### Analysis of wall-pressure fluctuation sources from DNS of turbulent channel flow. (arXiv:1911.08534v1 [physics.flu-dyn])

The sources of wall-pressure fluctuation in turbulent channel flow are studied using a novel framework. The wall-pressure power spectral density (PSD) $(\phi_{pp}(\omega))$ is expressed as an integrated contribution from all wall-parallel plane pairs, $\phi_{pp}(\omega)=\int_{-1}^{+1}\int_{-1}^{+1}\Gamma(r,s,\omega)\,\mathrm{dr}\,\mathrm{ds}$, using the Green’s function. $\Gamma(r,s,\omega)$ is termed the net source cross spectral density (CSD) between two wall-parallel planes, $y=r$ and $y=s$.…

### Justification of the discrete nonlinear Schr\”odinger equation from a parametrically driven damped nonlinear Klein-Gordon equation and numerical comparisons. (arXiv:1911.08514v1 [nlin.PS])

We consider a damped, parametrically driven discrete nonlinear Klein-Gordon equation, that models coupled pendula and micromechanical arrays, among others. To study the equation, one usually uses a small-amplitude wave ansatz, that reduces the equation into a discrete nonlinear Schr\”odinger equation with damping and parametric drive. Here, we justify the approximation by looking for the error…

### Magnetic and electronic phase transitions probed by nanomechanical resonance. (arXiv:1911.08537v1 [cond-mat.mes-hall])

Two-dimensional (2D) materials enable new types of magnetic and electronic phases mediated by their reduced dimensionality like magic-angle induced phase transitions, 2D Ising antiferromagnets and ferromagnetism in 2D atomic layers and heterostructures. However, only a few methods are available to study these phase transitions, which for example is particularly challenging for antiferromagnetic materials. Here, we…

### Modulational instability of dust-ion-acoustic mode and associated rogue waves in a non-extensive plasma medium. (arXiv:1911.08557v1 [physics.plasm-ph])

The modulational instability of dust-ion-acoustic (DIA) mode and associated rogue waves in a three component dusty plasma system (containing inertial warm ion and negatively charged dust fluids along with inertialess $q$-distributed electrons) has been theoretically investigated. A nonlinear Schr\”{o}dinger equation (NLSE) has been derived by employing the reductive perturbation method. It is observed that the…

### Machine Learning Classification Informed by a Functional Biophysical System. (arXiv:1911.08589v1 [physics.bio-ph])

We present a novel machine learning architecture for classification suggested by experiments on the insect olfactory system. The network separates odors via a winnerless competition network, then classifies objects by projection into a high dimensional space where a support vector machine provides more precision in classification. We build this network using biophysical models of neurons…

### Folding Rate Optimization Promotes Frustrated Interactions in Entangled Protein Structures. (arXiv:1911.08590v1 [cond-mat.soft])

Many native structures of proteins accomodate complex topological motifs such as knots, lassos, and other geometrical entanglements. How proteins can fold quickly even in the presence of such topological obstacles is a debated question in structural biology. Recently, the hypothesis that energetic frustration might be a mechanism to avoid topological frustration has been put forward…

### Multi-criteria community detection in International Trade Network. (arXiv:1911.08593v1 [physics.soc-ph])

Understanding the community structure has great importance for economic analysis. Communities are characterized by properties different from those of both the individual node and the whole network and they affect various processes on the network. We combine community detection with specific topological indicators. As a result, a new weighted network is constructed by the original…

### Robust Sub-Meter Level Indoor Localization With a Single WiFi Access Point-Regression Versus Classification. (arXiv:1911.08563v1 [eess.SP])

Precise indoor localization is an increasingly demanding requirement for various emerging applications, like Virtual/Augmented reality and personalized advertising. Current indoor environments are equipped with pluralities of WiFi access points (APs), whose deployment is expected to be massive in the future enabling highly precise localization approaches. Though the conventional model-based localization schemes have achieved sub-meter level…

### CoopNet: Cooperative Convolutional Neural Network for Low-Power MCUs. (arXiv:1911.08606v1 [cs.CV])

Fixed-point quantization and binarization are two reduction methods adopted to deploy Convolutional Neural Networks (CNN) on end-nodes powered by low-power micro-controller units (MCUs). While most of the existing works use them as stand-alone optimizations, this work aims at demonstrating there is margin for a joint cooperation that leads to inferential engines with lower latency and…

### Robust Adaptive Model Predictive Control with Worst-Case Cost. (arXiv:1911.08607v1 [eess.SY])

A robust adaptive model predictive control (MPC) algorithm is presented for linear, time invariant systems with unknown dynamics and subject to bounded measurement noise. The system is characterized by an impulse response model, which is assumed to lie within a bounded set called the feasible system set. Online set-membership identification is used to reduce uncertainty…