Morphogenesis and Growth Driven by Selection of Dynamical Properties

Organisms are understood to be complex adaptive systems that evolved to thrive in hostile environments. Though widely studied, the phenomena of organism development and growth, and their relationship to organism dynamics is not well understood. Indeed, the large number of components, their interconnectivity, and complex system interactions all obscure our ability to see, describe, and understand the functioning of biological organisms. Here we take a synthetic and computational approach to the problem, abstracting the organism as a cellular automaton. Such systems are discrete digital models of real-world environments, making them more accessible and easier to study then their physical world counterparts. In such simplified synthetic models, we find that the structure of the cellular network greatly impacts the dynamics of the organism as a whole. In the physical world, for example, the network property wherein some cells depend on phosphorus produces the cyclical boom-bust dynamics of algae on the surface of a pond. Using techniques of synthetic biology and cellular automata, such local properties can be abstractly specified, and the long-term, system-wide, and dynamical consequences of localized assumptions can be carefully explored. This thesis explores the potential impacts of Darwinian selection of dynamical properties on long term cellular differentiation and organism growth. The focus here is on the relationship between organism homogeneity (or heterogeneity) and the dynamical properties of robustness, adaptivity, and chromatic symmetry. This dissertation applies an experimental approach to test the following three hypotheses: (1) cellular differentiation increases the expected robustness in an organism’s dynamics, (2) cellular differentiation leads to more uniform adaptivity as the organism grows, and (3) for organisms with symmetry, growth by segment elongation is more likely than growth by segment reduplication. To explore these hypotheses, we address several obstacles in the experimental study of dynamical systems, including computational time limits and big data

Consensus under Misaligned Orientations

This paper presents a consensus algorithm under misaligned orientations, which is defined as (i) misalignment to global coordinate frame of local coordinate frames, (ii) biases in control direction or sensing direction, or (iii) misaligned virtual global coordinate frames. After providing a mathematical formulation, we provide some sufficient conditions for consensus or for divergence. Besides the stability analysis, we also conduct some analysis for convergence characteristics in terms of locations of eigenvalues. Through a number of numerical simulations, we would attempt to understand the behaviors of misaligned consensus dynamics.Comment: 23 pages, 9 figure

Evolutionary games on graphs

Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first three sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fourth section surveys the topological complications implied by non-mean-field-type social network structures in general. The last three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner's Dilemma, the Rock-Scissors-Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.Comment: Review, final version, 133 pages, 65 figure

Inter-numerology interference management with adaptive guards: A cross-layer approach

The next-generation communication technologies are evolving towards increased flexibility in various aspects. Although orthogonal frequency division multiplexing (OFDM) remains as the waveform of the upcoming fifth-generation (5G) standard, the new radio provides flexibility in waveform parametrization (a.k.a. numerology) to address diverse requirements. However, managing the peaceful coexistence of mixed numerologies is challenging due to inter-numerology interference (INI). This paper proposes the utilization of adaptive guards in both time and frequency domains as a solution along with a multi-window operation in the physical (PHY) layer. The adaptive windowing operation needs a guard duration to reduce the unwanted emissions, and a guard band is required to handle the INI level on the adjacent band. The guards in both domains are jointly optimized with respect to the subcarrier spacing, use case (i.e., service requirement), and power offset between the numerologies. Also, the multi-window approach provides managing each side of the spectrum independently in case of an asymmetric interference scenario. Since the allowed interference level depends on the numerologies operating in the adjacent bands, the potential of adaptive guards is further increased and exploited with a medium access control (MAC) layer scheduling technique. The proposed INI-based scheduling algorithm decreases the need for guards by allocating the numerologies to the available bands, considering their subcarrier spacing, power level, and SIR requirements. Therefore, INI management is performed with a cross-layer (PHY and MAC) approach in this study. The results show that the precise design that accommodates such flexibility reduces the guards significantly and improves the spectral efficiency of mixed numerology systems

A General Framework for Analyzing, Characterizing, and Implementing Spectrally Modulated, Spectrally Encoded Signals

Fourth generation (4G) communications will support many capabilities while providing universal, high speed access. One potential enabler for these capabilities is software defined radio (SDR). When controlled by cognitive radio (CR) principles, the required waveform diversity is achieved via a synergistic union called CR-based SDR. Research is rapidly progressing in SDR hardware and software venues, but current CR-based SDR research lacks the theoretical foundation and analytic framework to permit efficient implementation. This limitation is addressed here by introducing a general framework for analyzing, characterizing, and implementing spectrally modulated, spectrally encoded (SMSE) signals within CR-based SDR architectures. Given orthogonal frequency division multiplexing (OFDM) is a 4G candidate signal, OFDM-based signals are collectively classified as SMSE since modulation and encoding are spectrally applied. The proposed framework provides analytic commonality and unification of SMSE signals. Applicability is first shown for candidate 4G signals, and resultant analytic expressions agree with published results. Implementability is then demonstrated in multiple coexistence scenarios via modeling and simulation to reinforce practical utility

csi and csi7 current source inverters for modular transformerless pv inverters

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