Why proactive environmentalism is necessary

This paper examines how criminalizing the act of bribing a foreign public official affects international trade flows using a watershed global anti-corruption initiative – the 1997 OECD Anti-Bribery Convention. This multilateral agreement criminalized foreign bribery (previously illegal only for U.S. firms) in countries that represent over 75% of world exports. I exploit temporal variation in the implementation of the Convention along with variation in the level of corruption of importing countries to quantify the effects of the Convention on bilateral exports. In contrast to previous work on U.S. efforts to criminalize foreign bribery, I use a large panel of exporters and importers to control for a broad range of confounding global and national trends and shocks. I find that, on average, the Convention caused a reduction in bilateral exports from signatory countries to high corruption importing countries relative to low corruption importing countries. In particular, we observe a 5.6% relative decline in bilateral exports to importing countries that lie one standard deviation lower on the Worldwide Governance Indicators index of corruption. This suggests that by creating large penalties for foreign bribery, the Convention indirectly increased transaction costs between importing countries with high levels of corruption and exporting countries that criminalized foreign bribery. The Convention may have induced OECD firms to divert their exports to less corrupt countries; while at the same time, non-OECD firms that are not bound by the Convention may have increased their exports to corrupt countries. I also find evidence that the effects of the Convention differed across product categories.

A conceptual model suggesting that the ISO 14000 series is market driven and can prompt customer satisfaction.

This is the first in an occasional series on the dramatic national push to revamp how reading is being taught in the earliest grades. This EdSource special report examines the state of early reading in California, the needs of special learners, teacher preparation and training and curricula and textbooks that are driving instruction.

How governmental actions might overcome the pressures that keep small manufacturers polluting the sub-continent's environment?

This thesis takes a mathematical journey through concepts of synchronization, cascades, self-organized criticality, and flows on networks, establishing several novel emergent phenomena. It provides new analytical tools insights into the collective behaviors that can arise from the co-evolution of different dynamical processes on complex networks.

Emergence entails the birth of surplus complexity in a macroscopic system, when the whole becomes more than the sum of its parts. For example, ant colonies, composed of many seemingly dull and unimpressive individual ants display surprising structure and organization on the system level. And a cup of coffee that we label as hot and wet, is composed of molecules possessing neither of these properties. Emergent properties of some systems, e.g., in thermodynamics, can be summarized with concise, elegant equations. Yet, in many systems, even the full knowledge of the fundamental rules governing each element isn't enough. The field of Chemistry, for example, relies on quantum mechanics and can in principle be fully simulated given high enough computational power, yet it remains a complex, open ended field of research with centuries of tradition and no end in sight. This is mainly due to two reasons: One is the superiority of direct analytical models for the emergent properties over a blind search with simulations. The second is the lack of remotely enough computational power required for such simulations.

Complexity science studies the question of emergence in general, how the system can be more than the sum of its parts? Or why is it that ``more is different," as the esteemed Philip Anderson put it. The field of complex systems mainly focuses on the types of collective behaviors with wide applicability, including but not limited to flows, consensus formation, synchronization, cascades, self-organized criticality, and extreme events. Emergent phenomena usually rely on the interactions between subsystems, and hence network science with the primary focus on system composition through the relationships (the edges) between the subsystems (the nodes) is particularly well suited for answering such questions.

In this thesis, we will embark on a mathematical journey through these concepts, heavily relying on both, complex systems' and network scientific approaches, finding new analytical insights and supporting our findings with numerical simulations.

We start by coupling two quintessential models in complexity science: the Bak-Tang-Wiesenfeld (BTW) sandpile model of self-organized critical cascades and the Kuramoto model of synchronization. This fusion reveals emergent long-time oscillations not present in either model alone, punctuated by extreme dragon king events in the form of system-spanning cascades of cascades. Our analysis allows the characterization of the tipping point leading to dragon kings, frequency of oscillations, and cascade size distributions.

Abstracting from this specific phenomenon, we next explore different ways through which models of self-organized criticality could give rise to dragon kings. This leads to a natural taxonomy of different types of dragon king events, and provides a so far unknown necessary condition on self-organized criticality in general.

Next, we examine the interplay and co-evolution of diverse mobile agents on a network. Analogous to the social dynamics of intrinsically diverse individuals who navigate between and interact within various physical or virtual locations, agents in our model traverse a complex network of heterogeneous environments and engage with everyone they encounter. The precise nature of agents' internal dynamics and the various interactions that nodes induce are left unspecified and can be tailored to suit the requirements of individual applications. We derive effective dynamical equations for agent states which are instrumental in investigating thresholds of consensus, devising effective attack strategies to hinder coherence, and designing optimal network structures with inherent node variations in mind.

Finally, we consider flows on networks under various symmetries and conservations, such as human transportation, internet packets, power grids, and mailed packages. We construct a hierarchy of field-theoretic models, capable of accurately modeling the throughput, predicting sustainability collapse under growing demand, and allowing us to explore a spectrum of routing strategies, locate flow bottlenecks, and determine the potential benefits of dissipation.

The interplay between the structure of a networked system and the dynamics of its constituent elements, including their interactions, leads to non-trivial emergent behaviors. These behaviors can be essential to the function of the system as a whole, and thus mathematical frameworks that allow careful analysis of such behaviors are valuable. The contribution of this dissertation is to use the ideas of symmetries and balanced equivalence relations to show how network structure can be used to find the admissible patterns of synchronization (e.g., cluster synchronization states), track their dynamics, perform their linear stability analysis, and finally to retrieve the dynamics from data. An additional contribution is extending these principles to the analysis of cluster synchronization on hypergraphs. Hypergraphs allow capturing higher order interactions beyond the pairwise interactions captured in strictly dyadic network systems.

Symmetries are ubiquitous in nature. A networked dynamical system can have symmetries in its coupling structure, the dynamics of its constituent elements, or both. The first contribution of this dissertation is demonstrating how such symmetries present themselves in the structure and spectral properties of the Koopman operator, which is a linear infinite dimensional operator that exactly reproduces the dynamics of the system in the space of observables. This can be put into practice as the Koopman operator can be approximated via data driven methods. We demonstrate how the knowledge of the symmetries can be incorporated into such approximations to speed up the analysis and make it more accurate.

Cluster synchronization is a type of synchronization that is characterized by a subset of nodes in the system having fully synchronized trajectories (i.e., forming a cluster), while following a distinct trajectory from all the other clusters. Such behavior arises when all the nodes in the same cluster receive the same dynamical input from all the other nodes in the system. Therefore, symmetries as well as equitable partitions are useful tools to find the admissible cluster synchronization states for a given system. The second contribution of this dissertation is generalizing the results related to cluster synchronization in systems of coupled oscillators to study intricate patterns of synchronization, such as the family of states where cluster synchronization and splay states coexist. In such states, due to the interaction between the nodal dynamics and network structure, groups of oscillators become effectively decoupled despite the existence of physical coupling between them.

Networks capture pairwise (dyadic) interactions between elements, yet some systems are inherently higher order. For instance, a 3-species chemical reaction or a publication with three coauthors involve triadic interactions. The final contribution of this dissertation is to advancing the methodology of studying dynamics on systems with higher order interactions (e.g., triadic). Since such interactions can not be represented as a sum of dyadic interactions, their analysis requires new tools. Up to now, full synchronization on hypergraphs (which encode higher order interactions) has been the main focus of in the literature, since the dyadic projection of the adjacency tensor can be sufficient in stability calculations. We show that this approach is not sufficient for more intricate dynamics such as cluster synchronization with respect to determining admissible states and performing stability calculations. To address that, we introduce a formalism based on node and edge clusters, and demonstrate how to apply it to admissibility and stability analysis. This formalism provides a principled way to organize the analysis of dynamics on hypergraphs and serves as a tool to investigate the role of higher order interactions in stabilizing and destabilizing different states.

Tuberculosis Verrucosa Cutis (TBVC), a verrucous form of cutaneous tuberculosis, occurs from inoculation of tubercle bacilli into the skin of a previously sensitized patient with moderate to high degree of immunity. This disease is now rare in western countries and in India; the incidence of cutaneous tuberculosis has fallen from 2% to 0.15%. However two recent studies from the Indian subcontinent have reported the prevalence of cutaneous tuebrculosis as 0.7% (Varshney et al) and 0.26% (Patra et al)

This case is reported to demonstrate the indolent and extensive nature of tuberculosis verrucosa cutis in an immunocompetent individual and to highlight the importance of histopathology and empirical antitubercular therapy as an adjunct diagnostic tool.

The Biham-Middleton-Levine model (BML) is simple lattice model of traffic flow, self-organization and jamming. Recently, the conventional understanding was shown to be incomplete: rather than a sharp phase transition between free-flow and jammed, there is an additional region where convergence to intermediate states is observed, with details dependent on the aspect ratio of the underlying lattice. For aspect ratios formed by two subsequent Fibonacci numbers, intermediate states converge to ordered, periodic limit cycles (i.e., periodic intermediate (PI) states). In contrast, for square aspect ratios, intermediate states typically converge to random, disordered intermediate (DI) states. We show these DI states are very robust to perturbation and occur more frequently than the conventional states for some densities. Furthermore, we report here on the discovery of PI states on square aspect ratios, showing PI states are not just an idiosyncrasy of particular aspect ratios. Finally, we investigate features that lead towards jamming and identify that local effects can dominate. A strategic perturbation of a few selected bits can change the nature of the flow, nucleating a global jam. The global parameters, density together with aspect ratio, are not sufficient to determine the full jamming outcome.