Complex Dynamics in Dedicated / Multifunctional Neural Networks and Chaotic Nonlinear Systems

We study complex behaviors arising in neuroscience and other nonlinear systems by combining dynamical systems analysis with modern computational approaches including GPU parallelization and unsupervised machine learning. To gain insights into the behaviors of brain networks and complex central pattern generators (CPGs), it is important to understand the dynamical principles regulating individual neurons as well as the basic structural and functional building blocks of neural networks. In the first section, we discuss how symbolic methods can help us analyze neural dynamics such as bursting, tonic spiking and chaotic mixed-mode oscillations in various models of individual neurons, the bifurcations that underlie transitions between activity types, as well as emergent network phenomena through synergistic interactions seen in realistic neural circuits, such as network bursting from non-intrinsic bursters. The second section is focused on the origin and coexistence of multistable rhythms in oscillatory neural networks of inhibitory coupled cells. We discuss how network connectivity and intrinsic properties of the cells affect the dynamics, and how even simple circuits can exhibit a variety of mono/multi-stable rhythms including pacemakers, half-center oscillators, multiple traveling-waves, fully synchronous states, as well as various chimeras. Our analyses can help generate verifiable hypotheses for neurophysiological experiments on central pattern generators. In the last section, we demonstrate the inter-disciplinary nature of this research through the applications of these techniques to identify the universal principles governing both simple and complex dynamics, and chaotic structure in diverse nonlinear systems. Using a classical example from nonlinear laser optics, we elaborate on the multiplicity and self-similarity of key organizing structures in 2D parameter space such as homoclinic and heteroclinic bifurcation curves, Bykov T-point spirals, and inclination flips. This is followed by detailed computational reconstructions of the spatial organization and 3D embedding of bifurcation surfaces, parametric saddles, and isolated closed curves (isolas). The generality of our modeling approaches could lead to novel methodologies and nonlinear science applications in biological, medical and engineering systems

TAXONOMY OF SECURITY AND PRIVACY ISSUES IN SERVERLESS COMPUTING

The advent of cloud computing has led to a new era of computer usage. Networking and physical security are some of the IT infrastructure concerns that IT administrators around the world had to worry about for their individual environments. Cloud computing took away that burden and redefined the meaning of IT administrators. Serverless computing as it relates to secure software development is creating the same kind of change. Developers can quickly spin up a secure development environment in a matter of minutes without having to worry about any of the underlying infrastructure setups. In the paper, we will look at the merits and demerits of serverless computing, what is drawing the demand for serverless computing among developers, the security and privacy issues of serverless technology, and detail the parameters to consider when setting up and using a secure development environment based on serverless computin

Homoclinic puzzles and chaos in a nonlinear laser model

We present a case study elaborating on the multiplicity and self-similarity of homoclinic and heteroclinic bifurcation structures in the 2D and 3D parameter spaces of a nonlinear laser model with a Lorenz-like chaotic attractor. In a symbiotic approach combining the traditional parameter continuation methods using MatCont and a newly developed technique called the Deterministic Chaos Prospector (DCP) utilizing symbolic dynamics on fast parallel computing hardware with graphics processing units (GPUs), we exhibit how specific codimension-two bifurcations originate and pattern regions of chaotic and simple dynamics in this classical model. We show detailed computational reconstructions of key bifurcation structures such as Bykov T-point spirals and inclination flips in 2D parameter space, as well as the spatial organization and 3D embedding of bifurcation surfaces, parametric saddles, and isolated closed curves (isolas).Comment: 28 pages, 23 figure

Intelligent gradient amplification for deep neural networks

Deep learning models offer superior performance compared to other machine learning techniques for a variety of tasks and domains, but pose their own challenges. In particular, deep learning models require larger training times as the depth of a model increases, and suffer from vanishing gradients. Several solutions address these problems independently, but there have been minimal efforts to identify an integrated solution that improves the performance of a model by addressing vanishing gradients, as well as accelerates the training process to achieve higher performance at larger learning rates. In this work, we intelligently determine which layers of a deep learning model to apply gradient amplification to, using a formulated approach that analyzes gradient fluctuations of layers during training. Detailed experiments are performed for simpler and deeper neural networks using two different intelligent measures and two different thresholds that determine the amplification layers, and a training strategy where gradients are amplified only during certain epochs. Results show that our amplification offers better performance compared to the original models, and achieves accuracy improvement of around 2.5% on CIFAR- 10 and around 4.5% on CIFAR-100 datasets, even when the models are trained with higher learning rates

Effect of Punarnavadi Mandoor and Shiva Gutika in Acute Deep Vein Thrombosis - A Case Report

Objectives: To minimise the dose of Anti-platelet drugs and to treat the acute case of DVT through Ayurvedic oral medications. Methods: The present diagnosed case of DVT approached to OPD of KLE BMK Ayurveda Hospital with a complaints of swelling and pain in the calf muscle of the left lower limb associated with reddish brown discoloration in the foot and occasionally nasal and gum bleeding was treated consequently for 5 months with Punarnavadi Mandoor and Shiva Gutika orally. Results: There is significant decrease in the symptoms of DVT and also major changes seen in Venous Colour Doppler study of the left lower limb. Conclusion: Acute DVT is caused by a blood clot in a deep vein and can be life threatening as it may leads to serious complication like pulmonary embolism which can be cured through Ayurvedic oral medications

Analytical techniques for characterization of raw materials in cell culture media

Raw materials are a critical part of any cell culture medium; therefore, it is of utmost importance to understand and characterize them for high-quality product. The raw material characterization (RMC) program at SAFC focuses on individual screening of raw materials both analytically and biologically. The goal of the program is to develop the best-in-class knowledge base of the raw materials used in SAFC’s media formulations and their impact on performance of products