ASU Scholarship Showcase

We find that the flow of attention on the Web forms a directed, tree-like structure implying the time-sensitive browsing behavior of users. Using the data of a news sharing website, we construct clickstream networks in which nodes are news stories and edges represent the consecutive clicks between two stories. To identify the flow direction of clickstreams, we define the “flow distance” of nodes (L_i), which measures the average number of steps a random walker takes to reach the ith node. It is observed that L_i is related with the clicks (C_i) to news stories and the age (T_i) of stories. Putting these three variables together help us understand the rise and decay of news stories from a network perspective. We also find that the studied clickstream networks preserve a stable structure over time, leading to the scaling between users and clicks. The universal scaling behavior is confirmed by the 1,000 Web forums. We suggest that the tree-like, stable structure of clickstream networks reveals the time-sensitive preference of users in online browsing. To test our assumption, we discuss three models on individual browsing behavior, and compare the simulation results with empirical data.

Many adaptive systems sit near a tipping or critical point. For systems near a critical point small changes to component behaviour can induce large-scale changes in aggregate structure and function. Criticality can be adaptive when the environment is changing, but entails reduced robustness through sensitivity. This tradeoff can be resolved when criticality can be tuned. We address the control of finite measures of criticality using data on fight sizes from an animal society model system (Macaca nemestrina, n=48). We find that a heterogeneous, socially organized system, like homogeneous, spatial systems (flocks and schools), sits near a critical point; the contributions individuals make to collective phenomena can be quantified; there is heterogeneity in these contributions; and distance from the critical point (DFC) can be controlled through biologically plausible mechanisms exploiting heterogeneity. We propose two alternative hypotheses for why a system decreases the distance from the critical point.

S-cysteinylated albumin and methionine-oxidized apolipoprotein A-I (apoA-I) have been posed as candidate markers of diseases associated with oxidative stress. Here, a dilute-and-shoot form of LC–electrospray ionization–MS requiring half a microliter of blood plasma was employed to simultaneously quantify the relative abundance of these oxidized proteoforms in samples stored at −80 °C, −20 °C, and room temperature and exposed to multiple freeze-thaw cycles and other adverse conditions in order to assess the possibility that protein oxidation may occur as a result of poor sample storage or handling. Samples from a healthy donor and a participant with poorly controlled type 2 diabetes started at the same low level of protein oxidation and behaved similarly; significant increases in albumin oxidation via S-cysteinylation were found to occur within hours at room temperature and days at −20 °C. Methionine oxidation of apoA-I took place on a longer time scale, setting in after albumin oxidation reached a plateau. Freeze–thaw cycles had a minimal effect on protein oxidation. In matched collections, protein oxidation in serum was the same as that in plasma. Albumin and apoA-I oxidation were not affected by sample headspace or the degree to which vials were sealed. ApoA-I, however, was unexpectedly found to oxidize faster in samples with lower surface-area-to-volume ratios. An initial survey of samples from patients with inflammatory conditions normally associated with elevated oxidative stress-including acute myocardial infarction and prostate cancer—demonstrated a lack of detectable apoA-I oxidation. Albumin S-cysteinylation in these samples was consistent with known but relatively brief exposures to temperatures above −30 °C (the freezing point of blood plasma). Given their properties and ease of analysis, these oxidized proteoforms, once fully validated, may represent the first markers of blood plasma specimen integrity based on direct measurement of oxidative molecular damage that can occur under suboptimal storage conditions.

Sequential affect dynamics generated during the interaction of intimate dyads, such as married couples, are associated with a cascade of effects - some good and some bad - on each partner, close family members, and other social contacts. Although the effects are well documented, the probabilistic structures associated with micro-social processes connected to the varied outcomes remain enigmatic. Using extant data we developed a method of classifying and subsequently generating couple dynamics using a Hierarchical Dirichlet Process Hidden semi-Markov Model (HDP-HSMM). Our findings indicate that several key aspects of existing models of marital interaction are inadequate: affect state emissions and their durations, along with the expected variability differences between distressed and nondistressed couples are present but highly nuanced; and most surprisingly, heterogeneity among highly satisfied couples necessitate that they be divided into subgroups. We review how this unsupervised learning technique generates plausible dyadic sequences that are sensitive to relationship quality and provide a natural mechanism for computational models of behavioral and affective micro-social processes.

Many recent studies observe the increasing importance, influence, and analysis of resilience as a concept to understand the capacity of a system or individual to respond to change. The term has achieved prominence in diverse scientific fields, as well as public discourse and policy arenas. As a result, resilience has been referred to as a boundary object or a bridging concept that is able to facilitate communication and understanding across disciplines, coordinate groups of actors or stakeholders, and build consensus around particular policy issues. We present a network analysis of bibliometric data to understand the extent to which resilience can be considered as a boundary object or a bridging concept in terms of its links across disciplines and scientific fields. We analyzed 994 papers and 35,952 citations between them to reveal the connectedness and links between and within fields. We analyzed the network according to different fields, modules, and sub-fields, showing a highly clustered citation network. Analyzing betweenness allowed us to identify how particular papers bridge across fields and how different fields are linked. With the exception of a few specific papers, most papers cite exclusively within their own field. We conclude that resilience is to an extent a boundary object because there are shared understandings across diverse disciplines and fields. However, it is more limited as a bridging concept because the citations across fields are concentrated among particular disciplines and papers, so the distinct fields do not widely or routinely refer to each other. There are some signs of resilience being used as an interdisciplinary concept to bridge scientific fields, particularly in social-ecological systems, which may itself constitute an emerging sub-field.

A significant challenge of our time is conserving biological diversity while maintaining economic development and cultural values. The United Nations Educational, Scientific and Cultural Organization has established biosphere reserves within its Man and the Biosphere program as a model means for accomplishing this very challenge. The East Carpathians Biosphere Reserve (ECBR), spreading across Poland, Slovakia, and Ukraine, represents a large social-ecological system (SES) that has been protected under the biosphere reserve designation since 1998. We have explored its successes and failures in improving human livelihoods while safeguarding its ecosystems. The SES framework, which includes governance system, actors, resources, and external influences, was used as a frame of analysis. The outcomes of this protected area have been mixed; its creation led to national and international collaboration, yet some actor groups remain excluded. Implementation of protocols arising from the Carpathian Convention has been slow, while deforestation, hunting, erosion, temperature extremes, and changes in species behavior remain significant threats but have also been factors in ecological adaptation. The loss of cultural links and traditional knowledge has also been significant. Nevertheless, this remains a highly biodiverse area. Political barriers and institutional blockages will have to be removed to ensure this reserve fulfills its role as a model region for international collaboration and capacity building. These insights drawn from the ECBR demonstrate that biosphere reserves are indeed learning sites for sustainable development and that this case is exemplary in illustrating the challenges, but more importantly, the opportunities that arise when ensuring parallel care and respect for people and ecosystems through the model of transboundary protected areas around the world.

A central question in cognitive neuroscience is how unitary, coherent decisions at the whole organism level can arise from the distributed behavior of a large population of neurons with only partially overlapping information. We address this issue by studying neural spiking behavior recorded from a multielectrode array with 169 channels during a visual motion direction discrimination task. It is well known that in this task there are two distinct phases in neural spiking behavior. Here we show Phase I is a distributed or incompressible phase in which uncertainty about the decision is substantially reduced by pooling information from many cells. Phase II is a redundant or compressible phase in which numerous single cells contain all the information present at the population level in Phase I, such that the firing behavior of a single cell is enough to predict the subject's decision. Using an empirically grounded dynamical modeling framework, we show that in Phase I large cell populations with low redundancy produce a slow timescale of information aggregation through critical slowing down near a symmetry-breaking transition. Our model indicates that increasing collective amplification in Phase II leads naturally to a faster timescale of information pooling and consensus formation. Based on our results and others in the literature, we propose that a general feature of collective computation is a “coding duality” in which there are accumulation and consensus formation processes distinguished by different timescales.

Research on collective action and common-pool resources is extensive. However, little work has concentrated on the effect of variability in resource availability and collective action, especially in the context of asymmetric access to resources. Earlier works have demonstrated that environmental variability often leads to a reduction of collective action in the governance of shared resources. Here we assess how environmental variability may impact collective action. We performed a behavioral experiment involving an irrigation dilemma. In this dilemma participants invested first into a public fund that generated water resources for the group, which were subsequently appropriated by one participant at a time from head end to tail end. The amount of resource generated for the given investment level was determined by a payoff table and a stochastic event representing environmental variability, i.e., rainfall. Results show that that (1) upstream users’ behavior is by far the most important variable in determining the outcome of collective action; (2) environmental variability (i.e. risk level in investing in the resource) has little effect on individual investment and extraction levels; and (3) the action-reaction feedback is fundamental in determining the success or failure of communities.

Large-N comparative studies have helped common pool resource scholars gain general insights into the factors that influence collective action and governance outcomes. However, these studies are often limited by missing data, and suffer from the methodological limitation that important information is lost when we reduce textual information to quantitative data. This study was motivated by nine case studies that appeared to be inconsistent with the expectation that the presence of Ostrom’s Design Principles increases the likelihood of successful common pool resource governance. These cases highlight the limitations of coding and analyzing Large-N case studies.

We examine two issues: 1) the challenge of missing data and 2) potential approaches that rely on context (which is often lost in the coding process) to address inconsistencies between empirical observations theoretical predictions. For the latter, we conduct a post-hoc qualitative analysis of a large-N comparative study to explore 2 types of inconsistencies: 1) cases where evidence for nearly all design principles was found, but available evidence led to the assessment that the CPR system was unsuccessful and 2) cases where the CPR system was deemed successful despite finding limited or no evidence for design principles. We describe inherent challenges to large-N comparative analysis to coding complex and dynamically changing common pool resource systems for the presence or absence of design principles and the determination of “success”. Finally, we illustrate how, in some cases, our qualitative analysis revealed that the identity of absent design principles explained inconsistencies hence de-facto reconciling such apparent inconsistencies with theoretical predictions. This analysis demonstrates the value of combining quantitative and qualitative analysis, and using mixed-methods approaches iteratively to build comprehensive methodological and theoretical approaches to understanding common pool resource governance in a dynamically changing context.

This study extended the findings of Tighe and Schatschneider (2015) by investigating the predictive utility of separate dimensions of morphological awareness as well as vocabulary knowledge to reading comprehension in adult basic education (ABE) students. We competed two- and three-factor structural equation models of reading comprehension. A three-factor model of real word morphological awareness, pseudoword morphological awareness, and vocabulary knowledge emerged as the best fit and accounted for 79% of the reading comprehension variance. The results indicated that the constructs contributed jointly to reading comprehension; however, vocabulary knowledge was the only potentially unique predictor (p = 0.052), accounting for an additional 5.6% of the variance. This study demonstrates the feasibility of applying a latent variable modeling approach to examine individual differences in the reading comprehension skills of ABE students. Further, this study replicates the findings of Tighe and Schatschneider (2015) on the importance of differentiating among dimensions of morphological awareness in this population.