More Like this

1. Abstract Dynamics: A Progressive Linearization of Nonlinear Dynamics

   Shahhosseini, Amir; D’Souza, Kiran (June 2024, Springer)

   Lacarbonara, Walter (Ed.)

   This work proposes a computational approach that has its roots in the early ideas of local Lyapunov exponents, yet, it offers new perspectives toward analyzing these problems. The method of interest, namely abstract dynamics, is an indirect quantitative measure of the variations of the governing vector fields based on the principles of linear systems. The examples in this work, ranging from simple limit cycles to chaotic attractors, are indicative of the new interpretation that this new perspective can offer. The presented results can be exploited in the structure of algorithms (most prominently machine learning algorithms) that are designed to estimate the complex behavior of nonlinear systems, even chaotic attractors, within their horizon of predictability. 

   more » « less
2. Attacks on Continuous Chaos Communication and Remedies for Resource Limited Devices

   https://doi.org/10.1109/isqed57927.2023.10129355  

   Vishwakarma, Rahul; Monani, Ravi; Rezaei, Amin; Sayadi, Hossein; Aliasgari, Mehrdad; Hedayatipour, Ava (April 2023, 2023 24th International Symposium on Quality Electronic Design (ISQED))

   The Global Wearable market is anticipated to rise at a considerable rate in the next coming years and communication is a fundamental block in any wearable device. In communication, encryption methods are being used with the aid of microcontrollers or software implementations, which are power-consuming and incorporate complex hardware implementation. Internet of Things (IoT) devices are considered as resource-constrained devices that are expected to operate with low computational power and resource utilization criteria. At the same time, recent research has shown that IoT devices are highly vulnerable to emerging security threats, which elevates the need for low-power and small-size hardware-based security countermeasures. Chaotic encryption is a method of data encryption that utilizes chaotic systems and non-linear dynamics to generate secure encryption keys. It aims to provide high-level security by creating encryption keys that are sensitive to initial conditions and difficult to predict, making it challenging for unauthorized parties to intercept and decode encrypted data. Since the discovery of chaotic equations, there have been various encryption applications associated with them. In this paper, we comprehensively analyze the physical and encryption attacks on continuous chaotic systems in resource-constrained devices and their potential remedies. To this aim, we introduce different categories of attacks of chaotic encryption. Our experiments focus on chaotic equations implemented using Chua’s equation and leverages circuit architectures and provide simulations proof of remedies for different attacks. These remedies are provided to block the attackers from stealing users’ information (e.g., a pulse message) with negligible cost to the power and area of the design. 

   more » « less
3. Widening the Time Horizon: Predicting the Long-Term Behavior of Chaotic Systems

   https://doi.org/10.1109/ICDM54844.2022.00094  

   Zhuang, Yong; Almeida, Matthew; Ding, Wei; Flynn, Patrick D; Islam, Shafiqul; Chen, Ping (November 2022, IEEE ICDM)

   The understanding of chaotic systems is challenging not only for theoretical research but also for many important applications. Chaotic behavior is found in many nonlinear dynamical systems, such as those found in climate dynamics, weather, the stock market, and the space-time dynamics of virus spread. A reliable solution for these systems must handle their complex space-time dynamics and sensitive dependence on initial conditions. We develop a deep learning framework to push the time horizon at which reliable predictions can be made further into the future by better evaluating the consequences of local errors when modeling nonlinear systems. Our approach observes the future trajectories of initial errors at a time horizon to model the evolution of the loss to that point with two major components: 1) a recurrent architecture, Error Trajectory Tracing, that is designed to trace the trajectories of predictive errors through phase space, and 2) a training regime, Horizon Forcing, that pushes the model’s focus out to a predetermined time horizon. We validate our method on classic chaotic systems and real-world time series prediction tasks with chaotic characteristics, and show that our approach outperforms the current state-of-the-art methods. 

   more » « less
4. Beyond Alternans: Detection of Higher-Order Periodicity in Ex-Vivo Human Ventricles Before Induction of Ventricular Fibrillation

   https://doi.org/10.1101/2023.05.01.539003  

   Iravanian, Shahriar; Uzelac, Ilija; Shah, Anand D; Toye, Mikael J; Lloyd, Michael S; Burke, Michael A; Daneshmand, Mani A; Attia, Tamer S; Vega, J David; Merchant, Faisal M; et al (May 2023, bioRxiv)

   Abstract BackgroundRepolarization alternans, defined as period-2 oscillation in the repolarization phase of the action potentials, is one of the cornerstones of cardiac electrophysiology as it provides a mechanistic link between cellular dynamics and ventricular fibrillation (VF). Theoretically, higher-order periodicities (e.g., period-4, period-8,…) are expected but have very limited experimental evidence. MethodsWe studied explanted human hearts, obtained from the recipients of heart transplantation at the time of surgery, using optical mapping technique with transmembrane voltage-sensitive fluorescent dyes. The hearts were stimulated at an increasing rate until VF was induced. The signals recorded from the right ventricle endocardial surface just before the induction of VF and in the presence of 1:1 conduction were processed using the Principal Component Analysis and a combinatorial algorithm to detect and quantify higher-order dynamics. ResultsA prominent and statistically significant 1:4 peak (corresponding to period-4 dynamics) was seen in three of the six studied hearts. Local analysis revealed the spatiotemporal distribution of higher-order periods. Period-4 was localized to temporally stable islands. Higher-order oscillations (period-5, 6, and 8) were transient and primarily occurred in arcs parallel to the activation isochrones. DiscussionWe present evidence of higher-order periodicities and the co-existence of such regions with stable non-chaotic areas in ex-vivo human hearts before VF induction. This result is consistent with the period-doubling route to chaos as a possible mechanism of VF initiation, which complements the concordant to discordant alternans mechanism. The presence of higher-order regions may act as niduses of instability that can degenerate into chaotic fibrillation. 

   more » « less
5. Live‐Cell Imaging of Guanosine Tetra‐ and Pentaphosphate (p)ppGpp with RNA‐based Fluorescent Sensors**

   https://doi.org/10.1002/anie.202111170  

   Sun, Zhining; Wu, Rigumula; Zhao, Bin; Zeinert, Rilee; Chien, Peter; You, Mingxu (October 2021, Angewandte Chemie International Edition)

   Abstract Guanosine tetra‐ and pentaphosphate, (p)ppGpp, are important alarmone nucleotides that regulate bacterial survival in stressful environment. A direct detection of (p)ppGpp in living cells is critical for our understanding of the mechanism of bacterial stringent response. However, it is still challenging to image cellular (p)ppGpp. Here, we report RNA‐based fluorescent sensors for the live‐cell imaging of (p)ppGpp. Our sensors are engineered by conjugating a recently identified (p)ppGpp‐specific riboswitch with a fluorogenic RNA aptamer, Broccoli. These sensors can be genetically encoded and enable direct monitoring of cellular (p)ppGpp accumulation. Unprecedented information on cell‐to‐cell variation and cellular dynamics of (p)ppGpp levels is now obtained under different nutritional conditions. These RNA‐based sensors can be broadly adapted to study bacterial stringent response. 

   more » « less