Hundertneunundzwanzig Xe NMR for investigations of complex and dynamic systems

In this work, the remarkable versatility and usefulness of applications of Xe-129 NMR experiments is further extended. The application of Xe-129 NMR spectroscopy to very different system is studied, including dynamic and static, solid and liquid, porous and non-porous systems. Using the large non-equilibrium polarization created by hyperpolarization of Xe-129, time-resolved NMR measurements can be used for the online-monitoring of dynamic systems. In the first part of this work, several improvements for medical applications of hyperpolarized Xe-129 are achieved and their feasibility shown experimentally. A large gain in speed and reproducibility of the accumulation process of Xe-129 as ice and an enhancement of the usable polarization in any experiment requiring prior accumulation are achieved. An enhancement of the longitudinal relaxation time of Xe-129 is realized by admixture of a buffer gas during the storage of hyperpolarized Xe-129. Pursuing the efforts of simplifying the accumulation process and enhancing the storage time of hyperpolarized Xe-129 will allow for a wider use of the hyperpolarized gas in (medical) MRI experiments. Concerning the use of hyperpolarized Xe-129 in MRI, the influence of the diffusion coefficient of the gas on parameters of the image contrast is experimentally demonstrated here by admixture of a buffer gas and thus changing the diffusion coefficient. In the second part of this work, a polymer system with unique features is probed by Xe-129 NMR spectroscopy, proving the method to be a valuable tool for the characterization of the anisotropic properties of semicrystalline, syndiotactic polystyrene films. The polymer films contain hollow cavities or channels with sizes in the sub-nanometer range, allowing for adsorption of Xe-129 and subsequent NMR measurements. Despite the use of a ’real-world’ system, the transfer of the anisotropic properties from the material to adsorbed Xe-129 atoms is shown, which was previously only known for fully crystalline materials. The anisotropic behavior towards atomar guests inside the polymer films is proven here for the first time for one of the phases. For the polymer phase containing nanochannels, the dominance of interactions between Xe-129 atoms in the channels compared to interactions between Xe atoms and the channel walls are proven by measurements of a powder sample of the polymer material and experiments including the rotation of the films in the external magnetic field as well as temperature-dependent measurements. The characterization of ’real-world’ systems showing very high degrees of anisotropy by Xe-129 are deemed to be very valuable in future applications. In the last part of this work, a new method for the online monitoring of chemical reactions has been proposed and its feasibility and validity are experimentally proven. The chemical shift dependence of dissolved Xe-129 on the composition of a reaction mixture is used for the online monitoring of free-radical miniemulsion polymerization reactions. Xe-129 NMR spectroscopy provides an excellent method for the online monitoring of polymerization reactions, due to the simplicity of the Xe-129 NMR spectra and the simple relationship between the Xe-129 chemical shift and the reaction conversion. The results of the time-resolved Xe-129 NMR measurements are compared to those from calorimetric measurements, showing a good qualitative agreement. The applicability of the new method to reactions other than polymerization reactions is investigated by the online monitoring of an enzymatic reaction in a miniemulsion. The successful combination of the large sensitivity of Xe-129, the NMR signal enhancements due to hyperpolarization, and the solubility of Xe-129 gives access to the large new field of investigations of chemical reaction kinetics in dynamic and complex systems like miniemulsions.

An algorithm for controllability in complex networks

In this paper structural controllability of complex networks is anyzed. A new algorithm is proposed which constructs a structural control scheme for a given network by avoiding the absence of dilations and by guaranteeing the accessibility of all nodes. Such accessibility is solved via a wiring procedure; this procedure, based on determining the non-accessible regions of the network, has been improved in this new proposed algorithm. This way, the number of dedicated controllers is reduced with respect to the one provided by previous existing algorithms.

Stability threshold approach for complex dynamical systems

Acknowledgments This paper was developed within the scope of the IRTG 1740/TRP 2011/50151-0, funded by the DFG/FAPESP, and supported by the Government of the Russian Federation (Agreement No. 14.Z50.31.0033 with the Institute of Applied Physics RAS). The first author thanks Dr Roman Ovsyannikov for valuable discussions regarding estimation of the mistake probability.

Design and implementation of graphical user interfaces for complex simulations

The development of increasingly powerful computers, which has enabled the use of windowing software, has also opened the way for the computer study, via simulation, of very complex physical systems. In this study, the main issues related to the implementation of interactive simulations of complex systems are identified and discussed. Most existing simulators are closed in the sense that there is no access to the source code and, even if it were available, adaptation to interaction with other systems would require extensive code re-writing. This work aims to increase the flexibility of such software by developing a set of object-oriented simulation classes, which can be extended, by subclassing, at any level, i.e., at the problem domain, presentation or interaction levels. A strategy, which involves the use of an object-oriented framework, concurrent execution of several simulation modules, use of a networked windowing system and the re-use of existing software written in procedural languages, is proposed. A prototype tool which combines these techniques has been implemented and is presented. It allows the on-line definition of the configuration of the physical system and generates the appropriate graphical user interface. Simulation routines have been developed for the chemical recovery cycle of a paper pulp mill. The application, by creation of new classes, of the prototype to the interactive simulation of this physical system is described. Besides providing visual feedback, the resulting graphical user interface greatly simplifies the interaction with this set of simulation modules. This study shows that considerable benefits can be obtained by application of computer science concepts to the engineering domain, by helping domain experts to tailor interactive tools to suit their needs.

Basin stability approach for quantifying responses of multistable systems with parameters mismatch

Acknowledgement This work is funded by the National Science Center Poland based on the decision number DEC-2015/16/T/ST8/00516. PB is supported by the Foundation for Polish Science (FNP).

Data Based Identification and Prediction of Nonlinear and Complex Dynamical Systems

We thank Dr. R. Yang (formerly at ASU), Dr. R.-Q. Su (formerly at ASU), and Mr. Zhesi Shen for their contributions to a number of original papers on which this Review is partly based. This work was supported by ARO under Grant No. W911NF-14-1-0504. W.-X. Wang was also supported by NSFC under Grants No. 61573064 and No. 61074116, as well as by the Fundamental Research Funds for the Central Universities, Beijing Nova Programme.

Applying complexity science to air traffic management

Complexity science is the multidisciplinary study of complex systems. Its marked network orientation lends itself well to transport contexts. Key features of complexity science are introduced and defined, with a specific focus on the application to air traffic management. An overview of complex network theory is presented, with examples of its corresponding metrics and multiple scales. Complexity science is starting to make important contributions to performance assessment and system design: selected, applied air traffic management case studies are explored. The important contexts of uncertainty, resilience and emergent behaviour are discussed, with future research priorities summarised.

How Much Greater Than the Sum of Its Parts? Evaluating Interactions Between Complex Policies

This presentation focuses on methods for the evaluation of complex policies. In particular, it focuses on evaluating interactions between policies and the extent to which two or more interacting policies mutually reinforce or hinder one another, in the area of environmental sustainability. Environmental sustainability is increasingly gaining recognition as a complex policy area, requiring a more systemic perspective and approach (e.g. European Commission, 2011). Current trends in human levels of resource consumption are unsustainable, and single solutions which target isolated issues independently of the broader context have so far fallen short. Instead there is a growing call among both academics and policy practitioners for systemic change which acknowledges and engages with the complex interactions, barriers and opportunities across the different actors, sectors, and drivers of production and consumption. Policy mixes, and the combination and ordering of policies within, therefore become an important focus for those aspiring to design and manage transitions to sustainability. To this end, we need a better understanding of the interactions, synergies and conflicts between policies (Cunningham et al., 2013; Geels, 2014). As a contribution to this emerging field of research and to inform its next steps, I present a review on what methods are available to try to quantify the impacts of complex policy interactions, since there is no established method among practitioners, and I explore the merits or value of such attempts. The presentation builds on key works in the field of complexity science (e.g. Anderson, 1972), revisiting and combining these with more recent contributions in the emerging field of policy and complex systems, and evaluation (e.g. Johnstone et al., 2010). With a coalition of UK Government departments, agencies and Research Councils soon to announce the launch of a new internationally-leading centre to pioneer, test and promote innovative and inclusive methods for policy evaluation across the energy-environment-food nexus, the contribution is particularly timely.

Social-ecological resilience and biosphere-based sustainability science

Humanity has emerged as a major force in the operation of the biosphere. The focus is shifting from the environment as externality to the biosphere as precondition for social justice, economic development, and sustainability. In this article, we exemplify the intertwined nature of social-ecological systems and emphasize that they operate within, and as embedded parts of the biosphere and as such coevolve with and depend on it. We regard social-ecological systems as complex adaptive systems and use a social-ecological resilience approach as a lens to address and understand their dynamics. We raise the challenge of stewardship of development in concert with the biosphere for people in diverse contexts and places as critical for long-term sustainability and dignity in human relations. Biosphere stewardship is essential, in the globalized world of interactions with the Earth system, to sustain and enhance our life-supporting environment for human well-being and future human development on Earth, hence, the need to reconnect development to the biosphere foundation and the need for a biosphere-based sustainability science.

Mission and Scenario Planning for Unmanned Aerial Vehicles (Path Planning and Collision Avoidance Systems)

As unmanned autonomous vehicles (UAVs) are being widely utilized in military and civil applications, concerns are growing about mission safety and how to integrate dierent phases of mission design. One important barrier to a coste ective and timely safety certication process for UAVs is the lack of a systematic approach for bridging the gap between understanding high-level commander/pilot intent and implementation of intent through low-level UAV behaviors. In this thesis we demonstrate an entire systems design process for a representative UAV mission, beginning from an operational concept and requirements and ending with a simulation framework for segments of the mission design, such as path planning and decision making in collision avoidance. In this thesis, we divided this complex system into sub-systems; path planning, collision detection and collision avoidance. We then developed software modules for each sub-system

Learning representations for graph-structured socio-technical systems

The recent widespread use of social media platforms and web services has led to a vast amount of behavioral data that can be used to model socio-technical systems. A significant part of this data can be represented as graphs or networks, which have become the prevalent mathematical framework for studying the structure and the dynamics of complex interacting systems. However, analyzing and understanding these data presents new challenges due to their increasing complexity and diversity. For instance, the characterization of real-world networks includes the need of accounting for their temporal dimension, together with incorporating higher-order interactions beyond the traditional pairwise formalism. The ongoing growth of AI has led to the integration of traditional graph mining techniques with representation learning and low-dimensional embeddings of networks to address current challenges. These methods capture the underlying similarities and geometry of graph-shaped data, generating latent representations that enable the resolution of various tasks, such as link prediction, node classification, and graph clustering. As these techniques gain popularity, there is even a growing concern about their responsible use. In particular, there has been an increased emphasis on addressing the limitations of interpretability in graph representation learning. This thesis contributes to the advancement of knowledge in the field of graph representation learning and has potential applications in a wide range of complex systems domains. We initially focus on forecasting problems related to face-to-face contact networks with time-varying graph embeddings. Then, we study hyperedge prediction and reconstruction with simplicial complex embeddings. Finally, we analyze the problem of interpreting latent dimensions in node embeddings for graphs. The proposed models are extensively evaluated in multiple experimental settings and the results demonstrate their effectiveness and reliability, achieving state-of-the-art performances and providing valuable insights into the properties of the learned representations.

Dynamical estimates of chaotic systems from Poincare recurrences

We show a function that fits well the probability density of return times between two consecutive visits of a chaotic trajectory to finite size regions in phase space. It deviates from the exponential statistics by a small power-law term, a term that represents the deterministic manifestation of the dynamics. We also show how one can quickly and easily estimate the Kolmogorov-Sinai entropy and the short-term correlation function by realizing observations of high probable returns. Our analyses are performed numerically in the Henon map and experimentally in a Chua's circuit. Finally, we discuss how our approach can be used to treat the data coming from experimental complex systems and for technological applications. (C) 2009 American Institute of Physics. [doi: 10.1063/1.3263943]

Finding Quasi-Optimal Network Topologies for Information Transmission in Active Networks

This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

A calibration approach based on Takagi-Sugeno fuzzy inference system for digital electronic compasses

Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi-Sugeno (TS) fuzzy model. IS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on IS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated IS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the IS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests. (C) 2011 Elsevier Ltd. All rights reserved.

Puzzling challenges in contemporary neuroscience: Insights from complexity and emergence in epileptogenic circuits

The brain is a complex system that, in the normal condition, has emergent properties like those associated with activity-dependent plasticity in learning and memory, and in pathological situations, manifests abnormal long-term phenomena like the epilepsies. Data from our laboratory and from the literature were classified qualitatively as sources of complexity and emergent properties from behavior to electrophysiological, cellular, molecular, and computational levels. We used such models as brainstem-dependent acute audiogenic seizures and forebrain-dependent kindled audiogenic seizures. Additionally we used chemical OF electrical experimental models of temporal lobe epilepsy that induce status epilepticus with behavioral, anatomical, and molecular sequelae such as spontaneous recurrent seizures and long-term plastic changes. Current Computational neuroscience tools will help the interpretation. storage, and sharing of the exponential growth of information derived from those studies. These strategies are considered solutions to deal with the complexity of brain pathologies such as the epilepsies. (C) 2008 Elsevier Inc. All rights reserved.