at magnitudes found in more latitudinally diverse samples (Adj. R² = 0.14-0.28). However, far more variation in body surface-to-volume is attributable to genetic population structure (Adj. R² = 0.50-0.74). Moreover, genetic population structure accounts for nearly all of the observed relationship between contemporary temperature and body surface-to-volume among children and adults. Indeed, after controlling for population structure, contemporary temperature accounts for no more than 4% of the variance in body form in these groups. This effect of genetic affinity on body form is also independent of other ecological variables, such as dominant mode of subsistence and household wealth per capita. These findings suggest that the observed fit of human body surface-to-volume with current climate in this sample reflects relatively large effects of existing genetic population structure of contemporary humans compared to plastic response to current environments.

Background: The transition from the home to college is a phase in which emerging adults shift toward more unhealthy eating and physical activity patterns, higher body mass indices, thus increasing risk of overweight/obesity. Currently, little is understood about how changing friendship networks shape weight gain behaviors. This paper describes the recruitment, data collection, and data analytic protocols for the SPARC (Social impact of Physical Activity and nutRition in College) study, a longitudinal examination of the mechanisms by which friends and friendship networks influence nutrition and physical activity behaviors and weight gain in the transition to college life.

Methods: The SPARC study aims to follow 1450 university freshmen from a large university over an academic year, collecting data on multiple aspects of friends and friendship networks. Integrating multiple types of data related to student lives, ecological momentary assessments (EMAs) are administered via a cell phone application, devilSPARC. EMAs collected in four 1-week periods (a total of 4 EMA waves) are integrated with linked data from web-based surveys and anthropometric measurements conducted at four times points (for a total of eight data collection periods including EMAs, separated by ~1 month). University databases will provide student card data, allowing integration of both time-dated data on food purchasing, use of physical activity venues, and geographical information system (GIS) locations of these activities relative to other students in their social networks.

Discussion: Findings are intended to guide the development of more effective interventions to enhance behaviors among college students that protect against weight gain during college.

A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term “spatio” refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack “fingerprints” and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches.

Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers.

We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.

Background: Prior studies have shown that using uterotonics to augment or induce labor before arrival at comprehensive Emergency Obstetric and Neonatal Care (CEmONC) settings (henceforth, “outside uterotonics”) may contribute to perinatal mortality in low- and middle-income countries. We estimate its effect on perinatal mortality in rural Bangladesh.

Methods: Using hospital records (23986 singleton term births, Jan 1, 2009-Dec 31, 2015) from rural Bangladesh, we use a logistic regression model to estimate the increased risk of perinatal death from uterotonics administered outside a CEmONC facility.

Results: Among term births (≥37 weeks gestation), the risk of perinatal death adjusted for key confounders is significantly increased among women reporting uterotonic use outside of CEmONC (OR = 3 · 0, 95 % CI = 2 · 4,3 · 7). This increased risk is particularly high for fresh stillbirths (OR = 4 · 0, 95 % CI = 3 · 0,5 · 3) and intrapartum-related causes of early neonatal deaths (birth asphyxia) (OR = 3 · 1, 95 % CI = 2 · 2,4 · 5).

Conclusions: In this sample, outside uterotonic use was associated with substantially increased risk of fresh stillbirths, deaths due to birth asphyxia, and all perinatal deaths. In settings of high uterotonic use outside of controlled settings, substantial improvement in both stillbirth and early neonatal mortality may be made by reducing such use.

Most previous works on complete synchronization of chaotic oscillators focused on the one-channel interaction scheme where the oscillators are coupled through only one variable or a symmetric set of variables. Using the standard framework of master-stability function (MSF), we investigate the emergence of complex synchronization behaviors under all possible configurations of two-channel coupling, which include, for example, all possible cross coupling schemes among the dynamical variables. Utilizing the classic Rössler and Lorenz oscillators, we find a rich variety of synchronization phenomena not present in any previously extensively studied, single-channel coupling configurations. For example, in many cases two coupling channels can enhance or even generate synchronization where there is only weak or no synchronization under only one coupling channel, which has been verified in a coupled neuron system. There are also cases where the oscillators are originally synchronized under one coupling channel, but an additional synchronizable coupling channel can, however, destroy synchronization. Direct numerical simulations of actual synchronization dynamics verify the MSF-based predictions. Our extensive computation and heuristic analysis provide an atlas for synchronization of chaotic oscillators coupled through two channels, which can be used as a systematic reference to facilitate further research in this area.

Background: Medical and public health scientists are using evolution to devise new strategies to solve major health problems. But based on a 2003 survey, medical curricula may not adequately prepare physicians to evaluate and extend these advances. This study assessed the change in coverage of evolution in North American medical schools since 2003 and identified opportunities for enriching medical education.

Methods: In 2013, curriculum deans for all North American medical schools were invited to rate curricular coverage and perceived importance of 12 core principles, the extent of anticipated controversy from adding evolution, and the usefulness of 13 teaching resources. Differences between schools were assessed by Pearson’s chi-square test, Student’s t-test, and Spearman’s correlation. Open-ended questions sought insight into perceived barriers and benefits.

Results: Despite repeated follow-up, 60 schools (39%) responded to the survey. There was no evidence of sample bias. The three evolutionary principles rated most important were antibiotic resistance, environmental mismatch, and somatic selection in cancer. While importance and coverage of principles were correlated (r = 0.76, P < 0.01), coverage (at least moderate) lagged behind importance (at least moderate) by an average of 21% (SD = 6%). Compared to 2003, a range of evolutionary principles were covered by 4 to 74% more schools. Nearly half (48%) of responders anticipated igniting controversy at their medical school if they added evolution to their curriculum. The teaching resources ranked most useful were model test questions and answers, case studies, and model curricula for existing courses/rotations. Limited resources (faculty expertise) were cited as the major barrier to adding more evolution, but benefits included a deeper understanding and improved patient care.

Conclusion: North American medical schools have increased the evolution content in their curricula over the past decade. However, coverage is not commensurate with importance. At a few medical schools, anticipated controversy impedes teaching more evolution. Efforts to improve evolution education in medical schools should be directed toward boosting faculty expertise and crafting resources that can be easily integrated into existing curricula.

Resource allocation takes place in various types of real-world complex systems such as urban traffic, social services institutions, economical and ecosystems. Mathematically, the dynamical process of resource allocation can be modeled as minority games. Spontaneous evolution of the resource allocation dynamics, however, often leads to a harmful herding behavior accompanied by strong fluctuations in which a large majority of agents crowd temporarily for a few resources, leaving many others unused. Developing effective control methods to suppress and eliminate herding is an important but open problem. Here we develop a pinning control method, that the fluctuations of the system consist of intrinsic and systematic components allows us to design a control scheme with separated control variables. A striking finding is the universal existence of an optimal pinning fraction to minimize the variance of the system, regardless of the pinning patterns and the network topology. We carry out a generally applicable theory to explain the emergence of optimal pinning and to predict the dependence of the optimal pinning fraction on the network topology. Our work represents a general framework to deal with the broader problem of controlling collective dynamics in complex systems with potential applications in social, economical and political systems.

Successful identification of directed dynamical influence in complex systems is relevant to significant problems of current interest. Traditional methods based on Granger causality and transfer entropy have issues such as difficulty with nonlinearity and large data requirement. Recently a framework based on nonlinear dynamical analysis was proposed to overcome these difficulties. We find, surprisingly, that noise can counterintuitively enhance the detectability of directed dynamical influence. In fact, intentionally injecting a proper amount of asymmetric noise into the available time series has the unexpected benefit of dramatically increasing confidence in ascertaining the directed dynamical influence in the underlying system. This result is established based on both real data and model time series from nonlinear ecosystems. We develop a physical understanding of the beneficial role of noise in enhancing detection of directed dynamical influence.